strategy+business is published by PwC Strategy& Inc.
or, sign in with:
strategy and business
Published: May 21, 2003


Irrational Exuberance: How the Telecom Industry Went Astray

Another reason for demand overestimation is the use of forecasting techniques that are just plain poor, such as historical or geographical extrapolation. A classic example is that of a company planning to invest in cellular services in the interior of an emerging country. Many companies in this situation assumed that the average revenue per subscriber in the provinces would be the same as that of users in the nation’s capital. Yet cell phone usage in the interior of the country is almost always significantly lower than that in the main urban center: The size of cities — one of the variables that drive cell phone usage — is considerably smaller outside the capital, and smaller cities result in less time “on the move,” and therefore less cell phone usage. This analytical fallacy, in which individuals tend to make judgments by looking for similarities with previously known observations without expanding their frame of reference, is known in psychology as the representativeness heuristic.

Anchor Metrics
“Anchoring heuristics” also influence estimations of market size and company valuation. During the telecom bubble, we saw clearly that investors anchor and adjust the value of a company in a transaction on the basis of their past experience, notably the initial transactions in the market, even if those transactions had little bearing on what followed. For example, when WorldCom Inc. acquired MFS Communications Company Inc., it established for future transactions a valuation metric of six times assets. By using this as an anchor metric, however, later investors failed to take into account the revenue streams of individual companies or market structures at the time of the transaction. A competitive local exchange carrier (CLEC) in a duopoly — the situation when WorldCom bought MFS — is worth more than a CLEC in a fully competitive market. Often, market dynamics will shift, while the anchoring metric remains stable. New companies will enter the market and acquire funding based on the principle that if they can install the assets in the ground, they can achieve the anchor multiple. At the same time, competition increases, prices decline, and demand saturation leads to overcapacity and overvaluations.

The third variable contributing to a flawed business plan is the company’s misestimation of potential market share. This estimation falls victim to what economists label the “fallacy of composition.” According to this effect, the action of each individual agent is rational — or would be, were it not for the fact that others, also behaving rationally, collectively arrive at inaccurate conclusions. Investors may, for example, each estimate total demand accurately; but their market share projections do not incorporate the existence of many players going after the same market, leading them to vastly overestimate primary demand by effectively aggregating the market shares that all competitors intend to capture. A classic example of how convergent strategies lead to market-share misestimation can be found in the U.S. market, where the sum of CLECs’ projected market share was 20 times the actual aggregate demand in the local exchange market.

The fourth common investment mistake relates to errors committed at the time an entry strategy is developed. Even if demand and, consequently, potential revenues have been correctly assessed, investors can fall into what we call the critical mass trap. Akin to the myth of 1 percent technological substitution, the critical mass trap describes a firm’s overextension of its targeted area of service to reduce the burden of capturing a large share of a smaller market. This results in a “land grab,” which ratchets up the level of capital expenditures — an error that helps explain the plethora of bankrupt CLECs in the U.S. market.

Follow Us 
Facebook Twitter LinkedIn Google Plus YouTube RSS strategy+business Digital and Mobile products App Store



  1. Raul L. Katz, Maximilian Weise, and Daniel Yang, “The U.S. Wireless Industry: Consolidation Scenarios,” white paper, 2002; Click here.
  2. George Akerlof, “The Market for Lemons: Quality Uncertainty and the Market Mechanism,” The Quarterly Journal of Economics, Vol. 84, No. 3, 1970
  3. Abhijit Banerjee, “A Simple Model of Herd Behavior,” The Quarterly Journal of Economics, Vol. 107, No. 3, 1992
  4. David Collier and Richard Messick, “Prerequisites Versus Diffusion: Testing Alternative Explanations of Social Security Adoption,” American Political Science Review, Vol. 69, 1975
  5. Eugene Fama, “Agency Problems and the Theory of the Firm,” Journal of Political Economy, Vol. 88, 1980
  6. Kevin Keasey and Philip Moon, “Gambling with the House Money in Capital Expenditure Decisions: An Experimental Analysis,” Economic Letters, Vol. 50, 1996
  7. Howard Leichter, “The Patterns and Origins of Policy Diffusion: The Case of the Commonwealth,” Comparative Politics, January 1983
  8. E. McVoy, “Patterns of Diffusion in the United States,” American Sociological Review, Vol. 5, April 1940
  9. Mark Scanlan, “Hiccups in U.S. Spectrum Auctions,” Telecommunications Policy, Vol. 25, 2001
  10. Amos Tversky and Daniel Kahneman, “Judgment under Uncertainty: Heuristics and Biases,” Science, Vol. 185, 1974
  11. Allan Collins, Eleanor Warnock, Acello Nelleke, and Mark Miller, “Reasoning from Incomplete Knowledge,” in Representation and Understanding: Studies in Cognitive Science, edited by Daniel G. Bobrow and Allan Collins (Academic Press, 1975)
  12. Raul L. Katz, The Information Society: An International Perspective (Praeger, 1988)
  13. Lee W. McKnight, Paul M. Vaaler, and Raul L. Katz (eds.), Creative Destruction: Business Survival Strategies in the Global Internet Economy (The MIT Press, 2001)
  14. Charles P. Kindleberger, Manias, Panics, and Crashes: A History of Financial Crises (Basic Books, 1978)
  15. Robert J. Shiller, Irrational Exuberance (Princeton University Press, 2000)