Three Rules for Making a Company Truly Great
Much of the strategy and management advice that business
leaders turn to is unreliable or impractical. That’s because
those who would guide us underestimate the power of chance.
Gurus draw pointed lessons from companies whose
outstanding results may be nothing more than random
fluctuations. Executives speak proudly of corporate
achievements that may be only lucky coincidences.
Unfortunately, almost no one provides scientifically credible
answers to every business leader’s basic questions about
superior performance: Which companies are worth studying?
What sets them apart? How can we follow their examples?
Frustrated by the lack of rigorous research, we undertook a statistical study of thousands of
companies, and eventually identified several hundred among them that have done well enough for a
long enough period of time to qualify as truly exceptional. Then we discovered something startling:
The many and diverse choices that made certain companies great were consistent with just three
seemingly elementary rules:
leaders turn to is unreliable or impractical. That’s because
those who would guide us underestimate the power of chance.
Gurus draw pointed lessons from companies whose
outstanding results may be nothing more than random
fluctuations. Executives speak proudly of corporate
achievements that may be only lucky coincidences.
Unfortunately, almost no one provides scientifically credible
answers to every business leader’s basic questions about
superior performance: Which companies are worth studying?
What sets them apart? How can we follow their examples?
Frustrated by the lack of rigorous research, we undertook a statistical study of thousands of
companies, and eventually identified several hundred among them that have done well enough for a
long enough period of time to qualify as truly exceptional. Then we discovered something startling:
The many and diverse choices that made certain companies great were consistent with just three
seemingly elementary rules:
1. Better before cheaper—in other words, compete on differentiators other than price.
2. Revenue before cost—that is, prioritize increasing revenue over reducing costs.
3. There are no other rules—so change anything you must to follow Rules 1 and 2.
The rules don’t dictate specific behaviors; nor are they even general strategies. They’re foundational
concepts on which companies have built greatness over many years. How did these organizations’
leaders come to adopt them? We have no idea—nor do we know whether the executives even
followed them consciously. Nevertheless, the rules can be used to help today’s and tomorrow’s
leaders increase the chances that their companies, too, will deliver decades of exceptional
performance.
concepts on which companies have built greatness over many years. How did these organizations’
leaders come to adopt them? We have no idea—nor do we know whether the executives even
followed them consciously. Nevertheless, the rules can be used to help today’s and tomorrow’s
leaders increase the chances that their companies, too, will deliver decades of exceptional
performance.
Beyond Truisms
The impetus for our research was the increasing popularity over the past 30 years of “success study”
business books and articles. Perhaps the most famous of these are Thomas Peters and Robert
Waterman’s In Search of Excellence (1982) and Jim Collins’s Good to Great (2001), but there are
many others. The problem with them is they don’t give us any way to judge whether the companies
they hold up as examples are indeed exceptional. Randomness can crown an average company
king for a year, two years, even a decade, before performance reverts to the mean. If we can’t be
sure that the performance of companies mentioned in success studies was caused by more than
just luck, we can’t know whether to imitate their behaviors.
We tackled the randomness problem head-on. Finding what we assumed would be weak signals in
noisy environments required a lot of data, so we began with the largest database we could find—the
more than 25,000 companies that have traded on U.S. exchanges at any time from 1966 to 2010.
We measured performance using return on assets (ROA), a metric that reflects strong, stable
performance—unlike, say, total shareholder return, which may reflect the vagaries of the stock
market and changes in investor expectations rather than fundamental company performance. We
defined two categories of superior results: Miracle Work ers fell in the top 10% of ROA for all 25,000
companies often enough that their performance was highly unlikely to have been a fluke;Long
Runners fell in the top 20% to 40% and, again, did so consistently enough that luck was highly
unlikely to have been the reason. We call the companies in both these categories exceptional
performers. For comparison purposes, we also identified companies that were Average Joes. (See
the sidebar “Finding the Signal in the Noise.”)
The impetus for our research was the increasing popularity over the past 30 years of “success study”
business books and articles. Perhaps the most famous of these are Thomas Peters and Robert
Waterman’s In Search of Excellence (1982) and Jim Collins’s Good to Great (2001), but there are
many others. The problem with them is they don’t give us any way to judge whether the companies
they hold up as examples are indeed exceptional. Randomness can crown an average company
king for a year, two years, even a decade, before performance reverts to the mean. If we can’t be
sure that the performance of companies mentioned in success studies was caused by more than
just luck, we can’t know whether to imitate their behaviors.
We tackled the randomness problem head-on. Finding what we assumed would be weak signals in
noisy environments required a lot of data, so we began with the largest database we could find—the
more than 25,000 companies that have traded on U.S. exchanges at any time from 1966 to 2010.
We measured performance using return on assets (ROA), a metric that reflects strong, stable
performance—unlike, say, total shareholder return, which may reflect the vagaries of the stock
market and changes in investor expectations rather than fundamental company performance. We
defined two categories of superior results: Miracle Work ers fell in the top 10% of ROA for all 25,000
companies often enough that their performance was highly unlikely to have been a fluke;Long
Runners fell in the top 20% to 40% and, again, did so consistently enough that luck was highly
unlikely to have been the reason. We call the companies in both these categories exceptional
performers. For comparison purposes, we also identified companies that were Average Joes. (See
the sidebar “Finding the Signal in the Noise.”)
Comments
Post a Comment