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Computational Organizational Modeling Comes of Age Raymond E. Levitt Stanford University NAACSOS—June 2003 Raymond E. Levitt Stanford University NAACSOS—June.

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Presentation on theme: "Computational Organizational Modeling Comes of Age Raymond E. Levitt Stanford University NAACSOS—June 2003 Raymond E. Levitt Stanford University NAACSOS—June."— Presentation transcript:

1 Computational Organizational Modeling Comes of Age Raymond E. Levitt Stanford University NAACSOS—June 2003 Raymond E. Levitt Stanford University NAACSOS—June 2003

2 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 OUTLINE 1. How computational modeling & simulation (CM&S) have impacted engineering science and practice 2. How computational modeling & simulation are beginning to impact organizational science and practice 3. Chronology of the Virtual Design Team(VDT) — a mature computational organizational modeling & simulation framework 4. Where, and how fast, is CM&S going?

3 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Research Modalities in Engineering Science — (Pre-1960s) Empirical Data Inputs Outputs Physical Scale Models Inputs Outputs Empirical scaling rules Theory Physics Chemistry Biology (generally expressed as sets of linear or differential eq’s.)

4 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Limitations of Physical Scale Models u Costly and time-consuming to build  Required skilled physical model builders (often built by model shop technicians—not scientists) u Slow and costly to modify  Scientists could not adapt models rapidly to react to surprising data or to test new insights  Calibration against real world data took decades u Results needed to be interpreted with care  Many important effects do not scale linearly

5 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Physical Scale Models Inputs Outputs Empirical scaling rules Research Modalities in Engineering Science — (Post-1960s) Empirical Data Inputs Outputs Computational Modeling & Simulation Inputs Outputs Limiting modeling assumptions Theory Physics Chemistry Biology

6 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 How CM&S Affected Engineering Science and Practice u Rapidly declining time & cost to build and change models  Two orders of magnitude improvement  “disruptive” changes u Progress of Engineering Science Dramatically Accelerated  Could rapidly modify models to test & refine theory iteratively  “Regress” micro-modeling assumptions against meso/macro data u Engineering practice made huge leaps forward  “Real-time” prediction now feasible for even complex problems  Wider range of mathematically indeterminate problems can be solved  Computational modeling now part of standard BS/MS curricula u Model results still need to be interpreted with great care!  Violations of assumptions can be catastrophic —e.g. Sleipner platform)

7 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Research Modalities in Organizational Science—Pre-1970s Empirical Data from Natural Experiments Micro/Meso/Macro Inputs Micro/Meso/Macro Outputs Span 1 or, at most 2, levels Empirical Data from Synthetic Experiments Micro/Meso Inputs Micro/Meso Outputs Theory Sociology Psychology Economics (usually expressed in words & diagrams; sometimes in mathematical or computational models)

8 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Limitations of Synthetic Experiments u Modest time and cost to design and perform experiments u Validation, calibration against real world data is difficult  Individual motivation and context are very difficult to replicate  Many effects do not scale linearly u Ethical concerns nowadays preclude many kinds of experiments previously conducted on human subjects u No links between micro-behaviors and macro outcomes  Micro inputs and outputs cannot generally be related to, or reconciled with, macro data or even macro-theory  Result: Discipline-Based “Islands of Theorizing”

9 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Empirical Data from Synthetic Experiments Micro/Meso Inputs Micro/Meso Outputs Research Modalities in Organizational Science — Post ~1970 Empirical Data from Natural Experiments Micro/Meso/Macro Inputs Micro/Meso/Macro Outputs Computational Modeling & Simulation Micro/Meso/Macro Inputs Micro/Meso/Macro Outputs Nested models link micro- macro data and theories Theory Psychology Sociology Economics

10 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 How CM&S of Organizations Bridges the Micro  Macro Theory Gap Organization macro-theory Organization macro-experience Sociology/Economics/ Political Science Organization micro-theory Organization micro-experience Cognitive and Social Psychology Agent micro-behavior Agent- Based Simu- lation Organization micro-theory Organization micro-experience Cognitive and Social Psychology Emergent simulation macro-behavior

11 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 How Computational Modeling is Affecting Organizational Science and Mgt. Practice  Rapidly declining time and cost to start generating validated predictions for a modeled system u Organization Science poised to make huge leaps forward ÙCan now rapidly modify models to test & refine theory iteratively ÙCan “regress” micro-modeling assumptions against meso/macro data ÙValidated models beginning to serve as “virtual synthetic experiments” u Org. Design practice starting to incorporate CM&S ÙRapid feedback develops “management judgment” by induction  Enabling “flight simulation of alternatives” and “extreme collaboration” u CM&S Entering Mainstream Education and Research ÙComputational modeling & simulation now taught as part of PhD/MS/(BS) ÙMIT launching a Center for Computational Politics u Model results still need to be interpreted with care ÙContingency theory says context matters greatly! ÙDifferences in task, technology, … must be taken into account

12 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Case Study: The Virtual Design Team (VDT) u Initiated in 1987 to develop analysis theory and tools that managers could use to design organizations and work processes for fast-track projects u “Emulation model” vs. “theorem prover” u Commercialized in 1996 as SimVision ® u Ongoing research extending VDT’s agent-based emulation approach to wider scope of organizations and work processes

13 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 … behind the Virtual Design Team u Faculty Collaborators  James March (SU: Ed., Sociology, GSB)  John Kunz (SU: CIFE)  Yan Jin (USC: ME)  Clifford Nass (SU: Comm.)  Richard Burton (Duke: Business)  Martin Fischer (SU: CEE)  Bernardo Huberman (Xerox PARC: Physics)  Peter Glynn (SU: MS&E)  Pam Hinds (SU: MS&E)  Noah Mark (SU: Sociology)  Dianne Bailey (SU: MS&E)  Borge Obel (Odense U: Business School)  Kathleen Carley (CMU: CS)  Nosh Contractor (UIUC: Comm.)  Andrea Hollingshead (UIUC: Psych)  Janet Fulk (USC: Business School)  Peter Monge (USC: Comm.)  Douglass North (Wash. U: Econ., NL)  Steve Barley (SU: MS&E)  John Koza (SU: CS) u Students  Geoff Cohen  Tore Christiansen  Jan Thomsen  Douglas Fridsma  Gaye Oralkan  Yul Kwon  John Chachere  Per Björnsson  William Hewlett, III  Jolin Salazar Kish  Carol Cheng-Cain  Walid Nasrallah  Roxanne Zolin  Monique Lambert  Archis Ghate  Sam Miller  Ray Buettner  Mike Fyall  Alfonso Pulido  Ashwin Mahalingam  Michael Murray  Bijan Khosraviani  Ryan Orr  Tamaki Horii  Laleh Haghshenass

14 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Chronology of VDT  SimVision ® Steps in the Maturation of a COM&S Framework Research at Stanford U. by Levitt, Jin, Kunz, et. al. Research at Stanford U. by Levitt, Jin, Kunz, et. al. Concept/methodology development Simulation tool development 30+ validating case studies Mature technology Exclusive License Commercial Product Development 1987199719981999 1996 Vité Corp. Formed to Commercialize Technology Consulting & Analysis Product Offerings Ongoing VDT Research

15 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Trajectory of VDT Research Scope Organizational Flexibility LowHigh Predictable Unpredictable Task Predictability Nonroutine Projects Routine Projects Service/ Maintenance Work Communities of Practice

16 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 99-03: Lambert/ Buettner Model More Complex Social Behaviors Model More Innovative Tasks Model More Dynamic Organizational Forms VDT Scope Trajectory: Routine Projects to Non-Routine Communities of Practice Model More Effects of Communication/ Collaboration Tools Model More Effects of Communication/ Collaboration Tools 97-01: Miller 96-03: Fridsma/Cheng 95-99: Thomsen/Kish 90-94: Cohen/ Christiansen

17 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Maturation of Modeling User Interface

18 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 VDT Validation Trajectory Natural History 1995 ReasoningReasoning UsefulnessUsefulness RepresentationRepresentation Micro-Data Macro-Data Agent-Based Model Retrospective 1992 Prospective Intervention 1996 Prospective Cross-Model Docking 2001 Gedanken 1991 ToyToyProblemsProblems 19891989 IntellectiveIntellective ExperimentsExperiments 1990 ReproducibilityReproducibilityGeneralizabilityGeneralizabilityAuthenticityAuthenticity 1991

19 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Computational Virtual Experiments u CM&S of organizations now beginning to be used to replace some kinds of natural or synthetic social experiments u A validated “emulation” model can be viewed as an “organizational test bench” for theorem - proving experiments u CMOT Journal has already published several papers of this type  (Wong & Burton, Carroll & Burton, …)

20 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Using a Calibrated “Emulation” Model to Conduct Virtual Experiments Indirect Work (Days) LaminarTransition Turbulent Exception Rate

21 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Validation Trajectory for “Intellective” Modeling & Simulation SystemsReasoningReasoning UsefulnessUsefulness RepresentationRepresentation Micro-Theory Macro-Theory Agent-Based Model Cross-Model Docking Year (n+2) ToyToyProblemsProblems Year (n) IntellectiveIntellective ExperimentsExperiments Year (n+1) ReproducibilityReproducibilityGeneralizabilityGeneralizabilityAuthenticityAuthenticity Year (n+3) Replication Integration With Other Models Year (n+5) Replication Integration With Other Models Year (n+5)

22 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Commercialization of COM&S Tools

23 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Where is COM&S Going? u Games  From action games to Sims ® u Analysis tools for many kinds of planning  From military, intelligence, to other public agencies (e.g., building plans, health care, transportation)  Commercial (department stores, arenas, …) u Analysis Tools for Corporate Decision Making  From project design to enterprise design  Organizational aspects of M&A evaluation  Organizational aspects of supply chain optimization u Analysis Tools for Personal Decision Making  Evaluating your fit with a prospective employer  Evaluating compatibility with a marriage partner, …

24 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Progress of CM&S of Organizations 195019601970198019902000 CM&S in Engineering Science CM&S in Organization Science First use by leading edge consultants First taught at MS level in multiple universities Commercial SW — Routinely used in practice

25 Copyright 2002 Vite’ Corp Copyright © 2003 Raymond E. Levitt. NAACSOS — Pittsburgh —6/23/2003 Questions and Discussion u Faculty Collaborators  James March (SU: Ed., Sociology, GSB)  John Kunz (SU: CIFE)  Yan Jin (USC: ME)  Clifford Nass (SU: Comm.)  Richard Burton (Duke: Business)  Martin Fischer (SU: CEE)  Bernardo Huberman (Xerox PARC: Physics)  Peter Glynn (SU: MS&E)  Pam Hinds (SU: MS&E)  Noah Mark (SU: Sociology)  Dianne Bailey (SU: MS&E)  Borge Obel (Odense U: Business School)  Kathleen Carley (CMU: CS)  Nosh Contractor (UIUC: Comm.)  Andrea Hollingshead (UIUC: Psych)  Janet Fulk (USC: Business School)  Peter Monge (USC: Comm.)  Douglass North (Wash. U: Econ., NL)  Steve Barley (SU: MS&E)  John Koza (SU: CS) u Students  Geoff Cohen  Tore Christiansen  Jan Thomsen  Douglas Fridsma  Gaye Oralkan  Yul Kwon  John Chachere  Per Björnsson  William Hewlett, III  Jolin Salazar Kish  Carol Cheng-Cain  Walid Nasrallah  Roxanne Zolin  Monique Lambert  Archis Ghate  Sam Miller  Ray Buettner  Mike Fyall  Alfonso Pulido  Ashwin Mahalingam  Michael Murray  Bijan Khosraviani  Ryan Orr  Tamaki Horii  Laleh Haghshenass ?


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