The Origins of Discovery-Driven Planning

June 3, 2014 Editor 0

When HBR asked us to write about the origins of discovery-driven planning, we had to laugh. It all started back in the mid-1990s, with Rita’s “flops” file – her collection of projects that had lost their parent company at least US$50 million. (Perfume from the people who make cheap plastic pens, anyone? How about vegetable-flavored Jello?)

As we studied those failures, a pattern became clear to us. The projects were all being planned as if they were incremental innovations in a predictable setting: The assumption was that the organizations launching them had a rich platform of experience and knowledge upon which to draw. The venture leaders made critical assumptions which were never tested. The funding was often significant, and approved and handed out all at once. Leaders were personally committed to the particular strategy the ventures were pursuing. And it took a long time and a lot of money before they realized that the project had been barreling along, burning tons of cash, but heading for disaster.

Clearly, a new approach to planning was needed – one better suited to high potential projects whose prospects are uncertain at the start. In Mac’s entrepreneurship classes at Wharton, many of the elements of discovery-driven planning were already emerging from work he had done on milestone planning with Zenas Block at NYU. He stressed the importance of having a revenue model (as well as a cost model), of documenting and testing assumptions, and of moving ventures through a series of milestones, rather than trying to plan them all at once. It was on a business trip to Zurich, of all places, that all these ideas came together in a concept for a planning toolkit that would be suitable for new venture leaders.

So, what was different about DDP than conventional planning methods? First, we forced venture leaders to articulate right up front what success for their businesses would have to look like to make it worth the risk and justify the resources and the effort. Then, we’d ask them to do what Mac asks his entrepreneurship students to do, which was to benchmark the key revenue and cost metrics in their business against the market and against firms offering the most comparable products. Next, we’d force them to articulate the specific operational activities their business needed to carry out in very concrete terms. Mac always liked to ask his students to specify how they were going to get their “first five sales,” rather than put grandiose projected revenue numbers in their spreadsheets. As the venture teams were specifying these operations they thought would underpin their businesses, they’d have to be making assumptions, and in our planning model, we’d insist that they write them down. And finally, we’d drive the whole plan through a series of milestones (which we’ve subsequently renamed checkpoints) which represented the points in time at which the most sensitive assumptions could be tested. We’d ask our venture teams to re-evaluate their assumptions at these checkpoints, ahead of major investments. At that point, they could stop and disengage, redirect to a reconfigured plan or continue. We challenged venture teams to spend their imagination to avoid spending money – to use their creativity to learn as much as possible as cheaply as possible, reflecting the parsimony Mac demands in his entrepreneurship classes.

The worlds of strategy and innovation have gotten much closer to one another since the publication of Discovery Driven Planning, and increasingly entrepreneurial tools are used inside established corporations. As Rita argues in her book The End of Competitive Advantage, any such competitive advantage is eroding ever-more quickly, which means that firms need to create a pipeline of advantages to replace those that have been competed away. That in turn implies that innovation – and innovative strategy — needs to be a systematic, ongoing process with a set of tools and processes that let firms achieve innovative results reliably or abandon them inexpensively. The following enhancements to DDP methodology may be valuable for firms that need to continuously innovate:

• Firms will need to generate assumptions about who likely future competitors will be and design checkpoints to test whether and when brand new competitors are emerging, thus better anticipating disruption.
• They’ll need to make assumptions about when competitive attacks and erosion of profits will begin, and design checkpoints as indicators that this is happening so that the next advantage stage can be launched at the optimal time.
• Given the increasing rate of change, it doesn’t make sense to think past the next four checkpoints. This should move the conversation from “are we deploying enough (i.e., a lot of) money to try to build a sustainable advantage?” to “Do we have just enough money to get through the next three checkpoints?”
• To speed up the “demolition” of ventures that start off seeming to be good ideas but turn out to be flawed, we need to creatively design inexpensive, roughly right checkpoints that cheaply and quickly probe whether key assumptions are wrong.

 

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