Almost all strategy books that fill our shelves today suffer from a lack of testable hypotheses. How are we supposed to know whether a recommendation works if the only supporting evidence is anecdotal or based on case examples? There just isn’t any way to quantify and test those ideas, which is why lists of great companies fall apart so quickly.
While many ideas about strategy provide a lens for understanding why something failed or succeeded, what really matters is being able to peer into the future, not the past. That’s why my colleagues and I emphasize the use of deep, testable data, and have tried to find empirical benchmarks for strategy. In an earlier blog I explained the Power Curve of economic profit, and our finding that the average company in the middle three quintiles has just an 8% chance of moving to the top quintile over a decade. But what are the odds of your company moving up the Power Curve? And can you change them?
We can answer that by adding color to the picture: The more we know about a company, the more precisely we can estimate its odds of success. If the only thing we know about a person is that, well, they are a person, then the best estimate for their income is the global average of $15,000 per year. If we add information, such as that the person is American, our estimate jumps to the average U.S. income, or $56,000. If we know the person is an American 55-year-old male, the estimate jumps to $64,500. If that guy works in the IT industry, it jumps to $86,000, and if we know the person is Bill Gates, well, it’s a lot more than that.
Or consider an experiment The Economist described in “How to make a hit Hollywood film.” An analysis of the performance of more than 2,000 movies with budgets of more than $10 million released in America and Canada since 1995 produced the following formula: Create a child-friendly, action-packed superhero film with prospects of turning into a franchise. Set your budget at a healthy but not reckless $85 million. Convince a major studio to give it wide release during summer, and cast lead actors with solid box-office records but affordable salaries. “With reasonable reviews from critics and the audience alike, your film would make about $125 million at the American box office,” the magazine concluded.
The 10 variables that make the difference
Likewise, in assessing the probabilities of corporate success, you need to understand which attributes and actions are most important in determining your chances since, as my colleague Sven Smit recently explained, strategy is not about developing certainty but boosting your odds. That knowledge will guide your decisions about where to dedicate your efforts.
In our work looking at the performance of the world’s largest companies over a decade, we found 10 levers—out of 40 we examined—that are the strongest determinants of corporate success. But for these variables to matter, they need to meet a certain threshold. It’s not how smart you are, but how much smarter you are than the other kids taking the test.
We’ve grouped these levers into three categories: endowment, trends, and moves.
Endowment: This is what you start with. Our research shows the three variables that matter most here are your starting revenue (size), your debt level (leverage), and your past investment in R&D (innovation). Endowment determines about 30% of your odd of mobility on the Power Curve.
Size of your company. The larger your company is, the more likely you are to be able to improve your relative position. That may seem to contradict the success stories we read about startups, but when it comes to scaling the Power Curve, size amplifies the effects of performance improvement in absolute terms. To gain a significant advantage from this variable, you need to be in the top quintile in total revenue. Today, that means exceeding roughly $7.5 billion.
Debt level. There is an inverse relationship between how much leverage you have built into your current balance sheet and your chances of moving up the Power Curve. The less debt you have, the better your chances of moving up. The key here is to have a debt-to-equity ratio that is favorable enough to put you in the top 40% in your own industry.
Past investment in R&D. This indicates what prospects you’ve invested in and what you still may have to invest in. You need to be in the top half of your industry in your ratio of R&D to sales to gain a significant benefit from this variable.
Trend. The two key variables that fall into this category are industry trend and exposure to growth geographies. If your industry is moving up the industry Power Curve, you’re likely to benefit from that tailwind. If you’re operating in growth geographies, you’ll also get a boost, though being in the right countries doesn’t matter quite as much as being in an industry that trends upward. Trends determine about 25% of your odds.
Industry trend. The trend in your industry is the single most important of all 10 attributes. For your industry to be your friend, it needs to be moving up the Industry Power Curve by at least one quintile over a 10-year period. This is like the tide going in—or out—and lifting or lowering the average level of boats in the harbor.
Geographic trend. The key here is to be in markets that are among the top 40% for nominal GDP growth. Companies operating in more than one geographic market—which is most of the 2,393 we studied— would calculate the corporate-wide GDP growth figure based on the percentage of revenue you received from each geographic market. It’s intuitively clear that being exposed to faster-growing markets yields benefits—but equally interesting how overall macroeconomic conditions tend to be a footnote in many long-term strategy discussions.
Moves. While the industry trend is the single most important lever among the 10, it is the big strategic moves that, in aggregate, explain almost half of a company’s mobility on the Power Curve. Our research found five moves that, pursued persistently, can get you to where you want to go: programmatic M&A, dynamic allocation of resources, strong capital expenditure, strength of productivity program, and improvements in differentiation. (For a full exploration of these moves and how to ensure you’re executing them in a way that will have a real impact, please read this recent blog.)
Levers of upward mobility
So how do all these variables affect your relative position? The image below summarizes these 10 levers for companies starting in the middle quintiles of the Power Curve. One way to see their relative importance is to look at how the odds of upward movement change in different threshold regions for each variable. For example, if your company catches an industry mega-trend, then your chances of moving from the middle to the top rise to 24%--three times the 8% average. Alas, only the best-positioned 20% of companies get to enjoy that much tailwind. If, on the other hand, you face a strong headwind—like half the companies in the sample—your chances of upward movement are just 4%.
While I’ve explained each lever separately, in reality these attributes work in concert. The odds aren’t calculated by simple addition, but by careful accounting of combined influences. And the actions on the 10 levers typically have to be big in comparison with the competition. This is very important. A big move is not big because it’s hard, or because the team feels stretched; it’s big when it’s big relative to your competitors.
By measuring where you stand on each variable, you can determine what levers really matter to your own business. What makes this a powerful tool in battling the effects of the social side of strategy is that you now have a benchmark for the quality of a strategy that’s independent from subjective judgments. A good strategy is still hard to shape, but you can at least greatly increase your chances of understanding how close it is to a likely winner.
Martin Hirt is a senior partner in our Greater China office and co-author of Strategy Beyond the Hockey Stick with Sven Smit and Chris Bradley.
Originally published on LinkedIn.