Traditional asset-heavy companies may seem safe from explosive industry change, but there is trouble on the horizon. To stave off disaster, incumbents must transform their core operations while also growing into new businesses and industries.

Not all industries have been exposed to the “big bang” changes that are often associated with the spread of new technologies. When we analyzed exits from the S&P 500 between 2000 and 2015, we saw that more than half came from just three industries: consumer products, information technology, and financial services. In other sectors, changes in the rise and fall of companies have been much more gradual.

That may seem like comforting news to many leaders, but the reality is more complex. Our analysis of the performance of more than 1,200 companies in six of the most asset-heavy sectors —telecommunications, utilities, energy, materials, automotive, and industrials — revealed an equally worrying trend. (See “About the Research.”) Incumbents throughout these industries are falling prey to “industry compression”—a form of slow, but dangerous change that results in a prolonged decline of both operating profits and revenues.

A compressed core business, even in a long-established industry, can become altogether obsolete if a company fails to transform in time. To appreciate the intensity of compression, consider the accelerating decline of “voice” as a means of communicating via mobile telephone. From 2013 to 2015, average mobile voice revenue per user declined globally by 19%. A further 26% decline is expected through 2020.1 The business impact of this decline has been the stalling of a decade of growth: Revenues and earnings before interest, taxes, and amortization (EBITA — a measure of operating profits) in the sector have dropped by an average of 8% from 2013 to 2015, down from over 120% growth during the previous decade.

Companies at risk from the dangers of compression may not recognize the extent of the threat to their core businesses, as the life cycle of decline can be as stealthy as it is insidious. In the initial phase, companies experience a period of “empty” growth, as revenues continue to increase despite a stagnation in EBITA growth. In the next phase, companies see a further decay in performance, in which year-on-year EBITA declines at a faster rate than revenue. Then comes a period of brief recovery that provides a false hope that essential, structural challenges within the industry can be managed with business as usual; some companies drop prices in order to prevent a decline in revenue.

References

1.Accenture analysis based on Ovum, Mobile Subscription Forecast 2015-20, March 2016.

2.A.P. Moller-Maersk, “Profits overboard,” The Economist, Sept. 10, 2016, http://www.economist.com.

3.Accenture, “Future Business Models of European Energy Companies,” June 2016.

4.European Renewable Energies Federation, “The Potential for Energy Citizens in the European Union” (2016), available at http://www.recyclind.com/ (accessed March 9, 2017); UNEP and Bloomberg New Energy Finance, “Global Trends in Renewable Energy Investment 2016”, available at http://fs-unep-centre.org (accessed March 9, 2017).

5.Based on the combined market capitalization of publicly traded U.S. coal mines over a five-year period from Jan. 20, 2011 to Jan. 20, 2016.

6.Haier, “Haier’s Global Open Innovation Ecosystem,” Nov. 13, 2015, http://www.haier.net/en/research_development/Ecosystem/ (accessed March 9, 2017).

7.BASF, https://creator-space.basf.com/content/basf/creatorspace/en.html (accessed March 9, 2017).

8.R. Juskalian, “Bosch’s Survival Plan,” MIT Technology Review, June 21, 2016, www.technologyreview.com.

9.Ofcom, “The Communications Market 2015: Telecoms and Networks,” Aug. 17, 2015, https://www.ofcom.org.uk (accessed March 9, 2017).

10.G. Spanier, “BT boss aims to score with football,” The Independent, Feb. 19, 2013, http://www.independent.co.uk.

1 Comment On: The Big Squeeze: How Compression Threatens Old Industries

  • Chandler Wilson | March 27, 2017

    Would it be possible to get the raw data on that was used in the analysis i.e. the exits from the S&P 500 between 2000 and 2015?

Add a comment