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REALITY CHECK

Your Teams Aren’t Good Enough

Robin W. Spencer


Rob Spencer began his career in drug discovery at Syntex in 1981, after earning a BA in physics from Williams College and a PhD in biochemistry from MIT. Moving to Pfizer in 1987, he co-invented high-throughput screening, which led to the discovery of dozens of first-in-class enzyme inhibitors and receptor antagonists. In 2005, he created the role of full-time innovation process leader at Pfizer, a position that involved developing and implementing scalable business processes and over 200 business-oriented electronic challenges. He is now the director of research at Imaginatik, where he develops theory, business processes, and software to facilitate large-scale collaboration. rob_spencer@imaginatik.com


Welcome to Reality Check. In this column, I’ll paint provocative pictures for innovation managers based on snippets from science, history, demographics, and respected business observers. As an experimental scientist, I promise to be objective and cite my sources. As a former senior manager in a Fortune 100 corporation, I’ll strive to make this column worth your attention. As a lifelong rebel against intellectual laziness and unexamined premises, I’ll try to make you think. If you sometimes find the conclusions unsettling, that will be because the evidence is convincing and the arrow’s found its mark. Many thanks to Jim Euchner and MaryAnne Gobble for the opportunity!

Your Teams Aren’t Good Enough

It’s a pretty bald assertion. But what we know about people and knowledge, communication and teamwork, and the speed of change makes it certain: It’s almost impossible that you have the team you need today, especially if you’re building teams the old-fashioned way, by selecting people to work on a project from available employees.

People and Knowledge

Herbert Simon, computer scientist and Nobel Laureate in economics, did a study of chess grandmasters, from which he concluded that an expert’s memory can hold about 50,000 “chunks”—action-oriented facts or patterns (Simon 1996, 89–93). He also concluded that it takes about a decade of hard practice to attain such knowledge, the 10,000 hours of practice that Malcolm Gladwell (2008) concludes separate the best from the mediocre. If anything, it’s taking longer to become an expert as the ever-growing mountain of world knowledge is stretching the time it takes to develop creative expertise (Jones 2009).

Now consider a big, important business project, and try to estimate how many little facts might matter along the way. In my first career, pharmaceutical drug discovery, a project might easily require many thousands of nuggets: facts about historic approaches, biochemistry, tissue biology, physical properties, synthetic chemistry, patents, toxicity, disease, economics, regulations, and on and on. I suspect it’s no different if you’re designing and selling aircraft, automobiles, smartphones, or financial systems. It may be becoming more true as software becomes the differentiator in so many products, because software systems may be the most complex things that humans have ever created (Brooks 1995).

Conclusion: Developing new, market-creating or market-leading products takes world-class talent, built on a mass of detail and experience that takes an individual many years to acquire.

Communication and Teamwork

To accommodate the growing complexity of projects and the limits of any one person’s time and knowledge, work is increasingly done in teams, and the teams are getting larger (Jones 2009, figure 1C). But teamwork has intrinsic limits: Brooks’s Law (“The way to slow down a project is to put more people on it”) captures the tradeoff between the benefit of distributing the work to more people and the exponential growth in the inefficiency of interpersonal communication as teams expand (Brooks 1995). To work together, people must share not only facts but trust; unfortunately, our circles of trust are modest in size and slowly built (Dunbar 1997). The scaling math is not good: for a team of n people, the number of connections for facts and trust grows as n-squared, which is why the rule of thumb for effective team size is a number between four and ten. Bigger teams will have idle participants and bog down in slow decision-making. Fighting that tendency exacts a cost in hands-on management.

But if a team should be small, can we count on it to pick up the knowledge it needs from the rest of the company without having to formalize those connections? A large study at Cornell suggests not; an analysis of 14 million e-mails among 43,000 students showed that people at three or more degrees of separation (Alice knows Bob, who knows Christine, who knows David) will essentially never communicate (daily probability about 0.000005) unless they are formally brought together (Kossinets and Watts 2006). This is corroborated by theory and evidence showing that social networks get more fragile and costly at large scale, requiring continuous attention and infusion of rewards to persist (Ohtsuki et al. 2006).

Conclusion: Small, focused teams are ideal, but its unlikely that the few people available will have the right knowledge. Tapping into the experience of the larger organization takes deliberate, continuous effort.

The Speed of Change

Business is moving faster. For entire sectors of products, the time from first product launch to market maturity has been accelerating and is now commonly under a decade (Federal Reserve Bank of Dallas 1997, exhibit 8; DeGusta 2012). Median CEO tenure in the S&P 500 is only five years (Coates and Kraakman 2007), and changes in upper management often result in major shifts in strategy. Meanwhile, average employee tenure is even shorter, at 2–3 years per job for those over age 30, regardless of education level (Bureau of Labor Statistics 2012). For the first time in history, the rate of change is faster than the time it takes an individual to acquire relevant expertise (Modis 2002).

Conclusion: Things are changing faster than people can acquire the deep expertise they need.

Bringing It All Together

All of these facts taken together paint a discouraging picture: Managers usually select team members from those within their span of control. Project teams should be small. To create something new and globally competitive, team members need deep expertise, knowledge that takes a decade (or more) to acquire. But the pace of change is far shorter than ten years. So your team can’t possibly have the expertise it really needs.

What can we do? The first step is to acknowledge the need to change how we find talent and apportion work. I hope that the logic in this little column will convince you that there’s some truth here. The second step is to muster the courage to stop doing what’s always been done; as Peter Drucker says in one of his vivid metaphors, “Nothing requires more heroic efforts than to keep a corpse from stinking, and yet nothing is quite so futile” (Drucker 1985, 152). The third step is to take risks and try different approaches to getting the right expertise into your projects. In The Future of Management (2007), Gary Hamel concludes that the scope and power of the Internet for this purpose have yet to be appreciated; in fact, he suggests that Web 2.0 tools for team management could replace traditional, hierarchic management models (253–255). You can take small, specific, low-risk steps in this direction, for instance by launching Web-based problem-solving challenges that tap into all of your company’s knowledge to supply teams with needed expertise on a just-in-time basis (Spencer and Woods 2010).


References

Brooks, F. 1995. The Mythical Man-Month. New York: Addison-Wesley.

Bureau of Labor Statistics. 2012. Number of jobs held, labor market activity, and earnings growth among the youngest baby boomers: Results from a longitudinal survey. News release USDL-12–1489, July 25. http://www.bls.gov/news.release/pdf/nlsoy.pdf.

Coates, J. C., and Kraakman, R. 2007. CEO Tenure, Performance and Turnover in S&P 500 Companies. Harvard Law School John M. Olin Center for Law, Economics and Business Discussion Paper Series. Paper 595. http://lsr.nellco.org/harvard_olin/595.

Degusta, M. 2012. Are smart phones spreading faster than any technology in human history? MIT Technology Review, May 9. http://www.technologyreview.com/news/427787/are-smart-phones-spreading-faster-than-any/.

Drucker, P. 1985. Innovation and Entrepreneurship. New York: HarperBusiness.

Dunbar, R. 1997. Grooming, Gossip and the Evolution of Language. Cambridge, MA: Harvard University Press.

Federal Reserve Bank of Dallas. 1997. Time Well Spent: The Declining Real Cost of Living in America—1997 Annual Report. Dallas, TX: Federal Reserve Bank of Dallas. http://www.dallasfed.org/assets/documents/fed/annual/1999/ar97.pdf.

Gladwell, M. 2008. Outliers: The Story of Success. New York: Little, Brown.

Hamel, G. 2007. The Future of Management. Cambridge, MA: Harvard Business School Press.

Jones, B. 2009. The burden of knowledge and the “death of the renaissance man”: Is innovation getting harder? Review of Economic Studies 76(1): 283–317. http://www.kellogg.northwestern.edu/faculty/jones-ben/htm/BurdenOfKnowledge.pdf.

Kossinets, G., and Watts, D. 2006. Empirical analysis of an evolving social network. Science 311: 88–90.

Modis, T. 2002. Forecasting the growth of complexity and change. Technological Forecasting & Social Change 69(4): 377–404. http://www.growth-dynamics.com/articles/TedWEB.htm.

Ohtsuki, H., Hauert, C., Lieberman, E., and Nowak, M. 2006. A simple rule for the evolution of cooperation on graphs and social networks. Nature 441: 502–505.

Simon, H. 1996. The Sciences of the Artificial. 3rd ed. Cambridge, MA: MIT Press.

Spencer, R., and Woods, T. 2010. The long tail of idea generation. International Journal of Innovation Science 2(2): 53–63. http://www.scaledinnovation.com/innovation/publications/2010-06-longtail.pdf.