Operation Analysis 3
• Productivity
• Resource Management
Unit objectives
• Gain a frame of reference about productivity conundrums, develop a
point of view and be able to discuss this with others.
• Consider how services measurements might be developed to be
useful.
• Think about the “new economy” and these questions:
– Why do services resist productivity gains?
– Is services productivity an oxymoron?
– What are some relationships between innovation and
productivity?
2
Version 1.0
The paradox
• What is productivity anyway?
– Measure of economic efficiency
– Advances are a big source of increased potential income
• Baumol’s disease and productivity in Services
– “it still takes four musicians to play a string quartet”.
– As consumption shifts more and more toward services
• If productivity growth in services is inherently sluggish,
economic growth must inevitably slow.
• BUT productivity in Services is up!
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3
Economics
• Global services based economies
– Increasing ever faster
• Measuring services is a problem
– Data biases
– Inaccuracies
– Challenges
• New economy requires new economics?
4
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Productivity
Labor productivity = (Output / Labor input*)
*Where labor input = people or hours
Multi-factor productivity = (Output / Labor input**)
**Where labor input = expanded to include multiple forms
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Measuring services is a
challenge
•
•
•
•
History
Productivity
Quality
Innovation
• New approach
– Although productivity measurement should be part of
services measurement, it should not be the major focus
– Proposed: create a holistic multiple
indicator/multiple stakeholder approach to services
measurement
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Many factors must combine to create a
viable services measurement model
Classification
of Services
Business
Measurement
Models
(Dean’s work)
Potential
Services
Indicators
Stakeholder
Perspectives
Define
Services
Measures
Develop
Services
Measurement
Models
Anatomy of
a Measure
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Test,
challenge,
improve
Validate
Models
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Anatomy of a measure
•
•
•
•
•
•
•
•
Version 1.0
What is measured
Purpose of the measure
Validity
Reliability
Instrumentation
Precision
Role relations to measure
Time periods
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Measurement of services
Revenue
Output
•Service outcomes
•Availability
•Quality
•Value
•Variability
•Accessibility
Value
•Price
•Flexibility
•Competitiveness
•Experience
•Prestige
•Satisfaction
•Adaptability
•Innovation
•Focus
•Interchangeability
Input
Labor + Capital
Capability
Capacity
Cost
Cohesiveness
Complexity
Correction
Efficiency
Optimization
Risk
~
=
=
Productivity
Process
Resource levels
Risk
Social capital
Variability
Waste
Employees
Total Cost
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The role of measurement in services
sciences
• Measurements will
– Help define the new discipline
– Identify innovations in Services Science
• Validity of a measure
– Right purpose?
– Affected by other factors?
– Affected by the quality of the service?
– Effect on profit?
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Innovation and productivity
• Technology key to eliminate repetitive work
– Free people up to be creative
• What can we learn from manufacturing?
– Are there well known frameworks we can use
to increase productivity in services?
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Engineering model versus
interpretive model for enhancing productivity
• Engineering model
– Product design comes before process design
– Process predictable, repeatable
• For services, sometimes the engineering model works but has
limitations.
– Human judgment required
• Interpretive model
– Skills in understanding customer wants and needs
– Process continuously adaptive
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The two models have different implications for
performance improvement
Engineering model
Interpretive model
Design comes before process
Product and process intertwined,
Product design emerges from the
process, not specified in advance
Workers execute tasks
Workers interpret needs and
execute tasks
Improvements come from changes
to design or process
Improvements follow from
improving worker’s ability to elicit
and interpret, respond to the
situation to select work practices
from repertoire or learn or invent
new services
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Devolving
• Stuck at the top?
• To reach next peak requires
– Going down!
• Change perspective
• Not a natural human inclination
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Move away from studying
manufacturing
• Another point of view
– Service associated with goods
– Knowledge
• Study services innovation
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Version 1.0
Phases of a company’s view toward its
people
High
Employee
Pro-activeness
Individualized
Experience to
customers
Low
Encouragement
(respect)
Employment
(security)
Low
Empowerment
(responsibility)
“Innovention”
(personal
fulfillment)
Employable
(independence)
Individual
Creativity
Employee motivation
To apply own creativity and ingenuity
To invent solutions to problems
High
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Work Measurement
• Objective: determine the time for an average, trained person
to perform a task for 8-hour day under usual working
conditions and working at a normal pace  “Standard Time”
or “Normal Time”
• Bottom-up approach: adjust standard time according to
operator pace, allow “deviation” (almost always)
• Top-down approach: fixed standard time
• Normal Pace
• Actual Time: observed time  perform a task
• Allowance: (+/-) time for delay, personal needs, fatigue, etc
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Work Measurement (cont.)
• Direct Time Study
– Total actual time = 1+1.5+1+1.5+1 =6
– Performance rating = 90%
Subject
Hours
(10% slower)
English
1
– Normal time = (6 hrs)*(.9) = 5.4 hrs Calculus
1.5
– Allowance = 12.5%
Intro to IE
1
Physics
1.5
(reduced 3 hours sleeping time)
Psychology
1
– Standard time = (5.4 hrs)*(1.125)
= 6.075 hrs
18
Work Measurement (cont.)
• Time Study Standard Data: normal times from
direct time study of similar operation earlier
• Predetermined Times:
– Time values are assigned to the sub-task/element
– Total time = Telement / subtask

• Predetermined Time Standard Data:
– Time values are assigned to the element which its
value is from the “time study standard data”
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Productivity Measurement
Basics
• A ratio of organizational outputs & inputs
• Static Measurement: no base year comparison.
Direct ratio
• Dynamic measures:
Dynamic Productivity Index = Productivity this year
Productivity base year
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Physiological Aspects of
Human Activities
Money talks
Bored if nothing to do
Monotone job
Ask then they will give it
Positive response: clear objective, job
description, fair treatment, consistent, and
with respect
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Introduction to IE, Spr2008/KGA/GaTech ©KGA. All Rights Reserved
Machine versus Human Being
Performance
Characteristic
“Typical”
Machine Tool
“Typical”
Human Being
Range of operation
Mostly perform one basic
operation but some may
perform more
Extremely broad range
Work-piece size
Ranged from microscopicsized to extremely large size
Cannot perform operations on
extremely small or large size
Operation speed
Can be very fast
Quite slow
Tolerance Capabilities
Up to 0.001 inch
Very poor at accuracy and
repeatability
Energy Consumption
Very efficient
No stable consumption level
Maintenance requirement
Need regular maintenance
Need minor “maintenance”
frequently, i.e. basic needs. Major
overhauls are performed
continuously
Response to unexpected
occurrences
Very limited capability
Extremely resourceful and creative
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