by Hugh Courtney, Dan Lovallo, and Carmina Clarke
Senior managers are paid to make tough decisions. Much rides on the outcome of those decisions, and executives are judged—quite rightly—on their overall success rate. It’s impossible to eliminate risk from strategic decision making, of course. But we believe that it is possible for executives—and companies—to significantly improve their chances of success by making one straightforward (albeit not simple) change: expanding their tool kit of decision support tools and understanding which tools work best for which decisions.
Most companies overrely on basic tools like discounted cash flow analysis or very simple quantitative scenario testing, even when they’re facing highly complex, uncertain contexts. We see this constantly in our consulting and executive education work, and research bears out our impressions. Don’t misunderstand. The conventional tools we all learned in business school are terrific when you’re working in a stable environment, with a business model you understand and access to sound information. They’re far less useful if you’re on unfamiliar terrain—if you’re in a fast-changing industry, launching a new kind of product, or shifting to a new business model. That’s because conventional tools assume that decision makers have access to remarkably complete and reliable information. Yet every business leader we have worked with over the past 20 years acknowledges that more and more decisions involve judgments that must be made with incomplete and uncertain information.
The problem managers face is not a lack of appropriate tools. A wide variety of tools—including case-based decision analysis, qualitative scenario analysis, and information markets—can be used for decisions made under high degrees of uncertainty. But the sheer variety can be overwhelming without clear guidance about when to use one tool or combination of tools over another. Absent such guidance, decision makers will continue to rely solely on the tools they know best in an honest but misguided attempt to impose logic and structure on their make-or-break decisions.
A model matches the decision-making tool to the decision at hand, on the basis of three factors: how well you understand the variables that will determine success, how well you can predict the range of possible outcomes, and how centralized the relevant information is.
As you ponder which tools are appropriate for a given context, you need to ask yourself a fundamental question: Do I know what it will take to succeed? You need to know whether you have a causal model—that is, a strong understanding of what critical success factors and economic conditions, in what combination, will lead to a successful outcome. Companies that repeatedly make similar decisions often have strong causal models. Consider a retailer that has launched outlets for years in one country, or one that has made many small acquisitions of adjacent competitors.
One simple test of the strength of your causal model is whether you can specify with confidence a set of “if-then” statements about the decision. (“If our proposed new process technology lowers costs by X% and we are able to achieve Y% market share by passing those savings on to our customers, then we should invest in this technology.”) You should also be able to specify a financial model into which you can plug different assumptions (such as how much the technology lowers costs and how much market share you are able to capture).
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BASIL VENITIS
MANAGEMENT CONSULTANT AND FINANCIAL STRATEGIST
Basil Venitis identifies the highest-value opportunities, addresses the most critical challenges, and transforms management and financial strategies.
The customized approach of Basil Venitis combines deep insight into the dynamics of industries with close collaboration of the client, in order to achieve sustainable competitive advantage.
Venitis seeks to be the agent of change for his clients. He grounds each solution in how his client actually works and positions in the marketplace.
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