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Los Angeles-based AECOM Technology had a problem. An AECOM plant in Argentina had made a successful move into biofuels processing and was producing sugar dust as a byproduct of its biofuels production. The problem: Airborne sugar dust can be explosive — and AECOM was concerned about the possibility of having fireballs near its fuel processing. A team of AECOM employees based in London had several ideas, but after weeks of back and forth, a solution finally emerged — via an internal company bulletin board — from an AECOM engineer in Australia.
The type of challenge AECOM faced — locating internal knowledge on a specialized topic — exists in any large organization. The larger and more segmented the company, the harder it is to match its people to its problems. As Lewis Platt, former CEO of Hewlett-Packard, once noted, “If only HP knew what HP knows, we would be three times more productive.” How can a large organization address the challenges of managing information flows internally?
One answer is an internal knowledge market. In broad terms, internal knowledge markets are protected environments where users trade their knowledge via price mechanisms. Although such markets have existed in different forms for years,1 their use to facilitate knowledge transfer inside organizations is relatively new. Early adopters such as Infosys, Siemens, McKinsey & Co. and Eli Lilly have demonstrated their value for managing information flows relative to traditional knowledge-management solutions. For example, the software company SAP has used a knowledge market to facilitate peer-to-peer response to questions among enterprise software developers both within and outside the company. This form of Q&A has improved response times substantially while saving SAP more than $6 million in technical support costs.
The Leading Question
How can companies use internal markets to help employees locate specialized knowledge?
- Seed the internal knowledge market with key content and then subsidize development of additional solutions.
- Let prices float in the knowledge market.
- Manage the knowledge market like a market maker or the Federal Reserve — not like a central planner.
In general, markets cause resources to speak up and self-identify. They facilitate reuse of existing information, cause new information to be created when needed and efficiently regulate use of resources, including people’s time. Markets provide the framework to arbitrage gaps between problem and opportunity.
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1. The first known use of the term “knowledge market” is found in F.A. Hayek, “The Use of Knowledge in Society,” American Economic Review 35 (1945): 519-530.
2. The idea that groups tend to make better decisions than individuals was popularized by J. Surowiecki in “The Wisdom of Crowds: Why the Many Are Smarter than the Few and How Collective Wisdom Shapes Business, Economies, Societies, and Nations” (New York: Random House, 2004).
3. K. Boudreau and K. Lakhani, “How to Manage Outside Innovation,” MIT Sloan Management Review 50, no. 4 (summer 2009): 69-76.
4. For numerous examples, see H. Benbya, “Knowledge Management Systems Implementation: Lessons from the Silicon Valley” (Oxford, United Kingdom: Chandos Publishing, 2008).
5. Hayek, “The Use of Knowledge”; and J. Hirshleifer and A. Glazer, “Price Theory and Applications: Decisions, Markets and Information,” 7th ed. (Cambridge, United Kingdom: Cambridge University Press, 2005).
6. R. Garud and A. Kumaraswamy, “Vicious and Virtuous Circles in the Management of Knowledge: The Case of Infosys Technologies,” MIS Quarterly 29, no. 1 (2005): 25-34.
7. E. Servan-Schreiber, J. Wolfers, D.M. Pennock and B. Galebach, “Prediction Markets: Does Money Matter?” Electronic Markets 14, no. 3 (2004): 243–251.
8. Detail is provided in G. Parker and M. Van Alstyne, “Two-Sided Network Effects: A Theory of Information Product Design,” Management Science 51, no. 10 (October 2005):1494-1504; and T. Eisenmann, G. Parker and M. Van Alstyne, “Strategies for Two-Sided Networks,” Harvard Business Review (October 2006): 92-101.
9. C. Anderson, “The Long Tail: How Endless Choice Is Creating Unlimited Demand” (New York: Hyperion Books, 2006); and. E. Brynjolfsson, J. Hu and M. Smith, “Consumer Surplus in the Digital Economy: Estimating the Value of Product Variety at Online Booksellers,” Management Science 49, no. 11 (November 2003): 1580–1596.
10. T. Menon, L. Thompson and H. Choi, “Tainted Knowledge vs. Tempting Knowledge: Why People Avoid Knowledge from Internal Rivals and Seek Knowledge from External Rivals,” Management Science 52, no. 8 (August 2006): 1129-1144.
11. M. Van Alstyne, “Create Colleagues, not Competitors,” Harvard Business Review (September 2005): 24-28.
12. We thank Leslie Fine of Crowdcast for this example.
13. J.S. Brown and J. Hagel III describe this as a “pull” rather than “push” style of management. See J.S. Brown and J. Hagel III, “From Push to Pull: Emerging Models for Mobilizing Resources” Journal of Service Science 1, no. 1 (2008): 93-110.
14. M. Friedman, “The Quantity Theory of Money: A Restatement,” in “Studies in the Quantity Theory of Money,” ed. M. Friedman (Chicago: University of Chicago Press, 1956). Reprinted in M. Friedman, “The Optimum Quantity of Money” (Chicago: Aldine Transaction, 2005): 51-67.
15. P. Ernstberger, “Linden Dollars and Virtual Monetary Policy,” January 23, 2009, http://econpapers.org.
16. R. Bénabou and J. Tirole, “Incentives and Prosocial Behavior,” American Economic Review 96, no. 5 (2006): 1652–1678.
17. K. Ling, G. Beenen, P. Ludford, X. Wang, K. Chang, X. Li, D. Cosley, D. Frankowski, L. Terveen, A.M. Rashid, P. Resnick and R. Kraut, “Using Social Psychology to Motivate Contributions to Online Communities,” Journal of Computer-Mediated Communication 10, no. 4 (2005): article 10.
18. T. Malone, R. Laubacher and C. Dellarocas, “The Collective Intelligence Genome,” MIT Sloan Management Review 51, no. 3 (spring 2010): 21-31.
19. System/user adaptation is described in H. Benbya and B. McKelvey, “Toward a Complexity Theory of Information Systems Development,” Information, Technology and People 19, no.1 (2006):12-34.
20. M. MacDonald, P. Weill and S. Woerner, “Top Performing Firms Are More Effective at Digital Reuse,” research briefing, MIT Center for Information Systems Research, Cambridge, Massachusetts, October 2010.
21. S. Aral, E. Brynjolfsson and M. Van Alstyne, “Information, Technology and Information Worker Productivity: Task Level Evidence,” NBER Working Paper 3. No. 13172, National Bureau of Economic Research, Cambridge, Massachusetts, June 2007, www.nber.org.