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Organizational Productivity:

Modeling the Interrelationship of Organizational Culture, Intellectual

Capital and Innovation

Russell S. GonneringDavid Logan

SwarmFest 2014

2Friday, June 27, 14

“All models are wrong...but some are useful”

George Box Science and Statistics. J. Am. Stat. Assoc. 71, 791-799 1976).

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Why do some organizations just seem to perform better than most?

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5Friday, June 27, 14

It’s a group effort!

Mihaly CsikszentmihaliKeith Sawyer

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We Call That Group Effort “Organizational Culture”

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• Pattern of adaptation based on shared purpose, values, history, identity and future.

• Language, particularly generative, future-based language, is a primary means of establishing this shared experience

• A “Cultural Meme”, Increasing Returns, Positive Feedback

Organizational Culture

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Empiric Study• 10 years

• 24,000 people

• 2 dozen organizations

• Organizational Development Surveys

• Burke’s Cluster Analysis of Interviews

• Sociograms

• Confidential Self-ratings

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Logan, et al

• 5 Stages

• Dynamic, Internal and External Influences

• “Linear” Progression of Culture, but Path-Dependency!

• Nonlinear Progression of Performance

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13Friday, June 27, 14

Can’t Skip a Cultural Stage!

Nonlinear Jumps in Performance

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CSSSA 2012

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Probability of Stage 4

0"

0.1"

0.2"

0.3"

0.4"

0.5"

0.6"

0.7"

0.8"

0.9"

Configura5on"

1M"

1W"

1E"

2E"

1M1W"

1E1M1W"

2W"

3W"

2M"

1M2W"

4W"

1E2M2W"

5W"

2E4M4W"

3M"

4M"

6W"

4M4W"

7W"

8W"

2E4M4W"

2E4M8W"

E: Executive; M: Manager; W: Worker

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Science 1997;276:122-126

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PLOS One, March 27, 2013

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Model Evolution

• Productivity

• Close structural holes-”Triading”

• Values

• Purpose

• “Perspective”-Innovation

• Dunbar’s Number

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Starting Point

• Agents: number and role; culture, values, purpose, depth and breadth of knowledge, perspective (stochastic assignation)

• “Inverse Flocking Probability”

• Closure of Structural Holes-”Triading”

• Economy, General Tuner, modifiers of cultural exchange

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Starting Point

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Model

• 200 time ticks

• Agents meet in time and space

• Exchange culture and knowledge according to formula

• Additional stochastic “education” and “disillusionment”

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Exchange

!

Peer/Peer (Same Cultural Stage)

RM: role modifiers

Nonpeer: Magnitude Change

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Model - Culture Transition

• Stage 1 = < 20

• Stage 2 = 20 - 39

• Stage 3 = 40 - 59

• Stage 4 = 60 - 79

• Stage 5 = 80 and above

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Model

• Agents can advance in culture or “die” (culture < 20)

• New agents added at Organizational Culture thresholds (expansion/merger)

• Limited to 100 (Dunbar Number)

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Productivityy = k xα

y = Organizational Productivity k = Complex constant made up of Organizational Culture, variance of Values and Purpose, Innovation (variance of Perspective) x = Intellectual Capital (Organizational Knowledge x variance α = .75

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Productivityy = k xα

• Intellectual Capital is analog of mass in allometric scaling model

• Only indirectly dependent upon population

• k is not species-specific but related to Organizational Culture and ability to operationalize that Organizational Culture

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“Triading”

• Closure of structural holes

• Initiated at Organizational Culture thresholds

• All agents of “Triad” share in cultural/knowledge exchange

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Baseline: Stable though 1,200 ticks

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Inverse Flocking Probability

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Baseline, 200 ticks, no Triading

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Probability of Reaching Stage 4 Culture

All 2 Executives + all 4 Managers = 0% 2 Executives + 4 Managers + 4 Workers = 20%2 Executives + 4 Managers + 8 Workers = 55%

0"5000"10000"15000"20000"25000"30000"35000"

0" 20" 40" 60" 80"

Organiza(onal+Produc(vity+

Organiza(onal+Culture+

Organiza(onal5Produc(vity+Final+Culture:+56.46+

Organiza1onal4Produc1vity"

0"5000"

10000"15000"20000"25000"30000"35000"

0" 20" 40" 60" 80"

Organiza(onal+Produc(vity+

Organiza(onal+Culture+

Organiza(onal5Produc(vity+Final+Culture+:+63.08+

Organiza1onal4Produc1vity"

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Triading

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Probability of Reaching Stage 4 Culture

Baseline with Triading = 95%

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Baseline “Attractor”

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Triad “Attractor”

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Climbing the Mountain

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• Dynamic external influences

• Effect of new leadership

• Disruptive innovation

• Interrelationships?

Future Directions

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Thank You!

Contact me for further information:rsgonnering1@me.com

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References

1. Power, B: Achieving sustained cost reduction. HBR Blog Network, September 26, 2011 http://blogs.hbr.org/cs/2011/09/achieving_sustained_cost_reduc.html

2. Werner, R.M., McNutt, R.: A New Strategy to Improve Quality: Rewarding Actions Rather Than Measures. JAMA 301, 1375--1377 (2009).

3. Snowden, D., Boone, M.E.: A Leader’s Framework for Decision Making. Har. Bus. Rev. 85, 68—76 (2007).

4. Gonnering, R.: The Seductive Allure of “Best Practices”: Improved Outcome is a Delicate Dance Between Structure and Process. E:CO 13, 104—111 (2012).

5. Wilensky, U.: NetLogo [computer software]. Evanston, IL: Center for Connected Learning and Computer-Based Modeling, Northwestern University, (1999), http://ccl.northwestern.edu/netlogo/

6. Gonnering, R.: Modeling the Spread of a “Cultural Meme” Through an Organization. Annual Meeting, Computational Social Science Society of the Americas, Santa Fe, NM, September 2012.

7. Schelling, T.C.: Micromotives and Macrobehavior. W.W. Norton, New York (1978)8. Epstein, J.M., Axtell, R.L.: Growing Artificial Societies: Social Science from the

Bottum Up. MIT Press, Cambridge (1996).9. Axelrod, R.: The Dissemination of Culture: A Model with Local Convergence and

Global Polarization. J. Conflict Res. 41, 203-226 (1997).10. Epstein, J.M.: Agent-Based Computational Models and Generative Social Science.

Complexity 4, 41-60 (1999).11. Flentge, F., Polani, D., Uthmann, T.: Modelling the Emergence of Possession

Norms using Memes.J. Art. Soc. Soc. Stimul. 4, (2001). http://jasss.soc.surrey.ac.uk/4/4/3.html

40Friday, June 27, 14

12. Ball, P.: The Physical Modelling of Human Social System. Complexus 1, 190-206 (2004).

13. Epstein, J.M.: Remarks on the Foundations of Agent-Based Generative Social Science. SFI Working Paper 2005-06-024 (2005). http://www.santafe.edu/media/workingpapers/05-06-024.pdf

14. Csikszentmihaly, M.: Creativity: Flow and the Psychology of Discovery and Invention. Harper Perennial, New York (1996).

15. Sawyer, R. K.: Group Genius: The Creative Power of Collaboration. Basic Books, New York (2007).

16. Logan, D., King, J, Fischer-Wright, H.: Tribal Leadership: Leveraging Natural Groups to Build a Thriving Organization. Harper Business, New York (2011).

17. Dunbar, R. I. M.: Neocortex Size as a Constraint on Group Size in Primates. J. Hum. Evol. 20, 469—493 (1992).

18. Schein, E.H.: Coming to a New Awareness of Organizational Culture. Sloan Man. Rev. 25, 3-16 (1984).

19. Page, S.E.: Diversity and Complexity. Princeton University Press, Princeton NJ (2011).

20. Zaffron, S., Logan, D.: The Three Laws of Performance: Rewriting the Future of Your Organization and Your Life. Jossey-Bass, San Francisco (2009).

21. Arthur, W. B.: Increasing Returns and Path Dependency in the Economy. University of Michigan Press, Ann Arbor (1994).

22. http://www.triballeadership.net/what-is-tribal-leadership/diagnosing-culture23. West, G.B., Brown, J.H., Enquist, B.J.: A General Model for the Origin of Allometric

Scaling Laws in Biology. Science 276, (5309), 122-126 (1997).

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24. West, G.B., Brown, J.H., Enquist, B.J.: The Fourth Dimension of Life: Fractal Geometry and Allometric Scaling of Organisms. Science 284, (5420), 1667-1669 (1999).

25. West, G.B., Brown, J.H.: The Origin of Allometric Scaling Laws in Biology from Genomes to Ecosystems: Towards a Quantitative Unifying Theory of Biological Structure and Organization. J. Exp. Biol. 208, 1575-1592 (2005).

26. Gloor, P. A: Swarm Creativity: Competitive Advantage through Collaborative Innovation Networks. Oxford University Press, Oxford (2006). http://www.tlu.ee/~kpata/uusmeedia/Swarm%20Creativity_Competitive%20Advantage%20through%20Collaborative%20Innovation%20Networks.pdf, accessed 5/29/2013.

27. Box, G.E.P.: Science and Statistics. J. Am. Stat. Assoc. 71, (356), 791-799 (1976).

28. McNamara, A.: Can We Measure Memes? Front. Evol. Neurosci. 3, 1-7 (2011). http://www.frontiersin.org/evolutionary_neuroscience/10.3389/fnevo.2011.00001/full, accessed 8/21/2012.

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