© Noordhoff Uitgevers bv
Solving Managerial
Problems
Systematically
Hans Heerkens
Arnold van Winden
Translated into English by Jan-Willem Tjooitink
Noordhoff Uitgevers-Groningen/Houten
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© Noordhoff Uitgevers bv
Cover design: G2K Designers, Groningen, The Netherlands
Cover illustration: Stocksy
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© 2021 Noordhoff Uitgevers bv, Groningen/Houten, The Netherlands
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© Noordhoff Uitgevers bv
Foreword
Problem-solving is part of all fields of study and all corporate sectors.
Knowledge of the relevant subject or industry is indispensable, but can only
get you so far. A systematic problem-solving approach can be an invaluable
aid in dealing with problems. This book focusses on the Managerial
Problem-Solving Method (MPSM), a tried and true problem-solving method
which can be applied to various problems occurring in a multitude of
situations in all subject areas.
Solving Managerial Problems Systematically is a book for students, advisors,
and managers who want to solve complex practical problems without the
problem-solving method forcing them into a straightjacket. The MPSM
provides a framework for problem-solvers, and lets them decide which tools
from existing managerial theory they want to use. MPSM is a problemsolving method that provides a path to a solution, step by step. It helps
trouble-shooters arrive at solutions by ticking the boxes on a methodological
checklist, and teaches them to differentiate between knowledge and action
problems. The Language of Variables ensures that researchers remain
concrete, helping them to consciously weigh up alternatives and obtain
answers to questions they had not yet thought to ask. The MPSM
encourages its users to take advantage of their intuition.
The MPSM combines knowledge obtained through thorough research with
systematic problem-solving. Creative techniques are used as an aid in
coming up with solutions to problems.
The first two chapters of this book cover the MPSM as a whole. Chapter 3
is a stand-alone, a fictional story that uses the notes in a trouble-shooter’s
log to describe the way the MPSM is used to solve a managerial problem.
The next seven chapters discuss each of the method’s particular phases,
followed by Chapter 11 which covers the research cycle – a recurring
element found throughout the use of the MPSM.
This book does not go into a scientific or philosophical justification of the
method. The MPSM’s usefulness and underlying logic become apparent to
the reader without discussing theories posed by other authors. But there are
several literary references – so pick up a book from the bibliography if you
are interested in certain components of the problem-solving approach. They
may help by sparking new ideas for dealing with something that is not going
the way it should. As you read, you will find that much of what is discussed
in this book is based on existing knowledge. Not all of the individual parts of
the MPSM are brand new. This book is a way of combining theories and
methods into a practical reference work for dealing with all sorts of
managerial problems, from the seemingly easy to the truly complex.
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© Noordhoff Uitgevers bv
Our thanks go out to Business School Netherlands (BSN), Buren, the
Netherlands, one of the driving forces behind this book. Several years ago,
BSN invested in our book ‘No problem, an approach to all managerial questions and mysteries’, which was used as a basis for this book.
Enschede, Nieuwegein, the Netherlands, Summer of 2016
Hans Heerkens, Arnold van Winden
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Table of Contents
1
A Framework for The Best Solution 9
1.1
1.2
1.3
1.4
1.5
1.6
1.7
1.8
Characteristics of the Managerial Problem-Solving Method 11
Systematic or Creative Approach? 11
Phases of the Managerial Problem-Solving Method 12
MPSM Works Anywhere, Anytime 13
Tailored to Your Problem 13
The Language of Variables 13
Framework 14
Researching and Designing in One 15
Summary 16
Core Concepts 17
2
Untroubled Problems 19
2.1
2.2
2.3
2.4
2.5
Types of Problems 21
Problem as an Analytical Concept 21
Action Problems 21
Knowledge Problems 23
Linking Action and Knowledge Problems 23
Summary 26
Core Concepts 27
3
A Trouble-Shooter’s Log 29
3.1
The MPSM in Practice 36
4
In Search of the Core Problem 39
4.1
4.2
4.3
4.4
4.5
Reaching the Core Problem, Step by Step 41
Lining Up the Problems 41
Cause and Effect 42
Choosing the Core Problem 43
Making Problems Quantifiable 46
Summary 50
Core Concepts 51
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D3: Do, Discover, Decide 53
5.1
5.2
5.3
5.4
Three Principles of a Plan of Attack 55
D3 Explained 55
Benefits of a Systematic Approach 56
Walking A Thin Line 57
Summary 58
Core Concepts 59
6
In Search of the Unknown 61
6.1
6.2
6.3
6.4
Looking Closely at the Problem 63
Locating the Problem 63
Researching Causes 63
Considering Earlier Solutions 67
Summary 69
Core Concepts 70
7
An Overview of Options 73
7.1
7.2
7.3
7.4
7.5
7.6
7.7
7.8
Seven Steps to a Possible Solution 75
Defining the Decision 75
Defining the Decision-Making Process 75
Establishing Criteria 77
Scaling Criteria 78
Weighting Criteria 79
Providing Alternative Options or Using Existing Possibilities 84
Evaluating the Attractiveness of Available Options 86
Summary 88
Core Concepts 89
8
The Client’s Move 91
8.1
8.2
8.3
8.4
Three Reasons for Deviating from an Advisory Report 93
Politically Charged Decisions 93
Considering Other Interests 94
Handling Risks 95
Summary 97
Core Concepts 98
9
A Systematic Approach 101
9.1
9.2
9.3
Two Principles of Implementing a Solution 103
A Brief Description 103
Realising an Idea 103
Summary 105
Core Concepts 106
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Keep Improving 109
10.1
10.2
10.3
10.4
Three Principles of a Structured Evaluation 111
Evaluation as a Balancing Item 111
MPSM: Guiding Along the Path of Evaluation 112
Evaluating Systematically 112
Summary 114
Core Concepts 115
11
In Search of Knowledge 117
11.1
11.2
11.3
11.4
11.5
11.6
11.7
11.8
11.9
Gathering Knowledge Using the Research Cycle 119
Formulating the Research Goal 119
Formulating the Problem Statement 120
Formulating the Research Questions 122
Formulating the Research Design 123
Performing the Operationalisation 125
Performing the Measurements 126
Processing the Data 127
Drawing Conclusions (Reviewing the Problem Statement) 128
Summary 129
Core Concepts 131
Sources 132
Illustration Acknowledgements 133
Index 134
About the Authors 135
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1
1
A Framework for The
Best Solution
Which is more effective: tackling a problem systematically or doing so
creatively? Using the MPSM, an acronym of Managerial Problem-Solving
Method, you can apply a systematic approach to your work while still
retaining creativity.
This chapter addresses the following questions:
* How can a creative and a systematic approach complement one
another?
* What types of problem can the MPSM be used for?
* At what point in your problem-solving approach do you start conducting
research?
* Why does the MPSM work?
Managerial Problem-Solving
The Language of Variables 14
Method 11
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How to Find a New Violinist
1
After 43 years of loyal service, violinist
Albert closes the lid on his violin case for
the very last time. The regional symphonic
orchestra will have to start looking for a new
violinist. But the members of the strings
section are divided on how to proceed. A
number of musicians prefers a systematic
approach, with a list of prerequisites for
potential new recruits. Others would rather
focus on finding a virtuoso artist, someone
who plays from the heart; they are less
interested in credentials. The chief
conductor asks both sides to come up with
a well-founded proposal.
Those favouring the systematic school of
thought feel that a new violinist should be a
graduate of an academy of music. Applicants
should have at least five years’ experience
in a large orchestra. Neither famous violin
concertos by great composers nor more
obscure works by lesser giants should hold
any secrets for them. The requirements are
to be published in an advert. A selection
commission, consisting of the conductor, a
first violinist, and a cellist, will be reviewing
new applicants based on an established
checklist of requirements. Whoever meets
these requirements demands best will get
the job.
The second group opts for a different
approach. These musicians aim to publish
an announcement in a major national
newspaper. They are looking for a violinist
who plays ‘from the heart’. Any musicians
interested in being part of the orchestra can
come by next Wednesday afternoon to
present their performance. The strings
section will then decide which applicant
would best fit the orchestra.
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Which approach should the chief conductor
go for? The systematic approach has a high
chance of yielding a performer capable of
handling the work. The creative approach,
on the other hand, may uncover some homeschooled musical marvel – a passionate
violinist who would have otherwise been
overlooked.
Put it like that, and the creative approach
would seem to have the most benefits.
But it does come with some risks. What if
the ‘brilliant’ violinist plays a soulful and
touching rendition of a piece by Vivaldi at
the Wednesday afternoon audition, but
then utterly butchers a sonata by Bach
during an official recital? Are they familiar
enough with the violin score? Are they fast
enough when it comes to reading
musical notes or rehearsing for new
performances?
The final decision is left to the chief
conductor. Both options have their own
advantages and disadvantages. So he
chooses a third option: a combination of
the two methods. Any interested violinist is
invited to demonstrate their skill on
Wednesday afternoon, on one condition:
they have to be a graduate of an academy
of music. Based on performance, the
orchestra will choose the most passionate
violinist who, happily, also meets the
minimum prerequisites for playing in an
orchestra. For a while, the chief conductor
considered inviting all comers, and having
them take an academic level test. But that
approach would take up a lot of time – time
the chief conductor does not have.
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§ 1.1
A FRAMEWORK FOR THE BEST SOLUTION
Characteristics of the Managerial ProblemSolving Method
Some people refuse to enter a supermarket without a grocery list. If a job
needs doing well, they will swear by using an established plan of attack or a
solid script. Others rely on their creativity and adaptability. They tend to
work based on circumstances. They need some elbow-room to arrive at
better solutions. So how can you work systematically without losing out on
creativity? This chapter introduces the Managerial Problem-Solving Method
(MPSM). These are the characteristics of the MPSM:
* The MPSM is a method in which the creative and the systematic
complement each other
* The MPSM is divided into seven phases
* The method can be used anywhere and at any time
* Problems are handled in their organisational context
* Problems are expressed in terms of variables
* The MPSM is an adaptable framework
* There MPSM is a method in which investigating and trouble-shooting
meet
§ 1.2
11
1
Managerial
Problem-Solving
Method (MPSM)
Systematic or Creative Approach?
The MPSM is not stringently rigid, but a framework for you to fill in as you
need. Without requiring too much complicated prior knowledge, it allows you
to reach solutions to managerial problems in a variety of situations. But you
do need to know how you can apply the MPSM’s methodology in a
meaningful manner. Which is best: a systematic or a creative approach?
Think of it as a choice between putting your money into investments, or into
a savings account. Investing money can help you increase your funds more
rapidly than saving money at a bank. But the reason not everybody has fully
poured their own capital into investments is because investing comes at a
greater risk. This is similar to using a creative approach to solve a problem.
You may come across imaginative solutions, frequently better than what a
systematic approach could have yielded. But there’s a relatively greater
chance that your inventive idea will not be practical, or simply does not
work. So should you revert to the systematic approach?
A systematic approach is one that looks for a good, practicable solution in a
stepwise manner. But that solution is not necessarily the best possible
answer to your problem. A company that wishes to excel needs something
more. If all companies in a certain field were to use the systematic approach,
they could all arrive at the same solution, with the same advantages, using
the same strategies. In that case, a systematic approach has done nothing
for a company in terms of profiling, of distinguishing itself from the
competition. A competitive advantage cannot be achieved by a systematic
approach alone – if it could, the systematic approach would be all anyone
would use.
A creative approach has major potential rewards, but a relatively greater risk
of failure. There are rarely any brilliant strokes of luck involved in the
outcome of the systematic approach, but it will generally yield acceptable
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results. It is not always possible to say which of the two approaches will
work the best beforehand. In some specific cases, there may be a clear
preference. In practice, it is often convenient to opt for a systematic
approach while also applying your creativity during certain stages. Think, for
example, of developing a name for a new model of car. You start with a list
of requirements – as systematically as possible. Using books on marketing
and brand management, you establish your demands, i.e. what you expect
from a car’s name. Then, you select whatever criteria you feel are relevant.
For example, the new name should follow a similar pattern as earlier
models by the same manufacturer.
Once you have established you list of demands, it is time to start thinking of
names – time to get creative. In a brainstorming session, you come up with as
many names as you can. Then you switch back to the systematic approach.
You verify your potential names against the list of established requirements.
You pick whichever best fits the bill. Following this line of reasoning, it should
come as no surprise that Vauxhall produces a car called the Cascada. That
name fits in perfectly well with Vauxhall’s established range of seemingly Latin
names ending in -a used for their other cars: Corsa, Astra, Meriva, Insignia
and Zafira.
The Managerial Problem-Solving Method allows you to embark on necessary
creative jaunts within a systematic approach to a problem. Those
excursions can be essential for reaching quality solutions. The creative
approach is most prevalent in phase 4 of the MPSM; the phase where you
look for alternative solutions. The systematic approach and the creative
approach are not contradictory; instead, they are complementary.
Depending on the situation, use either a systematic approach, a creative
approach, or a combination of the two. The MPSM lets you do whatever
best serves your purpose.
1
§ 1.3
Phases of the Managerial Problem-Solving
Method
The MPSM is one of several systematic problem-solving approaches.
Developed by the University of Twente, the MPSM is based on several
different problem solving methods. The MPSM consists of the following
seven phases:
1 Defining the problem
2 Formulating the approach
3 Analysing the problem
4 Formulating (alternative) solutions
5 Choosing a solution
6 Implementing the solution
7 Evaluating the solution
When using the MPSM for problem-solving purposes, you follow the seven
phases sequentially – but you may have to backtrack on occasion, too. It is
quite possible to find that the problem you established in phase 1 does not
manifest itself as you thought it did once you reach phase 3. This could
mean you need to return to phase 1, and review your initial diagnosis.
All in all, this approach looks neither very new nor original. The MPSM does
not appear to deviate substantially from existing problem-solving methods.
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13
Investigating, analysing, concluding, implementing and evaluating; they are
all there. And yet, the MPSM is different from other, often more limited
problem-solving models.
§ 1.4
MPSM Works Anywhere, Anytime
1
There are methods which only apply to a certain field or area of expertise.
Look at Van den Kroonenbergs technical problem-solving model, for
example. Building a bicycle becomes a piece of cake using this detailed
method for designing tools or equipment. But it gets you nowhere if what
you want to design is an organisation. Another example: Strategic
management uses a variety of models designed specifically for a single
purpose. Think of the SWOT analysis, Porter’s five forces model, or a
fishbone diagram. Each is a very convenient tool for a specific situation –
but they all have their limits in terms of applicability.
The MPSM is a more general method, applicable for various problems
encountered in various situations in all areas of expertise. It has helped a
waste management company solve an issue with working hours which did
not fit with garbage truck routes; mathematics alone was not enough to
solve this logistical puzzle. MPSM’s consistent approach helped make an
airport better suited to certain types of aircraft. It has improved productivity
of packaging machines. The MPSM can be used anywhere, anytime.
§ 1.5
Tailored to Your Problem
Many problem-solving methods are only concerned with whatever solution
technically solves the problem. Established powers and concerns in an
organisation are not investigated. Who has access to what information?
What does the decision-making process look like, and how does it work?
What is going on behind the screens? There are many and frequently
unclear aspects involved, many or all of which may, to some greater or
lesser extent, be responsible for the problem. Power factors are not
explicitly covered by the MPSM - these are already touched upon when
defining the problem. Using the MPSM, you will find that no problem is an
isolated issue. Any problem is a problem in the context of an organisation.
The MPSM takes that into account, thereby guiding you to a tailored
solution.
§ 1.6
The Language of Variables
In some models, the same arrow indicator is used to describe a causal link
here or a sequential order there, before suddenly representing a hierarchical
relationship between different employees. As a result, objects, activities,
and variables can become muddled. The MPSM does not suffer from this
problem. Using the MPSM, reality is expressed in variables – and variables
only. Formulating these variables carefully allows you to establish
inconsistencies in your analyses quite easily. Even the most intricate
problem-solving approaches become easy to untangle.
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Language of
variables
1
Reality is more than variables. This is also true for the harsh reality of any
problem. Nevertheless, the MPSM restricts itself to the so-called language of
variables. Both problems and reality itself are only expressed in terms of
variables. The reason for that is simple: if you cannot express something in
terms of variables, then it cannot contribute to a solution… nor can it be a
problem. Restricting yourself to variables lets you structure a problem clearly,
which helps you visualise it in a model. If you then use arrows to connect
individuals - actors, as the jargon has it – to the variables, discerning the
actual problem becomes rather difficult. Figure 1.1 is an example of a
scheme in which we see both variables and actors. Relationships are
depicted between actors (management and employees) and variables
(productivity and profit). This makes identification of problems (causes and
effects) difficult. What does the relationship between management and
employees mean? Employees are not a cause of productivity; instead, a
characteristic of employees is that they attain a certain level of productivity.
So, in this case, productivity is a characteristic (variable) of employees. The
arrow that should be there between productivity and profit is actually nowhere
to be found. This means it has become difficult to identify the problems.
Hence, this scheme is not a good model. If there were an arrow between
productivity and profit, it would be clear that productivity was the cause of
profit. Then, we would have identified two problems and the scheme (without
the objects) would have been a good model.
FIGURE 1.1
§ 1.7
Connections between actors and variables
Employees
Productivity
Management
Profit
Framework
Many problem-solving methods require thorough and dedicated study before
you can use them to go anywhere near an actual problem. For example,
getting to grips with Mintzberg’s configurations, complete with their
coordination mechanisms, feedback loops, and design parameters can take
a while. And by the time you do, you will not yet have made any progress
with the problem itself. The MPSM, on the other hand, sets itself apart by
its simplicity. You do not need to know the seven phases by heart; a global
idea is all you need - as long as you have this book at hand.
The phases of the MPSM are the basis for you own problem solving
approach. You should look at this approach as a framework, a grid for you
to fill in as you want. Each of the phases allows you to use different models,
techniques and methods to your hearts content. This lends itself to
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A FRAMEWORK FOR THE BEST SOLUTION
methods used in project management. If you are looking into connections
and causes (phase 3), McKinsey’s 7S-model (Athos & Pascal 1982 and
Peters & Waterman 1982) can be a useful tool. If you are trying to come up
with alternative solutions (phase 4), you may benefit from creativity
supporting techniques such as brain storming sessions or mind maps.
Every phase in the MPSM lends itself to the use of convenient tools and
instruments from the various management theories. It is a general
approach which allows enough room to use different, specific instruments
as needed.
§ 1.8
15
1
Researching and Designing in One
Most books on methodology are concerned with research methodology,
which centres on how to acquire knowledge and information. A minority of
methodological literature is concerned with designing, with solving practical
problems. In this book on the MPSM, research and design go hand in hand.
You are unlikely to research a problem for the sheer joy of it. The goal of
nearly all research is to contribute to resolving a situation you are unhappy
with. In order to come to grips with a problem, you need knowledge. In order
to get knowledge, you conduct research; you investigate. Using existing
literature, you can certainly go some way when it comes to researching or
designing solutions. But getting the two to mesh can be quite a hassle. It
starts with formulating complex situations in an organisation in terms of
problems that are both relevant and manageable. What sort of knowledge
do you need for your research? If you are able to come up with a suitable
problem definition, you will soon be faced with new obstacles: how are you
going to use your new-found knowledge? Why did you conduct research in
the first place? The MPSM helps you ensure that your research is useful
and lets you assist in solving problems for companies and non-profit
organisations.
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Summary
1
▶ The Managerial Problem-Solving Method allows you to embark on
necessary creative jaunts within the systematic approach to a problem.
These excursions are a requirement for reaching quality solutions.
▶ The MPSM is one of several systematic problem-solving approaches.
When using the MPSM, you follow the steps described in these seven
phases:
* Defining the problem
* Formulating your approach
* Analysing the problem and asking questions. What is the nature of
the problem? What is causing it? Why are any existing solutions not
used?
* Formulating (alternative) solutions
* Choosing a solution
* Implementing the solution
* Evaluating the solution: did it work?
▶ The MPSM is applicable to various problems encountered in various
situations in all areas of expertise.
▶ The MPSM takes into account that no problem is an isolated issue. A
problem is embedded in the context of an organisation, and needs a
fitting solution.
▶ Using the MPSM, you express a problem in terms of variables.
Formulating these variables carefully allows you to establish
inconsistencies in your problem-solving work quite easily.
▶ The MPSM should be considered a framework, a grid for you to fill in as
you need. Each of the phases allows you to use different models,
techniques and methods for a custom problem-solving approach.
▶ In this book on the MPSM, research and design go hand in hand. The
goal of nearly all research is to contribute to resolving a situation you
are unhappy with. In order to come to grips with a problem, you need
knowledge. The MPSM helps you ensure that your research is useful and
lets you assist in solving problems for companies and non-profit
organisations.
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A FRAMEWORK FOR THE BEST SOLUTION
17
Core Concepts
1
Managerial ProblemSolving Method
A problem-solving method for managerial problems that uses
both creative and systematic approaches, such as investigating
and resolving. There are seven phases to the MPSM, which you
follow step by step:
1 Defining the problem
2 Formulating your approach
3 Analysing the problem and asking questions. What is the
nature of the problem? What is causing it? Why are any
existing solutions not used?
4 Formulating (alternative) solutions
5 Choosing a solution
6 Implementing the solution
7 Evaluating the solution: did it work?
The Language of Variables Expressing problems in terms of variables. You untangle an
issue and define it as a series of variables, measurable
attributes. Some variables can only be measured using
indicators.
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2
Untroubled Problems
2
What exactly is a problem? And how can it be solved? By using a systematic
problem-solving method or by conducting research? The MPSM bridges the
gap between action and knowledge problems.
This chapter addresses the following questions:
* What is an action problem?
* What is a knowledge problem?
* What is the link between action and knowledge problems?
Action problem 21
Knowledge problem 23
Discrepancy 22
Research population 23
Problem owner 22
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Lacking in Drive
2
Mr Stark, general director at a production
company, has come to feel that his
employees are insufficiently motivated. The
reality deviates from the norm; in other
words, there is a discrepancy. However,
Mr Stark is unsure as to the size of this
discrepancy. He has reached out to an
expert in the field, who has been given the
task of coming up with measures that will
increase motivation all-round. During the
initial brief between the director and the
advising consultant, Mr Connoté, the
following conversation takes place:
Director Stark: ‘I am not satisfied. The staff
is not properly motivated. We need to get
that motivation up.’
Consultant Connoté: ‘How low is the level of
motivation?’
Director Stark: ‘Lower than it should be.’
Consultant Connoté: ‘And how high would
you like it to be?’
Director Stark: ‘Higher than it is now.’
So what is Mr Connoté to do? There is not
a scrap of hard data available. He has
been tasked with solving a problem which
is based on nothing but someone’s gut
feeling. That hardly qualifies as evidence.
Mr Connoté’s brow furrows, but he resolves
not to ignore the perceived ‘problem’.
‘Where there is smoke, there is a fire,’ he
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thinks. Connoté sets to work. His first order
of business is to establish how low (or high)
levels of motivation currently are. That is a
knowledge problem. He needs to find a way
to measure motivation. One way would be to
check to what extent employees are willing
to work overtime, and compare those figures
to surveys taken at competing companies…
if similar surveys even exist. Connoté can
also check employee absenteeism or
turnover figures. Together with the director,
Connoté establishes a ‘motivation
benchmark’ using the indicators of
absenteeism, turnover, and overtime.
Connoté rounds off his investigation. His
conclusion? Based on the benchmark
established in consultation with the director,
employee motivation levels are, in fact, not
below par after all. The indicator values do
not deviate from those found at competing
companies. Which means there is no action
problem after all. Mr Connoté reports his
findings to the board. Job done. The solution
to the knowledge problem has made further
action unnecessary.
But it could have gone a different way. If
Connoté had concluded motivation levels
were indeed too low, there would have been
an action problem after all; one for him to
solve.
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§ 2.1
UNTROUBLED PROBLEMS
Types of Problems
Problems mean worried faces, tear-stained pillows, and general misery.
Problems keep people up at night. Problems are bothersome, complicated,
inconvenient, and occasionally slightly mysterious. There are many faces to
‘the unsolvable’. Our language has numerous synonyms for the word
‘problem’: an impediment, an obstruction, a complication, a difficulty, a
dilemma, a matter, a puzzle, an issue, or a question. Solving a managerial
problem does not involve feelings of sadness, or other emotions for that
matter. It is simply to do with not liking or not knowing something. This
chapter considers the problem to be a purely analytical concept. You will
become more acquainted with both action and knowledge problems, and
with how the two are connected.
§ 2.2
21
2
Problem as an Analytical Concept
All problems share a common denominator: Once you have one, you will want
to get rid of it. It does not matter whether the problem refers to someone’s
(love) life, laptop, or production line. Some people are skilled at passing off
their problems onto others. Some people try to sweep their problems under
the rug. Whoever you may be – nobody enjoys being a problem owner.
One small comfort: there have been others before you. Take heart in the
many witticisms and profundities left to our troubled world by a great slew of
pundits, poets, and philosophers, such as: ‘Problems are only opportunities
in work clothes’ (Henry J. Kaiser, quotes.net), ‘No problem can be solved
from the same level of consciousness that created it’ (Albert Einstein,
quotes.net), ‘All progress is precarious, and the solution of one problem
brings us face to face with another problem’ (Martin Luther King, Jr., quotes.
net), or: ‘If a problem has no solution, it may not be a problem, but a fact not to be solved, but to be coped with over time’ (Shimon Peres, quotes.net).
Philosophical discussions about problems tend to pass many people by in
favour of the real thing. Students, advisors, or managers, for example, can
actually see something going wrong. Think of a negative cash flow, declining
returns on investments, or underutilisation of production capacity. Whatever
it is, it is not what they want or expect it to be. And, importantly: They are
looking for a solution. To their minds, a problem is not some tragic
happening, but an adversary to be faced head on. They sink their teeth into
the matter, looking for unknown causes and not letting go until all
‘mysteries’ are unravelled. That includes (re)investigating the illogical and
the easily explicable; whatever it takes to make the problem go away.
A neutral and carefree approach turns any problem into an analytical
concept. Something you do not like or do not know; an action problem or a
knowledge problem, as they are known in the jargon.
§ 2.3
Action Problems
Anything or any situation that is not how you want it to be, is an action
problem. It is where reality deviates from your norm. An action problem is
having a fiver in your wallet when you actually need a twenty. You are only a
quarter of the way towards your goal. And you may want to do something
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Action
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about it, for example by looking for a job or borrowing money. You take
action in order to solve your problem.
Alternatively, you can choose not to do anything at all. You let things lie. You
settle for your fiver, in effect lowering your norm by 75%. As a result, there is
no longer a difference between your norm and reality; there is no longer a
problem. Doing nothing is still doing something; it is adjusting your norm to
reality. No muss, no fuss.
2
The definition of an action problem is as follows:
Discrepancy
An action problem is a discrepancy between the norm and the reality,
as perceived by the problem owner.
Action problems occur whenever things do not go your way. You expect your
sales people to realise a 40,000-euro turnover every month. But figures for
the first half year show a monthly turnover of barely 25,000 euros. There is
a discrepancy between your 40,000-euro norm, and the actual 25,000-euro
turnover per employee per month.
Problem owner
The problem owner is whatever entity, be it a person, a group, or an
organisation, feels that a certain problem exists. Action problems express both
the norm and reality in terms of variables. Variables are characteristics of
people or organisations. In the turnover example, you are the problem owner
and the variable is expressed as the monthly turnover per employee. These
observations seem obvious. In practice, though, they may lead to uncertainties.
How did you decide on your norm? Why did you select this variable? And how
do you quantify your variables? These are all difficult, practical questions.
Chapter 4 discusses the concept of variables used in phase 1 in greater detail.
An action problem never occurs on its own. Sales can be low while
productions costs are high. The one may be connected to the other. A useful
tool to establish whether problems are connected is the problem cluster,
sometimes known as problem bundle (see chapter 4, figure 4.1), a model
which uses arrows to indicate existing connections between problems in
terms of cause and effect. Connections established, you can choose which
problem to solve. Whichever problem you select (note that how to do so will
be explained later in the book) becomes the ‘core problem’. You can deal
with multiple core problems at once, provided you have the time and
resources you need for your approach. But make sure you set your priorities;
each core problem must receive enough attention at the right time.
Managerial Problem-Solving Method
Action problems can be solved using many different methods. This book
focusses on the Managerial Problem-Solving Method (MPSM), which
consists of seven phases:
1 Defining the problem
2 Formulating your problem-solving approach
3 Analysing the problem
4 Formulating (alternative) solutions
5 Choosing a solution
6 Implementing the solution
7 Evaluating the solution
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§ 2.4
Knowledge
problem
UNTROUBLED PROBLEMS
Knowledge Problems
Something is not right. You encounter a situation you want to change – you
want to improve it. In this case, you are faced with an action problem. In
other cases, the problem may have to do with information: something you do
not know or do not understand. That means you will have to conduct research
in order to obtain knowledge. You are looking to solve a knowledge problem.
The definition of a knowledge problem is as follows:
Research
population
23
2
A knowledge problem is a description of the research population, the
variables and, if necessary, the relations that need to be investigated.
A knowledge problem concerns learning something about the world around
you. It involves a part of reality. For example, you want to find out monthly
turnover figures per sales employee. Or you may want to investigate
relationships between variables, such as the connection between monthly
turnover per sales employee and sales employees’ current length of
employment.
The research population consists of the person(s), group(s), or
organisation(s) that are the subject of the investigation; the subjects you
wish to know something about. In the previous example, the sales employees
are the research population. Monthly turnover per sales employee and length
of employment are the variables. The relation you are investigating is the
possible connection between monthly turnover and length of employment.
Knowledge problems can be descriptive or explanatory in nature. You may
want to know the what, without needing to know the why – for example when
looking to find out monthly employee turnover. For other knowledge problems,
the why may be just as important as, or even more important than, the what –
for example when investigating what factors influence monthly employee
turnover.
Research Cycle
Knowledge problems are not about changing a situation. You are only
interested in information. Your knowledge is gathered through research. The
procedure for solving a knowledge problem is known as a research cycle.
This cycle consists of eight phases:
1 Formulating the research goal
2 Formulating the problem statement
3 Formulating the research questions
4 Formulating the research design
5 Performing the operationalisation
6 Performing the measurements (gathering data)
7 Processing the data
8 Drawing conclusions (reviewing the problem statement)
§ 2.5
Linking Action and Knowledge Problems
This book is about dealing with action problems: the Managerial ProblemSolving Method is a guide to solving action problems. Yet you will frequently
encounter knowledge problems along the way. Knowledge problems crop up
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during virtually all phases of the MPSM, except during the phase where you
choose a solution. Knowledge problems should be resolved according to the
research cycle procedure. There are many books on the art of research.
This book only covers the research cycle (see Chapter 11) in the broadest
of terms.
2
When you are dealing with an action problem, you will nearly always need a
certain amount of knowledge. As soon as you find that there is knowledge
you need and do not already have available, you move away from the MPSM
and enter the research cycle. Once you have completed the cycle (and your
investigation), you re-enter the MPSM at the phase where you left it. Using
the knowledge you have obtained, you proceed to deal with the action
problem. As such, the approach to your knowledge problem becomes a
means of solving your action problem. One example would be mending a
punctured tyre. You start with an action problem: one of your tyres is flat.
That leads to a knowledge problem: you need to know where exactly the tyre
has been punctured. So you move to investigate. Once you have established
the location of the puncture, you proceed to solve your action problem: you
fix the puncture.
Note that you should never stick the ‘knowledge problem’ label onto just any
old issue. Not every instance where you need information is by definition a
knowledge problem. In some cases, the knowledge you need may already be
present elsewhere, for example in annual reports or records. Obtaining the
required knowledge would just be just a matter of searching, not researching.
In other cases, you may not even need to know all the ins and outs, as long
as you have a global impression. You may be best served by using your
common sense and making well-founded assumptions. Say, for example, that
other parties have already conducted research into the problem earlier, but
you are unable to obtain the information from their reports. It would be
enough to talk about the earlier research using a representative sample, or
interviewing individuals involved in earlier research. You might learn that
motivation levels were low enough to warrant some form of action even back
then. That means you do not need to know exactly how low those levels were
for your new problem-solving approach – and as such, no additional research
is needed. If you cannot obtain the information you need and are unable to
provide an educated guess, you will need to formulate a knowledge problem.
Not everyone is always immediately clear on the difference between action
and knowledge problems. Action problems deal with unique and concrete
norms. For example: what would be the best way of improving employee
motivation levels? That would appear to be a knowledge problem, a question
which needs an answer in the form of information. In fact, however, it is an
action problem posing as a knowledge one. The problem is not concerned
with an actual, measurable situation, but with what is the accepted norm; a
norm is not something that exists in reality, but something that has to be
established based on preference. The so-called ‘best way’ is nothing but a
norm. And you are looking to ‘improve’ motivation. Also a norm. Improving
means that motivation levels would be higher than they are now once you
have finished implementing a solution. For a knowledge problem, the norm
is that the answer has to be correct. That is a general norm, which applies
to all knowledge problems. But the level of exactness of the knowledge you
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UNTROUBLED PROBLEMS
25
are looking for may differ from one problem to the next. Table 2.1 is an
overview of the characteristics of both action and knowledge problems.
TABLE 2.1 An action problem involves an undesired situation. A knowledge problem
involves a lack of knowledge.
Description
Action Problem
Knowledge Problem
Definition
An action problem is a discrepancy between the norm and
reality, as perceived by the
problem owner.
Appearance
Things are not as you want
them to be.
Problem Identification
Perception
(There is a fiver in my wallet;
I need a twenty!)
Specific
Managerial Problem-Solving
Method (MPSM)
A knowledge problem is a
description of the research
population, the variables and,
if necessary, the relations that
need to be investigated.
You require knowledge.
Formulation
Problem Description
Norm
Problem-Solving
Approach
2
Problem Statement
Question
(How much money is left in my
wallet?)
General
Research cycle
Tip: Limit Yourself to Important Knowledge
Problems
In the problem-solving approach to an action problem, there is often a solid
need for knowledge. Knowledge problems lurk around every turn; and you
will soon become completely turned around if you expect to deal with each
knowledge problem individually. On top of that, you will generally not have
enough time to deal with all of them via the research cycle anyway. The
advice, therefore is this: Limit yourself to the largest, most important
knowledge problems, and be thorough when taking them on. Whatever slew
of smaller knowledge problems is generally undeserving of your attention;
answers you find hardly tend to have any impact on the solutions in your
problem-solving approach. Think of buying a new car. If what you want is the
most fuel-efficient car available, looking into built-in accessories is
pointless; the only relevant information concerns fuel-efficiency.
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Summary
2
▶ ‘Problem’ is an analytical concept. It is something you do not like or do
not know.
▶ An action problem is when the problem owner perceives a discrepancy
between the norm and reality; the existing situation is not as it should be.
▶ A knowledge problem is when the problem owner does not have the
information required to deal with the problem. Some form of research is
required. A knowledge problem involves a description of the research
population, the variables and, if necessary, the relationships that need
to be investigated.
▶ An action problem is resolved using the MPSM (Managerial ProblemSolving Method). The MPSM consists of the following phases:
1 Defining the problem
2 Formulating the approach
3 Analysing the problem
4 Formulating (alternative) solutions
5 Choosing a solution
6 Implementing the solution
7 Evaluating the solution
▶ A knowledge problem is resolved using the research cycle. It consists of
eight phases:
1 Formulating the research goal
2 Formulating the problem statement
3 Formulating the research questions
4 Formulating the research design
5 Performing the operationalisation
6 Performing the measurements (gathering data)
7 Processing the data
8 Drawing conclusions (reviewing the problem statement)
▶ The MPSM is where action and knowledge problems meet; where a
problem-solving method and research go hand in hand. When dealing
with an action problem, you always need a certain amount of knowledge.
As soon as you find that there is information you need and do not
already have, you move away from the MPSM, and enter the research
cycle. Once you have completed the cycle (and your investigation), you
re-enter the MPSM at the phase from which you left off. Using the
knowledge you have obtained, you proceed to deal with the action
problem. As such, the approach to your knowledge problem becomes a
means of solving your action problem.
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UNTROUBLED PROBLEMS
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Core Concepts
2
Discrepancy
A deviation, a situation where two things do not match.
Problem-solving involves dealing with a discrepancy, a
deviation, between the norm and reality.
Action Problem
A discrepancy between the norm and reality, as perceived by
the problem owner.
Knowledge Problem
A description of the research population, the variables and,
if necessary, the relationships that need to be investigated.
Research Population
The person(s), group(s), or organisation(s) that are the subject
of the investigation you are performing.
Problem-Owner
The person(s), group(s), or organisation(s) who are (or perceive
themselves to be) responsible for a solution to a problem.
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3
A Trouble-Shooter’s Log
3
Things are looking pretty grim at Lock Plastic Production in Wolverton. For
the third consecutive quarter, the company finds itself in the red. You have
been recruited as their trouble-shooter, a problem-solver tasked with
investigating and solving ‘the problem’. But what, exactly, is ‘the problem’.
And how are you going to deal with it? You set out to solve the problem
following the seven phases of the Managerial Problem-Solving Method.
This chapter addresses the following questions:
* How does the MPSM work in practice?
* Which activities are involved in the different phases?
* What are the results of the different phases?
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Substantial stagnation in the
plastics plant
A trouble-shooter’s log
3
Things are looking pretty grim at Lock Plastic Production in Wolverton. For the third
consecutive quarter, the company finds itself in the red. You have been contracted to help
the company find a way out. You set out to work along with a project team. You approach
the issue according to the MPSM (Managerial Problem-Solving Solution). Using a log, you
keep a record of your findings for each of the phases of the MPSM.
Phase 1 Identifying the Problem
Thursday, January 6th, at Lock’s
Drafted a list of identified problems: many colleagues leaving; old, frequently broken
machinery; new materials apparently too hard to properly process; revenue from loyal
clients fading; barely any new clients; sales team hardly leave the premises; poorly trained
sales team; education levels of production staff (too) low; cost figures increasing;
‘competitors are more innovative’.
Friday, January 7th, headquarters
Had a closer look at the issues indicated. Some questions unanswered: Are the new
materials actually too hard to process, or are they not properly treated before processing?
Do Sales stay away from clients, or is that just Marketing’s perception? Are competitors
really ahead in terms of new products, or is that just a feeling resulting from Lock’s own
people being very familiar with their products? Focussed on the missing information.
Created insight into the cluster of problems. And looked for and identified the most likely
cause: Lock will not be able to go on using their antiquated and worn machinery.
Phase 2 Formulating the Approach
Wednesday, January 12th, at Lock’s
Advised director to attack the problem at the root. He needs to free up funds and invest
them in new machinery. Director was less than thrilled. Still managed to convince him of the
urgency. Received go-ahead for formulating the problem-solving approach. Required
machines unlikely to be found at a local hardware store. Director to give final verdict on the
investment later. Made the rounds on-site, talked to several people there. Got some ideas
concerning requirements for new machines, and some issues to keep in mind in case of a
switch-over. Surprisingly, not all employees feel new machines are necessary; a thorough
revision of current machines should be enough. Added advantage: Investment could be
spent on next generation of machines due in two years, expected to be superior to currently
available models. Additionally: New machines will not help with Sales agents just hanging
around on-site…
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Friday, January 14th, headquarters
Compiled an overview of all activities. Still some ambiguities left. Made a list of things to
look into, and a ‘to do’-list. Many people somehow involved in the problem. Supervisors
very willing to assist, but often lacking in technical expertise. Tech Support only available on
demand. Found four employees willing to take part in project team. Drafted division of
labour. Competitor with modern machinery supremely uninterested in receiving visitors.
Some of Lock’s employees expressed fear of being replaced by new machines.
Emailed detailed plan of attack to Lock. Lots of work to be done, but at least there is the
prospect of a solution.
Phase 3 Analysing the Problem
3
Tuesday, January 18th, at Lock’s
A day in the life of Tech Support. Meticulously investigated the entire production line. Found
frequent stagnation during many stages of production. Fabricating building materials, e.g.
cement trays, buckets, seems effortless. However, found significant underutilisation in the
production of garden chairs, crates, and window sills. Was told that problem had been
looked into earlier. Advice back then was to switch over to softer plastics. Why was that
advice ignored? Was it even ignored?
Took home a stack of Tech Support logs. Logs include overview of all malfunctions reported
and repairs performed over the past two years. First impression: seems no single
malfunction occurred more than once. Rules out an all-encompassing cause. Are the old
machines really the problem? Or is it the people using those machines?
Wednesday, January 19th, headquarters
Planned initial meeting with project team. Drafted agenda and sent out invites. Anticipated
on upcoming research. Looked for explanations. Why do the old machines keep falling
apart? Matter of age, of wear and tear? How are breakdowns related to low levels of
education among production staff members? According to the existing logs, only very few
malfunctions occur during injection moulding of plastics. During finishing, cutting machines
frequently fail when processing new, harder plastics. Similar failures occur when finishing
thermoplastics which soften when heated. But for those types of plastics, fewer instances
of stagnation seem to occur. What is the connection between the hardness of the materials
and machine failure?
Should allocate some time to ‘materials science’ during next week’s project team meeting.
Thermoplastics, polymers. What types of materials does Lock use? What happens during
the chemical processes those materials are subject to? What are the properties of those
materials?
Thursday, January 27th, project team meeting
Project group seems like a good bunch of people. Made progress on the research design.
Luckily, one of the members is a chemical engineer. He will draft a list of the properties of the
various plastics and other materials used. We will cross-reference his list with the list of
stagnations. What is the relationship between materials used and frequency of machine
failure?
Scheduled (interim) research report for mid-February.
Friday, January 28th, project team meeting
Tech Support to approach suppliers of possible new machines; going to look into what
types of materials can be processed in a new production line.
Chemical engineer Peter Wall discussed hardness and usability of the ‘plastics’. Quality
info. Loses Tech Support once he reaches ‘non-interlinked linear macro-molecules’ and
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‘Van der Waals interactions’. Some of the materials used by Lock are indeed rock solid,
harder than the materials used when the machines were first bought 15 years ago.
Research group present the cross-referenced table of materials and failures. Hardness of
materials seems hardly of influence on production errors. Only differences occur during the
finishing stages. Calculations show a link between hardness of plastics and cutting
machine failure. Data is quite rough. Researchers still looking into a way of obtaining more
accurate figures. Final report due in 14 days.
3
Thursday, March 3rd, at Lock’s
Research group asking for more time. Talked to Sales. New, harder materials mean tougher
products. ‘Market demands solid, quality plastics.’ Plastic window frames and sills need to
be rock solid. Even the smallest amount of give or elasticity, as found in softer materials, is
unacceptable in the construction industry. Garden furniture requires similar durability, on top
of design quality. Main competition of outdoor plastic chairs, benches, and tables is in the
form of durable, hardwood equivalents.
Wednesday, March 9th, headquarters
Received the requested research data. Staggering amount of info! Lots of detailed figures
for each type of plastic. Earlier impression confirmed: The harder the plastic, the bigger the
chances of cutting machine failure… and the bigger the chances of stagnation. Hardness of
materials plays no role during earlier parts of the production process. But those are not
without failure altogether. What causes the issues there?
Results should be sent to project team. What is next? Use softer materials? Sharper,
stronger cutting blades? Boost cutting machine power output? Need to invite project team
for creative session. How is Lock going to decide on a working solution? Have to think about
decision-making process. What is required of the solution? And who will have final say?
Phase 4 Formulating (alternative) solutions
Monday, March 14th, headquarters
Informed directors of research results by phone. Gone through decision-making process.
Entire board of directors needs to be involved in important investments. Consensus
required. But Lock needs several options to pick from. Company expects several alternative
solutions which all meet certain established criteria. Not all criteria equally important. A
question of weighting criteria. One key focus is on efficiency. Lock wants to be rid of
underutilisation during the production process. The most important issue is not the cost; it
is solving the problem.
Drafted and weighted a list of criteria. Sent to project team for comments. Buried under an
avalanche of argumentation for the weighting. Assigning own weights proves impracticable.
Weighting is subjective – impossible to please everyone. Asked several key players to
weight criteria instead. They divided 100 points across all criteria. Method proved
acceptable. Individually assigned weights seem surprisingly evenly matched. Averaged the
weight for each criterion. End results not that different from initial set-up. Difference: Lock
employees assigned greater weight to importance of machine noise. Legitimate difference.
They will be the ones working with these machines every day. Would this change have led to
a different final outcome? No way of knowing until after… when it will be too late.
Friday, March 25th, project team meeting
Inspiring meeting. Made inventory of ideas. Opted not to look at problems during earlier
stages of production for now. Focus is on the finishing stages, cutting the plastics. Many
ways of cutting possible: punching, sawing, laser-cutting, ‘water-cutting’, and die-less
crimping (without die-cut). Alternatively: Outsourcing, contracting out to third party. There
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are companies who specialise in CAD-driven cutting, managing complex shapes to
exceptional levels of accuracy.
Cross-referenced solutions with materials used. Thickness could be an issue when using
laser cutters. How to clean and dry materials once cut using water/sand method? How
much would outsourcing cost? Agreed to gather additional information. Drafted division of
labour. Information deadline is end of next week. Project group will get overview of all
options with scores per criterion. After that, establish advice via conference call.
Thursday, April 7th, project team
conference call
Water-cutting and laser-cutting less practical for Lock’s production process than initially
assumed. Three types of cutting tools and outsourcing option remain. Machine no. 2 came
out on top, followed at some distance by machines 1 and 3. Outsourcing is wildly expensive
and finishes last. Project team decides on cutting machine 2.
3
Monday, April 11th, headquarters
Articulated final recommendations. Sent report to Lock via letter and email. Brief talk with
management. Board of directors to make a decision next month. Have been invited to
provide short presentation.
Wednesday, April 20th, headquarters
Finished up presentation for board.
Phase 5 Choosing a Solution
Tuesday, May 10th, board of directors meeting
Board of directors chooses not to follow suggested advisory report. Lock has opted for
outsourcing instead. Specialised company to be put in charge of the cutting stage. Board
has different considerations regarding risks. New cutting machines are more advanced and
appear more reliable than current models. Unfortunately, operating them is not easy. This
poses a real danger of poorly finished products. And new machines still have a risk of
failing. Would place Lock back at square one. Also, possible to establish well-defined supply
terms. Outsourcing does appear more expensive, but board feels increase in costs can be
offset by reduction in staff. Expectations are that price negotiations can also be struck in
Lock’s favour. Have been tasked with executing the plan: begin the search for a ‘plastics
cutter’ along with the project team.
Phase 6 Implementing the Solution
Wednesday, May 1st, headquarters
Tried to bring project team up to speed over the phone. Two members on holiday. Sent them
a thoroughly detailed email. Did manage to talk to two others. Their response: resigned, but
understanding. Will be meeting next week to discuss next steps. Drafted initial plan for
implementation. Requested quotes from three potential cutting companies. The information
picked up studying cutting machines still proves useful: we know exactly what criteria the
possible partners need to conform to.
Friday, May 20th, project team meeting
Continued fleshing out the implementation plan. A lot of work needs to be done before Lock
can successfully outsource the finishing/cutting stage. Now faced with the first logistical
problem. Currently, finished products are neatly packaged and sent to wholesalers,
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sometimes to construction companies. Under new situation, intermediate products will first
need temporary packaging before being sent to the cutting company. Following cutting,
should they be sent directly to the wholesalers or clients, or first be returned to Lock? Will
the cutting company (be able to) provide packaging? Is there a possible role for wholesalers
to play? We have received quotes from the various companies. Drafted and weighted a list
of criteria with the project team. Johnsons’ in Swindon rates highly in terms of reliability and
craftsmanship, and is also the cheapest. The distance is a real drawback. Several trucks of
plastic intermediates would need to travel 100 kilometres back and forth every day.
Johnsons’ has confided they would be willing to set up a branch at Lock’s. Seems an
interesting possibility, deserves to be looked into. Drafted a division of labour.
3
Tuesday, May 31st, Johnsons’, Swindon
Went with Lock’s management to meet with Johnsons’. A fine business. Collaboration onsite at Lock seems a real possibility. Johnsons’ will be crunching numbers to come up with
a proposal.
Friday, June 10th, project team
meeting
Johnsons’ proposal currently with management. Drafted a detailed plan of implementation,
emailed to Lock management. Included separate communications plan. Rumours
concerning disposal of Lock’s cutting department already circulating. Company needs to
provide openness and offer perspective. Employees from that department will be posted at
Johnsons’. Need to be told they will still be working at Lock’s, though wearing Johnsons’
overalls. Suggested calling a company meeting as part of the communications plan. Next
week seems prudent.
Tuesday, June 14th, at Lock’s
Discussed implementation plan with Lock management. Company will be in charge of
executing implementation. Starting September 5th, Johnsons’ will be taking care of Lock’s
in Birmingham. Agreed to evaluate sometime spring. Time to send out the invoice.
Phase 7 Evaluating the Solution
Thursday, February 16th, headquarters
On the phone with Lock management. Company has been out of the red for the past six
months! Collaboration with Johnsons’ is proceeding perfectly. Barely any stagnation during
production. Outsourced finishing costs are higher than for finishing in-house. Revenue only
modestly increasing. Have yet to attract new clients. Lock does not seem overly keen on
evaluating. Wonder why? Possibly anxious that further evaluation will refocus on problems
occurring at earlier production phases – problems which are as yet unsolved. Managed to
convince management of the need for evaluation. Invited project team to discuss evaluation
method.
Friday, February 24th, project team meeting
Nice to see the gang again. One new face, Jim’s successor (following Jim’s retirement).
Mood is characterised by satisfactory collaboration with Johnsons’. Barely any problems in
production. Some questions as to the need for evaluation. Following a discussion, team
agrees that evaluation is necessary. Should make sure staff fully understand the need for
evaluation. Otherwise, they will not bother filling in evaluation forms. Some time spent on
matter of ‘over-capacity’. Using Johnsons’ new cutters, the finishing stage has been sped
up rapidly – meaning the production line is no longer occupied full time. Possibility for
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A TROUBLE-SHOOTER’S LOG
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increase in revenue there. But how? A lot of input for a questionnaire. Agreed to email
concept to project team next week.
Monday, February 27th, headquarters
Drafted questionnaire, emailed to project team.
Friday, March 5th, headquarters
Not a bad turn-out on the questionnaire. Staff filled in 33 forms via online link, 48 using
pen and paper. Hardly any surprises in finishing or production. Staff is satisfied overall.
Hardness of materials is no longer an issue. A lot of criticism involving Sales – apparently
not doing enough to reel in new clients. Account managers are good at maintaining existing
contacts, but cannot hold their own as representatives – not skilled at setting up meetings
or convincing new clients. Business canvassing course in order? Or recruit expertise from
elsewhere: new Sales agents? Drafted evaluation report with findings, advice and
recommendations; sent to project team for review.
3
Friday, March 14th, headquarters
Processed project team’s notes in the evaluation report. Sent in report to Lock
management. Red figures have been fully dealt with. Time to solve a new problem.
Suggested the problem of ‘over-capacity’ should be dealt with structurally in an
accompanying letter. Scheduled a call for Tuesday.
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§ 3.1
The MPSM in Practice
During each phase of the MPSM, you, the problem-solver, have to take
several different steps. What does each phase involve, exactly? What is the
result of each phase? And how does that work in practice? The following
table describes what has to be done during each phase and what each
phase results in. By way of example, the same has been described in
practical terms using the case example of the plastics plant at the start of
this chapter.
3
TABLE 3.1 A schematic overview of activities and results of the seven phases of the
Managerial Problem-Solving Method, plus a practical description of the same using
the Lock Plastic Production case.
THE MPSM (MANAGERIAL PROBLEM-SOLVING METHOD)
MPSM Phase
Activities
Results
Lock Case
Phase 1:
Defining the Problem
- drafting inventory of
problems
- make problem cluster
- select core problem
- express problem in
variables
- global problem
identification
- insight into
cluster of
problems
- company cannot
continue with
worn machinery
Phase 2:
Formulating the ProblemSolving Approach
- draft problem-solving
approach
- use D3 (Do, Discover,
Decide) to describe the
activities and knowledge
required, and choose from
the various options
available within your
approach
- plan for the
problem-solution
process
- activities outlined
- established need
for investigation
- plan of attack
established
Phase 3:
Analysing the Problem
- re-examine problem
identification and problem
cluster, and fill in missing
details
- look for causes
- review why any earlier
solutions have not worked
- use research cycle to
solve knowledge problems
- use a model to document
relationships between
problem and cause
- definition and
analysis of both
problem and
problem
identification
- reviewed logs
detailing failures
- researched
connection
between
hardness of
materials and
machine failure
- hardness is
important for
finish
Phase 4:
Formulating (Alternative)
Solutions
- describe a solution
- establish decision-making
process
- draft list of criteria
- scale criteria
- weight criteria
- invent alternatives or use
existing possibilities
- evaluate alternatives
- report on
alternatives and
their desirability
- board of directors
to decide
- board wants to be
able to choose
- project group to
weight criteria
- cutting machine
2 is the best
option
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A schematic overview of activities and results of the seven phases of
the Managerial Problem-Solving Method, plus a practical description of the same
using the Lock Plastic Production case.
TABLE 3.1 (cont.)
THE MPSM (MANAGERIAL PROBLEM-SOLVING METHOD)
Phase 5:
Choosing a Solution
- select one of the possible
solutions
- solution to the
problem
- company to
outsource cutting
stage
Phase 6:
Implementing the Solution
- draft an implementation
plan
- provide brief and step-bystep description of
activities
- detail approach to
possible resistance
- change
- filled in details of
plan
- came to
agreement with
Johnsons’
- openness
regarding
outsourcing
- September 5th:
cutting now
outsourced
- convince participants of
the need for evaluation
- evaluate all phases of the
MPSM
- perform structured
evaluation
- comparison of
effected situation
to desired
situation
Phase 7:
Evaluating the Solution
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3
- company not
desperate for
evaluation
- convinced board
- sent
questionnaire
- processed info
- out of the red
- deal with new
problem using
MPSM?
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4
In Search of the Core
Problem
4
Among the many possible things an organisation may feel are not going as
they should, it is important to find the one thing that really matters.
Something that will make a real difference: the core problem. You identify
the core problem during phase 1 of the MPSM, defining the problem.
This chapter addresses the following questions:
* What types of problems are there?
* Which are causes and which are effects?
* Which core problem do you deal with (first)?
* How do you make a problem quantifiable?
Problem Context 41
Problem Cluster 42
Quick and Dirty 41
Concretising Variables 47
Problem Identification 42
Decomposing (or Splitting) Variables 47
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Inventory First; Research Second
4
Mattress manufacturers Sleep-So-Well have
to deal with the facts; their machines are
old, their production staff is virtually
untrained, their sales team performs below
par, their margins are low, their turnover is
poor, and their profits are appalling.
Problems are mounting. You cannot deal
with all of them at the same time. You have
to make a choice.
‘We have a problem. Figures for this quarter
are disappointing. Would you please
investigate?’ Easier said than done. It is not
clear what exactly is going on. It could be a
number of things: from aging machinery to
poorly trained staff to unskilled salespeople
to low profit margins. The reason for the
investigation, disappointing results, is
known. You are an advisor to Sleep-So-Well,
and you have been advised to look into the
problem. Where do you start? What problem
do you focus on first? Do you look at one of
the bottlenecks, or do you focus on an
underlying cause?
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You can only choose a problem if you know
which ones are available to solve. First order
of business: making an inventory. You
underline all potential problems in the
company’s documentation. You draft a list of
all problems you encounter, using established
information and interviews with employees
who have some insight into the company’s
issues. You use the information you gather
as part of your inventory of knowledge.
Common sense will help you establish
connections between causes and effects.
That will tell you a lot, without any need for
dedicated research. You can establish the
age of the machines, and the staff’s training
levels: both things which can be classified
as problems. Which means there could be
more than one problem. During this phase,
you inventory all problems you encounter.
You are not yet concerned with acquiring
new knowledge. You systematically make an
inventory of the knowledge that is already
available.
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§ 4.1
IN SEARCH OF THE CORE PROBLEM
Reaching the Core Problem, Step by Step
Problems come in twos. Or threes. Or even more. For any company, there is
generally more than one thing going less than well. This overarching mess
of problems is called the problem context. There is usually not enough time
or money available to solve all problems at once. So which problem do you
deal with first? For every-day problems, the choice tends to be easy. What is
the first thing you do if you really need to fix a bike that has several
defects? Fix the tyre or fix the bell? The tyre, no doubt. Organisational
problems can similarly be classified in terms of urgency. You can arrive at
the core problem in four steps. Core problems are those whose solution will
make a real difference. You can identify them step-by-step by:
* Making an inventory of existing problems;
* Indicating the causes and effects, and use them in a problem cluster;
* Choosing which core-problem to deal with; and
* Making your problem quantifiable.
§ 4.2
41
Problem context
4
Lining Up the Problems
For your inventory, your sources are both interviews with staff and existing
written information; for example, earlier reports on stagnation along the
production line, or problems in other departments. Your work should be
quick and dirty. There is no need for real research just yet. First, you make
an inventory of existing data and perspectives. This creates a list of
problems both perceived and actual. You examine that list critically. Remove
any overlap. Formulate the problems in the most concrete possible terms. If
something is not a true problem, you remove it from the list. The result is a
cleaned up list of problems.
Quick and dirty
Gathering problems often seems easier than it is. You can easily tell
whether machines are old when you give them a once-over. But it is possible
they may still work just fine. You can establish that their age means they
have become unreliable. But even that does not mean they should be
replaced outright. It may be possible to resolve the problem by simply
having staff take better care when handling the old timers – better care than
they needed to take when the machines were originally installed.
In this example, you can completely untangle the question and express it in
terms of variables, or characteristics. You use the language of variables.
There are three variables in this case:
* the age variable: Is the problem due to the machines’ age?
* the reliability variable: Are the machines unreliable?
* the operational quality variable: Are the employees careful enough when
handling the machines?
Those three variables are all part of different problems. A problem can have
only one variable. If there is more than one variable, that means there is
more than one problem.
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§ 4.3
Cause and Effect
The problems in your inventory may or may not have any relation to each
other. To establish whether or not they do, you will first need to know the
relationships between the variables. Is reliability a result of age, and not
of employee usage? Or has usage always been a factor, even when the
machines were brand new? If so, why has this never been an issue until
now? Has staff training quality dropped? Asking questions like these will
help clarify matters during problem identification. Questions to consider
during this stage of the problem-solving method are:
* Why is this a problem now? And why was it not doing so before?
* Who are causing or influencing the problem?
* Who are experiencing hindrance as a result of this problem?
* Is this problem also found in other offices or similar companies? If so,
does it occur in the same order of severity?
Problem
identification
4
Problem cluster
FIGURE 4.1
Problem Cluster
Which problems are related? Which are not? It is time to find out the
connections between problems. The tool you use for that is called a
problem cluster (see figure 4.1). A problem cluster is used to map all
problems along with their connections. It serves to bring order to the
problem context, and to identify the core problem. Additionally, a cluster is a
helpful tool in communications with a client. It helps you discuss problems
in context and verify your impressions. Even an outsider can use a problem
cluster to identify and differentiate between cause and effect at a glance.
There is little use in trying to deal with all problems at once. Focus on one
or just a few problems whose solution would contribute greatly in improving
the problem context. Try to determine causes and effects. If you do not end
up dealing with causes, you may just be combatting symptoms instead of
underlying issues. Suffering from a headache? Take an aspirin for instant
relief. But what caused your headache in the first place? Was it stress?
Excessive drinking? If you do not fix the cause, you will have a sore head
again soon enough – too much overtime or too many drinks, and you will be
back where you started. A problem cluster is a tool used to create insight.
It is a model in which you indicate connections in a cluster of causes and
effects. You visualise the causal links between the various problems.
Figure 4.1 shows a problem cluster of problems at a production company.
It illustrates that problems are not isolated events.
Problem cluster of problems at a production company
Old
machines
Unreliable
machines
Low
occupancy
High production
costs
Poor quality
sales staff
Poorly trained
staff
Low
profit margins
Low
sales figures
Low
profits
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IN SEARCH OF THE CORE PROBLEM
43
Low profits tend to be indicative of other problems in a company. Ageing
machines, for example. Unschooled or poorly trained staff. Mediocre sales
agents. Production costs turn out to be high, and profit margins too low. And
sales figures are struggling as well. The problem cluster brings order to the
problem context and indicates the connections between problems.
A problem cluster is a relatively easy model for indicating causally connected
problems and bottlenecks. Other models do exist, such as the relationship
diagram, and the fishbone model or Ishikawa diagram (Ishikawa, 1985).
Filling in one of these fishbone models is often tricky, since all factors are
linked through the central spine. It shows you that matters are connected,
but not exactly what the nature of these connections is. A problem cluster is
different in that is shows you the connections between problems at a
glance. The core problem is instantly identified. The same is not possible
with a fishbone model. Figure 4.2 shows a fishbone model of problems at a
production company. The causes of the low profits are clear. But how are
these problems connected? What should you deal with first? Is low
occupancy the major issue? Or should you deal with the ageing machinery?
FIGURE 4.2
4
Fishbone model of problems at a production company
Low sales
figures
Poor quality
sales staff
Poorly trained
staff
Low
occupancy
Low
profits
Old
machines
§ 4.4
Unreliable
machines
High
production costs
Low
profit margins
Choosing the Core Problem
Your next step is to look for a core problem to deal with. In practice, companies
often deal with several core problems at once. If possible, the sensible thing is
to limit the number of core problems; better to deal well with one issue than
half-handedly with several. Choosing your core problem should take some
serious deliberation. You use the following four rules of thumb:
1 The problem cluster shows all problems you have identified as such. Not
all unwanted situations are problems for you to solve. A problem is only
recorded in your cluster if you are sufficiently sure it actually occurs. You
should be convinced that there is a relationship with other problems. If
not, leave it out of the problem cluster. If you end up dealing with a
situation that does not turn out to have been a problem, you will have
spent a lot of energy and goodwill. Additionally, you will have delayed the
solution to the actual problem.
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4
Nevertheless, you should make sure to write down those ‘problems’ you
are unsure of. They may end up being relevant after all. Even problems
you were initially unsure about can end up being the cause of your core
problem.
2 Follow the chain of problems back to these problems which have no
direct cause themselves. Initially found problems tend to be the result of
other problems. The problem cluster in figure 4.1, for example, shows
low occupancy as the cause of high production costs. Low occupancy
here is itself the result of unreliable machinery – which is due to the age
of the machines. In this case, the machines’ age is the problem furthest
removed along the cluster from the problem you started with. It has no
cause in itself, and is therefore possibly a core problem. This example
does not stipulate, for example, why the old machines have not been
replaced. And that probably does not matter either when it comes to
solving the problem. At this time, there is no need to speculate why the
machines were not replaced earlier.
3 If you cannot influence something, then it cannot become a core
problem. Say you deal in inflatable rubber dinghies. It has been a poor
spring, and a poor summer as well. Lots of rain, nearly every day. And
bad weather means few customers. You could, in that case, conclude
that the cause of your profit margins is due to the poor weather. Yet there
is little using in labelling the quality of the weather as your core problem.
How are you going to fix the weather?
But it is a different matter if you redefine the problem. For example:
Revenue depends on the weather. Fluctuations in weather conditions
lead to fluctuations in profits. Poor weather leads to reduced sales
figures. That is a problem you would be able to solve by looking for
markets elsewhere; preferably somewhere with nicer weather all-round.
If you cannot solve a problem, you should take one step forward in your
problem cluster, and deal with the next problem in line – provided that
problem is one you can deal with.
4 If more than one problem in the cluster remains, you should choose to fix
the most important problem. The most important problem is whichever
one whose solution would have the greatest impact effect at the lowest
cost. You should base your decision on a global impression, an educated
guess, since you do not yet know what the solution is going to be. It is
generally possible to say whether a solution is going to cost in the order
of millions or tens of millions, for example. And it is also generally
possible to have a stab at the effect a solution will have on the overall
situation, on the problem context.
At this point, you can perform a global cost-benefit analysis. That will tell
you what will have the most effect relative to efforts or costs. In figure 4.1,
for example, additional schooling for existing sales staff would be cheaper
than a long-term loan used to invest in new machines. Extra staff training
sessions may improve productivity as long as the machines keep working,
but will not do much good should the machines fail: the problem will remain
unsolved. In the long term, replacing the machines will probably lead to
greater profits that retraining the sales department. And so you end up
choosing to buy new machines, even though they may come at some cost.
However, once you have solved the core problem – here: buying new
machines – you may still choose to deal with another (core) problem, such
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IN SEARCH OF THE CORE PROBLEM
45
as staff training. You may even have to solve a new problem in some cases,
if the solution to the first problem you dealt with did not work, or only
worked partially. In the example, the unschooled staff may still need
additional training before they can handle the new machines properly.
You are advised to involve your client in your selection of the core problem.
That way, they will not be caught off guard by a solution to a problem they
were not even aware existed. Additionally, solving a managerial problem
does involve certain costs, for example in case you need to do research. For
that reason, you are generally required to submit your choice of core
problem to your client anyway.
Carefully Choosing Variables
Now that you have established a core problem to deal with, it is time to turn
to the discrepancy between the norm and the reality of your problem. The
first step is to accessibly formulate the problem. You should preferably use
a single sentence containing both the norm and the reality. For example:
customers have awarded our service over the past six months 7.5 out of
10, while we are after 8 out of 10. Exact figures, such as the 7.5 average,
are not always known. But you may have picked up some signals from
complaining customers instead. That may still leave you with enough
information to assume that satisfaction is below the norm of 8 out of 10.
Now you can deal with the problem, whatever its size, before it gets worse.
But if you are completely unsure if the problem falls below the norm – in
other words: whether a problem even exists – it is better to focus on a
different problem. What you can do in that case, is establish a baseline,
e.g. perform a customer satisfaction survey. The results of that baseline
can later be compared to new survey results.
4
In order to describe your problem, you have to express both the norm and
reality in terms of variables. It is important to keep the following three
things in mind:
* Be careful when selecting your variable. Whatever variable you use for
the norm and for reality should be defined carefully, even if you do not yet
have any relevant data. For example, it is important to understand that
there is a difference between a problem of insufficient profits or
insufficient profit margins. Insufficient profits may lead you to lower your
prices, thereby increasing your revenue. That is not possible if it is your
profit margin that is the problem. In that case, lower your prices would
lead to even lower profit margins.
* Express both the norm and the reality as the same variable. Do not say:
Last month’s profit share should have been 25%, but we only sold 1,500
products. That would not be a problem if 1,500 conformed exactly to a
25% market share. But if those 1,500 items only account for 10% of
products sold overall, you have a genuine problem. So in order to make
an insightful comparison between the norm and the reality, you should
use the same variable. Choose either market share in percentages, or
number of products sold per month.
* Use only one variable per problem. Trouble-shooters tend to want to
solve more than one problem at the same time. Or they focus on causes
and effects simultaneously. The result? They cannot choose between
employee motivation and productivity, and formulate the problem as:
‘Because motivation is down, productivity is down as well’; a statement
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that is difficult to express as a variable, essentially being a combination
of two problems! Which variable should you choose? In this example,
productivity is probably being affected by motivation. In that case, you
should deal with the cause, the core problem, of poor motivation.
§ 4.5
Making Problems Quantifiable
Next, you need to be able to come to grips with the problem. This means
expressing the norm and the reality of your action problem as a concrete,
quantifiable variable. That can often by quite tricky. It is easy to measure
revenue per employee per month; but how do you measure staff motivation?
Does it come in kilogrammes? As a concept, motivation is difficult to
express in measurements.
4
Variables that cannot be measured must first be made quantifiable. We call
this process ‘operationalisation’. Operationalisation is often a multi-step
process. The ‘loyalty to the company’ variable is first translated into, for
example, the ideas of ‘motivation’ and ‘work-involvement’. Then, you
proceed to step two: the actual operationalisation. For the concept of
motivation, you would use indicators: willingness to work overtime, amount
of absenteeism, turnover figures. These indicators can often be expressed
in units you can measure or count, such as: ‘Employees are willing to pull
two shifts of overtime per month’, ‘Absenteeism is at 4.3% of FTE’, or
‘Employment length is three years and four months on average’. An
indicator, in other words, is a variable you have made measurable.
This use of indicators in measurements is also common in the field of
physics. One example is a mercury-based thermometer. You observe the
level of the mercury to determine warmth or cold. You are not actually
measuring heat. You are using an indicator of heat, instead. By heating a
substance, in this case mercury, the vibrations or kinetic energy of the
molecules change. This leads to an increase in the volume of the mercury
filling, and that increase is what you actually measure.
In physics, one indicator tends to be enough to provide accurate and precise,
replicable measurements. This does not tend to hold true for other sciences
or fields. You are generally recommended to use more than one indicator.
But do not go overboard. One indicator can be not enough. Using two or
three will get rid of most accidental disruptions. For example: absenteeism
can be a fine indicator of motivation. But if the figures you use were recorded
during the outbreak of a seasonal flu, you will be looking at a substantial
increase in absenteeism which is not necessarily related to motivation at all.
But why should you be conservative when it comes to the number of
indicators? Indicators may end up disagreeing with one another if too many
are used. For example: You have opted to measure motivation levels using
the indicators of absenteeism, willingness to work overtime, and involvement
in staff outings. The absenteeism and overtime indicators may indicate high
levels of motivation; meanwhile, however, people cannot be bothered to take
part in the outings. Does that mean their motivation levels are low? The
staff outings do not relate to the work itself, but they do have something to
do with whether employees enjoy being part of the company. The more
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indicators you use, the bigger the chances that you begin to stretch the
meaning of the variable. In the example, you have stretched the meaning
from ‘labour-related motivation to ‘labour- and company-related motivation’.
Little wonder the indicators have started disagreeing with each other.
An indicator does not always work in all circumstances or in the same
manner. As mentioned, absenteeism may be an indicator for motivation. But
not in this example: The staff of an agrarian company calls on their
management. The employees work in a warehouse which, at times, is cold
and damp. The rain tends to get in. They want a location which is water- and
windproof. ‘Cannot be done,’ replies management: ‘Warehouses are
susceptible to draught. It comes with the territory. A little wind or rain is
inevitable.’ The employees beat a disappointed retreat.
One month on, the warehouse has been equipped with a new computer used
to keep track of supplies. In no time at all, the draughty building is sealed
hermetically in order to protect the computer from the elements. Management
is confident this will also improve motivation levels. As it turns out, motivation
levels do not improve at all. Even though the improvements in climate control
mean people call in ill less often, the resulting reduction in absenteeism has
no influence on motivation levels. The indicator has failed. In fact, motivation
levels appear to be dropping. The staff feels they have been had. ‘They take
better care of their machines than of their crew’, people grumble.
Because humans are emotional creatures, the laws of physics do not
always apply to their thoughts or actions. For example, the status of an
employee in many companies is directly proportional to the size of their
company car. But this same indicator, car size, will probably backfire if
applied to an organisation like Greenpeace. There, the status of an
employee who purchases a large, environmentally unfriendly vehicle may
actually be lowered as a result.
4
Concretising and Decomposing
In managerial problems, indicators are used to quantify variables. But there
is one condition: you have to be able to motivate the connection between
the indicator(s) and the variable(s). This means that, if you use indicators
for the variable of motivation, you have to find arguments using existing
literature or research which prove, for example, a connection between
increased absenteeism and low motivation levels. If that connection checks
out, you will have chosen well-founded indicators for your variable. Using
indicators, you highlight several aspects of your variable. Together, these
indicators may or may not exactly encompass the variable. The motivation
variable, for example, may be quantified using the indicators of
absenteeism, willingness to work overtime, and employee turnover.
Together, these indicators will not account exactly for 100% of motivation
levels. This method is called concretising variables.
Concretising
variables
Some variables can be split up into separate parts. Say you use revenue
and costs as indicators of profit. Combined, these two aspects add up to
your variable exactly. If you want to find out the output capacity of an
electrical machine, you will need to split up the output variable. That
requires the formula of power in watts, which is: power = current x voltage.
Or, in terms of units: watts = volts x amps. In these examples, the combined
indicators are exactly equal to the variable. This method is called
decomposing variables.
Decomposing
variables
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Tips for Using Variables and Indicators
4
Indicators help you quantify a problem. But how do you choose the right
indicators? And how many do you even need? Here are some tips for using
indicators:
* Do not use too many, and do not use too few. Use too many indicators,
and you risk contradictions between indicators. You will often also be
measuring something you did not intend to with your original variable,
because you are measuring another variable as well. In addition, you run
the risk of losing track of indicators. On the other hand, one indicator is
almost never enough. Use three or four. Any possible deviations which
occurred when you measured the various indicators can then be used to
offset one another.
* Take all circumstances into account when choosing your indicators. What
makes sense in one case may be pointless in another.
* When selecting an indicator for an effect, your best choice is a direct
consequence of the problem. Whatever you do, make sure you follow the
chain of cause and effect closely. Here is what not to do: you select
motivation as an indicator of profit in the chain ‘Motivation levels are high,
leading to increased efforts. The result is higher production levels for
better quality products. In turn, that leads to a higher price per product
and, as such, increased revenue. Eventually, that revenue will lead to an
increase in profit since costs have not gone up.’ Certainly, in this case
motivation is a yardstick of profit. But there are many other steps in
between the two that also have an effect on profit. As such, the actual
role of motivation is quite unclear.
* Never use a cause as an indicator. Doing so will mean you will not be
able to measure the effect of your solution. Think, for example, of using
working conditions as an indicator of motivation. Providing helmets,
safety goggles and protective clothing improves working condition in a
quarry. Your working conditions indicator increases, and so you know that
motivation levels increase as well. But the problem is that poor working
conditions were (part of) the cause of poor motivation levels. If you
change the working conditions, motivation levels will change by definition.
As such, you cannot use working conditions to measure motivation
levels. You need other indicators for that.
* You do not always need to express variables as numbers. If you want to
establish the perceived quality of a cinematic film, you can also use the
indicators good, medium, and bad. Those will tell you enough about the
quality without expressing it as a number.
Setting a Norm
Indicators make variables quantifiable. Those variables are used to
concretise the action problem. You indicate exactly what the difference is
between the norm and the reality. For example, this year’s increase in
revenue is only 7% instead of the 10% you are aiming for. Your variable is
revenue increase in percentages. The norm is 10% per year.
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A norm for annual increase in revenue, employee absenteeism, or turnover
does not simply pop up out of the blue. Setting a norm should be preceded
by an analysis. In this case, the increase in revenue of 10% may be needed
because the company has a position in a growing market. Substantial
growth will ensure that the market share, and hence a competitive
advantage, are maintained.
A norm must be set in a certain context. Manufacturing companies have to
follow applicable legislation. The implications of that legislation are taken
into account when setting the norm. The same applies for consumer
demands regarding product quality. High norms can lead to high priced
products. Hypodermic syringes, for example, are relatively expensive. Their
price is a result of the cost of their sterilised packaging. The effectivity norm
(here: sterilisation) is high, which means the price is, too. Here, base-norms
are at loggerheads. There is a dilemma between two base-norms: costs and
effectivity. Whatever the problem, there will always be certain base-norms at
odds with each other. Keep an eye out for these incompatibilities to make
sure you prevent setting unrealistic or unattainable norms.
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Summary
4
▶ When identifying a problem in an organisation, you proceed step by
step.
You make an inventory of existing problems. Your work should be quick
and dirty. You do not perform any real research. You inventory existing
data and perspectives. You use different sources for your inventory,
such as available documentation and information from interviews.
▶ Next, you look for causes and effects. You draft a problem cluster in
which you map the different problems and their mutual relationships.
Doing so structures the problem context, allowing you to identify the
core problem. You use the following rules of thumb for this process:
* You only include a problem in the cluster if you are sufficiently sure it
is an actual problem. If you are not, you do not add it to the cluster.
* Proceed down the chain of cause and effect until you reach the cause
which is furthest removed from your initial problem. That cause is no
longer the effect of another cause.
* If you cannot influence it, it cannot be labelled a core problem.
▶ Then, you choose which core problem to deal with. That will be the most
important problem in the problem cluster. At this time, you can choose
to first perform a global cost-benefit analysis for the approaches to the
different core problem. If you do, pick the most appropriate problem –
lowest costs, highest reward.
▶ The last step is to make the problem manageable. You express the norm
and the reality of your problem in a concrete, measurable variable. You
may need to use indicators in order to actually measure anything. When
using indicators, consider the following tips:
* Use more than one, but not too many, indicators, preferably three or
four;
* Consider all circumstances when choosing your indicators;
* Preferably use only direct consequences when using indicators to
measure effects;
* Never use a cause as an indicator.
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Core Concepts
Concretising Variables
A method of quantifying variables. Using indicators, you
highlight one or more aspects of your variable. You may
choose to use more than one indicator for the same variable.
Together, these indicators may or may not exactly encompass
the variable.
Decomposing Variables
A method of quantifying variables. Variables can sometimes
be split up into separate parts. Combined, these parts add up
to your variable exactly. The variable for profit, for example, is
made up of the indicators of revenue and costs.
Problem Context
The full scope of existing problems, which may or may not be
related.
Problem Identification
Systematically establishing a quantifiable core problem.
Problem Cluster
A model used to map different problems and their mutual
relationships. A problem cluster serves as a means of
structuring the problem context, and is used to identify the
core problem.
Quick and Dirty
(Identification)
A rapid, uncomplicated inventory of existing inventory of
existing data and perspectives made without performing
actual research.
Language of Variables
Expressing a problem as a variable. You untangle an issue
and define it as a series of variables, measurable attributes.
Some variables can only be measured using indicators. There
is only one variable for any problem.
4
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5
D3: Do, Discover, Decide
What activities should you undertake in in order to deal with your problem?
Who do you involve in the process? How do you know when you are done?
You set down your problem-solving method on paper. You draft your plan of
attack in phase 2 of the MPSM, formulating the approach.
5
This chapter addresses the following questions:
* What do you need in terms of capabilities, knowledge, and choices?
* How do you arrive at a systematic approach?
* What level of accuracy and detail does your plan need?
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The Best Financial Expert
for the Project Group
Your project group needs some financial
expertise. But who to choose? The
controller, the financial analyser, or the head
of administrations? Who would be the most
useful?
5
The company is expanding rapidly – and it is
not yet showing any signs of stopping soon.
It is time to take action. How about moving
to a new location? Opening up a second
branch? Building a new story onto the
existing building? Plenty of ideas, for sure.
But whatever the best short and long term
answers for dealing with the exceptional
growth rate, they need to be financially
sound.
Without a financial expert, the project group
is headed for failure. The project leader is
certain of that. Now that he is drafting his
plan of attack, it is down to a matter of
doing, discovering, and deciding. Doing is
for what actions need to be taken: Ask
someone to join the team. But who? The
controller, with his helicopter view? The
financial analyser, known for his solid
approach? Or the chief admin, who has
exceptional knowledge of the company?
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Best thing for it is to gather some
information – in other words, discovering.
The group leader picks up pen and paper,
and starts listing the pros and cons of all
three financials. The controller is not a
typical accountant, and keeps a broad
perspective. He is always busy. Everybody
seems to need his attention and financial
advice. The financial analyser is a young
guy, but he is a competent professional. He
does occasionally need some direction.
The chief admin is an all-round financial
expert. He knows the company back to
front. He is somewhat known for his rigid
conser vativism.
After much deliberation, the project leader
has to discount the controller; he simply
does not have the time. The chief admin is
not flexible enough for this project. So now
the choice is easy: The younger financial
analyst is the best match for the project
team, despite his occasional need for
direction. The project leader picks up the
phone and makes a call.
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Three Principles of a Plan of Attack
How do you set to work on a problem in a company? How do you begin your
approach if, say, the Czech specialist in seals, valves, and taps has not yet
reached the expected sales growth in Eastern Europe? With whom do you
take up the issue? Do you restrict yourself to the Sales department? Are
you sure that the sales concerns are shared by the entire company? Is
there enough money available to work with?
A complex problem has many sides. Should you review all of them? Where
do you even start? If you just jump in the deep end, you run the risk of
overlooking something. You may keep coming across new aspects that need
to be highlighted. If you are not careful, before too long you will not be able
to see the forest for the trees. What you need is a plan of attack. You
formulate your approach using the following three principles:
1. Use D3: Do, Discover, and Decide
2. Proceed according to a systematic approach
3. Describe your plan in detail
D3: Do, Discover,
and Decide
5
§ 5.2
D3 Explained
When approaching an action-based problem, you go your own way. You
venture out to come to a solution. You research and investigate until you
have the information you need. That requires the use of the research cycle
(see Chapter 11). Your approach and your investigative research will often
involve making choices. These choices involve the principle of D3. Here, D3
is not Dichlorodiphenyldichloroethane, a breakdown product of DDT; nor is it
a rather unimpressive anagram of the commonly used abbreviation of threedimensional stereoscopic vision. D3 refers to the three aspects of Do,
Discover, and Decide.
Research cycle
The first aspect, Do, encompasses all activities you need to perform. That
includes things both easy and hard. It can be as simple as writing a ‘to
whom it may concern’ introduction of who you are and what your role as
investigator of employee absenteeism is going to involve. Basically
everything you need to do from drafting a problem-solving approach to
proposing a budget to requesting support for your investigation.
The second, Discover, is everything you need to know and understand. An
important part of that is asking questions with the goal of obtaining
knowledge. There are things you have to figure out. Formulating your
questions so that their answers give you the information you need, is part
of Discover.
The third and final aspect, Decide, is about selecting the proper options.
Who do you involve in your investigation? Who do you leave out? Similar
choices are made in your problem-solving approach. What do you do if
working conditions are poor? Do you focus on the quality of the old
machinery, or the climate control system along the production line? What do
you take into account, and what do you ignore? If there is more than one
alternative, you choose the winning option based on a comparison of criteria
you have weighed up.
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Do, Discover, Decide. Other phases of the MPSM will also involve you having
to perform several different actions. You may not know where to start, what
to ignore. If you find yourself in that position, turn to D3. It will help you get
your affairs in order.
§ 5.3
5
Benefits of a Systematic Approach
You generally deal with managerial problems alongside others. Working in
project teams is the norm. In addition to your team, you need people from
various divisions in the company: IT, finance, executive decision-making. You
will deal with the owner and the victims of the problem, and with people
assisting you in solving the problem even though it does not affect them.
You need to establish everyone’s position clearly. Here, a systematic
approach is your friend. You ask questions, and make sure to take at least
the following steps:
1 You find out which parties are forced to deal with the problem, aside from
the problem owner. Who are being troubled by the problem? Those are
the victims.
2 You establish which parties will be important in investigating the
problem. Will you need permission from certain people? Are they allowed
to free up time for you? Who is in charge of financial support, of
manpower? Are you free to approach clients for interviews?
3 You determine what information you need to deal with the problem.
Where can that info be found?
4 You track down the people you will need at later stages in advance.
Whose help will you need to analyse the problem? These are your
helpers.
5 You set up a division of labour for your assistants. Who does what? How
do you put the right people in charge of the right tasks? You may need to
split up the problem. This will allow you to assign specific project team
members (and their skills) to different parts of the problem.
6 You formulate a list of conditions. Are there any limitations? Is it possible
to provide a solution without having to deal with legal complications? Are
redundancies on or off the table? When does the problem need to be
resolved?
This approach will give you an insight into what people to recruit for your
project team. It generally also sheds light on any parties that still need
convincing, and indicates people who will not be of much use – either
actively or passively. People not affected by whatever bottleneck you are
looking into, tend not to be desperate to work on its solution with you. They
will be too busy doing what it is they are doing. Some employees may
simply not feel like participating. This phase tends to be where, you, the
trouble-shooter, come across sensibilities or hidden agendas that may
hinder an effective approach; useful information when it comes to
determining who you should count on in your project team, and who you can
expect to help pave the road to a solution. Think, for example, of managers
who free up funds or employee time to assist in your approach.
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D3: DO, DISCOVER, DECIDE
57
Walking A Thin Line
Some plans of attack are described down to the last detail. Every individual
activity during every individual phase has been fully worked up. You might
read: ‘Project member Young to interview product line staff in week 1.
Interviewees: Johnson, Rudd, and Williams. Young to ask members 12
questions (see appendix 3.2) each. Information from interviews to be
processed according to model found in appendix 3.3 …’ As plans go, this is
quite a detailed example. The particular situation to which it is applied may
require this level of detail. In other cases, it may be more useful to limit the
description of your planned activities to broader terms. Note that there is no
fixed rule regarding level of detail of a plan of attack. But there are some
guidelines:
* Accuracy is key. Depending on the situation, activities should be
described broadly or in detail. Your description should be able to serve
as your fall-back during the problem-solving process. The level of required
detail of your approach tends to become clear as you are formulating it,
since that is when you become aware of what exactly the job requires.
* Avoid obligatory descriptions such as: ‘This is required in order to involve
all employees in the approach’. Be selective! You do not always need to
involve everyone in all aspects. Focus on the people who have to deal
with the problem. And avoid creating expectations you may not be able to
live up to. If people are asked for their input, that does not necessarily
mean they get a say in the decision-making process. Be sure they
understand that. Make sure there are no false impressions.
* Demonstrate that you are able to solve the problem. Among other things,
your capability will be demonstrated by a carefully and accurately
projected final result. A solid approach and a capable project team will
do the rest.
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Summary
▶ When formulating your problem-solving approach, you describe you
planned actions as precisely as possible. You review all actions needed
to successfully resolve your approach. You need D3 (Do, Discover,
Decide). Do is everything you need to undertake; Discover is everything
you need to know; and Decide is selecting the appropriate options.
5
▶ The next step is systematically mapping your problem. This starts with
asking the question you need answered, including at least the following:
* Which parties have to deal with the problem? Who are the owner and
victims of the problem?
* Which parties are in charge of the required resources?
* What information do you require?
* Whose help will you need during which phases of your approach? Who
are your helpers?
* What is the division of labour in your project team?
* What are the possible or existing limitations?
▶ Once you have the answers to your questions, you can begin formulating
your approach. This requires precision. When formulating an approach,
consider the following pointers:
* Be accurate in describing your activities. You should be able to rely on
your descriptions later.
* Be selective! Only write down what you need for your problem-solving
approach. Do not overstate or embellish matters.
* Demonstrate that you are able to solve the problem.
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Core Concepts
D3: Do, Discover, Decide
A method used for bringing order to a problem-solving
approach. D3 stands for Do, Discover, and Decide. Do is
everything you need to do for your approach to work; Discover
is everything the parties solving the problem need to know;
and Decide is selecting the appropriate options from the
multitude of aspects of an often complex problem.
Research Cycle
A systematic approach to research performed in order to
obtain required information. Allows the researcher to arrive at
a conclusion through a stepwise process, thereby answering a
previously formulated problem definition.
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6
In Search of the Unknown
You have established what the problem is in broad terms. But this may not
have answered all of your questions. You may still be wondering what exactly
is going on, and what is causing it. You need hard data. The information you
need may already be known, or at least available. Often, your next step will
be to conduct research. You deal with knowledge-based problems in phase 3
of the MPSM, analysing the problem.
6
This chapter addresses the following questions:
* What exactly is the bottleneck?
* What is causing it?
* Why have earlier solutions not worked?
Problem Analysis 63
Sequential Order 67
Measurement Levels 64
Statistical Relationship 67
Causality 67
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Pimp My Production Line
6
Monday morning, a vase of flowers on the
desk. Location director Brown’s first day at
work. He checks his watch. Nine o’clock.
Brown opens the meeting. He tells everyone
a little about himself, and suggests the
managers to briefly introduce themselves
and what it is they do. He also asks
everyone: What do you feel is the company’s
most significant problem, what do you think
is causing it, and how do you think it could
be resolved?
The marketing manager jumps the gun:
‘That is an easy one. Our production costs
are too high. As a result, we do not turn a
large enough profit. It is all down to those
old, unreliable machines. So here is my
solution: We invest in new machinery.’
The operations manager gives a consenting
nod: ‘I could swear I was listening to myself,
just then. Last week, production hall 2 was
shut down. It took nearly all of Thursday to
fix the issue. I would think those machines
are over 20 years old by now. There is only
so much they can take. The machinery is in
desperate need of renewal.’
It goes on for a while, one manager after the
next. Brown listen to his team patiently.
Once everyone has had their say, he takes
the floor: ‘Thank you for your input. I must
confess to some slight confusion. You all
seem to know what the problem is, you
seem to know its main cause, and you even
seem to know how it should be solved. So
why has nothing happened. Why is there no
replacement plan for the old machinery?
What is holding us back?’
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The assembled group is quiet for a moment.
Then, the financial manager says: ‘Money.
There is none available for renewing the
production line.’ The operations manager
shakes his head at that: ‘The problem is not
that there is no money. It is to do with the
unwillingness to spend any. New machines
would set us back a little in the way of
finances, that is true. But did you know there
is an entire industry devoted to refurbishing
the older models? There is a company in
Lancashire, specialising in reconditioning
factory machinery. They inspect the old
machines and revise what they can. We
would only need to replace the machines
they cannot pimp up. So we would be able to
reconstruct out entire production line from
the refurbished existing machines and
maybe one or two new models.’
‘I was under the impression pimping is
something that was only done to old cars’,
smiles Brown. ‘All kidding aside: We should
start by having a look at what is actually
going wrong during production. Pimping up
our existing machinery could be a solution,
but we would first need to establish that our
machines are suitable for that process. And
who knows, there may be other things issues
as well. I am going to assign a project team.
We need to start making some headway. I
want this problem analysed in detail, so we
know exactly what is going on. We need to
prevent investing time and money in a
solution that does not address the actual
problem. Dig deep, I say. We will untangle
everything until we are sure we know what is
causing us grief.’
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63
Looking Closely at the Problem
How is the problem constructed? What details would give you greater
insight into the cause(s) of the problem? Why are those old machines more
often turned off than on? Is it a matter of production efficiency? If so, during
what production stages? And why have other, earlier solutions not worked
properly?
You have already had a quick and dirty look at the problem. You have also
gained insight into causes and effects using the problem cluster. You know
what core problem you want to address. Next, you need to start digging
deep. You begin your research. That can also involve looking at possible
causes you had not yet assigned to the problem cluster. In essence, it boils
down to three activities:
1 Filling in details
2 Looking for causes
3 Reviewing why earlier solutions have not been satisfactory
§ 6.2
Locating the Problem
During the problem analysis, you take a renewed and very close look at the
problem you have selected. You look for details; for example, where exactly
is the problem located? You know there is a problem along the production
line, but that is quite a large area. Where is the hitch? Is it an assembly
problem, or a matter of supplying resources? You try to visualise the
bottleneck as accurately as possible.
§ 6.3
Problem analysis
6
Researching Causes
Next is a quest for possible causes of the problem. Closely examining the
production line may have told you that the problem comes from a tardy
supply of resources. So your question then is: What is causing the
resources to be delayed? You attempt to solve a knowledge-based problem
using the research cycle (see Chapter 11). That is the default procedure
when research is needed. Sometimes, other people may already have the
information you need. All you need to do is check. But in many companies,
you will need additional information – knowledge obtained through research.
There are various successful researching methods. You can conduct
interviews, or reference scientific literature to find known causes of similar
situations. Whatever your approach to research, you need to have some
idea of where to start looking. And that is easier said than done. You may
have found many different causes, and not be able to research them all. It
is better not to waste your time in pursuit of the most unlikely causes; so
your focus should mainly be on the most logical ones. During this initial
orientation, it may be useful to have a sneak peek at some of the available
literature on your subject. It may give you some ideas for possible leads in
your research. Do not jump to conclusions – you will not find any new
answers without first conducting research.
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In your research, you should mind the following:
1 First list the possible causes of the problem you know of.
2 Involve others in looking for causes. Talk to key figures and people
dealing with the problem.
3 Select a limited number of causes to examine in detail. This is often not
as simple as it seems, since you may have found many potential causes
following your interviews and talks. People rarely come up with exactly
the same causes. Their ‘truth’ is often based on a certain (self)interest.
Deciding which causes are the most important is something you should
do yourself.
6.3.1
Quantifying Variables
An action problem is expressed in variables. This was part of phase 1,
defining the problem. A knowledge problem is also expressed in variables
you have concretised and made quantifiable using indicators. Indicators are
also applied to the possible causes of a knowledge problem. Causes can
be just as vague as the actual problems. For example, insufficient
communication between internal and external service departments is a
possible cause of unsatisfied customers; a cause you can research. But
what exactly is the nature of this cause of dissatisfaction? Are there no
meetings scheduled involving both departments? Is the external service
department unavailable because its staff tends to be on the road? Do the
representatives give only the same information as the people available via
the helpdesk? Does the internal department adequately respond to signals
received by the external department? These types of questions all represent
possible indicators of ‘insufficient communication’.
6
Measurement
levels
Measurement Levels
You have assigned variables to the causes. You have also concretised the
variables using indicators. Your next goal should be to measure the
indicators as accurately as possible. There are four different measurement
levels. These levels vary in terms of precision:
1 Nominal Variables. The values of the variables are not quantitatively
related. Religious conviction is an example of a nominal variable. You
cannot, for example, say that a protestant church member has either
more or less religious conviction than a member of the catholic church.
They just have different convictions.
2 Ordinal Variables. The values of these variables make some claim as to
quantity, but their exact value is unknown. They can, however, be ordered
or sorted - for example from greatest to smallest - since you know that
one value is larger than another. You do not know, however, exactly how
much larger. If, as part of a questionnaire, you are asked to what degree
you agree with a certain statement, there tend to be different possible
answers – for example, five options ranging from ‘fully disagree’ to ‘fully
agree’. This tells you that someone who indicates a ‘somewhat agree’
option is less in agreement than if they had selected ‘fully agree’; but
you do not know exactly how much less.
3 Interval Variables. The values of these variables are expressed in
numbers, as amounts. It is possible to comment on differences between
values of variables. The interrelationships between the different values
are still unclear. Say that you leave your office building, which is currently
at a snug 20 degrees centigrade. Outside temperature is 14 degrees.
Wearing only a shirt, you are suddenly quite chilly. You run toward your
car. You have experienced a 6 degree drop in temperature. But you
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cannot express your feeling of chilliness as having increased by around
30%. If you express temperature in kelvins, the office was at 293 and
outside was at 287. That is a decrease of around 2%. Percentages, in
this case, are meaningless.
4 Ratio Variables. Like interval variables, the values of these variables are
expressed in numbers. Here, however, it is possible to establish the
ratios between values. If, for example, the political party in office goes
from 88 seats to 66, then that is a 25% decrease in the number of seats.
Researchers should strive for the highest measurement level, ratio level.
This allows for the most quantitative of analyses. Tests may be conducted in
a such a manner as to yield results that can be measured at a higher level.
Employee satisfaction, for example, can be measured at ordinal level using
a questionnaire. Alternatively, you can measure how many people leave the
company during a year. The higher the measurement level, the better you
can compare results. But you should always be mindful that your ‘hard data’
does not lead to a false sense of security. Counting how many employees
leave tells you nothing about why they leave. Is it because their partner has
found work elsewhere, or because they are expecting children? Or does it
actually have to do with how they enjoy their work? Questions focussed on
the direct causes of employee turnover – ordinal measurements, in other
words – would probably give you a better insight into the matter in this case.
6
The reliability of your research results is another factor influenced by the
measurement level of your variables. A measurement level can be a
deciding factor when determining which statistical tests you can and cannot
apply. This will have an effect on, for example, the size of the sample used.
6.3.2
No Research for Its Own Sake
The problem analysis is concerned with relationships between causes and
effects. You attempt to visualise all factors that could influence the
solution. This can lead to a vast swathe of possible causes and issues coresponsible for the problem. In your quest for explanations of problems, do
not feel you should untangle every single little detail. There is no point in
conducting research for the sake of having conducted research. Some
problems do not require a cause to be fixed.
Imagine you are staring in confusion at the nail that was lying on the road,
now sticking from your wheel. You may be wondering how that pointy little
thing got to be where it was, but the answer to that question will certainly not
bring you any closer to the problem of your flat tyre. For that, you will need to
set to work fixing it. If the nail is still lodged in there, your first order of
business is to take it out; now, you are one step closer to a solution. Similarly
for an incidental case of pneumonia: If you have it, you will want to be rid of it.
The doctor may not particularly care whether you contracted it when you fell
into cold water, or were standing somewhere draughty for too long. Currently,
the problems that need to be resolved are a painful chest and possible fever.
But if your pneumonia is not an isolated event, if you have been suffering
from it more frequently, then that is a different story altogether. In that case,
the doctor will most definitely want to check for bacteria, viruses, or fungi.
And, perhaps, the conditions that caused you to contract your illness should
be established to help prevent the same thing from happening again.
Here, the problem that needs to be solved is your susceptibility to
pneumonia – not your pneumonia itself.
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Three Tips for Researching Causes
1 When faced with a multitude of causes, choose only the most important
ones that you know you will be able to influence. Something you cannot
alter does not need to be researched. The weather, for example, is a
major factor in revenues of holiday camp sites or ski lodges. But try as
you might, you will not be able to make it snow or cause the sun to come
out.
2 Keep in mind that some causes trump others. Do not turn all causes into
knowledge problems to be researched using the research cycle. Focus on
those causes you expect to have a major influence on the solution.
3 Try to examine as many relationships as you can within your available
timeframe. Scientifically speaking, nothing should be excluded. But since
time is virtually always limited, you need to be practical about matters.
6.3.3
6
Using Models to Outline Variable Influence
The relationships between the problem and its causes can be outlined in a
model, a depiction of reality. This model is similar to the problem cluster
you used during phase 1 of the MPSM. You work with a variable that may be
expressed using indicators, and arrows that indicate causal relationships.
Note that there are several differences between this model (see figure 6.1)
and a problem cluster (see figure 6.2). You fill in the model with whatever it
is you do not know and therefore need to research. The problem cluster is
filled in with things you already do know, omitting things that you do not.
And another difference: A model is about establishing relationships, not
about depicting known relationships. You do not assign values to the
variables as you would in a problem cluster, but you adjust the variables to
discover if there is a relationship. For example, a model can be about the
relationship between working conditions and motivation. The problem
cluster would address these aspects in terms of specific qualitative values,
such as poor working conditions as the cause of low levels of motivation.
The following is a depiction of outward similarities between a model and a
problem cluster.
Figure 6.1 shows the model of the problem: ‘What is the relationship
between working conditions and motivation?’ You use this model to indicate
that you wish to examine what happens to employee motivation levels if
there is a change in working condition.
FIGURE 6.1
Relationship between working conditions and motivation
MODEL
Working conditions
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Figure 6.2 shows a part of a problem cluster for the problem: ‘Motivation
levels (too) low’. You use the problem cluster to indicate the encountered
relationship between levels of motivation, which are too low, and the
working conditions, which are poor. This shows you that poor working
conditions cause motivation levels to be (too) low, and that these conditions
are therefore a core problem.
Part of a problem cluster for the problem ‘Motivation
levels (too) low’
FIGURE 6.2
PROBLEM CLUSTER
Poor working conditions
§ 6.4
Motivation level (too) low
Considering Earlier Solutions
6
Problems are often older than when you just start researching them. A
production line in difficulty will have had troubles long before today. And it is
frequently already known what the bottleneck is; delayed resource supplies,
for example. In that case, there will have been suggestions for stricter
terms and contracts with supply companies – but for some reason, those
contracts were not implemented, or did not have the desired effect. You will
often find earlier proposed solutions in company documents, some entirely
untried. During this phase, you should review whether those earlier
solutions can actually work this time around.
Causal Relationships
During the problem analysis phase, the most important feature is
relationships between problems and their causes. A relationship can be
defined as a causality, a cause-and-effect type relationship, if it meets the
following three criteria:
1 There is a sequential order: The cause must precede the problem, the
effect. The cause of poor working conditions leads to the problem of
poor motivation levels.
2 There is a statistical relationship. If the value of the cause changes, so
should the value of the problem. The reverse is also true: if the value of
the problem alters, so should that of the cause. If the weather is good,
you will find many people at the beach; if the weather is bad, the
beaches tend to be empty. This is a statistical relationship between the
quality of the weather and the number of people at the beach.
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6
Not every statistical relationship is a causal one. By way of example,
consider the once established statistical link between the number of
people enjoying a beach-front coke and the number of people drowning in
the sea. You should not conclude that drinking coke is hazardous to your
health – the number of drowning victims could also be higher as a result
of more people visiting the beach on a sunny day. More people are likely
to have a refreshing beach-side coke on a sunny afternoon than on a
rainy morning, since there would be fewer people at the beach anyway.
3 There are no alternative explanations for this part of the problem. There
is nothing but one single cause of the problem. For example: A company
was suffering from a large amount of downtime. The only apparent cause
was motivation. The problem disappeared when the manager addressed
the motivational issue. He told a colleague with the same problem:
‘When I came on board, people’s motivation went up, and downtime fell.’
The other manager shakes his head and says: ‘We were in the same
boat: a lot of downtime, poor motivation. Even when I addressed the
issue of motivation, nothing happened to the downtime.’ The first
manager comments: ‘I clean forgot! I also brought in some new
machines. That helped improve motivation and decreased downtime. The
new machines were the actual solution to the problem.’ In this example,
no causal relationship exists between motivation and downtime. But
there was a causal link between two other relationships. The first is the
quality of the machinery and motivation – the new machines were more
convenient to work with. The second was between the quality of the
machines and the amount of downtime – the new machines produced
better quality products. The only factor causing the problem in this case
was the quality of the machines.
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Summary
▶ During the problem analysis phase, you conduct research because you
need more information. You review your problem identification and
problem cluster. You fill in the missing details. You look for as yet
unknown explanations for your problem. You re-examine previously
suggested solutions.
▶ You use the research cycle to solve your knowledge-based problem. This
takes you to the answer to your problem definition step by step.
▶ During your research, you keep the following in mind:
* Make sure you quantify your variables using indicators.
* Formulate your variables at the highest possible measurement level.
* Limit your research to important causes that will contribute to the
solution. Review as many relationships as you can in the time you
have. Choose only causes you can affect.
* Use a model to record the relationships between problems and
causes.
* Look for causal relations and not just statistical ones.
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Core Concepts
Causality
The relationship between cause and effect.
Measurement Levels
Levels at which variables can be measured. There are four:
* nominal variables. Values are named.
* ordinal variables. Values are ordered.
* interval variables. Distances between variables are known.
* ratio level variables. Ratios between variables are known.
Problem Analysis
Researching a problem to find out its causes, and
establishing interrelationships between causes and effects.
Statistical Relationships
A numerical relationship between a cause and a problem.
Involves variables whose values change together.
Sequential Order
A condition for causality. A problem is always preceded by a
cause.
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7
An Overview of Options
Now that you have established the size and shape of the problem, it is time
to start working on a solution. You review your options for removing the
problem from the equation. You weigh up the various options, and provide
an insightful report for your client. As such, during phase 4 of the MPSM,
you formulate alternative solutions, so that management can make a final
decision.
7
This chapter addresses the following questions:
* Which criteria should a solution conform to?
* Which criteria are the most important?
* How do you arrive at alternative solutions?
Consensus 76
Sub-Attributes 78
Qualified Majority 76
Majority Rule 81
Attributes 77
Lexicographical Method 81
Non-Compensatory Criteria 77
MoSCoW Rules 82
Conjunction Criteria 77
Synectics 85
Cut-Off Criteria 77
Morphology 86
Killer Requirements 77
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HQ in Hampshire or
Hertfordshire?
Selemat Makan and HongKong Food have
joined forces. The two major suppliers of
Asian foodstuffs have decided on an equal
authority merger. The first problem they run
into is where to establish their headquarters
and central storage facilities. Should they
go for Hampshire, known for its large
Indonesian community in addition to being
the base of operations of Selemat Makan?
Or in the south of Hertfordshire, nearer the
London basin – a major international melting
pot and home to HongKong Food?
7
The management boards are unable to
decide. They have postponed making the
final call for now. A project group has been
asked to provide advice. Project leader York
Fu has invited both managing directors for a
meeting. He subjects both to an intensive
interview. First, he asks whether it is
essential that the new headquarters and
central storage are located close together.
Then, the following questions follow in rapid
succession:
* Who are involved in the final decision?
Both boards? Or just the directors?
* Does the advice need to be limited to
either Hampshire or Hertfordshire? Or
would the newly merged company also
consider other options?
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* Will the final decision be made based on
majority rule? Or must all parties reach
consensus?
* What are the most important criteria? Are
they all equally important?
* Does either director have any personal
preference?
And on, and on… York Fu’s barrage of
questions seems inexhaustible. The
directors are first asked to debate the
issues. Then, for each question, they have
to provide only one consensual answer.
All questions answered, York Fu and the
project group set to work. Two weeks later,
he presents their findings to the gathered
deciding parties of the new Asian foodstuffs
wholesaler. He has brought a PowerPoint
presentation illustrating the decision-making
process. It details which arguments were
considered, and how important each
argument was considered to be. Based on a
professional approach, York Fu and his team
have provided a decision document
containing several options. Using their work,
York Fu could make a final decision – but he
will not be the one doing so. That honour is
left to the deciding parties, hopefully along
the lines of York Fu’s proposal.
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§ 7.1
AN OVERVIEW OF OPTIONS
75
Seven Steps to a Possible Solution
You have examined the problem from all angles. You know exactly what is
going on. Time for a solution. But what criteria should that solution fulfil?
Say your company needs to deliver parcels around an urban area. Do you
choose the latest Mercedes Vito or a Ford Transit for your drivers? Or do you
opt for an environmentally friendly approach, choosing transportation by
bicycle instead of delivery van? What is clear is that the current fleet of cars
has fully depreciated. What you need is a possible way out of this dilemma;
preferably more than one. You have to come with and review several
options. You do so according to the following seven-step plan:
1 Defining the decision
2 Defining the decision-making process
3 Establishing criteria
4 Scaling criteria
5 Weighting criteria
6 Coming up with optional solutions or using existing possibilities
7 Evaluating options
§ 7.2
Defining the Decision
You start by carefully defining what the decision actually entails. Does your
client only have to choose which car would be the best option for delivering
parcels around the urban jungle? Or is that decision preceded by another
process, where the best mode of transportation for the narrow, pedestrian
oriented city streets still has to be determined? In case of the latter, the
choice is not between different delivery vans, but between, for example, a
bike, a lorry, and an electric van or coach. You may first have to decide
whether the currently used vans even need to be replaced, or whether they
should merely be refurbished. That all depends on the findings that follow
from your problem analysis. The question of the best type of delivery van
only becomes relevant if you know for sure that new delivery vans are what
you need.
§ 7.3
7
Defining the Decision-Making Process
The party responsible for a final decision often consists of a group of
people. The members of such a group may hold different or even conflicting
views. One thing the decision-makers definitely need, however, is structure:
a set of rules used to guide the decision-making process. The following are
important points to consider:
* Establish who the decision-makers are. Is it down to one individual, or is
it the responsibility of the entire board of directors? Take into account any
sensitive areas or issues, such as possible relationships between one of
the decision-makers and, for example, a supplier of delivery vehicles.
Such issues need to be approached mindfully, and possibly diplomatically.
* Determine how the decision is constructed. Is it a one-time vote between
all possible available options? Or is the number of available options
gradually reduced, with each round of selections using a decreasing
number of decision-makers? For example, a project group may be put in
charge of reducing a longlist of suppliers to a shortlist. That shortlist is
what the board uses to make the final decision.
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Consensus
Qualified
majority
7
* Agree on rules for the decision-making process. Are the decisions to be
based on consensus? Or are they down to majority rule? And, in that
case, does it concern standard or qualified majority?
* To weight or not to weight. Weight is what indicates how important
different criteria are. The higher the weight, the more important the
criterion. Assigning weight to criteria has its pros and cons.
An important reason in favour of working with weighted criteria is that if
you do not assign weights, you run the risk of missing out on the best
option. Say you have to choose between two cars. Meaning to save time,
you do not assign weights to individual criteria, being speed, fuel
efficiency, and number of passengers. Your first option, car 1, has a top
speed of 200 kilometres per hour, good fuel efficiency, and room for four
individuals. Car 2 has a top speed of 220 kilometres per hour, is less
economic in terms of fuel use, and is able to accommodate five
individuals. As you have not weighted these criteria, you will probably
choose whichever car scores the highest in the largest number of criteria
– here, car number 2. But are those additional 20 kilometres an hour
that important if you have to deal with a 120 kilometre an hour speed
limit? Does the extra passenger room even matter if you are likely to
make most of your trips by yourself? Are those criteria worth the
additional cost from the increased fuel consumption? Maybe, maybe not.
The only way of knowing for sure is by weighting.
Weighting does have its drawbacks. It is demanding work, and not always
reliable. People sometimes (sub)consciously assign different weights
from what they have indicated. And they do not think to inform the
trouble-shooter of that fact. Criteria can be split up into different parts
which can be weighted individually. That is a process that can carry on to
near infinity, causing you to lose sight of the bigger picture.
In some cases, it does not matter whether or not you weight your criteria.
If all criteria are approximately equally important, weighting criteria will
often lead to the same choices as not weighting them. You can generally
only establish whether criteria are equally important once you have an
idea of their weights. To weight or not to weight? Whatever you do, at
least try to estimate whether there are clear potential differences in
weight between criteria.
* Be mindful of subjective elements. Subjective elements are issues
which, considering the goal of the decision, should not actually be of
influence to the decision. Questions to ask are: Is the company’s best
interest always the prime concern during the decision-making? Are there
any personal interests involved? Or are the decision-makers focussing on
their individual departments instead of the organisation as a whole?
Rational and irrational arguments can sometimes be intertwined. Try to
take these different motivations into account, and take control if they
(threaten to) influence a decision.
* Ensure the decision-making process is clearly established. It is not just a
matter of options, of contents. The manner in which decisions are made,
the process, should also be clear from the start. Items to consider are
agreements concerning majority rulings or consensus, or on whether or
not to weight criteria. If the decision-making process is unclear, people
are able to disregard procedure.
* Guide the procedure. This is a task which can be performed by a
secretary of a project group or the project leader, along with a chairperson
or director. Agree on a set of ground rules regarding following procedure.
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* Consider the acceptation process of the final decision. Every decisionmaker will have to eventually accept the decision, even though it may not
be the outcome they had hoped for. If they do not, the decision may not
be implemented properly. This means that you will need to do more than
merely inform parties following a decision. You need to involve people in
the process.
§ 7.4
Establishing Criteria
Before you start thinking about solutions, you should first establish the
criteria. Do not first come up with a solution and then invent a matching set
of requirements. Some problems are in desperate need of a solution. Some
people may choose any available option without knowing exactly how it
contributes to the solution of the problem. The preference for a particular
solution can often occur without the actual pros and cons being known. One
example is the popularity of the Joint Strike Fighter jet among the Royal
Netherlands Air Force. That branch of the military had had good experience
in using the F-16, an American product. The French Mirage fighter jet, on the
other hand, was much less well-known. For that reason alone, the Rafale,
the follow-up to the Mirage, had little chance of being selected as the
replacement to the F-16. Since the JSF is also an American product, it was
favoured as the replacement from the outset.
When establishing criteria, also known as attributes, you will need to deal
with a client’s preconditions and wishes. There may be some criteria that
need to be met by definition. These are known as non-compensatory. You
will find various different names for these criteria in relevant literature, such
as conjunction criteria, cut-off criteria or killer requirements. Scoring too high
or low on one of those criteria is not something that can be redeemed, or
compensated, by scoring higher on another. When choosing a new type of
delivery van, one non-compensatory could be a sliding door allowing the
driver to more easily reach the packages. In that case, a vehicle that is more
fuel-efficient, less expensive in terms of initial purchase, and whose safety
performance is rated higher, still would not qualify if it lacked a sliding door.
Attributes
Noncompensatory
7
Conjunction
criteria
Cut-off criteria
Killer
requirements
A client can set various demands. Are they looking for a risk-free solution?
Or are they motivated by money, wanting the most profitable option in spite
of potential risk? These are some possibilities you could be faced with:
* Effectiveness. Maximising effect. The client is looking for the best
possible solution, even if it is a relatively expensive one. What counts,
are the gains. If the gains concerned are monetary in nature, this is
known as ‘maximising profits’.
A client can require an investment has to be recouped within a certain
time-frame. This requirement can be subject to various calculation
methods. Calculating the break-even point will tell you when a solution
stops costing money, and starts to generate a profit. Calculating the net
present value lets you calculate the free cash flows of various options,
for example.
* Efficiency. Limiting resources or maximising profits. Efficiency is
concerned with two things: either use the minimum required resources to
reach a certain goal, or us the available resources to reach maximum
revenue.
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* Risk. Minimising risks. Here, avoiding danger is the motto. This can mean
you will reach solutions which, when used on a worst case scenario, will
still lead to the best possible and/or still acceptable result. There may
be more effective options possible, but those are considered too
perilous.
Criteria tell you something about the effect of certain options on the
solution to a problem. When valuing those effects, you can encounter two
possible obstacles. The first is that you may not be fully certain a particular
effect will actually occur. For example, you expect that an advertising
campaign will lead to increased turnover for your product... but how high
should you expect that increase to be? In these types of situations, it is
best to work based on expectations. This will let you work according to a
worst case and/or best case scenario.
There are also those effects which are difficult to quantify. That is the
second obstacle. Effects in question can, for example, be concerned with
the ease with which internal reorganisations, possibly consisting of forced
redundancies, are accepted. Try expressing that one in numbers! Your best
bet, instead, is to use different variant possibilities which you can then
compare. The level of acceptance for plan A could be greater than that for
plan B, even though you may not know exactly how much greater. You could
try using a questionnaire to establish preference – which is a seemingly
simple solution. But you should nevertheless be careful when interpreting
the results. The fact that 60% of personnel prefers plan A and 40% prefers
plan B does not guarantee that plan A is preferred. The 60% may feel that
plan A is only marginally better than B, and the 40% may feel that plan B is
vastly superior to plan A. Properly interpreting the outcomes will require you
to analyse the arguments used in favour of the different plans. This will help
you predict whether or not the 40% group may also settle for plan A.
7
§ 7.5
Scaling Criteria
Eventually, you will want to know which option best fits the established
criteria. For that, you will need to assign scores to each criterion. You can
do so by awarding points on a scale of 1 to 5 to each of the different
criteria, for example. Each point on the scale should have a particular
meaning. You could choose to award only 1 point for an average fuel
efficiency of 1 to 8 mpg (miles per gallon) or lower. Between 8 to 16 mpg
would score 2 points, and a car averaging 32 or more miles to the gallon
would score the maximum of 5 points. Another option is to award a value of
1 to the worst possible score, and a value of 5 to the best possible one
without using numerical values.
Sub-attributes
Each criterion can be divided into sub-attributes. You split up your criteria
into separate components. When choosing a new office building, its
accessibility by car can be a criterion. Sub-attributes could be the relative
distance to motorway exits, the average lengths of on-route traffic queues,
or the amount of available parking space. Each of these sub-attributes
awards a criterion points on a certain scale. The advantage to this method
is that it allows you to cast a much more concrete verdict. You can also
weight the sub-attributes. But there is a danger of losing track of the bigger
picture, and getting bogged down in prominent but ultimately uninfluential
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details. And you may also wonder whether there is any point to the
laborious task of weighting a seemingly endless list of sub-attributes. This
detailed approach should therefore be reserved for those situations where
you expect it can have a serious impact on the final decision.
Establishing sub-attributes is a helpful way of clarifying how a particular
attribute is actually defined. It tells you at a glance what an attribute is
(or is not) concerned with This will help you form a better picture of which
attributes to weigh up against each other. This idea is supported by academic
research (see insert ‘A Weighty Matter’). Test subjects in laboratory conditions
were asked to weight attributes used in a decision-making process. The
subjects, not used to the concept of weighting, used between a third to a
quarter of their invested energy in coming up with and combining subattributes. Some of these subsection criteria were weighted, some were not.
Attributes and sub-attributes are not assigned points on a scale for nothing.
You are looking for the most appealing option. In doing so, you look for two
things: The extent to which an option solves the problem, and whether an
option would produce any side effects. A solution to combat low levels of
productivity could have a negative effect on quality, for example. You would
therefore award this option fewer points for the ‘quality’ criterion.
Side effects need not always be unintended, however. If the main reason for
replacing machinery, for example, is to prevent failures or drop-outs, an
intended and planned advantage could be that the newer, more modern
machines improve product quality.
7
The point scale does not have to be restricted to scores between 1 and 5.
What matters is that you work as accurately as possible. What this means
is that, in practice, your scale should neither be too coarse nor too fine. You
could express the level of comfort of a car in a scale of 1 to 100, for
example. But a deciding factor between scoring 53 and 54 points would be
nearly impossible to imagine. The same problem would not occur for a scale
from 1 to 5. Whatever you do, make sure you are consistent. This means
that the difference in appeal between the scores of different attributes has
to be comparable. For example, a car can be appreciated in terms of safety
and comfort. In that case, the values for scoring 4 points would need to be
the same for both comfort and safety. You cannot have a score of 4 mean
‘appealing’ when it comes to comfort and ‘unappealing’ when it comes to
safety. Additionally, you also need to take into account the laws of
economics, such as the law of diminishing marginal utility. In short: More is
not always better. If you feel like a snack, then chances are that two
hotdogs later you will value the third one on your plate somewhat lower than
the first two. This has relevance on the distance between the values on your
scale which, in this case, need not be constant.
§ 7.6
Weighting Criteria
Using the scores you have attributed to the different criteria, you can begin
comparing available options. But comparing scores is not the short of it:
Not all criteria are equally important. You can distinguish between levels of
importance by weighting your respective criteria.
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When choosing a new restaurant location, an organisation looking for many
on-site visitors will value accessibility over the presence of other
restaurants in the vicinity. The latter can be an advantage if local
restaurants are only visited infrequently. So where those restaurant holders
may value the presence of other local eateries at 0.2 times the score, a
nearby bus stop and a large on-site parking lot could be valued at a factor
of 0.3 and 0.4 times their score respectively. The weights should be used in
combination with a point scale. Table 7.1 is an example of using scores and
weighting criteria in practice.
TABLE 7.1
Example of options with weighted criteria
Options/Criteria
Car accessibility
Bus accessibility
Representative location
Local restaurants
Final score for each option
7
Option 1
Option 2
Score
Weight
Total
Score
Weight
Total
2
3
4
5
0.4
0.2
0.3
0.1
0.8
0.6
1.2
0.5
5
4
2
1
0.4
0.2
0.3
0.1
2.0
0.8
0.6
0.1
3.1
3.5
There are various methods of assigning weight, for example:
* awarding marks to different criteria
* distributing a number of points between criteria
* using pairwise comparison valuation.
First, choose between criteria 1 and 2: which of the two is more important?
Then, compare criteria 1 and 3. Keep comparing pairs of criteria and
determine which is the more important of the two for all pairs of criteria.
The winning criterion is awarded a point; whichever criterion has the most
points is the most important. Note that these are ordinal values.
Once you have finished comparing the pairs, you will be left with your
various criteria sorted in a ranking order: criterion 1 is more important than
criterion 3, criterion 2 is more important than criterion 1, and so on. While
this does allow you to distinguish between the levels of importance of
particular sets of criteria, it does not allow you to weight the criteria (e.g.
saying that ‘criterion 2 is weighted at 0.4’ or ‘criterion 1 is weighted at
0.2’). A possible solution to this problem is to start by performing paired
valuations, and then distribute points between the criteria. This will allow
you to distinguish between criteria in terms of numbers of points; but it
should not affect the order of your initial paired valuations, of course.
Choosing repeatedly from a number of available options. Think, for example,
of the way many career choice tests are structured. Career choice test
attempt to help people make a decision by giving them an insight into how
important they find various job aspects. Looking at criteria such as task
variety, status, salary, or job security, candidates are asked to choose
between different sets of three or four professions several times.
Realistically, this requires candidates to assign weight consciously or
subconsciously. The value or level of importance your candidate awards to
the various criteria is determined from their choices. If someone
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consistently picks whichever job has the highest salary, that means they
value money relatively highly. There are some disadvantages to this method,
however. One is that you are trying to help people by weighting certain
aspects; but actually, you are letting them choose before you do the
weighting. Another issue is that your subjects’ decisions are influenced by
the knowledge that they are taking part in a test. Real-life decisions may
actually be influenced by numerous factors, such as emotional distress.
Weighting criteria helps you maintain a reasonably reliable approach; it does
not particularly matter whether you ask people to do so by choosing what
they feel is most important, or by using paired valuation or another method.
For routine decision-making, these approaches are all up to 70 to 80%
accurate.
That does mean, however, that there is a 20 to 30% possibility for error - a
substantial percentage for high-stakes decisions. Just look at the hordes of
students who take part in career tests in high school or secondary school;
at least 1 in 4 of higher vocational education or university students drops
out as a result of having made what they feel is ‘the wrong decision’.
Majority Rule
In practice, the process of decision making is different from choosing
between theoretical numbers on paper. People often do not actually weight
the various criteria. They may simply assume that all criteria are equally
important, and then choose whichever criterion has the highest score on
the largest number of criteria. This is called majority rule. Alternatively,
participants may already know which criterion is the most important, but not
how important the other criteria are. This will often make them choose
whichever option scores the highest in the most important criterion: the
lexicographical method.
Majority rule
7
Lexicographical
method
Some criteria can be hard to weight properly. You could weight the criterion
of ‘brand’ when shopping around for a new car, since you’re looking to buy a
Ferrari… but what is that weight based on, realistically? Is it a matter of
emotion, of personal preference? That personal preference may end up
costing you a lot of money. You may feel a criterion is important, but be
unable to explain exactly why that is. In that case, be honest with yourself
and make your decision. Either trust your intuition and weight that criterion
substantially, or use only justifiably important criteria (and ignore any
‘emotionally charged’ ones).
Difficult decisions can be made easier by staggering the decision-making
process. First, limit the number of options by setting several noncompensatory criteria; that is, those qualities or aspects that must be met
by definition. If you are looking to buy a car, for example, one of your criteria
could be ‘maximum price’; call it €20,000. In that case, you would not have
to worry about the fuel efficiency of a brand-new Rolls Royce, or whether the
latest S-class Mercedes comes with remote controlled doors. And, in setting
this maximum, you have also influenced the importance of potential status
gained from your new car; a €20,000 car is unlikely to be an important
status symbol. Using a number of non-compensatory criteria will generally
help limit the number of options to something more manageable. But do
make sure you do not eliminate all options outright.
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The Importance of Argumentation
Sometimes, the final scores of the available options may be grouped very
tightly together. In that case, the weights of the different attributes should
determine the final decision. However, those weights may be viewed
differently by clients on the one hand, and advisors on the other. In addition,
the process by which people arrive at weights is generally uncertain.
Nevertheless, we do have some understanding of the theory behind
weighting. Whichever attribute is recommended by the most arguments tends
to be seen as the most important. These results, while having been found in
scientific research, have not yet been sufficiently proven or published.
You are recommended to think long and hard about the importance of your
selected attributes. For example: Do the arguments used factually apply to
the attributes concerned? You might, for example, think that a high
maximum speed can help a motorcycle avoid dangerous situations. That
reasoning is flawed. Getting away from trouble does not require a high
maximum speed per se – what is needed is the ability to accelerate quickly
and be on your way at the first sign of trouble.
You can come up with dozens of criteria, and divide them into layer upon layer
of sub-attributes. But make sure you first determine which attributes actually
matter. If you are looking into the safety levels of a vehicle, physical weight can
be a sub-attribute. But is it really the vehicle’s weight you are after? Safety is
more of a matter of chassis strength and stopping distance. The stronger the
chassis, the heavier it probably is (barring the use of carbon fibre or certain
polymers); the heavier the chassis, the longer the stopping distance. If you are
unable to determine chassis strength or stopping distance, leave out those
criteria and use overall weight as a replacement. But if you do manage to find
out those figures, for example through a dealership or the manufacturer, you
can leave out the overall weight indicator instead. Go through all of your (sub-)
attributes in a similarly critical fashion; with any luck, your list of attributes will
be much shorter by the time you are through.
7
Next, you review whether all sub-attributes are relevant at all times. You
take into account the different phases of the problem-solving process, for
example by first choosing a prototype which you can improve or expand
upon at a later date. In project-based development of software used by
employees, for example, the wish list is often quite comprehensive. A new
CRM (short for ‘customer relation management’) system should, according
to the marketing department, have a virtually endless list of options for
managing customer relations. The purchase of a CRM system, therefore,
can be preceded by drafting a long list of criteria and sub-attributes, which
are then weighted. Those various wishes may, due to restrictions in time or
budget, be impossible to fulfil immediately. In that case, you will need to
establish some priorities: things that needs to be done right now versus
things that can potentially wait till later.
MoSCoW rules
MoSCoW Rules
In these situations, the MoSCoW rules (Stapleton, 2005) are truly a boon.
You can use these rules to classify the demands or requirements into
different categories, from those that are essential to those that would be an
added luxury. This will allow you to develop a less complicated basic trial
version, for example. That trial version can then later be enhanced gradually.
Table 7.2 is an example of the application of the MoSCoW rules to the
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purchase of a content management system (CMS) for the development of a
scheduled new website, and the translation of the rules into weights.
TABLE 7.2 MoSCoW rules applied to the purchase of a content management system.
The final column indicates how the MosCoW rules can be interpreted in terms of
weighting.
MoSCoW-rule
General
CMS website
Weight
Must Have
Solution will not work if these
demands are not met
(minimum)
Customer uses website to
access database
Prerequisites,
non-compensatory
criteria
Should Have
Solution will still work without
meeting these demands
(would be required if more
time were available)
Search functionality in
database
High weight
Could Have
Demands can easily be
left out
Extensive search functionality
by words, sentence fragments,
key phrases, and dates
Low weight
Want to Have but
Will Not Have This
Time Around
Clients wishes which cannot
be implemented now
Personalised customer pages
with overview of consulted
pages, orders, and offers
Very low to no weight
(or criterion is dropped)
A Weighty Matter
In the field of decision-making theory, much is paid to how weights are
ascertained and what types of circumstances can influence them. Does the
way the problem is formulated influence the weight people ascribe to a
criterion, for example? Little is currently known about the thought processes
people experience when establishing weights: the importance assessment.
Research (Heerkens, 2003, and Heerkens, Norde & Van der Heijden, 2011)
indicates the following trends:
* Actors performing importance assessments spend a lot of energy on
clarifying what the attributes actually mean. This is not done by defining
attributes, but by splitting them up into as many as forty sub-attributes.
* They are not concerned with whether all (sub-)attributes have been
identified. They hardly assess the importance of any attributes. For each
individual attribute, they establish how important it is without involving
any of the others. In addition, they do not rely on a common denominator,
such as money.
* People who are more experienced in assessing importance hardly differ
from people with little experience when faced with a new assessment.
7
The following is a list of tools which can be used to ensure a more
structured importance assessment process:
* Consciously assessing whether all attributes have been identified.
* Explicitly linking argumentations to (sub-)attributes.
* Relating (sub)attributes to each other (as in the delivery vehicle’s safety
example. You would use the weight of the chassis as a sub-attribute if
information about stopping distance or chassis strength are unavailable).
* Leaving out superfluous attributes.
* Making explicit any emotionally charged attributes as best as possible.
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§ 7.7
Providing Alternative Options or Using Existing
Possibilities
There are various means at your disposal for finding more than one
solution. First, before you reach out for help, try doing things under your own
power. Try to come up with as many optional solutions as you can during
this stage. Nothing and no one is standing in your way of coming up with
original ideas.
Only when you have had a long, hard think should you turn to others. There
are several methods used to generate optional solutions. Older solutions
provided by others are sometimes an excellent answer to your current
question. Consult relevant professional literature and published scientific
research. Or interview people, and see what options they can come up with.
In addition, there are creative techniques which you can employ to produce
new options.
7.7.1
7
Existing Research
Professional literature and scientific research may offer a practical solution
when you are looking for answers to your questions. Many problems have
already been presented with solutions courtesy of other experts. You are
free to copy from their work, as long as you properly source your material. If
you intend to adopt procedures, methods, tools, or others solutions used in
corporate life, mentioning a source generally will not be enough. Here,
patents and copyrights are important barriers to consider. But as for
existing scientific research: Do not hesitate to use what others have already
provided. Do make sure, however, that you carefully consider whether their
options, often conceived to combat a more or less different situation, can
apply to your specific case.
7.7.2
Creative Techniques
Aside from using scientific research, there are more creative ways of
reaching practicable solutions. Coming up with optional solutions is down to
creative skills. How do you use your and others’ inventive genius to arrive at
different solutions that also work well? There are different methods used to
tap into hidden sources in various situations. The following techniques are
used frequently:
* Brainstorming
* Synectics
* Morphology
Brainstorming
A brainstorming session allows a group of people to come up with a lot of
ideas at leisure. There are few restrictive agreements. Each member comes
up with a couple of ideas in turn. Meanwhile, the others do not give any
comment. Each participant only comes up with new suggestions. Those
suggestions can be in line with or even directly opposed to what has already
been mentioned. The point is to use association: One idea gives birth to
another. From the long list of ideas, you take whichever inspired notions
seem most promising. Then, as a team, you determine which ideas would or
would not be suitable for further development. Brainstorming is appropriate
when you need to come up with a new name for a product, but not when you
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are dealing with a technical flaw in an engine that keeps overheating, for
example. It is always a definable problem whose solution can be described
in a few words, without needing to draft complicated schedules or drawings.
One variation on brainstorming is brainwriting. This involves people writing
their ideas on forms which are passed around; this is another way of having
group members inspire each other without having the entire group comment
on what is being suggested. Once the forms have been used by all group
members, you have each individual indicate which ideas they thought were
the best. The resulting list of ideas can then be used by the same or
another group to formulate new ideas. In practice, brainwriting is more
effective than brainstorming. Brainstorming is attractive to the participants.
They feel involved in the problem-solving procedure, even though they
understand their idea may not be the one that gets selected.
Synectics
You can also choose a more structured technique. Synectics is a method
which imposes substantive rules on the associations. You take your
problem along on a jaunt to another world, such as classical antiquity or the
animal kingdom. You review whether you can find an analogue problem in
that environment, and solve it there. That solution is what you use on your
actual problem. Similarly, the designers of the F/A-18 fighter jet at
McDonnell Douglas (now Boeing) explored the world of the insects. They
studied how these diverse little creatures land from an airborne state. In
this case, it was a grasshopper whose legs formed the inspiration for the
landing gear used in the F/A-18. Synectics can be a way of inspiring
progress. But always make sure whether the solution is fully applicable. Not
all realms, times, or places are the same; as a result, solutions from one
situation may not work in others. The grasshopper’s eight legs, for example,
translated into three wheels for the F/A-18 (Rozenburg & Eekels, 1998).
Synectics
7
In order to successfully remove cancerous tumours, doctors studied the art
of warfare in the Middle Ages. How do you breach a heavily walled city?
Randomly hammering away at the main gate itself is not at all effective,
since that is where the defences are the strongest. And it only lends itself
to attack by those soldiers on the exact front lines. But if an army focusses
its assault on key positions along the wall’s perimeter, the defending party
will have to divide their strength to try and absorb the attack. A similarly
staggered approach is used by specialists in order to safely remove
tumours. A laser beam can be used to remove growths – at a risk of burning
off healthy surrounding tissue. Just as with the hostile city, doctors instead
focus on several points along the tumour’s edge. They use laser beams
which, individually, are not powerful enough to damage healthy tissue. But
when these lasers focus on the same spots, they can burn and combat the
cancer effectively.
Synectics and variants of this technique can help you arrive at original and
inventive solutions. You can use a contrasting example, or work on the
basis of a more extreme solution. For the development of a fast car, for
example, you can first design the slowest moving car, or imagine one that
travels at the speed of light. Whatever variant you choose, be sure to take
your time and, if the situation calls for it, work with different participants.
The most important thing is that you do not overlook any important,
promising solutions.
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Morphology
Morphology
There are also methods which use fixed patterns to help you arrive at a
desired design or solution, for example through the use of morphology. You
divide the problem you are trying to solve into different pieces. You come up
with variations for each piece. Then, you combine the variations into new
formations. This will help you arrive at new, original insights – only one of
which you will eventually need.
Say there is a factory that produces hammers, and that they are looking to
branch out to a new product. Morphology can be a great asset. First, line up
the characteristics (variables) and their values into something resembling
this:
* Force: manual
* Function: hitting nails into a board
* Operating method: hit the nail
* Components: head and handle
* Materials: steel and wood
In order to arrive at a different product, you change one or more of these
values. For example:
* Force: hydraulic, electric, pneumatic
* Function: drilling screws into a board, paperweight, removing nails from a
board
* Operating method: exert pressure, push, pull, wrench
* Components: power transfer, position detection
* Materials: concrete, plastic, cardboard, paper
7
This new list can lead you to a new machine which drills screws into wood
electrically: a screw gun.
The advantage of using morphology is that it allows you to work in little
steps, thus reducing the length of the creative leap needed to arrive at a
novel idea. A disadvantage is that you assume a certain object or situation
as your starting point. This can cause you to subconsciously limit your train
of thought to a certain direction, potentially leading to tunnel vision.
§ 7.8
Evaluating the Attractiveness of Available
Options
Indicate which option will be the most effective in solving the problem. Use
a matrix such as the one shown in table 7.1. You offset the options against
criteria which you have scored and weighted. The option which achieves the
highest overall score is the one you, the trouble-shooter, recommend.
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Choices Come with Strings Attached
As an advisor, you may occasionally find yourself in a predicament. Your
presentation of available options is not just a matter of technique. One the
one hand, you want to inform a client of all options and their associated
costs as best as possible. On the other, you need to make choices and limit
what is a complex matter. And there are some strings attached to the choices you make.
You run several risks. Those who limit themselves to technical analyses will
turn up with complicated proposals. The image of the situation they portray
is seemingly objective, and often concerned with only part of reality. And
that is the reason this approach does not work. Interested parties can use
these types of results to further whatever agenda they may have; a situation not at all conducive to swift decision-making.
Those who make their client’s life easier by limiting the number of options,
on the other hand, will be blamed for exerting an overbearing influence on
the decision-making process.
Every trouble-shooter makes their own professional calls in judgement.
There is nothing at all wrong with that. But it is important that, during the
entirety of the process, you properly communicate with your client. That
means interim and periodic meetings. And if adjustments have to be made,
you will need to re-secure the appropriate parties’ commitment. These
procedures have been developed in project management techniques, such
as Prince 2 (Koning & Van Onna). There, the project leader reports to the
client if progress threatens to deviate from what was initially agreed upon.
The project leader describes the cause and its effects, alternate solutions
for reducing or undoing the deviations, and their consequences for costs,
returns, and risks.
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Summary
▶ When formulating optional solutions, you look for options which can be
used to solve a problem. You generate and compare several options.
You advise you client of the best solution based on your argumentation.
You provide you client with a comprehensive report on the different
options. You prepare the decision-making process for the selection of a
solution.
▶ You describe what exactly needs to be decided on.
▶ You establish the decision-making process and develop a method for
deciding which solution to employ.
▶ You establish criteria. You indicate possible options. Ask the client what
they require of a solution.
7
▶ You assign points on a scale to the criteria, for example between 1 and 5.
▶ You weight the criteria. There are several methods for weighting criteria
which can involve users of the final solution or product.
▶ You come up with options or use existing possibilities. First, think of as
many possible solutions as you can. Then, involve others in your search
for alternative options, for example by conducting interviews or using
creative techniques, such as brainstorming, synectics, or morphology.
Be sure to use information or solutions other researchers have already
come up with, if possible.
▶ You indicate which solution is best suited to solving the problem.
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Core Concepts
Attributes
Characteristics of solutions.
Conjunction Criteria
Demands that a potential solution has to meet by definition.
Scoring too high or too low in these criteria cannot be
redeemed or compensated by scoring higher elsewhere.
Conjunction criteria are also known as cut-off criteria,
non-compensatory criteria or killer requirements.
Consensus
A state where all parties participating in a meeting are in
agreement.
Qualified Majority
An agreement which sets additional demands with regards to
decision-making. For example, decisions will only be validated
if at least two thirds of the decision-makers agree, or if at least
50% of the relevant decision-making parties is present.
Lexicographical Method
A method of deciding using a set of ranked criteria. The
options are first compared based on the most important
criterion. Whichever option scores the highest, is selected.
In case of a tie, the next-most important criterion is used until
there is a winner.
Majority Rule
A rule that favours the option which scores best in the largest
number of criteria. Here, all criteria have equal importance, and
none are weighted over others.
Morphology
A creative technique used to come up with (design) solutions.
MoSCoW Rules
A method of prioritising requirements and demands that are
part of a solution. The consonants in Moscow represent must
have, should have, could have, want to have but will not have
this time round.
Sub-Attribute
Part of a criterion, a characteristic of an option. Splitting a
criterion or attribute into component parts yields subattributes.
Synectics
A creative technique for coming up with solutions based on
looking at a problem in a different realm, time, or place.
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8
The Client’s Move
With your job as advisor complete, you have presented the client with a
report detailing several possible solutions to choose from. You have provided
argumentation as to which option would be the best match. Nevertheless,
your client may not end up following your suggestion. But why would that
happen? There are reasons for deviating from an expert’s opinion. It is all
down to the client’s wishes in phase 5 of the MPSM, choosing a solution.
This chapter addresses the following questions:
* Does the decision-maker’s responsibility for the consequences of a
decision influence their choice?
* Do decision-makers and advisors view assigned scores and weights of
options the same?
* Do decision-makers differ from advisors in their risk assessment?
Threshold Value 95
8
Probability Theory 95
Scenario 95
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A Colourful Advert
‘There is good news and bad news’, says
Brent Shaper over the phone. The CEO of
Cardboard & Paper International, a merger
of cardboard manufacturer Outmark and
packaging company Ditchfield located along
the Port of Tilbury, is in good spirits. ‘Bad
news first: We have had to dismiss all three
of your options for our advertising campaign.
But fear not. You need not spare any
expense in turning all eyes to our strongest
and cheapest moving box yet. We want a run
of six half page ads in the national and
regional papers you suggested. That is quite
close to your option C. What we will be
adding, is colour. We want our logo to be in
colour.’
8
‘That will be an additional 250,000 pounds.
Is that not slightly over the top for a 3-by-5centimetre square that reads Cardboard &
Paper in green?’, project leader Mark
Courtland delicately points out. Shaper will
not have it: ‘Mark, there are no second
impressions. Go big or go home.’
with the advertising agency for days, and the
project team has spent hours crunching the
numbers to come up with three fully fledged
possibilities for a good but affordable
advertising campaign. The three variants
were compared exhaustively. After much
careful deliberation, Courtland decided to
suggest option C: a £1,950,000 advertising
campaign which, like the other two options,
would still be within the realm of the
2-million-pound budget. And now the board
of directors have decided to add a cool
quarter million on top of that. Just because
the logo has to be in colour. ‘It looks nice
enough, that little hit of green, but it is too
dear.’ That was what the gathered
professionals concluded regarding the use
of a highlight in the adverts.
‘So what could have happened during that
management meeting?’, thinks Courtland.
He will have to confer with Shaper tomorrow.
First things first: Time to call the advertising
agency. There is advertising space that
needs to be booked.
Feeling somewhat deflated, Courtland puts
down his phone. He has been consulting
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THE CLIENT’S MOVE
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Three Reasons for Deviating from an
Advisory Report
You have finalised your consultancy report regarding the company’s
production capacity problems. You have carefully weighed up the various
options based on the overall picture. You have conducted analyses of their
cost effectiveness. You have weighted various criteria. In doing so, you have
provided your client with a clear insight into what would be the best way of
dealing with the problem. As an example, you have suggested moving to a
different production location. But management decides differently. They
have a different view of the potential risks concerning recruiting technicians
in the area you have suggested. The company is to remain where it is. But
management does give the go-ahead for the construction of a second
production hall on the current premises.
Your advice, carefully considered though it is, has not been followed. Since
your advisory report is based on your judgement, a client may have a
different view of the available options. This means the client can have a
different interpretation of the options, potentially leading them to choose
something else than what you have suggested. Three explanations for a
client deviating from the ‘best’ option:
1 The client is responsible for the decision and its consequences; the
advisor is not.
2 The advisor and client may view assigned scores and weights differently.
3 The decision-maker assesses the risk differently.
§ 8.2
Politically Charged Decisions
‘The decision-maker has to make their call in the context of the
organisation. This context is something the advisor needs to steer clear of.’
This is a view occasionally held in boardrooms. Advisors whose advisory
report is discounted, tend to take a disparaging view of a decision following
such a statement, and comment on its ‘politically charged’ nature. In their
eyes, the company has opted not for the best possible choice, but for one
that would, for example, sit all right with important suppliers. Which is
something management might hope to benefit from.
8
But taking a political view of decisions is not necessarily a bad thing. Once
you make a decision, you will need to deal with its consequences, its
outcome. That is quite a responsibility to bear. In the realm of business,
executive decisions can have far reaching consequences the advisor may
not always be able to fully appreciate. Should Apple begin marketing an
improved iPad based on rumours that their competitors plan to come out
with new models, superior to the current generation of iPads? Introducing a
successor would mean the end for a current hit product. Or should Apple
remain confident in their current model’s ability to deal with the competition
for the time being?
‘No authority without responsibility’: Wisdom fit for framing on a boardroom
wall. The advisor dots all i’s and crosses all t’s to arrive at the best possible
option. The decision-maker can take that information on board, but will also
look further. Decision-makers have to deal with strategic consequences, and
make their decisions in relation to the solution of other problems.
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The advisor compares the different options and assesses what the best
possible option would be. The decision-maker studies the advisory report
and the choice as it is presented, but makes their choice independently.
The difference here is one between evaluating and choosing. The decisionmaker also has a responsibility towards shareholders. The manager who
makes the decision is usually a generalist who places the choice for a
certain option in a broader context. The advisor is sometimes not even
asked to take the context into consideration. There is often no information
available. Soft factors, such as ambition, the quality of management,
creativity, or workplace atmosphere, may also be involved. These are
difficult to measure. The advisor focusses on assessing the alternatives
they, in their role as expert, have come up with. Decision-wise, the option of
having someone contribute their solutions without any obligations is a good
thing. That contributor will not be hindered by others, or by consequences
outside of the reach of the investigation.
§ 8.3
8
Considering Other Interests
If yours were the final call, you would undoubtedly not blindly limit your
decision to the options you were presented with. Other issues can also have
their influence. Additionally, there may be certain theoretical reasons for not
choosing the most attractive option. The advisor finds the best possible
solution by calculating score times weight, taking into account any minimum
requirements. A manager faced with a decision may use other benchmarks,
for example that of majority rule: the manager chooses whichever option
scores the highest in the largest number of attributes. A choice like that is
easily justified to others: every advantage is an argument in favour, and
complicated explanations of why one advantage is ever so slightly more
important than another are superfluous. But there are disadvantages to this
approach. An alternative that does not score very high marks all round, but
does score highly in the most important criterion, may easily be discounted.
This method is likely to be used if none of the options are head-andshoulders above the rest. In these cases, securing acceptance of the
decision can be more important than choosing the best option (which, in all
likelihood, is not that much better than the alternative that was selected).
Remorse
Another motivation may be an attempt to avoid potentially regrettable
situations. Nobody likes to feel buyer’s remorse once they realise they have
made a ‘wrong’ decision - something that can happen if the scores of the
various options are grouped very closely together. Deciding on the best
option may mean having to miss out on all the perks of another. The
decision-maker may assess the advantages differently, or take the
convictions of other interested parties to heart when making the decision
not to follow the advisor. Those parties may view attributes with lower
scores as more important.
Acceptance of others, incidentally, is not a separate attribute. Sometimes,
the decision-maker implicitly takes the wishes of others into account, for
example those of fellow directors or employees. It is not a good idea for the
advisor to take this issue of remorse into account – any final consideration
is the client’s own responsibility.
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THE CLIENT’S MOVE
95
Handling Risks
Advisors naturally take the risks of the different options into account. But
decision-makers do so explicitly. They regard the risks in a broader context,
and can also factor in the risks into the scored and weighted criteria is
different ways. Here are some examples:
* A high threshold value for a non-compensatory criterion. The minimum
requirement for the capacity of a new production line may be 50,000
coffee machines per year, even though you have room to store only
20,000; the same kind of decision as demanding a new car has at least
five seats even though there are only three of you. What you do not use
can be used as backup.
* Different scenarios. A decision is based on various scenarios (possible
future states). Scenario 1, for example, may leave little room for
employment opportunities, but more for economic growth. Scenario 2
comes with a solid increase in employment opportunities, at barely any
economic growth.
* Flexibility. Managers may decide on purchasing a computer system with
capabilities far beyond what is currently required. These capabilities may
consist of functionality they do not yet fully grasp, but which the company
may come to need at a later date. Compare this to purchasing a heavier,
more expansive car with a tow bar. Should you later decide to take a
caravan holiday, you will already have the car you need for the job. You
have added an extra attribute. This can be specific (e.g. a tow bar) or
more generally applicable (e.g. ‘flexibility’). The disadvantage of the more
general attributes is that they are hard to properly value.
* Modifying/Adapting weights. Decision-makers weight attributes differently
if they assess the risks involved to be higher. They might choose for a
fleet of fuel efficient cars that nevertheless did not score the best in a
costs/benefits analysis. The company is prepared to put more money
down because they are taking into account a future increase in fuel
prices.
In the field of probability theory, risk is defined as probability times
consequences. Probability is the number of times something occurs, usually
expressed as a percentage. The consequence is the loss in value you incur
if the risk occurs. Based on the probability times consequences formula,
risks are assessed as acceptable or inacceptable. For frequently occurring
risks, using the probability theory definition works well. For example: your
experience with customers is that 1 to 2% does not pay their bills. This
means you do not know which customers this applies to, but you do know
how much money is involved. If you have very few customers, the same
does not hold: if only one customer skips the bill, the effect on the total
revenue will be much greater.
Threshold value
Scenarios
8
Probability
theory
Some consequences may be so major as to face the decision-maker with
an impossible task. Think, for example, of the field of nuclear energy, where
the effects of a nuclear disaster would be incalculable. Due to the extreme
nature of the results, any potential risk would be too great. In effect, this
would prevent you from making any decisions at all involving nuclear energy.
But since it comes with major advantages, there are governments willing to
invest in the construction of a nuclear power plant. Their decision, in this
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case, is not merely based on probability times consequences. Indeed, it is
often unclear how such decisions are actually made. One possible
explanation is that the decision-makers also take a longitudinal view of the
consequences. In that case, the question may become: What would be the
effects of a nuclear disaster on people born 40 years from when it occurs?
They would not know of a world any different from the one they live in. If,
in 2020, the nuclear plant in Dungeness suffers a meltdown, it could take
out a large chunk of England’s Southeast. Someone who wakes up in
Maidstone-sur-Mer in 2040, now home to England’s coastline, will not feel
any sense of loss for the High Weald, Royal Tunbridge Wells, the White
Cliffs of Dover, etcetera. While this approach seems exceedingly cynical,
the alternative, of course, is just to move away from using nuclear energy
altogether – discarding any and all life-changing advantages in the process.
Aside from risk acceptance, the decision to build a nuclear power plant is
also based in the realms of legitimacy and equity, even ethics – topics not
covered in this book.
8
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Summary
▶ The final decision is the client’s prerogative. Based on other
considerations, a client may deviate from professional and founded
advice. As such, advisors and decision-makers can arrive at different
choices. These may often come across as politically charged in the eyes
of the advisors. That need not be the case – it need not even be a bad
thing.
▶ The trouble-shooter compares the options and assesses what the best
possibility would be. The decision-maker reviews the submitted
selection, but their decision is an independent one. The decision-maker
places the choice for a particular option in a broader context, for
example involving a level of responsibility toward shareholders. The
advisor does not have this responsibility.
▶ When assessing alternatives, an advisor reviews scores, weights, and
prerequisites. The decision-maker may deal differently with the
weighting, for example by choosing to apply majority rule. This leads to
whichever option conforms to the largest number of attributes.
▶ Decision-makers explicitly take all risks into account in their
deliberations. They view the risks in a broader aspect than the advisor.
This may lead them to make different choices.
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Core Concepts
Threshold Value
Minimum amount (of products needed for profitable
production).
Probability Theory
A method used to calculate the risks involved in an option or
event. Risk is defined as probability times consequences. The
probability is the average number of times a certain thing
occurs, usually expressed as a percentage. The consequence
is the loss of value incurred when the risk occurs. Based on
the probability times consequences formula, risks are assessed
as acceptable or inacceptable.
Scenario
A construction of a possible future state of an aspect of the
world. Scenario planning is a way of using various scenarios as
the basis for a decision, since it provides an insight into how
certain options would work in practice.
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9
A Systematic Approach
The die is cast. Management has discussed the plan and chosen a
solution. The next step is its execution, which is about details and ways of
making the advice a reality. You draft an implementation plan in phase 6 of
the MPSM, implementing the solution.
This chapter addresses the following questions:
* What are the steps that need to be taken in order to develop the plan?
* What is needed to mobilise employees?
9
Implementation Plan 103
Bottom-Up 104
BCH Model 103
Change Management 104
Top-Down 104
Yammer 104
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Developing a Training Plan
A local company’s commercial branch is due
an upgrade. Time to send the managers back
to school. A certificate from a written course
in marketing is no longer sufficient. Company
leadership is in need of management
strategies and techniques. MBA is the new
standard for Sales. Thus sayeth the board.
A training plan details how the current
managers and team leads should develop.
Now it is down to the plan’s execution.
The HRM department holds a meeting.
There is work to be done. A project group is
tasked with filling in all the details of the
training plan. A sub-group will tackle the
necessary steps. A legal advisor will review
the contracts that employees will need to
sign. The HRM team has questions, many
questions. How many working hours will be
allotted for employee studies? Will this lead
to staffing issues? And how will any issues
be handled? Are employees required to
refund the training fees if they leave within
the next three years? Or should that be a
five-year term? Can you force people to stay
on at the company for a certain number of
years following the training?
Two HRM members and a communications
advisor are asked to consider
communications. How are they going to get
managers back to hitting the books? An
MBA title is a nice thing to have, but
studying takes time – even free time. Is
everyone willing to invest theirs?
The head of P&O tells her staff: ‘For a
moment, I was sure that finishing our
training plan and getting it past the board
would have been the end of it. But looking
at what we still need to do, it is almost like
we have not done any work at all.’
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A SYSTEMATIC APPROACH
103
Two Principles of Implementing a Solution
Using your formulation of alternative solutions, you have provided your client
with an insight into what would be the best option for dealing with the
problem. Also, you have given a global indication of what the consequences
of that choice would be. Meanwhile, the client has made a decision. Your
job now is to provide a detailed overview of what is needed in order to
develop the solution. You describe the steps needed to realise your advice
in an implementation plan. You work according to these two principles:
* You briefly describe the activities that need to be performed, step by
step. This is the technical side of your plan.
* You describe the roles of individuals, and how to get them on-board with
the change. This is the social side of your plan, involving change
management.
§ 9.2
A Brief Description
You indicate the activities the organisation will need to perform. You answer
many operational questions. A management MBA course is concerned with
questions like: How do you get all managers to pass? Which training
organisation will you ask for input on the programme? How do you enable
possibilities for studying? How do you deal with understaffing issues once
managers head off to business school? What kind of contract should you
and your employees agree upon? Are they allowed to study during working
hours? Are they required to refund the training costs if they leave? Can you
compel people to stay on for three years following their studies? How do
you handle long-term students?
Choices also occur during the execution. Just like with assessing and
deciding on alternatives, these lend themselves to using criteria. First, line
up what a solution needs to conform to; then, select the most attractive
one, for example a particular training organisation.
Your implementation plan is a brief description of the necessary activities.
Make sure it is appropriately detailed. Do not overdo it on the specifics.
What needs to be clear above all is the reason why the company is taking
this course. Develop your solution; do not come up with new ones.
§ 9.3
9
Implementation
plan
Realising an Idea
Solving problems means changing, reorganising activities, and restructuring
organisations. There are different ways of doing so, for example by
assessing according to the BCH model (Balance, Cohesion, and
Heterogeneity) by Weggeman et al. (Kor, Wijnen & Weggeman 2007). This
model demonstrates the cohesion between six organisational aspects,
including culture, structure, and management style. McKinsey’s 7S model
can also be of help. Whatever method you use, make sure you consider the
following points when writing your evaluation plan:
* Per intended measure, indicate what the goal or sub-goal is. Include the
costs and the responsible party/parties.
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Top-down
Bottom-up
Change
management
Yammer
* Check up on the progress of changes. To that end, develop a system of
control. Do not be conspicuous when monitoring people; this will earn
you their aversion.
* Be clear in your intended method. Do you opt for a top-down approach,
putting management in charge of the solutions or change, making
communications a one-way affair, and leaving middle management in
charge of informing staff? Or do you go for a bottom-up approach, putting
more emphasis on the importance of employee input?
* Make sure to respond adequately to possible resistance against change.
Take into account existing corporate culture. Invest in change
management. Involve people in the different steps of the change
process. Let them take part in courses. Clarify which decisions they have
a hand in. Make sure their expectations are realistic, and let them know
which factors are beyond their control.
* Organise internal communications. Consider how you are going to inform
everyone working in the company. You can choose from a vast array of
tools. The transfer of information can occur through staff or work
meetings, the company president’s blog, intranet pages, social media
platforms like Yammer, the company magazine, or a special project
journal. Make sure people are able to respond to the information
provided.
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Summary
▶ Your implementation plan is concerned with precisely detailing the
execution of the solution, as well as with the necessary steps to ensure
everyone is on board.
▶ Be brief and precise in your description of steps required to properly
implement the solution.
▶ In case of choices, use criteria - just as with assessing and deciding on
alternatives.
▶ Be systematic. Provide sufficient detail for each measure, and perform
progress checks according to a system of control.
▶ Anticipate resistance to change. Be clear about the intended approach:
top-down or bottom-up. Let people take part in courses. Organise
internal communications.
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Core Concepts
Bottom-Up
A direction of communications in an organisation. Bottom-up
means workplace input is possible.
BCH Model
A model used for an internal analysis of an organisation. The
letters B, C, and H represent Balance, Cohesion, and
Heterogeneity. The model demonstrates the cohesion between
six organisational aspects. These are: strategy, structure,
culture, systems, management style, and personnel. All of
these aspects are interrelated. A change in one is felt
throughout the others. Each aspect has a hard (quantifiable)
and a soft (unquantifiable) side. Internal communications can
influence parts of the BCH model
Implementation Plan
A plan of attack which details what needs to happen in order to
implement adopted advice in an organisation.
Top-Down
A direction of communications in an organisation. Top-down
means all communications originate from management and
move along any existing intermediate layers until they arrive at
the workplace.
Change Management
Supervise, organise, and (have others) execute change within
an organisation.
Yammer
Yammer is like Twitter for companies. One of various social
media platforms which work by submitting short messages.
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10
Keep Improving
By and large, the problem has been solved. The goals of the problem-solving
method seem to have been met. But that does not always mean smooth
sailing. What could be the cause of that? You proceed with an evaluation in
phase 7 of the Managerial Problem-Solving Method. You review whether the
solution works as intended. A full evaluation of all the steps in your
problem-solving approach; that is the main task during phase 7 of the
MPSM, evaluating the solution.
This chapter addresses the following questions:
* How do you convince people of the value of an evaluation?
* How do you handle an evaluation professionally?
10
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Evaluating the new website
It took some doing, but the evaluation is
underway. None of the parties involved were
very keen on cooperating, but management
has managed to persuade them. Generally
speaking, everyone is pleased with the new
working method. ‘What is the point in talking
about it?’ they said at first. Eventually though,
they popped by to evaluate the new website
for packaging suppliers.
10
For some time now, the suppliers of pallets,
labels, cardboard, and other packaging
materials have been signing in weekly to the
website of a food manufacturer. This provides
the material planners with a rapid overview
of over a thousand materials which are in
stock at 69 suppliers. Things used to be
much different: The email servers would
become overburdened with the massive load
of messages to-and-fro.
The new approach seems a vast
improvement. But it is not without the
occasional hitch. In one case, the quality of
the pallets supplied was not as expected. Or
the red colouring of the labels deviated too
much from the standard. How come these
oversights had not been spotted?
Fritz Button is head of the packaging
department, and in charge of the evaluating
discussion. First, he asks those present if
they are satisfied with the new working
method. There is no one who wants to
return to the old system; that much soon
becomes clear. Overall, things are going
well.
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But there are some flaws in the execution,
which mainly seem to involve the quality of
the materials supplied. What could be
causing the issues? According to Sven
Grubman, the company relies too heavily on
brokers who grab their materials from
wherever they can. ‘Those guys are cowboys.
Today, they will order pallets from Oslo, but
tomorrow, if the price drops twenty cents,
they will happily switch to a Bulgarian
supplier. All they are concerned with, is
price.’ Bert Latefield confirms his colleague’s
statement: ‘Those companies will shop
around anywhere, particular where printed
matter is concerned. Anywhere from Belgium
to Southern Europe. And if they are looking
at large batches, and they have the time,
they turn as far as Asia.’
‘So how do we deal with this?’, asks Button.
There are some suggestions to contract
other suppliers. ‘So who do we trust
instead? Would it not be better to sit down
with the most important materials suppliers?
We are a major client for them – it should
not come as a surprise that we expect their
quality to match’, says Grubman.
That is a suggestion Button can work with.
He wants to set out straight away: ‘Sven,
would you gather up some examples of good
and bad pallets? I will get in touch with the
guys who supplied them. And Bert, who do I
talk to about the labels?’
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KEEP IMPROVING
111
Three Principles of a Structured Evaluation
Your implementation provided a description of how the solution should be
implemented in the company. By now, the organisation has adopted the
solution to the problem defined in phase 1 of the MPSM. Next is the
evaluation, an investigation into the effects of the change. The structured
way of approaching an evaluation is by using a list of focal points, such as
establishing the goal; finding out who the interested parties are; reviewing
which problem indicators you want to evaluate; and setting terms for the
evaluation method. In addition, an evaluation can be used to track down
those effects that you had not considered or had not thought of as
important. Say, for example, that you are the operator of a taxi van service
and want to evaluate your product. The evaluation criteria in that case are
linked to your passengers’ wishes. As it turns out, your transportation is
not limited to passengers – you also operate as a small package delivery
service. In that case, you will also need to evaluate your cargo. That
might lead you to purchase new vans to deliver packages across town. A
structured evaluation operates on three principles:
* Convincing people of the usefulness of an evaluation.
* Evaluate all phases of the MPSM, not just the final decision itself. Make
sure you also review issues you found earlier during your evaluation, but
which seemed unimportant at the time.
* Deal with the evaluation professionally.
§ 10.2
Evaluation as a Balancing Item
Users or decision-makers will rarely be the ones asking for an evaluation.
They tend not to see any point in it. Or they are not interested in its
outcome. Evaluating scores low on the scale of priorities. So if you want to
be able to perform a proper evaluation, you will need to be persuasive. And
take into account these potential arguments, facts, and attitudes you may
encounter on your path:
* ‘There are better ways of spending our time’. Investing in the new and
novel tends to go down much better than challenging established
activities or working methods.
* You may find that the goals that were set were too vague. Keeping things
vague can be in people’s interest. This makes it impossible to compare
the actual situation to the desired results.
* ‘That is just the way things are around here. Cannot be helped’. Office
staff may have become used to the occasional network outage.
Employees have come to accept the issue. And they are not looking
forward to the fuss involved in an evaluation.
* Those who have championed the new approach, can often also be found
to oppose evaluating. An evaluation might show that the new approach
does not work after all, and that things need to be changed again. That
could be construed as a loss.
10
Evaluations. Nobody seems to be looking forward to them. These feelings of
evaluations being a necessary (or even unnecessary) evil are further
strengthened if nothing is done with the resulting information. You can
establish that something does not work. This is immediately followed by the
question: ‘So now what?’ Results can also lead to bickering. ‘Huzzah,’
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exclaim the supporters of the new approach following an 8% increase in
revenue. ‘An abject failure,’ mutter its opponents, because in their minds,
an 8% increase nowhere near justifies the investments that have been
made. In this case, it would appear that no clear agreements were made as
to what would have constituted an acceptable investment or increase in
profit. Either that, or people have simply changed their minds.
§ 10.3
MPSM: Guiding Along the Path of Evaluation
The objections to an evaluation and its associated problems can be
removed by applying the MPSM. You use the method to track down
indicators and causes of the problem, which lead to the criteria to be used
for evaluating solutions. This allows you to measure the effects to the
solution. In addition, you will have set goals during the process of
formulating alternatives. Those goals can be reviewed during the valuation
to see whether the desired effects have been substantial enough. If not,
you can go back to phase 3, the analysis of the problem. You may find
causes for the disappointing results there for the taking. It is even possible
that solutions you discounted earlier may end up being exactly what you are
looking for now. The phases of the MPSM also guide you along the path of
your evaluation, by reviewing your activities and findings at each different
phase.
§ 10.4
Evaluating Systematically
Take the people who fill in your questionnaires seriously. Do not merely
send out a short email, but provide a good, attractive looking questionnaire.
Make it easy to work with. People will feel less burdened if, for example, all
they have to do is check a box for yes or no. Use as many close-ended
questions as possible, but do allow people to write down any comments
they may have.
10
Summative
evaluaton
Formative
evaluation
Your evaluation should leave nothing to chance. You will need a professional
approach to gain the confidence of any naysayers. Be systematic, and first
establish the actual goal of your evaluation. Three important things to
consider in that respect are:
1 Checking whether your goals have been met. You measure whether the
problem has been reduced without looking at its causes. This is known
as a summative evaluaton.
2 Finding out the causes of the effects. For example, checking whether the
implementation went according to plan. This is known as a formative
evaluation.
3 Consider whether there are any possible improvements to be made.
Once you have established the goals of your evaluation, your next step is to
decide who is going to execute it. Should it be the trouble-shooter’s own
job? They know the company’s situation, and as such have access to a
wealth of information. But they are not impartial. The best approach is to
contract an evaluator from outside. And hiring an advisor costs money, you
can certainly demand a level of quality for whatever you spend.
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Line up the indicators of the problem you are evaluating. These consist of
the most important indicators of your original problem, but also those issues
subject to much uncertainty, the goals and effects whose importance was
(or will be) recognised later, or which are valued highly by the higher-ups. You
have to examine the full scope of the problem environment. That includes
any unintended (side-)effects. Say you are investigating whether costs were
successfully reduced by restructuring the production process. During your
evaluation, you may learn that the reorganisation had a side-effect:
Personnel costs have increased because more temps were hired. Those
temps were needed because of an increase in absenteeism which itself had
gone up because the reorganisation caused people to experience their work
as monotonous.
Involve Others in the Evaluation
Find out who have an interest in the solution of the problem. You will soon
arrive at individuals or groups who were originally bothered by the bottleneck.
But you may need to expand the list from there, for example with people who
are experiencing possible negative side-effects of an implemented change.
Convince the interested parties of the usefulness of the evaluation. Make an
inventory of questions they need answered. Try to get them to commit to the
evaluation – a job which is made more easy by setting agreements with
them. Think of the working method, others’ contributions to the evaluation,
and the method of discussing the results. Out of sight is out of mind, so
keep up the pace. If you fail to inform everyone on time, you may lose their
support. Make sure you keep (and keep to) a tight schedule.
Process the opinions of all parties involved in your final report. People need
to feel heard. That will not necessarily mean you will arrive at a unanimous
verdict, but it does mean that everyone will have to acknowledge that the end
of the evaluation process has been reached. Set up communications
regarding the results of your evaluation. Respond to the different needs for
information of different groups. It is generally advisable to stick to the same
story - but you may, for example, need to adjust the tone of voice, perspective,
or vocabulary to your target audience. What is crucially important to one
group can be considered an insignificant side-effect by another. Point out the
importance of taking the improvements suggested in the evaluation seriously.
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As the evaluation ends, the feedback process begins. Make sure that
everyone is convinced of that fact. The evaluation is not the end – it is the
beginning. There is a margin between the current and desired situations.
The problem owner is experiencing a discrepancy between the norm and
reality, an action-based problem. You return to the MPSM to focus on
phase 1, defining the problem.
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Summary
▶ The evaluation of an implemented solution should be handled in a
structured manner.
▶ People are often not keen on an evaluation. Convince them of its
usefulness.
▶ Use your findings from the different phases of the MPSM if the desired
effects of a change are not encountered strongly enough. You may find
the causes in the analysis, or may be able to use solutions you had
discounted earlier.
▶ Handle the evaluation professionally. Among others, this involves:
establishing the goal of the evaluation, making an inventory of people
experiencing the problem, formulating your goals as to be able to
evaluate them after, determining the indicators of the problem,
assembling the evaluation team and, above all, involving others in the
evaluation process.
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Core Concepts
Formative Evaluation
A way of evaluating whereby you review the causes of the
effects encountered. Reviewing whether the implementation
has gone according to plan, for example. This also involves
establishing whether your goals have been met.
Summative Evaluation
A way of evaluating which focusses on establishing whether
your goals have been met. You measure whether the size or
severity of the problem has decreased without looking at its
causes.
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In Search of Knowledge
While dealing with your problem, you will run into questions or uncertainties.
You will regularly find that you do not have the knowledge necessary to
deal with these issues. To obtain that knowledge, you will need to conduct
research. How do you solve knowledge problems? Using the research cycle,
you systematically collect the data you will need during virtually every phase
of the Managerial Problem-Solving Method.
This chapter addresses the following questions:
* What are the characteristics of a good problem statement?
* How do you arrive at a research design?
* What is the appropriate measuring method?
* What conclusions can you draw from the data you have obtained?
Cross-Sectional Research 124
Operationalisation 126
Longitudinal Research 124
Validity 127
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An Experienced Sales Team:
The Way Forward?
There is no more to be gained on the cost
side of things. A thorough analysis of the
disappointing quarterly figures concludes that
the only way forward is to sell more. That is a
bit of a bother. Major advertising campaigns
and radio commercials have so far failed to
do the trick. No choice but to hire better
sales agents. Just a matter of pulling a
couple of experienced, knowledgeable, and
technologically savvy salespeople from a hat.
But will that do the trick? Are those men and
women guaranteed to up the revenue? By
how much? Does existing literature indicate
that a year’s worth of experience equals a
certain increase in sales made?
What you have are questions. What you
need is knowledge. You can only begin to
solve your action problem once you have an
answer to your knowledge problem or
problems. You need to conduct research.
You approach the issue systematically. You
establish how your research should be
conducted, step by step. Your goal is clear;
so now you turn to formulating your problem
statement, your research questions, and
your research design. And then you start
answering questions: what are the variables
that make up the problem you are
researching? How should you conduct your
measurements? What about how the data is
processed? Once you have answered those
questions, you will have arrived at your
preliminary destination: drawing conclusions
by reviewing your problem statement.
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Gathering Knowledge Using the Research Cycle
Solving a managerial problem does not seldom involve researching certain
matters. Without the required data, your problem-solving approach will
grind to a halt. Before you can continue, you will first need to solve your
knowledge problem. Research is a regularly required step during nearly
every phase of the Managerial Problem-Solving Method. Only phase 5,
where you decide on which solution to choose for solving the problem, is
an exception. All other phases occasionally involve a short trip to the eight
phases of the research cycle, which are:
1 Formulating the research goal
2 Formulating the problem statement
3 Formulating the research questions
4 Formulating the research design
5 Performing the operationalisation
6 Performing the measurements (gathering data)
7 Processing the data
8 Drawing conclusions (reviewing the problem statement)
As with the MPSM, you may occasionally need to move back and forth
between the phases of the research cycle. When formulating the research
design, you may find that it is not possible to gather data (i.e. measure) by
questionnaires alone. If, for example, you want to investigate unconscious
behaviour of members of a works council, you will not be able to do so using
a questionnaire alone. You will need to adjust your problem statement,
limiting it to conscious behaviour. Adjusting the work you did during earlier
phases of the cycle is sometimes known as ‘retconning’. Retconning can
occur during every phase following phase 1 of the research cycle.
§ 11.2
Formulating the Research Goal
The research cycle starts with formulating the goal of your research. You
state the reason for wanting to solve the knowledge problem. The results of
your investigation are needed in order to deal with your action problem.
During this phase, you have to define what it is that you need to know. You
need the answers to a certain number of questions. What information is
required? What is already known? What is still missing? What knowledge do
you need your research to yield? Consider whether you need all missing
knowledge right now, or whether part of it can wait till later. Based on your
research results, you may have to conduct supplementary research later.
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Make sure you avoid conducting research for its own sake. An incorrect
research goal is easily identified. Come up with a hypothetical answer to
your research goal and see to what extent you can use it to solve your
action problem. If the answer does not help or even matter, you will have
asked the wrong question, and set the wrong goal.
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§ 11.3
Formulating the Problem Statement
You have established why you need to solve your knowledge problem. Time
to start the next phase: formulating the problem statement. Within the
context of the research cycle, formulating the problem statement means
formulating the knowledge problem. The smart thing to do is to formulate
the problem statement as a question. Avoid using a statement or theorem
for this purpose to make it easier to discern between an action problem
(formulated as a statement) and a knowledge problem (formulated as a
question).
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When formulating your problem statement, take into account the type of
research you are going to conduct. Make sure you take the following steps:
* Determine the type of research. Establish whether your research is to be
explanatory or descriptive. Descriptive research is about establishing
facts, for example the amount of absenteeism. Explanatory research is
about relationships between variables, for example the causes of
absenteeism. Whether you need to explain or describe depends on the
research goal.
* Define the variables. Similar to how you would as part of the MPSM, you
define variables like the revenue per employee in euros, or the length of
employment in years.
* Indicate the possible relationships between variables to be researched.
Note that this should be part of explanatory research only. There are
several possible scenarios:
– The first is that you know exactly which relationship(s) you want to
investigate. For example, if the poor working conditions the office staff
are subject to are most likely the cause of the low motivation levels,
and management has already got a plan in place improving the
situation with the help of new blinds and climate control. Here, your
problem statement could be: To what extent do the working conditions
determine the office staff’s motivation levels?
– The second is that you are already aware of several causes, but do
not yet understand which of these really matters. This means your
problem statement should be defined along the following lines: To
what extent do the working conditions, levels of training, and/or
possible rewards influence employee motivation?
– The third is that you do not have any clue as to the causes
whatsoever. In that case, your problem statement could start off as:
Which factors influence office staff motivation levels? This situation is
complicated by the fact that these factors may number in the
hundreds. Your best bet would be to start with some preliminary
research. You begin by studying relevant literature and conducting
some interviews aimed at uncovering potential factors. Next, your
main research investigates the influence of a limited number of
factors, the factors you expect to be the most likely culprits
considering the circumstances. Obviously, you do run the risk of
researching the wrong factors or overlooking others. But you should
limit that risk by being thorough in your work. Solid preliminary
research will reduce the chances of your main research failing.
* Determine the research population. These are the people, objects, or
items you wish to gain knowledge about, for example the sales team or
members of the accounting department.
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* Draft a model. You visualise the variables and their relationships.
Relationships are indicated using arrows. Figure 11.1 is a model of a
problem statement, namely: To what extent does the motivation of
employees in the accounting department influence productivity?
Model of a knowledge problem concerning the
relationship between motivation and productivity
FIGURE 11.1
Level of Motivation
Level of Productivity
* Choose a theoretical perspective. You indicate from which philosophy
found in scientific literature you intend to operate. Where motivation is
concerned, you will find that you will soon arrive at Maslov’s hierarchy of
needs. But Maslov has not been the only one to consider this topic. For
example, motivation can also be regarded from the perspectives of
Festinger’s theory of social comparison, or Herzberg’s two factor theory.
Whatever theory you choose; you define your variables based on
scientific literature. Alternatively, you can opt for a so-called disciplinary
perspective. For example, you only evaluate the financial consequences
of a certain decision, and do not consider its social repercussions. In any
case, you should note that the variables used in your problem statement
fit the perspective used.
Problem Statement Pointers and Pitfalls
* For research purposes, a close-ended question does not make for a
convenient problem statement. The answer to the question ‘Are the
employees motivated’ is simply either ‘Yes’ or ‘No’. A better question
would be: ‘What is the level of motivation of the employees?’
* Are you after facts or opinions? For example, do you want to know how
advisors feel about a certain topic, or do you want to know the facts
behind it? You could ask the advisors for the factual information... but
are they sure to be right, or objective? For example, the answer to
question ‘What reasons do investment advisors give for the rapid
development of countries like Brazil, Russia, India, or China?’ does not
yield a value-free answer. It would be better to ask: ‘What are the
reasons for the rapid development of countries like Brazil, Russia, India,
or China?’ You can consult investment advisors on both questions – their
answers could very well be different. Similarly, scientific literature is
home to a fair share of differing or even conflicting facts and opinions.
Your job is to compile them into your own conclusions.
* Make sure your question does not contain a norm. That would mean you
would be looking at an action problem, instead of a knowledge problem
in need of research. An example of a norm used in a problem statement
is: What should the company do to improve their German revenue?
‘Improve’ means the problem owner perceives a difference between the
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actual revenue and the desired revenue. In other words, they perceive a
discrepancy between the norm and the reality – an action problem. The
word ‘should’ also implies that there is a norm. Note that research never
tells you what you should do; at most, it tells you what you could do.
* The problem statement should not be almost the same as the research
goal. The problem statement explains what you intend to research. The
research goal explains why you intend to conduct research. Say your
problem statement is: What is the relationship between motivation and
productivity? You research goal in that case should not be: Gaining an
insight into the relationship between motivation and productivity. Rather,
it should be: Verifying the supposed cause (here: motivation). This is
knowledge you will need in order to implement the appropriate measures.
* Make sure you do not overgeneralise the problem statement. That will
not help you find specific enough conclusions for solving your knowledge
problem and thereby your action problem. Solving a more contained
knowledge problem is often more effective. An example of an
overgeneralised problem statement is: Which activities within the
production process are not proceeding according the established
procedures? A problem statement like that risks a flood of generalised
information, without going into the necessary details. In this case, it
would be better to examine part of the production process, thereby
generating more specific information which you can use for
improvements.
* Limit the number of variables in your problem. The large the number of
variables you investigate, the larger your problem becomes. Analysing
vast numbers of variables and their relationships soon becomes a timeconsuming matter. A thorough investigation into a more accessible
number of variables is much preferred.
§ 11.4
Formulating the Research Questions
Next, you start formulating your research questions. These are questions
used to split up a problem statement, thereby making it more accessible.
Research questions are also convenient for a proper division of labour; you
can assign aspect of your research to different researchers based on the
different questions.
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It is important that the research questions are somehow systematic.
Problem statements lend themselves to many hundreds of questions, but
the ones you actually ask should be relevant. And you should, of course,
make sure there is nothing you have overlooked. Two things made easier by
using a systematic approach in order to concretise your problem statement.
When coming up with research questions, use your systematic approach in
tandem with a creative one. First, come up with as many questions as
possible. Next, cluster the questions according to their theme(s). Order the
clusters into a structured whole; a system or logic. This will help you pick
out any bottlenecks. For example, not all themes may fit your system, for
example leading to answers indicating both personnel and financial
problems. This may mean that certain questions are irrelevant to solving
your knowledge problem, or that you should reassess your logic. And your
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side-step into systematic logic can also inspire new ideas. If you find
indications of both personnel issues and financial issues, you could
consider that these are both managerial functions. So: ‘What about other
similar functions, such as commerce, R&D, and production?’
You can keep refining this method, until you arrive at an appropriate and
complete set of research questions. This way, you will prevent omitting any
important topics or asking the questions twice. You can test the quality of
your research questions by applying the following questions:
* Do the research questions contain all the variables of the problem
statement?
* Do the research questions have any new variables not found in the
problem statement? If so, you will need to adjust either the problem
statement or the research questions.
* Do any of the research questions overlap? Remove any (partial)
unwanted duplicates.
* Has the number of variables and relations per research questions been
kept to a minimum? Aim for two variables per research question.
§ 11.5
Formulating the Research Design
You have established the topic of your research. You have formulated your
research goal, your problem statement, and your research questions. You
know what you are going to look into. Next, you need to establish how your
research is to be conducted. That starts with strategy. You formulate how
you intend to reach your goal. Making choices, that is the thing now. Here
are several choices to consider:
* Do you want to influence your variables? A lot of research requires that
you measure only, and do not influence any factors yourself. Say, for
example, that you want to measure iPad owner satisfaction with the
device’s user-friendliness. You can interview iPad users about their
experiences. Alternatively, you can have a group of subjects complete
certain tasks and then ask them about their feelings regarding userfriendliness afterwards. The latter is a type of experiment, an
assignment, which influences them. The assignment which uses the
iPads here is called a ‘stimulus’.
You can also give subjects a set of different iPad assignments of
increasing levels of difficulty. This way, you can measure whether their
opinion of user-friendliness is influenced by the degree of difficulty of the
assignment. You can even vary the external conditions of the test, for
example between fully closing to fully opening the blinds – text on an
iPad is sometimes difficult to read in direct sunlight. The measurements
you can get from an experiment are accurate, but experiments are often
expensive and demand secure preparations. You need to prevent your
measurements being influenced by forces outside your control.
* Do you wish to be in direct contact with your research population? Desk
research or literature studies do not put you in touch with your research
population. A questionnaire or observational study will bring you closer to
the group you are investigating. Literature studies are relatively cheap, and
convenient if no research population is available – something that can
occur if, for example, you want to research events or situations in the
distant past. Contact with a research population will often yield information
not available from any literature, such as personal opinions of office
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Cross-sectional
Longitudinal
11
employees. On top of that is the fact that your own research can let you
measure exactly what you are interested in, while other people’s research
is more confined to their interests. One disadvantage is that research
involving contact with a research population is often quite expensive – and
not all participants are necessarily looking forward to cooperating.
* Do you conduct your research under laboratory conditions? The option to
perform research under controlled circumstances is a potential asset. It
is also, however, a more expensive way of researching. In addition, you
will have to very carefully determine the circumstances or setting. Do you
intend to go for broad or for in-depth research? If you want to know to
what extent Joe or Jane Public is in favour of a military mission to Africa
or Asia, then that is considered broad research – and a questionnaire is
an instrument well-suited to the task.
But if you want more insight into organisational changes within a
company, you could opt for a case study of several months’ worth of
internal investigations. That type of research is known as in-depth.
* Do you choose cross-sectional or longitudinal research? Cross-sectional
research is where all measurements are conducted virtually
simultaneously. Think of a one-time questionnaire on employees’
opinions of the new travel expenses remuneration arrangement. But, on
the other hand, if you approach the same group or address the same
topic at different points over a (longer) period of time, this is known as
longitudinal research. Longitudinal research is the type used if you want
to know, for example, how the employees’ opinions of the remuneration
arrangement have changed over time. You might submit your
questionnaire immediately following the arrangement’s introduction,
followed by additional measurements (using the same or a similar
questionnaire) three months and/or six months later. This longitudinal
research may show that employees were initially dissatisfied but, in time,
have begun to see the advantages of the new arrangement.
‘To Do’-List
The answers to the previous questions constitute your research strategy.
The details of your research design are completed by establishing the
points on the following ‘to do’-list:
* Research Population. This may require a more specific description of
the individual(s), group(s), or organisation(s) you wish to use as the
subject of your research than you had given in your problem statement.
This is especially true for explanatory research. If, for example, you are
researching the relationship between the innovative capabilities of
small-to-medium-sized chemical companies and their success rate,
your research population should not be limited to successful
companies only. You are not only measuring how innovative very
successful companies are; you also want to know how innovative less
successful companies are. Only then can you make some claim as to
whether successful companies are more innovative than less
successful ones.
* Subjects. This concerns the units or group you are actually going to
measure. Say that your unit is car mechanics. The units need not
necessarily be parallel to the research population; in this case, the
research concerns car dealerships. These dealerships are companies;
abstract concepts which you cannot interview for an opinion. For that
reason, you choose a different subject - here, car mechanics.
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* Sample. You will need to decide on conducting a sampling and, if so,
establish how your sampling is to be executed. You could choose a
random sample, where all elements of the group from which you draw
your subjects stand an equal chance of taking part; or a representative
sample, where, for example, the ratio of men to women matches the
reality. Alternative, you can opt out of sampling, but choose an extreme
case, examining the most unusual aspects since those are the ones you
stand to learn the most from.
* Data Gathering. There are various and varied ways of gathering data, with
examples including but not limited to: observations, interviews,
questionnaires, or analyses of primary sources.
* Processing and Analysing. How do you handle your data? Do you
emphasise the quantitative or the qualitative? Obtaining some telling
quantitative data is nearly always possible; it is highly insightful to
conduct open interviews to ascertain how employees feel about a
company’s reward system. But that sort of information dramatically gains
in conviction if you can demonstrate that dissatisfied employees number
in the order of 70%. The danger of restricting your research to the
qualitative is that the conclusions you reach tend to be overly generalised,
or even ambiguous. Some numerical data used in a supporting role is a
good way of deciding, for example, which of a number of possible
qualitative explanations are the most likely candidates. But there are
some downsides to quantitative research as well. Numbers can offer a
false sense of security. An average of 5-year tenures of 78% of employees
seems a good thing. Low employee turnover figures mean low training or
recruitment costs. But it is entirely possible that many people opt to stay
not out of loyalty, but because they simply have no one else that will hire
them. The question is: Are those the people you would want working for
you? Another potential hitch occurring in quantitative research is that
measuring variables takes substantial preparation. If you are interested in
someone’s opinion, a few general questions made more explicit during an
interview, a form of qualitative research, can be sufficient. If you are
interested in expressing, for example, an employee’s opinion on a reward
scheme in terms of a score out of 10, you will have to carefully consider
what you are going to ask. But is this required planning time a
disadvantage? You should note that thoroughly preparing your questions
has a way of saving time later on. A massive pile of numerical data is
more easily to analyse than a massive pile of quantitative data, no matter
how clear and interesting your questions seemed during the interviews. In
hindsight, the notes you made and the conversations you recorded may
turn out to contradict each other, or even be unrelated to the matter you
were trying to touch upon in your problem statement.
* Report Structure. You come up with a layout and preliminary table of
contents for your research report in advance.
* Activity Schedule. You draft a planning for all the steps you aim to take
during your research, to which you can refer back along the way.
§ 11.6
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Performing the Operationalisation
Now that you know what it is you want to research and how you are going to
go about it, it is time to make your variables quantifiable. Abstract variables,
such as status, motivation, or assertiveness, cannot be measured. You
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need to operationalise them using indicators. This process is the same as
for variables found in action problems (see paragraph 4.5: Making Problems
Quantifiable). If you wanted to measure the status levels of managers, you
could look at the authority they are attributed, or the size of their office, for
example. The larger the office, the higher the status level. Note that you
will need to be able to provide evidence of the relationship between the
indicator and the variable, either using existing or original research.
Indicators are used to highlight a number of aspects of your variables. The
combination of aspects does not necessarily have to encompass the
variable exactly. This method of using indicators is known as concretising.
Alternatively, you may need to split up your variables into separate
components. The indicators of profit, for example, are turnover and costs.
When settled against each other, these variable do exactly amount to your
variable. This method of splitting up variables is known as decomposing.
Operationalisation
§ 11.7
11
Concretising or decomposing/splitting variables are logical approaches to
operationalisation. It will help readers of your research report understand
your methods. Because you have specifically indicated what it is you intend
to measure, you will be able to handle existing theories in a better, more
focussed manner. Proper operationalisation also ensures your research will
yield the data you expect it to. In the example of manager status saw the
use of the maxim ‘The bigger the office, the higher the status’. Here, office
size is an indicator of status. The same rule will not apply to a manager who
has been kicked upstairs, and has received a larger office by way of
compensation. You have to make sure the indicators you use are tailored to
the circumstances of your investigation; are you looking at successful
managers, or managers who have been kicked upstairs?
Performing the Measurements
You research report is not limited to the results of your measurements – it
should also indicate any factors potentially influencing their validity and
reliability. For example, you should mention the level of cooperation your
interviews received. Is it possible to draw conclusions if an important part
of the research population refused to cooperate? You should also mention
any possible errors in the measuring method. It is possible that a lot of the
people you interviewed did not understand some (or any) of the questions
they were asked. What did you do to correct that oversight? Are your actions
potentially of influence on the results?
The scientific quality of all research is measured by its reliability and its
validity. In the example of a watch, for example, you will see the connection
between the two concepts. If you have a watch that is always ten minutes
fast, then you have a reliable watch. However, its time measurement is not
valid - it does not indicate the correct time, but rather what time it will be
ten minutes from now. If, on the other hand, you have a watch that wavers
between being fast and being slow, then your watch is unreliable in its
timekeeping. It may occasionally hit on the correct time as it moves from
fast to slow; even a watch that does not run at all will indicate the correct
time twice every 24 hours. But the points at which these faulty watches do
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so are accidental – and they are unknown if you do not have a reliable
watch to verify them with.
If a watch is unreliable, then its time measurement cannot be considered
valid.
Reliability is concerned with the stability of the research results; similar
research conducted at a later date using the same method ought to yield
the same results. Validity is concerned with the contents. Have you
measured what you intended to measure? Does the questionnaire yield the
correct data? There are many potential threats that can compromise the
validity of your research. These are three examples:
1 Internal Validity. This is concerned with whether the research design and
your measuring instruments have been properly formulated and
constructed. One potential threat is that of self-selection. If you want to
replace company PCs with iPads, and you ask for several volunteers to try
them out, there is every chance that you will end up with a group of digital
device enthusiast; people whose approach to a company iPad would be
radically different from that of the average employee. The information you
gain from this experiment, therefore, is probably of very little use.
2 External Validity. To what extent can you apply your research to other
groups than your research population? Here, the main threat is that of
unjustifiable generalisations. Measures that effectively address
vandalism in a small town environment are not necessarily very useful
when applied in a major city.
3 Construct Validity. This type of validity is concerned with abstract
concepts. You establish whether they have been properly operationalised,
logically related and, where possible, based on available scientific
knowledge. A potential threat is that of an insufficiently specific definition
of the concepts used in the problem statement. This is something that
happens if, for example, the problem statement is concerned with
employee motivation without specifying what ‘motivation’ entails. Is it
only concerned with employees performing their tasks, or also with
working for the company with a measure of satisfaction? Using a problem
statement that clearly specifies how ‘motivation’ is defined means
limiting the risk of using indicators for both types of motivation.
§ 11.8
Validity
Processing the Data
Your research design will generally not allow for a detailed schedule or plan
for the analysis of your data. That is not a problem, because you will often
come to new insights during the measuring phase – and that would mean
having to revisit and change a previously established analysis plan.
Nevertheless, your research design does need some comments regarding
data processing, if only for you to help guide yourself along the right lines
and help you keep an eye on your route along the way. Whatever you do, try
to make sure your method of analysis is a simple one. Complicated
statistical models are only useful if the quality of the information available
is exceedingly high. Generally speaking, though, it is not. A simple cross
table tends to suffice quite well.
During this phase, you should also remember to spend some time on an
evaluation of the validity and reliability of the measurement results. Have
enough people taken part in your questionnaire for you to be able to draw
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any conclusions? Have any of the interviewees misinterpreted some of the
questions, leading to inconsistent answers? Should you really have been
measuring some additional variables as well? Since hindsight is 20/20, you
will often find points you could have changed or improved. That is generally
not a problem; no research is perfect, and there are almost always enough
interesting results left to work with. Be that as it may, though, you have to
be honest about any mishaps in your research report. And ‘retconning’ (see
paragraph 11.1) will often get you a long way.
§ 11.9
Drawing Conclusions (Reviewing the Problem
Statement)
You have arrived at the final step in your investigation. It is time to draw
your conclusions, to see what exactly your research has yielded. Can you
give a full answer to your problem statement? Or can you only draw
conclusions for certain aspects or situations?
Truthfully consider to what extent you have been able to answer the problem
statement. New insights or missing data may force you to conclude that
there are some questions still open. That is not a problem, as long as you
can be honest about it. If you find, for example, that you cannot make any
claims about the entire company, but only about a single branch, then say
so – and do not make recommendations for the entire company anyway.
You may even have to adjust your problem statement – keep in mind the
potentially useful concept of ‘retconning’.
Remember that any result is a result. If you wanted to establish whether the
old machinery is the cause of the poor quality of goods produced, and it
turns out that it is not, then that does not mean your research has failed. At
most, you will have to restart the search and come up with alternative
causes of the poor quality. And the knowledge that the machines are not
the culprit is still valuable. It is not an obvious fact, or you would not have
been pursuing it as a cause anyway.
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You check whether you have met the prerequisites of your research. To do
so, you can use these questions. Can you answer both with ‘Yes’?
1 Are the facts (i.e. the results) separate from your personal interpretation
(i.e. your conclusions/opinions)?
2 Is there an explicit link between the solution to the knowledge problem
(i.e. your research) and the actions you will need to perform to solve the
action problem?
If the answer to either question is ‘No’, then you will need to conduct
additional research. If it is a resounding ‘Yes’ all round, then you can use
your newfound knowledge to continue dealing with your action problem.
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Summary
▶ You will require knowledge at various points during your problem-solving
approach. Knowledge may require research. The research cycle is a way
of conducting research step by step.
▶ Begin by formulating your research goal. State the reason for wanting to
solve the knowledge problem.
▶ Formulate a problem statement. Phrase it in the form of a question.
Consider the type of research involved: descriptive or explanatory.
Define your variables and indicate the relationships to be researched.
Establish your research population. Draft a model. Use a theoretical
perspective if necessary. Keep the following tips in mind:
* Do not phrase your problem statement as a close-ended question.
* Draw your own conclusions from potentially biased and conflicting
available information
* Make sure your problem statement is not identical to your research
goal
* Do not overgeneralise your problem statement
* Limit the number of variables to keep your research orderly and
accessible.
▶ Formulate your research questions systematically.
▶ Formulate your research design, the intended strategy of your research.
Answer the following questions:
* Do you want to give your subjects stimulus?
* Do you want or need to be in contact with your research population?
* Do you conduct your research in laboratory conditions?
* Do you want your research to be broad or in-depth?
* Do you want to conduct cross-sectional or longitudinal research?
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▶ Operationalise your variables (resulting in indicators). You can choose to
concretise: use indicators to highlight several aspects of your variable
which need not necessarily amount to the variable exactly. Or you can
choose to decompose: split up your variables into separate components
which, when combined, add up to your variable exactly.
▶ Perform your measurements.
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▶ Indicate how you processed the data. Clarify how you gathered your
data. Choose as uncomplicated a method of analysis as possible.
Indicate any potential influences on their validity and reliability.
▶ End by drawing conclusions and revisiting the problem statement.
Consider whether you can fully answer the problem statement. If so, use
your newfound knowledge to solve your action problem. If your
conclusions can only apply to certain aspects or situations, you will
need to conduct additional research.
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Core Concepts
Cross-Sectional Research
A method of research which involves performing all
measurements virtually simultaneously.
Longitudinal Research
A method of research which involves performing measurements
at different points in time. These measurements are then
compared for differences.
Operationalisation
Using indicators to make variables quantifiable.
Validity
Refers to the quality of research results. Are you measuring
what you had intended to measure? There are several types of
validity, such as internal validity (concerned with properly
formulating and constructing research designs and measuring
instruments), external validity (concerned with the extent to
which the research can be applied to groups other than the
research population), and construct validity (concerned with
whether abstract concepts are properly operationalised,
logically coherent and, where possible, based on available
scientific knowledge).
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Sources
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Internet:
Quotes via quotes.net. Taken from http://www.quotes.net/quotations/problems on July 11th,
2016
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Illustration Acknowledgements
Shutterstock, New York: p. 8, 18, 28, 38, 52, 60, 72, 90, 100, 108, 116
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Index
A
Action problem 21
Attributes 77
B
BCH model 103
Bottom-up 104
C
Causality 67
Change management 104
Concretising variables 47
Conjunction criteria 77
Consensus 76
Cross-sectional 124
Cut-off criteria 77
D
D3: Do, Discover, and Decide 55
Decomposing variables 47
Discrepancy 22
F
Formative evaluation 112
I
Implementation plan 103
K
Killer requirements 77
Knowledge problem 23
L
Language of variables 14
Lexicographical method 81
Longitudinal 124
M
Majority rule 81
Managerial Problem-Solving
Method (MPSM) 11
Measurement levels 64
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Morphology 86
MoSCoW rules 82
N
Non-compensatory 77
O
Operationalisation 126
P
Probability theory 95
Problem analysis 63
Problem cluster 42
Problem context 41
Problem identification 42
Problem owner 22
Q
Qualified majority 76
Quick and dirty 41
R
Research cycle 55
Research population 23
S
Scenarios 95
Sequential order 67
Statistical relationship 67
Sub-attributes 78
Summative evaluaton 112
Synectics 85
T
Threshold value 95
Top-down 104
V
Validity 127
Y
Yammer 104
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About the Authors
Hans Heerkens (1958) teaches the methodology of problem-solving,
researching, and decision-making as part of various courses at the
University of Twente and several business schools. His research and
advisory work are concerned with the managerial aspects of aviation,
in particular the development of unmanned cargo aircraft and
strategical decision-making processes in the aviation and defence
industries. He holds a PhD in decision theory.
Arnold van Winden (1957) teaches Communications at the
Amsterdam University of Applied Sciences. He is thoroughly familiar
with communications and project management, and the subjects he
teaches include communications during change processes and
dealing with the media. For many years, Van Winden worked in various
communications-related functions. He studied journalism and
obtained an MBA at Business School Netherlands.
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