The Secret of Successful Scenario Planning

By David Niles for

David Niles of SSAToday almost no business operates without some kind of scenario planning. Executives take pride in rigorously evaluating wide varieties of potential influences on their businesses, from customer moves to supplier changes, shifts in energy prices, competitive actions and a whole host of other business drivers.

Given the ubiquity of scenario planning, why do so many businesses find themselves playing catch-up when their market environments change? Recent dismal share performances and record defaults make it undeniable that this aspect of corporate planning has significant deficiencies.

Look at the automobile industry. A year ago, cheap financing, a core driver of growth, was drying up, crippling suppliers and putting auto retailers across the country out of business.

Yet one notable exception, the auto retailer AutoNation ( AN –news – people ), experienced profitability and positive cash flow in 2008 and 2009, and its stock price has appreciated nearly 400% since October. It’s a firm with locations in some of the hardest hit regions in the U.S., in Florida and the Southwest. It’s in one of the worst industries to be in right now. Staring into that abyss, what kind of performance do you think you would have achieved? How has AutoNation done it?

Backtrack three years to 2006. The conventional wisdom at the time held that Americans would go on and on buying 14 million to 16 million automobiles a year. The number might vary, but not by more than perhaps 10%. This assumption was based on the stable underpinnings of auto demand–cheap financing by car companies (and by home equity loans) and a customary replacement cycle of three years. Looking at the averages, you can easily see how executives might have made those now clearly erroneous assumptions.

Mike Jackson, the chairman and chief executive officer of AutoNation, took a different approach. He looked beyond the homogenized data and asked himself, What if buyers began to hold off and replace their cars after five years instead of three? What if the financing spigot–either for the automotive companies or for the individual consumer–got turned off? These things didn’t seem to be very likely three years ago, but if they came to pass they could (as they did) have a devastating effect on the industry. The fact that Jackson asked these questions ultimately had profound impact on AutoNation’s ability to survive in 2009.

Jackson had the wisdom to look at low-probability but high-consequence events that could rock his business. He avoided the trap of planning based on averaged data.

In business, as in life, real outcomes often don’t follow the averages. Yet much of corporate strategy and finance is planned as if they always did. Far too many companies make strategic and financial planning a routine exercise. They take last year’s budgets and results and assume some modest variation from the mean. Even when they do regular scenario planning they fail to delve deeply into their operations, or look at how multiple events might interrelate (for instance, increased energy costs and their impact on interest rates, which in turn would likely affect the cost of capital for one’s customers and their businesses).

From an investor’s perspective, the idea of planning for low-probability, high-consequence events is well treated in Nassim Nicholas Taleb’s book The Black Swan: The Impact of the Highly Improbable. Taleb’s method is very similar to what CEOs need to be doing–understanding the key leverage points of their economic models. For instance, many executives don’t take the time to understand what alters the financing of their customers’ purchases, or what their investors’ or lenders’ ultimate incentives are. Just that kind of misjudgment left many companies stranded in the fall of 2008, when the commercial paper markets dried up. They found themselves in a scramble for liquidity; they had to slash investments, hold back their strategies and shift their attention from their customers to their balance sheets.

By relying on simple variations on the mean, companies effectively homogenize the data they get, and they miss crucial key information. When you average out your customers’ demand, you lose sight of those customers’ key decision thresholds. Which ones will buy from you tomorrow and why? What does that say about their changing needs? Similarly, when thinking about competition, you can’t just model out where your competitors were last year in terms of pricing and service. You have to discern where you think they’ll be in the future

What Jackson and AutoNation did was understand better than their competitors the root drivers of car demand: cheap financing and a short replacement cycle. Modeling out what could disturb the fragile financing infrastructure that supported automotive purchases, they discovered the possibility of a huge near-term disruption in their customers’ ability to pay. And modeling out what could happen to their business if their customers began to hold on to cars longer, they discovered that they could reduce their inventory levels and increase their emphasis on service operations, just when customer demand began to lean that way. The results of those two perceptions–and AutoNation’s discipline in acting on them–set the stage for the company’s recent success.

These ideas may not sound revolutionary, but very few businesses show the discipline to create scenarios and measure probabilities for large but unexpected market changes.

Try it yourself. Start thinking about the four or five key assumptions you make in your forecasts. What will happen with your suppliers? Why? What will happen with your customers? With your competition? Why? Then apply a probability to each scenario, based on your impression of the likelihood of its occurring. Probabilities allow you to start to balance resource allocation to the most likely outcomes while not ignoring the possibility of others.

Lastly, look across those scenarios. What are their key themes and underlying drivers? When you do that you can model other scenarios and, just as important, set a focus on leading indicators that will help you prepare for different eventualities. I think you’ll find that the result is a deeper understanding of your business, and greater agility. By better evaluating specific possible outcomes, their probabilities and their underlying drivers, you can greatly improve your company’s ability to see around corners and prepare for the future.

David Niles is president of SSA & Co., a consulting firm that focuses on strategic process management.