Title: Thermodynamics of Productivity Framework for Impact of InformationCommunication Investments
1Thermodynamics of Productivity Framework for
Impact of Information/Communication Investments
- Ken Dozier
- USC Viterbi School of Engineering Technology
Transfer Center - CITSA 2004
- July 21-25, 2004
2Presentation
- Problem (7 slides)
- Approach (9 slides)
- Results (5 slides)
- Conclusions (1 slide)
- Future (1 slide)
3A System of Forces in Organization
Direction
Cooperation
Efficiency
Proficiency
Competition
Concentration
Innovation
Source The Effective Organization Forces and
Form, Sloan Management Review, Henry Mintzberg,
McGill University 1991
4Make Sell vs Sense Respond
Chart SourceCorporate Information Systems and
Management, Applegate, 2000
5Supply Chain (Firm)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
6Supply Chain (Government)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
7Supply Chain (Framework)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
8Supply Chain (Interactions)
Source Gus Koehler, University of Southern
California Department of Policy and Planning,
2002
9Theoretical Environment
Seven Organizational Change Propositions
Framework, Framing the Domains of IT
Management Zmud 2002
10Framework Assumptions
- U.S. Manufacturing Industry Sectors can be
Stratified using Average Company Size and
Assigned to Layers of the Change Propositions - Layers with Large Average Firm Size Will Have
High B and Lowest T(1/B) - Layers with Small Average Firm Size Will Have Low
B and High T (1/B) - The B and T Values Provide the Entry Point to
Thermodynamics
11 Thermodynamics ?
- Ample Examples of Support
- Long Term Association with Economics
- Krugman, 2004
- Systems Far from Equilibrium can be Treated by
(open systems) Thermodynamics - Thorne, Fernando, Lenden, Silva, 2000
- Thermodynamics and Biology Drove New Growth
Economics - Costanza, Perrings, and Cleveland, 1997
- Economics and Thermodynamics are Constrained
Optimization Problems - Smith and Foley, 2002
12Thermodynamics ?
- Mathematical Complexity Could Discourage
Practitioners - Requires an Extension of Traditional Energy
Abstractions - Expansion May Require Knowledge to be Considered
Pseudo Form of Energy?! - Knowledge Potential and Kinetic States?!
- Patent potential
- Technology Transfer Kinetic
- Tacit versus Explicit
13Constrained Optimization Approach
- Thermodynamics
- A systematic mathematical technique for
determining what can be inferred from a minimum
amount of data - Key Many microstates possible to give an
observed macrostate - Basic principle Most likely situation given by
maximization of the number of microstates
consistent with an observed macrostate - Why pseudo?
- Conventional thermodynamics energy rules
supreme - Thermodynamics of economics phenomena energy
shown by statistical physics analysis to be
replaced by quantities related to productivity,
i.e. output per employee
14Pseudo-Thermodynamic Approach
- Macrostate givens N and E, and census-reported
sector productivities p(i) - Total manufacturing output of a metropolitan area
N - Total number of manufacturing employees in
metropolitan area E - Productivities p(i), where p(i) is the
output/employee of manufacturing sector I -
- Convenient to work with a dimensionless
productivity - p(i) p(i)/ltPgt (Chang Simplification)
- where ltPgt is the average value for the
manufacturing sectors of the output/employee for
the metropolitan area. - Thermodynamic problem with the foregoing
givens - What is the most likely distribution of employees
e(i) over the sectors that comprise the
metropolitan manufacturing activity ? - What is the most likely distribution of output
n(i) over the sectors?
15Pseudo-Thermodynamic Approach
- Relations between total metropolitan employee
number E and output N and sector employee numbers
e(i) and outputs n(i) - E S e(i)
- N S n(i)
-
- Relation between sector outputs, employee
numbers, and productivities -
- n(i) e(i) p(i)
-
- n(i) e(i)ltPgtp(i)
-
- Accordingly,
- N S n(i) S e(i) ltPgt p(i)
16Pseudo-Thermodynamic Approach
- Look for the (microstate) distribution e(i) that
will give the maximum number of ways W in which a
known (macrostate) N and E can be achieved. - Number of ways (distinguishable permutations) in
which N and E can be achieved - W N! / ? n(i)!E! / ? e(i)!
- Maximization of W subject to constraint
equations of previous slide - Introduce Lagrange multipliers ? and ß to take
into account constraint equations - Deal with lnW rather than W in order to use
Stirling approximation for natural logarithm of
factorials for large numbers - lnn! gt n lnn- n when n gtgt1
17Optimization
- Maximization of lnW with Lagrange multipliers
- ? / ? e(i) lnW ?N-Sn(i) ßE-Se(i)
0 - Use of relation between n(i) and e(i) and p(i)
- ?/ ? e(i) lnW ?N-S e(i)ltPgtp(i)
ßE-Se(i) 0 - where, using Stirlings approximation
- lnW N(lnN-1) E(lnE-1) - S e(i)p(i)ltPgtlne(i)
p(i)ltPgt-1 -
- - S e(i)lne(i)-1
18Resulting Distributions
- Employee distribution over manufacturing sectors
e(i) - e(i) D p(i)-p(i)/p(i)1 Exp -
ßp(i)/1p(i) - where the constants D and ß are expressible
in terms of the Lagrange multipliers that allow
for the constraint relations -
- Output distribution over manufacturing sectors
n(i) - n(i) DltPgt p(i) 1/p(i)1 Exp -
ßp(i)/1p(i) - Two interesting features
- NonMaxwellian i.e. Not a simple exponential
- An inverse temperature factor (or bureacratic
factor) ß that gives the disperion of the
distribution
19Figure 1 Predicted shape of output n(i) vs.
productivity p(i) for a sector bureaucratic
factor ß 0.1 lower curve and ß1 upper
curve.
Output
n(i)
p(i)
20Figure 2. Predicted shape of employee number
e(i) vs. productivity p(i) for a sector
bureaucratic factor ß 0.1 lower curve and ß1
upper curve.
Employment
e(i)
p(i)
21Figure 3. Data Employment vs productivity for
the 140 manufacturing sectors in the Los Angeles
consolidated metropolitan statistical area in 1997
Data
22Productivity Paradox
Figure 4. Productivities in Los Angeles
consolidated metropolitan statistical area.
(Ignore Industry Sector Average Company Size)
1.8
1.6
1.4
1.2
1
Ratio of 1997 productivity to 1992 productivity
0.8
0.6
0.4
0.2
0
0
15
30
45
60
75
90
105
120
135
Average rank of per capita information technology
expenditure
23Stratified
Figure 5. Productivities in Los Angeles
consolidated metropolitan statistical area. (3
Industry sector sizes)
1.8
1.6
26 largest company size sectors
1.4
1.2
26 intermediate company size sectors
24 smallest company size sectors
1
Ratio of 1997 productivity to 1992 productivity
0.8
0.6
0.4
0.2
0
0
15
30
45
60
75
90
105
120
135
Average rank of per capita information technology
expenditure
24Conclusions
- Agreement with industry sector behavior to
thermodynamic model. - Consistent across multiple definitions of
productivity. - Interaction between average per capita
expenditure on information technology,
organizational size and the average increase in
productivity - IT investment alters B
- High IT (electronics) Investor changed their B,
Low IT Investor (heavy springs) did not
25Future Work
- Examine NAICS consistent 2002 and 1997 U.S.
manufacturing economic census data - Use seven organizational change proposition
strata to further explore the linkage between
organizational size and productivity. - Compare results across the strata and within each
stratum - Check for compliance to thermodynamic model
- Expand to technology transfer