Eric Ries, Harvard Business School’s ‘Entrepreneur-in-Residence’ and the founder of Lean Startup, has been interviewed a number of times recently following the launch of his Lean Startup book. As we have argued before at Analyst First, the ‘unknown problem / unknown solution’ domain—in which and for which the Lean Startup approach was developed—reflects the world of Business Analytics. In the 12 to 18 months since giving the last interview we linked to, Ries has significantly enriched the ideas of Lean Startup. Two new interviews are highly recommended. The first is from the Commonwealth Club of California’s Inforum program. Details here and audio file here, or here. The second is from the ITConversations network’s Tech Nation program. Details and download here.
Ries takes it as axiomatic that enterpreneurs seek to create “institutions of lasting value” in an unstable environment. He defines a startup as any “human institution designed to create something new under conditions of uncertainty”. The role of the Lean Startup toolkit is to help entrepreneurs navigate the best path in this context. Most contemporary management tools have their heritage in twentieth century manufacturing and are based on forecasting and planning. They assume that the world is stable enough to be predicted such that plans can be reliably devised and executed. As Ries points out, and should be obvious, this assumption simply doesn’t hold in the environments in which many of us now work.
In the twenty-first century we can build almost anything that can be imagined. The challenge is not to build more stuff. It’s to build the right stuff. Most startups fail, says Ries, because they make the wrong things. The key activity of a startup should therefore be learning, not building. What creates value for a startup is it determining whether or not it’s on the path to a sustainable business.
Lean Startup is a scientific approach to new product development which treats everything a startup does as an experiment. The goal is to collect data (feedback about what customers want) with minimal cost, not to build to a pre-determined product specification (which assumes what customers want) with minimal cost. In service of this, the Lean Startup movement is developing ‘innovation accounting’, an attempt to revolutionise the existing accounting paradigm so that it can operate under conditions of uncertainty and instability. The current planning-based paradigm (are we on time, on budget?) is unable to distinguish between the threshold of success and the brink of failure. The core question being asked by innovation accounting is, instead: are the experiments the team’s doing affecting customer behaviour?
Clearly there are implications here for Business Analytics. We’ve often written here of the uncertainty inherent in data-driven analysis, and of the unsuitability of the default IT project plan-based, build-centric, waterfall approach to what is inescapably an exploratory and learning-oriented set of activities. Much of the Lean Startup approach translates directly into the Analytics Lab. However, the constraints faced by those attempting to innovate from within already established organisations (who Ries terms ‘intrapreneurs’) are not the same as those which frame the entrepreneurial enterprise. Entrepreneurs operate until the financial capital provided to them by venture capitalists runs out. The ‘lean’ in Lean Startup seeks to maximise the number of experiments they can run before this happens. The entrepreneurs described by Ries all enjoy a large and fundamentally interchangeable prospective customer base. Many unsuccessful experiments can be run on different user populations in search of a loyal base, essentially without consequences. Unhappy users don’t stick around. This is not the case for intrapreneurs. Within an organisation there are only a limited number of prospective analytics customers, and disappointing any one group leaves a legacy. The scarce resource for intrapreneurs is political capital.
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