Last weekend, I spoke with a friend who just returned from Italy. He asked: do you know how long it took to build the St. Peter’s basilica?
120 years! That’s 1.2 centuries. Or, a decent-sized-fraction of a millennium.
Awe-inspiring, no doubt. But what is particularly remarkable is that the basilica planners had to answer some extremely important questions before construction even began: would the building accommodate the size of the community in 120 years? Would the design meet the aesthetic tastes of our grandchildren? To answer these questions without the luxury of Excel, Stata or dartboards (created 100’s of years later by our friends in England) must have required luck—and prayer.
In many ways, it’s the equivalent of a modern-day, consumer product development cycle. In a sea of shifting segments, who will purchase my product when it finally hits store shelves? Not an easy question to answer, even with modern, predictive tools we now have at our disposal.
This long product development cycle is nothing new to the automotive industry, and is captured in the bowing of two new vehicles: the Chevy Volt and the redesigned Jeep Grand Cherokee (the two ‘poster-cars’ for the rebirth of the American auto industry). Both are generating lots of media attention. But which one will appeal more to buyers? The gas hog or the gasless? Two years ago, consumers joined a waitlist for a hybrid. Now, the US government is declaring a slightly different message: Americans like big cars. The shifting target phenomenon is nothing new to marketers. Besides the obvious myriad of segments, volatile externalities like gas prices significantly impact the buying patterns of the US auto consumer. So, someone’s Volt preference today very well could be a Grand Cherokee tomorrow.
The current crop of American autos is being hailed as fitting for the public’s taste. Will it match consumption patterns tomorrow? No one knows.
But within many of our manufacturing members’ organizations, the debates rage. Despite sophisticated models and scenario planning tools, most of these organizations struggle to reach adequate confidence levels around the likelihood and impact of each potential future state to take any decisive action.
The trick seems to be to avoid the endless discussion of probabilities, and focus on prioritizing the right focus for action by identifying the most certain changes to the environment and to business capabilities over relevant time frames—the goal being not to develop a more accurate model, but to ensure that the actions you are taking will guarantee success under the circumstances of the top three most probable scenarios. MLC members can click here for a case study of how an automaker did just that (beginning at page 31).
After that, of course – pray.
MLC members, for more on innovation and managing cross-functional teams in new product development, please visit our organizational management and innovation topic centers.
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