research and statistical analysis would be difficult. Its products are relatively novel in this market, it will be facing unfamiliar competitors, it’s less sure of supplier reliability, and it knows less about whom to hire and how to train them. In this situation, McDonald’s can use qualitative scenario analysis to get a better sense of possible outcomes. It can build scenarios on the revenue side that cover a wide range of customer acceptance and competitor response profiles. On the supply side, scenarios might focus on uncertainties in the emerging market supply chain and regulatory structure that could cause wide variation in supplier costs and reliability. These scenarios will be representative, not comprehensive, but they will help executives assess the upsides and downsides of various approaches and determine how much they are willing to invest in the market. Executives should supplement the scenarios with case-based decision analysis of analogous business situations. They might look at outcomes from their own or other fast-food entries in developing markets or consider outcomes from a consumer goods entry in this particular market.
Tools: Qualitative scenario analysis supplemented with case-based decision analysis
Situation 4: You don’t understand your causal model, but you can still predict a range of outcomes. Suppose McDonald’s wants to enter a new line of business with a new business model, such as consulting services for food-service process improvements. In this case, executives probably can’t define a full causal model or easily identify the drivers of success. However, that doesn’t mean they can’t define a range of possible outcomes for the venture by tapping into the right information sources—for example, by getting estimates of success from people who have more experience with this business model or by aggregating information about the range of outcomes experienced by others using similar business models. It’s often easier to tap into outcome data (and thus define a range of possible outcomes) that define an underlying business model than to ask people to reveal the details of their business models. (That “secret sauce” is confidential in many companies.)
Tools: Case-based decision analysis
Situation 5: You don’t understand your causal model, and you can’t predict a range of outcomes. Even a well-established market leader in a well-established industry faces decisions under high levels of ambiguity and uncertainty. When considering how to respond to the recent concern about obesity in the U.S. and the backlash over the fast-food industry’s role in the obesity epidemic, McDonald’s can’t be sure of what effect various moves might have on customer demand. The backlash has the potential to fundamentally rewrite the rules for leadership in the fast-food industry and to make existing decision-making models and historical data obsolete. McDonald’s certainly can’t accurately forecast future