”Complexity Theory and
Innovation Management”
Dr. Harri Jalonen
Principal lecturer
Turku University of Applied Sciences, Finland
harri.jalonen@turkuamk.fi
http://www.youtube.com/watch?v=Naf0jxDd-R0
Nowadays private and public organizations have to face new challenges.
Complexity, uncertainty, crisis, change, and turbulence are common for all kind of
organizations. This also questions traditional approaches for innovation
management. More theoretical and practical knowledge is needed for the
understanding of the approaches, models and tools for supporting the renew and
the development of new business models. Adapting complexity theories, this
lecture provides a new perspective on innovation management in complex
organizations."
“One has to make up his mind whether he
wants simple answers to his questions – or
useful ones… ….you cannot have both.”
(Joseph Schumpeter, in 1930)
‘creative destruction’
”The question is not how capitalism
administers existing structures, but how it
creates and destroys them, causing
continuous progress and improved standards
of living for everyone”
(Joseph Schumpeter in 1930s)
Knowledge/information is the basis for
development of new products, production
processes, the opening of new markets,
adoption of new raw materials, and
reorganizing of economic sectors.
(Joseph Schumpeter in 1930s)
Agenda
1) 10 Starting points
2) What is an organization?
3) What is an innovation?
4) A short introduction to complexity theory
5) Case: ”Managing innovations in complex welfare service systems”
harri.jalonen@turkuamk.fi
1) 10 Starting points
harri.jalonen@turkuamk.fi
STARTING POINTS (#1)
DATA – INFORMATION – KNOWLEDGE
harri.jalonen@turkuamk.fi
STARTING POINTS (#1)
a) Data
-not yet intrepreted symbols
-simple observations
-unstructured facts
-text that does not answer questions to a particular problem
harri.jalonen@turkuamk.fi
STARTING POINTS (#1)
b) Information
-”in form”, ”informare”
-a flow of meaningful messages or data with meaning/structured
data with relevance and purpose
-includes all the documents and verbal messages that make sense
or can be interpreted by organizational members
-transferred or shared among people
-involves actions of sensing, collecting, organizing, processing,
communicating, and using expressions and representations of
own or others’ knowledge
-text that answers the questions who, when, what or where
harri.jalonen@turkuamk.fi
STARTING POINTS (#1)
c) Knowledge
-justified true belief (Platon)
-the capacity to act (Sveiby)
-experience, values, insights and contextual information
-obtained from experts based on actual experience
-originates and is applied in minds of “knowers”
-personal
-involves understanding, using, applying, interpreting:
the “knowers” know
harri.jalonen@turkuamk.fi
STARTING POINTS (#1)
EXAMPLE
Data
54554
 exam results
Information
Extract from a study register
A course code
2920205
2920210
2920405
2920600
A course mark
5
4
5
5
Knowledge
Course marks are exceptional  it´s worthwhile to consider postgraduate
harri.jalonen@turkuamk.fi
STARTING POINTS (#1)
VALUE OF INFORMATION/KNOWLEDGE
Increase the capacity to
act
.
”Train leaves from London to Edinburgh”
”Train to Edinburgh leaves 22nd of
November 10:15 a.m. from the King’s
Cross”
STARTING POINTS (#2)
Two types of Knowledge
(Nonaka & Takeuchi 1995 and Polanyi 1967)
TACIT KNOWLEDGE
(Subjective)
EXPLICIT KNOWLEDGE
(Objective)
Knowledge of experience (body)
Simultaneous knowledge (here and now)
Analog knowledge (practice)
Knowledge of rationality (mind)
Sequential knowledge (there and then)
Digital knowledge (theory)
e.g.,
Intuitions
Unarticulated mental models
Embodied technical skills
e.g.,
Meaningful set of information articulated in clear
language incl. numbers or diagrams
Personal, context -specific
Formal, objective, codifiable
harri.jalonen@turkuamk.fi
STARTING POINTS (#2)
Test your tacit knowledge.
http://www.sveiby.com/articles/TacitTest.htm
Karl-Erik Sveiby
www.sveiby.com
harri.jalonen@turkuamk.fi
STARTING POINTS (#3)
INFORMATION SEEKING IS COSTLY
The optimal amount of information is
reached when further efforts are not
worth their cost.
harri.jalonen@turkuamk.fi
STARTING POINTS (#3)
”The difference between the information available
and the information required
for an optimal decision.”
(Galbraith, 1973)
”Information can have a positive or negative value
depending on whether it is a source of pain or
pleasure. People and organizations often do not
want more information.”
(Weick & Ashford, 2001)
harri.jalonen@turkuamk.fi
STARTING POINTS (#3)
Information stickiness
(von Hippel, 1994)
Information stickiness is a result of costs related to acquire, transfer, and use of
information compared to the value or benefit of the information sought
Due the stickiness information seekers and information providers do not
encounter each other in a way that they are able come to new insights that were
not available based on information from one source.
harri.jalonen@turkuamk.fi
STARTING POINTS (#4)
”The VALUE of knowledge is
a function of TIME”
BUSINESS
VALUE
Business event
DATA LATENCY
VALUE
LOST
Data ready for analysis
ANALYSIS LATENCY
Information delivered
DECISION LATENCY
Action taken
(Hackathorn 2004)
TIME
ACTION TIME
harri.jalonen@turkuamk.fi
STARTING POINTS (#5)
”All men by nature
desire to know”
Aristoteles (384 BC – 322 BC)
”Ignorance is bliss.”
(Gray, 1765)
STARTING POINTS (#5)
The hidden side of the knowledge
behavior = information avoidance
Cognitive
Social
Technological
Cultural
Economic
INFORMATION
FILTERS
(Jalonen 2010)
harri.jalonen@turkuamk.fi
STARTING POINTS (#5)
”ingrained pattern seeking”
”confirmation bias”
Nassim Nicholas Taleb (2007) The Black Swan.
The Impact of the Highly Improbable.
harri.jalonen@turkuamk.fi
STARTING POINTS (#5)
(Taleb 2007)
harri.jalonen@turkuamk.fi
STARTING POINTS (#5)
All swans are white – are they?
harri.jalonen@turkuamk.fi
STARTING POINTS (#5)
1) Joey seemed happily married. He killed his wife.
2) Joey seemed happily married. He killed his wife to get her
inheritance.
(Taleb 2007)
The second statement seems more likely…
However, it is a pure mistake of logic, since the first, being
broader, can accommodate more causes, such as he killed his
wife because he went mad, because she cheated him with the
postman, because he entered a state of delusion and mistook
her for a financial forecaster……..
harri.jalonen@turkuamk.fi
STARTING POINTS (#6)
Logic of
convergence
Knowledge
exploitation
Knowledge
exploration
AMBIDEXTROUS
ORGANIZATION?
Facts
Explicit knowledge
Hierarchy
Boundaries
Decision-Making  choices
Problem-Solving
Measurement
Ideas, intuitions
Tacit knowledge
Interpretation
Autonomy, empowerment
Interaction
Decision-Making  alternatives
Problem-Finding
Dialogue, communication
Logic of
divergence
harri.jalonen@turkuamk.fi
STARTING POINTS (#7)
harri.jalonen@turkuamk.fi
STARTING POINTS (#7)
(Eppler & Mengis 2004)
harri.jalonen@turkuamk.fi
STARTING POINTS (#7)
-too much information
-too little information
 Information anxiety
Uncertainty = absence of information
Equivocality, Ambiquity = existence
of multiple and conflicting
interpretations and lack of
understanding
(Daft & Lengel 1986, Weick 1995)
harri.jalonen@turkuamk.fi
STARTING POINTS (#8)
INFORMATION REDUNDANCY
PROBLEM AND INEVITABLE CONDITION
…is annoying and time consuming to the user, since
the user may need to read the same information
multiple times in multiple different documents. Once
the user finds a particular piece of information in one
document, time should not be wasted reviewing the
same information in many other documents
(Brill & Dumais 2006).
…is an enabling for knowledge creation which is
defined as the exitence of information that goes
beoynd the immediate operational requirements of
organizational members
(Nonaka &Takeuchi 1995).
harri.jalonen@turkuamk.fi
STARTING POINTS (#9)
Innovation is a world of uncertainty and equivocality!
But at the same time uncertainty is a basis for new knowledge!
(Moensted 2006)
harri.jalonen@turkuamk.fi
STARTING POINTS (#10)
A normal problem for managers is
to decide on potential innovation
growth projects at an early stages
of development.
They often face a pressure both to
avoid failures of investments in
’false positives’ and also projects
later proven successful in other
contexts, i.e. ’false negatives’.
(Moensted 2006)
harri.jalonen@turkuamk.fi
STARTING POINTS (#10)
Clear tendency to fail
http://www.ideachampions.com/weblogs/archives/2010/06/55_reasons_why.shtml
56 Reasons Why Most Corporate Innovation Initiatives Fail
"Failure is only the opportunity to begin again, only this time
more wisely."
Henry Ford
"Success is the ability to go from failure to failure without
losing your enthusiasm."
Sir Winston Churchill
Uncertainty &
Ambiguity
Divergence &
Convergence
Data-Information-Knowledge
Information
redundancy
Information
filters
Information
overload
Time
Explicit-Tacit
Knowledge
Confirmation
bias & pattern
seeking
”Trying is the first step to failure”
Homer Simpson
Knowledge
explotion &
exploration
Value
PROPOSITION #1
Knowledge cannot be managed – only enabled.
This is done through a process of interaction, in
which people interpret information and make
judgements on the basis of it.”
2) What is an ORGANIZATION?
harri.jalonen@turkuamk.fi
WHAT IS AN ORGANIZATION?
WHAT IS AN ORGANIZATION?
Some features of organization
-it is about people (their needs, ambitions, fears…)
-it is about interaction between people (within the same organizational level and
between different organizational levels)
-it is about other resources (factor of production: capital, machinery…)
-it is about goal (setting and achievement)
-it is about boundaries (in and out)
-it is about management and leadership
 It´s more or less messy!
harri.jalonen@turkuamk.fi
WHAT IS AN ORGANIZATION?
Organization as a Jigsaw Puzzle
• There are boundaries (straight edged pieces)
• Each piece plays a specific role
• Pieces are highly interconnected
• Each piece is unique in its nature
• The solution may be fragile (breaks)
• The whole is more than the sum of its parts
• Central and peripheral pieces
• There are ‘natural groupings’ (colour)
• Pieces need someone to connect them
• Speed of solution relies on the ability to ‘see’ the whole
picture
(Paraskevas 2007)
WHAT IS AN ORGANIZATION?
ORGANIZATION
a VERB or a NOUN?
harri.jalonen@turkuamk.fi
WHAT IS AN ORGANIZATION?
”It´s not the strongest of the species that survive nor the
most intelligent, but the one most responsive to change”
(Charles Darwin)
In what ways can it be paralleled to an organization?
WHAT IS AN ORGANIZATION?
Is it ”a machine” or ”machine-like
OR
Is it ”an organism like dynamic living
system”?
harri.jalonen@turkuamk.fi
WHAT IS AN ORGANIZATION?
ORGANIZATION as a SYSTEM
• A system is any set of mutually interdependent elements
that co-exist with a purpose.
• The mutual interdependence of a system means that
changes introduced into one part of the system will bring about
changes elsewhere.
(Paraskevas 2007)
WHAT IS AN ORGANIZATION?
(Paraskevas 2007)
WHAT IS AN ORGANIZATION?
As the ontology shifts,
epistemological and
methodological
consequences are
explicit…
harri.jalonen@turkuamk.fi
WHAT IS AN ORGANIZATION?
The Two Cultures of Management*
a nature of problems
Old and
routine
problems
New and
changing
problems
a nature of solutions
Only old ideas
are needed
Skills and
knowledge
are at use
Risks can be
calculated
New and novel
ideas are needed
complexity
uncertainty
New skills and
knowledge are
needed
Uncertainty not
turned into risk
unpredictability
Best fit can be
found
* Charles Percy Snow, The Two Culture and Scientific Revolution
Create knowledge
to meet an evolving
world
48
WHAT IS AN ORGANIZATION?
Traditional Management
It means simply this:
Make an analysis of your
environment , design your
strategies, make everybody
align with them, and act
Plan,
act,
evaluate,
and correct
(Harisalo 2009)
49
WHAT IS AN ORGANIZATION?
Assumptions of Traditional
Management
• Knowledge is a product – its only problem is how to find it
• Knowledge helps to recognize strong trends
• Strong trends helps to decide what the organization will do and
provide to its customers
• These decisions – strategic of their nature – require biggest possible
consensus – unanimity – in the organization
• Aligning the organization requires hierarchy in division of labor
• Strategic purposes legitimize the organization’s existence
(Harisalo 2009)
50
WHAT IS AN ORGANIZATION?
Interaction as a Strategic Way to Create Value
It means simply this:
Value is created together with
service professionals and clients
Designing,
experimenting,
implementing, and
correcting are
reciprocal processes
(Harisalo 2009)
51
WHAT IS AN ORGANIZATION?
Assumptions of Reciprocal
Management
• Its true nature is research and development:
– from implementing to meeting new challenges in work
• Novel ideas and knowledge are created in interaction:
– from knowledge management to managing ignorance in work
– from executing plans to discovering possibilities
• Divergent thinking, different thinking, paradoxes, and constructive
opposites are needed to speed up interaction:
– the job of managers is to pave way to these things which in traditional
management were barriers of efficiency and effectiveness
• Experiments in small scale must be allowed and managerial
responsibilities must be decentralized
(Harisalo 2009)
52
PROPOSITION #2
Organizations are organic, living systems. People in
complex organizations hardly even accomplish their
joint actions and goals following entirely the
designed systems and processes. Pre-designed
systems simply cannot encompass every event in
complex environments. However, coherent efficient
action can (and should) take place also in complex
environments.
harri.jalonen@turkuamk.fi
3) What is an INNOVATION?
harri.jalonen@turkuamk.fi
WHAT IS AN INNOVATION?
Innovation is the generation, acceptance
and implementation of new ideas,
processes, products or services which have
(economic) value (Rogers 1983)
Radical innovation
The creation of something entirely new
Incremental innovation
Primarily adaption of an existing product or process
harri.jalonen@turkuamk.fi
WHAT IS AN INNOVATION?
“Seeing things in a new way” &
“Doing things differently”
(Joseph Schumpeter, 1934)
Novelty in action (Altshuler & Zegans 1997)
harri.jalonen@turkuamk.fi
WHAT IS AN INNOVATION?
Novelty is context-dependent!
Every idea has been an innovation sometimes.
Any list of innovations must change with the times.
(Rogers & Shoemaker, 1971)
harri.jalonen@turkuamk.fi
WHAT IS AN INNOVATION?
“Innovation is work rather than play:
Everything always comes from
work, including the free gift of the idea
that arrives.”
(Meier 2007)
“Chance favours only the prepared
minds.”
(Pasteur 1822-1895)
harri.jalonen@turkuamk.fi
WHAT IS AN INNOVATION?
Innovation is not good nor bad!
“Innovation is a ’moment of danger’
because you loose control.”
(Meier 2007)
harri.jalonen@turkuamk.fi
http://freakonomics.blogs.nytimes.com/2010/02/09/change-happens/
harri.jalonen@turkuamk.fi
SERENDIPITY
SERENDIPITY
http://www.nautis.com/2007/07/what-is-serendipity/
harri.jalonen@turkuamk.fi
WHAT IS AN INNOVATION?
harri.jalonen@turkuamk.fi
WHAT IS AN INNOVATION?
Dilemmas in management of innovations
Equilibrium
Stability
Fit to model
Analysis
Exploiting opportunities
Known
Management
Closeness
Dynamic
Change
Creating model
Intuition
Exploring opportunities
Not yet known
Entrepreneurship
Oppeness
AMBIDEXTROUS
ORGANIZATION?
harri.jalonen@turkuamk.fi
PROPOSITION #3
What is needed is not ‘good design’ for innovation
per se, but creation of the conditions that allow the
emergence of innovation.
4) A short introduction
to complexity theory
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
Complexity - a situation or a problem that is difficult to understand or
complicated to handle
English word ”complex” is derived from the Latin
Complex behaviour arises from the intricate inter-twining or interconnectivity of elements within a system and between a system and its
environment (Mittleton-Kelly 2003)
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
Complexity – a basic property of a system
Complexity enriches traditional systems theory by amplifying additional
characteristics of complex systems and by stressing their inter-relationship
and interdependence (Mittleton-Kelly 2003)
Complexity does not comprise a single, unified theory but rather a family of
theories, arising from the fields of biology, physics, chemistry, computer
simulation, evolution and mathematics (Mittleton-Kelly 2003).
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
1) SELF-ORGANIZATION
Self-organization is a more or less spontaneous process
without externally applied coercion or control.
Entropy is important factor of the process of self-organization.
Self-organization consisting of phases such as production of entropy, disequilibrium
and chaos, reduction of entropy and finally new organization.
(Ståhle 2004)
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
In case of social systems, entropy can be understood as a capability to produce
and reduce information. Entropy forms the basic dynamics of social systems.
An increasing of information may have various consequences. When
considered in the context of social system, increasing of information opens up
new possibilities, but it also means exclusion of others.
Information can be understood simultaneously both as a potential as well as a
significant source of threat.
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
2) EMERGENCE
Emergence means complex organizational structure growing
out of simple rules.
The whole is something that cannot be foreseen from what is known of the
component parts.
(Lewin 1993)
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
What is important is that systems may have a great diversity of components
but relatively simple relations between parts such as most machines and
technical systems.
In other words, it is not just the great number of interactions but the quality of
those interactions.
Complex behaviour of the system emerges from the connectivity and
interdependence its parts (Mitleton-Kelly 2003).
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
3) FAR-FROM-EQUILIBRIUM, SPACE OF POSSIBILITIES, BIFURCATION and
PATH-DEPENDENCY
Far-from-equilibrium means that the complex system is continually
changing. To ensure its survival, the system has to be able to produce and
reduce entropy.
Bifurcation point is a choice between two or more possibilities which are
constrained by earlier choices (path-dependency).
Space of possibilities implies that it is impossible to explore all possibilities.
Path-dependency means that every choice of individual is the result of a
individuals selection among a finite set of perceived choices as well as the
past choices made that have shaped that individuals life path.
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
(Mitleton-Kelly 2003, Nicolis &
Prigogine 1989)
COMPLEXITY THEORY
The complexity theory sees conflicts and opposite interests as triggers which create
tensions and multiply interactions of the system
Conflicts and opposite interests can be seen as imperative nodes that forces system to
make choices. In complexity theory, these nodes are called bifurcation points. They are
some kind of the moment of truth in which the system has different options.
When a social entity is faced with a bifurcation point, it endows
the entity space of possibilities (Mitleton-Kelly 2003).
Therefore, the bifurcation can be seen as a source of innovation. The alternatives at the
bifurcation point “are sources of innovation and diversification, since the opening up of
possibilities endows the individual and the system with new solutions” (Mitleton-Kelly
2003)
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
4) DIVERSITY
Diversity is the state or quality of being different. Increasing the diversity of
the system means more observation capabilities and fewer blind spots.
An actor of the system
(Jalonen 2007)
”World” that the system can observe
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
Ashby´s law of requisite variety (1957): a system has to have enough resources
at its disposal to be able to cope with the complexity of its environment.
In other words, the principle of requisite variety implies that the complexity of
environment can be met by the complexity of system.
(Clippinger 1999)
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
ENVIRONMENT
ORGANIZATION
ENVIRONMENT
ORGANIZATION
ENVIRONMENT
ORGANIZATION
ENVIRONMENT
ORGANIZATION
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
5) CONNECTIVITY and INTERDEPENDENCE
Connectivity and interdependence points that actions by any individual may
affect (constrain or enable) related individuals and systems.
Because of limited information capacity of individual actors, to solve highly
interconnected and multidimensional (i.e. wicked) problems or to realize
promising policies and generating innovations, there is the need to for
interactions between a wide variety of actors (Kooiman 1993; Castells 1996,
Sotarauta 1997).
Such interaction may generate not only a larger information and knowledge
base than an individual, but also a better one on which to base decisions.
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
(Jalonen 2007)
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
6) FEEDBACK and NON-LINEARITY
Without feedback there is no emergence or self-organization. Positive
feedback enhances and stimulates systems capability, whereas effects of
negative feedback are opposite (detracting, inhibiting).
Non-linearity implies that behavior of the system may not depend on the
values of the initial conditions. In complex systems, dynamical interactions
are non-linear, i.e. small causes can have large results, and vice versa. A
system is dynamical when it changes over time.
“The flap of a butterfly´s wings in Brazil set off a tornado in Texas” (Lorenz,
1963
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
Circular interdependence
(Jalonen 2007)
COMPLEXITY THEORY
7) CO-EVOLUTION
Connectivity applies not only to components within a system but also to
related systems. It can be said that a system and its environment “coevolves”, with each adapting to the other.
Interactions and interdependencies between system and its environment.
Co-evolution means “that the evolution of one domain or entity is partially dependent on
the evolution of other related domains or entities, and that one domain or entity changes
the context of the other(s)” (Mitleton-Kelly 2003).
Adaptation & Selection
harri.jalonen@turkuamk.fi
COMPLEXITY THEORY
COMPLEXITY THEORY
Adapted Sotarauta & Srinivas 2005
harri.jalonen@turkuamk.fi
PROPOSITION #4
Organisations as complex systems:
i) do not ‘behave’ in a straightforward predictable
way, ii) consist of a huge number of diverse
interrelated elements, iii) trivial causes can have
massive effects (no linear relation between cause
and effect), iv) control over the system is virtually
impossible and v) dapt to environmental changes
and evolve together with their environment.
harri.jalonen@turkuamk.fi
harri.jalonen@turkuamk.fi
5) Case: ”Managing
innovations in complex
welfare service systems”
by Harri Jalonen & Pekka Juntunen
A paper presented at ICEG 2010 in Cape Town, South Africa.
The paper is currently in review process to be published
in Baltic Journal of Management
harri.jalonen@turkuamk.fi
CASE
A Starting Point (1/2)
A growing number of welfare services are being provided through co-operation between
the public and private sectors.
i) Co-operation = fertile ground for innovations in welfare services.
ii) Co-operation = creates complicated organisational interlacing, which, in turn, may lead
to a situation where this innovation potential remains unrealised.
 It is these public-private partnerships that are seen to produce complex welfare service
systems that cannot be understood on the basis of what is known about the individual
components of these systems.
CASE
A Starting Point (2/2)
Innovation = novelty in action
Innovation = “seeing things in a new way” and “doing things differently”
Experimentation and high tolerance of risk-taking and fail as success mechanisms for
innovation.
It is argued that the public sector suffers from a lack of success mechanisms. The public
sector has ‘asymmetric incentives’ for innovations. The incentives are asymmetric because
successful innovations are not rewarded, while unsuccessful innovations may have grave
consequences.
However, innovations are needed, partly due to an increasing pressure to respond to the
demands from the customers and partly due to diminishing resources for supplying
services.
CASE
Aim and research question
The main aim of this paper is to develop a framework that deepens our understanding of
managing innovations in a welfare service system.
What kinds of management practices can be
used in supporting innovative actions in
complex welfare systems?
The paper concentrates on the interaction processes within the welfare service system and
between the welfare system and the surrounding environment.
CASE
Research design
Qualitative methods  purpose is to gain an understanding of how practitioners “define the
situation”.
The empirical data was collected by conducting semi-structured interviews with leading office
holders and representatives [n=50] of welfare service providers in the Helsinki region of
Finland.
All of the interviewees hold a manager or director position in their organization. Based on the
interviewees’ experience, it is reasonable to expect that they have “something to say on the
topic”.
The topics for the interviews were determined by issues identified in the relevant innovation
and complexity literature. The empirical material collected in these interviews was analyzed
using Yin’s (2003) pattern matching logic. In our paper, pattern matching refers to a method
whereby the interview material was interpreted with the concepts of complexity theories.
CASE
Research site
The value network of social services in the City of Helsinki (Finland).
The City of Helsinki is a large municipal organization with around 40,000 employees and an
annual expenditure of around 3,000 million Euros.
-highly fragmented and difficult to perceive  the value network has been launched as a
strategic concept for describing the complex operating environment.
COMPLEX
SYSTEM
The Social Services Department has five responsibilities: Child Day Care Services, Services
for Families with Children, Adult Services, Elderly Services and Management and
Development Centre. The department produces welfare services in about 700 units.
Services are also bought from about 600 external producers. The amount of outsourced
services has steadily increased and in 2008 the department was buying services with about
220 million Euros. The value network of Social Services Department has formed during a
long historical continuum and today, it forms a multi-layer network of very diverse
agreements and relationships.
This particular service system provides an interesting field for the development of systemlevel innovation thinking due its societal importance and its highly intangible outputs and
outcomes.
CASE
Complexity as Theoretical Framework (1/3)
Complexity refers to the feature of the system.
A system can be defined as a complex system if it exhibits an emergence phenomenon
occurring due to the connectivity and diversity of its parts.
‘Emergence’ refers to the “coming-into-being of novel, ‘higher’ level structures, patterns,
processes, properties, dynamics and laws, and how this more complex order arises out of
the interactions among components that make up the system itself”.
While the complex system is aggregated from its parts, the interplay between these parts
produces emergent patterns that cannot be analytically reducible to the constituent parts.
In practice emergence results from the process whereby each welfare service provider
continually decides which other organizations it will engage with, and what information
and other resources it will exchange with them.
CASE
Complexity as Theoretical Framework (2/3)
Complexity arises from the nature of the issues in the welfare domain.
Public policy problems can be characterized as ‘malignant’, ‘vicious’ and ‘tricky’. Such
problems, especially in the welfare domain, are “wicked problems” in the sense that they
have no definitive formulation; solutions are not true or false; there is no test for a
solution; every solution has a consequence; they do not have simple causes; and they have
numerous possible explanations, which, in turn, frame different policy responses.
In health care, for instance, a good example of a wicked problem is the goal of increasing
equality in the service delivery while simultaneously trying to decrease the costs of the
care.
CASE
Complexity as Theoretical Framework (3/3)
Complexity of objectives and values in the public sector.
Compared to the private sector, the public sector fulfils various values and pursues multiple
goals.
Efficiency = reduction in the cost of operation and in the generation of profits AND procedural
adherence to the rule of law, due process and obedience to legislative mandates.
The public sector suffers ‘innovation deficit’, which can be explained by the detrimental sideeffects of pursuing efficiency. Innovation is difficult in the public sector because the goal of
efficiency is inconsistent with the goal of innovation.
Paradoxically, ‘good values’, such as efficiency, accountability and transparency, may lead to the
emergence of higher level [a]dynamics, which can ossify the structures of welfare provision. An
emergence, in this sense, manifests itself as an inability of the welfare service system to change
and grow through experimental endeavour in order to meet new environmental threats and
opportunities.
CASE
A story of successful innovation is actually
that ‘form follows failure’.
“When fear of failure replaces a capacity to
experiment and create trial and error
learning, the result is unlikely to be an
artefact that actually works” (Potts, 2009)
The real issue is how, on the one hand, to
facilitate the processes of “seeing things in
a new way”, and, on the other hand, how
to ensure that “things are done differently”.
”Trying is the first step to failure”
Homer Simpson
CASE
Innovation supportive conditions (1/4)
TRUST
“...new ideas are often generated when someone discovers the problem. If you can
trust that you are not in trouble when you tell problems, it could encourage more
innovation”.
“...service providers do not always bring out the problems involved service
provision because they fear that it worsens their position in the negotiations with
the Social Services Department.. ...it is this uncertainty or lack of confidence that
pull the rug from under the development of new ways of action”
CASE
Innovation supportive conditions (1/4)
Creating trust
Trust helps to build up space for creativity innovation, and encourages people to ’see
things differently’. It enables playing with ideas .
Personal and system trust  new ideas are given every chance to succeed.
Important is that personal and system trust not only reduces complexity and makes up for
obscurity caused by imperfect knowledge but also increases certainty, because certainty
does not call for correct and certain knowledge but rather the fact that the actors can
predict each other’s behaviour.
Trust increases the welfare service system´s ability to take risks and withstand failures. An
atmosphere of trust lowers the mental threshold that suppresses thinking that differs from
the conventional.
CASE
Innovation supportive conditions (2/4)
RESPONSIVENESS
“…if you want real partnership, I mean not just rhetoric of partnership, the service
delivery should be considered in open and dialogic conversations between service
providers and the Social Services Department... dictate do not lead to best
outcomes”.
“The cruel fact is that we [private sector service providers] compete to get the
contract with the Social Services Department.”
“it is not reasonable to regard other service providers just as rivals... ...sometimes
the most valuable innovation impulses come from them... ...therefore it is important
to seek informal settings where you can meet and exchange thoughts with
colleagues from outside your own organization.”
CASE
Innovation supportive conditions (2/4)
Increasing communication responsiveness
Responsiveness refers to reciprocal communication processes where the actors of the
system co-create relationships that “evoke potential in a trusting environment”.
Responsive communication processes create trust, which, in turn, can increase the welfare
service system’s capacity to renew itself and generate new services.
Innovations are rooted in the interplay between the cooperative–competition intentions of
the actors. Instead of imposing innovation from the ‘centre of the welfare service system’,
innovation should be allowed to emerge from the ‘periphery of the welfare service
system’.
Therefore, the task of innovation management is not to control the actors but to facilitate
responsive processes, which, in the words of Schön (1973), include “detecting significant
shifts at the periphery, paying explicit attention to the emergence of ideas in good
currency, and deriving themes of policy by induction”.
CASE
Innovation supportive conditions (3/4)
Connectivity and interdependencies
“We don´t operate very well in the system level. There is a lot of administrative
hurdles between the social services and the health care services... especially in
elderly care... ...These hurdles hinder developing customer-oriented services...
...sometimes we forget that the customers’ problems don´t follow the logic of
administration.”
“...it is not easy to talk about new ideas... ...it seems that they [the Social Service
Department] just politely listen what we tell them... ...too often ideas remain
ideas... ...don´t proceed to the implementation stage... ...there is some kind of
cultural stickiness.”
“Sometimes we ask service providers to introduce new ideas of how to meet the
changing needs of citizens. I think it is reasonable to expect that service providers
with the best experience in the field could think services from the new perspectives
and develop new kind of services... ...However, we have found that there are service
providers that are not very agile... ...it seems like they miss old good days and don't
want to see the reality of what happened.”
CASE
Innovation supportive conditions (3/4)
Utilising connectivity and interdependencies
Connectivity and interdependency are essential for the system´s evolution. It is the degree
of connectivity which determines the network of relationships and the transfer of
information and knowledge.
‘Strong’ and ‘weak’ ties (Granovetter, 1973).
Weak ties improve the welfare service systems´ ability to see things “in a new light”,
whereas strong ties support the conversion of seeing into “doing differently”. Weak and
strong ties increase information redundancy in the welfare service system. Information
redundancy is important for innovation because it means the use of more elements than
necessary to maintain the performance of the system in the event of failure of one or more
of the elements. In other words, information redundancy reduces the fear of failure,
which, is one of the main obstacles to innovation.
CASE
Innovation supportive conditions (4/4)
Diversity
“Diversity is important because the needs of clients are varied… …it is not possible
to develop new services without understanding of various needs, and getting
understanding requires knowledge that is dispersed different actors.”
CASE
Innovation supportive conditions (4/4)
Pursuing diversity
Most people take risks on the basis of known rather than unknown probabilities. ‘Playing
safe’ may be disastrous in the decision domains around innovation, because the usefulness
of innovation cannot be known a priori may induce public organizations to play safe and stay
away from uncertainty and experimentation.
’Boundary spanning’ = a combination of the different functions, processes and roles that are
used by the actors who try to guide their interaction in a direction that produces results.
‘Boundary spanners’ = information filters & knowledge interpreters regulate the flows of
information that both come into the system from the environment and go out of the system,
and change information into forms others can understand . They ensure that the welfare
service system not only has clearly expressed rules and guidelines but also openness to new
ideas and influences, and a willingness to change old patterns.
CASE
Conclusions
While adapting the complexity-based interpretation that the innovation is emergent in its
nature, we do not claim that an emergence is the result of a process of pure selforganization.
Instead of claiming that innovations “simply happen” or “bubble up”, we believe that a
new order, i.e. innovation, is more appropriately constructed rather than self-organized as
such (cf. Hazy et al 2007, Goldstein 2003).
Adapting Hazy et al (2007), we think that innovation requires constant support and
resources. The ‘success’ of an innovation much depends on the attention the actors bring
to the innovation process. We argue that by paying attention to trust, responsive
communication processes, connectivity, interdependencies and diversity, it is possible to
create favourable conditions for innovations in complex welfare systems.
INNOVATION as a COMPLEX PROCESS
‘CREATIVE
DESTRUCTION’
POSITIVE FEEDBACK
DYNAMIC
CREATIVE
ABRASION
Strengthen
Equivocality
TRUST
Enables
Ambiquity
Crumbling
INTERACTION
Communication in
strong & weak ties
Builds
Diversity of ideas
Information redundancy
Power conflicts
Controversial interests
NEGATIVE FEEDBACK
INNOVATION
Emerges
DEADLOCK
See more....
Aasen, T. M. B. (2009) Innovation as social processes. A
participative study of the Statoil R & D program Subsea Increased
Oil Recovery (SIOR), Norwegian University of Science and
Technology.
Fonseca, J. (2002) Complexity and innovation in organizations.
New York: Routledege.
Jalonen, H. & Juntunen, P. (2011?) “A Framework for Enabling
Innovation in Complex Welfare Service Systems”, Baltic Journal
of Management