Plans are useless but planning is indispensable. - Dwight D. Eisenhower
My company, OpenBI, just celebrated its 7th birthday. When my partners and I decided to start a BI/analytics consultancy in early 2006, I set about developing a five-year plan to lay out our business model and woo angel investors. I suppose you could say that effort was successful: the shiny document and accompanying spreadsheets told a compelling-enough story to launch the company with adequate funding. And OpenBI’s had a nice subsequent run, with steady growth and consistent profitability.
Yet when I looked back at the 2006 documents recently, I couldn’t help but smile. The plan, modeled on a successful consultancy of the 90s, was quite distant from actual experience. In retrospect, it was doomed from the get-go, with a flawed financial mindset anchored in mid-90s technology hyper-growth. Alas, the early 2000s weren’t nearly so accommodating, as the following graphic attests.
But even more than the uncooperative economy – you can make money in good times and bad -- there was a naiveté about the plan that became more than apparent after I read the May, 2013 Harvard Business Review article, “Why the Lean Start-Up Changes Everything”, by Steve Blank. Blank’s thesis is that the traditional 5-year business plan is pretty much useless, failing to adequately capture the essence of start-ups. The main problem is the assumption that “it’s possible to figure out most of the unknowns of a business in advance, before you raise money and actually execute the idea.” His rationale is as follows:
‘1. Business plans rarely survive first contact with customers. As the boxer Mike Tyson once said about his opponents’ prefight strategies: “Everybody has a plan until they get punched in the mouth.”
2. No one besides venture capitalists and the late Soviet Union requires five-year plans to forecast complete unknowns. These plans are generally fiction, and dreaming them up is almost always a waste of time.
3. Start-ups are not smaller versions of large companies. They do not unfold in accordance with master plans. The ones that ultimately succeed go quickly from failure to failure, all the while adapting, iterating on, and improving their initial ideas as they continually learn from customers.’
Blank’s antidote? The lean start-up, in which a temporary, agile organization “searches” for a repeatable, scalable business model. The tenets of Blank’s lean start-up methodology include accepting that at the beginning all the businessman has is a series of assumptions, good guesses and untested hypotheses. Step one revolves on summarizing these hypotheses on how the new enterprise will create value for itself and its customers using a framework called a business model canvas.
The second phase, customer development, tests the hypotheses by soliciting feedback on the business model. “Then, using customers’ input to revise their assumptions, they start the cycle over again, testing redesigned offerings and making further small adjustments (iterations) or more substantive ones (pivots) to ideas that aren’t working.” Finally, the third phase deploys agile development techniques, eliminating wasted time and resources by developing the product iteratively and incrementally.
While lean start-up thinking might be relatively new, the recognition of the perils of top-down planning is not. Over three years ago, I blogged on Discovery-Driven Planning, an approach to strategy formulation espoused by B-School professors Rita Gunther McGrath and Ian MacMillan. “Discovery-driven growth is a way of planning to grow that doesn’t require a lot of analytical information at the outset. It recognizes that many of the data that you need to make decisions don’t exist at the time that you have to make the decisions. It’s a plan to learn.”
Gunther believes the biggest problem with traditional planning is that it takes “untested assumptions that underlie the plan and treats them as facts.” The assumptions in turn trigger confirmation bias, the “all-too-human tendency to embrace data that support what we believe to be true.” Adds MacMillan, “You have to make assumptions. The key issue is to know from the start that the plan is wrong. That's the only thing I know about the plan -- that it's wrong. So, how do I plan in such a way that I come out with the right solution but not necessarily know what it is at the outset? That's what discovery-driven planning is all about. It's a plan to learn. We don't know. So what are we going to learn? What you really want to do is you want to learn cheap and you want to learn fast, and if it's wrong you want to go and do something else or you want to redirect.”
Developmental economist William Easterly has long been a critic of heavy planning in his discipline. He contrasts top-down Planning unfavorably with bottom-up Searching. “In a business context, the Planner thinks she already knows the answers, which are derived from planned solutions to technical engineering problems. A Searcher, on the other hand, acknowledges upfront that she hasn't all the answers, but is intent on finding them through trial and error. Planners have grand ideals; Searchers are modest in intent, looking for little victories. Planners are top-down experts; Searchers are bottom-up experimenters. For Planners, the plan with fixed objectives is too often the end game; Searchers, in contrast, are not unduly attached to their ideas, but instead are flexible and nimble, willing to vary objectives with learning. Planners raise expectations; Searchers crave feedback and accountability.”
A commonality of Lean Start-Ups, Discovery-Driven Planning, and Searchers over Planners? The belief in the ascendance of the scientific method and analytics over experts – the understanding that a methodical, cautious, experimental, data-driven, learn-as-you-go approach trumps a meticulously-planned, expert-driven strategy more often than not.