These days, the Lean Startup Movement is in full swing, largely thanks to the momentum of important books such as The Startup Owner’s Manual by Steve Blank and The Lean Startup by Eric Ries. The tomes popularize useful and powerful concepts that have been successfully practiced by select firms for decades.
However, to get started understanding and teaching these concepts, it’s important to distinguish “Lean” and “Lean Startup.” The concepts, tools, and principles of Lean (quality, tqm and six-sigma) and Kaizen are very important for “incremental innovation.” The methods and techniques of Lean are as applicable on the revenue and customer side as they are for the cost and efficiency side. This approach is structured, analytical, and step by step.
On the other hand, the concepts and methods of Lean Startup are less structured; they are more about rapid prototyping, faster learning, and emergent strategy development. In short, they are more applicable to “radical innovation.” Specifically, the Lean Startup thinking helps us get away from the Big Bang approaches that most large firms, governments, and NGOs tend to prefer or use; at most times because of the lack of knowledge about alternatives. Lean Startup concepts are the right tools to use when there is uncertainty and ambiguity, i.e., in all startup situations and radical innovation (as opposed to incremental).
All startups and radical innovation have too many variables and too many unknowns. When you are dealing with unknowns, one is talking about uncertainty or ambiguity. Risk is about the “known” world—known variables with data from the past. You can calculate and estimate risk using analytical tools. When you know the variables and you have data from the past, you can analyze, predict, plan, and then take action. This is known as “deliberate or intended strategy.” However, uncertainty is about the known unknowns (known variables but no data from the past) and ambiguity is about unknown unknowns (variables that can only be uncovered once action is taken).
We can go into the future in primarily two ways: (1) Analysis before Action and (2) Analysis after Action. Amid unknown variables, most analysis and hence prediction of outcomes a priori is futile. Unfortunately, most novice entrepreneurs, large firms, and governments predominantly still prefer this mode of going into the future. Most five-year strategic plans and business plans fall under this category.
To better understand the distinction between the two modes of going into the future, let us look at some recent examples of innovation and change:
- In Nov. 2011, former Apple retail-star Ron Johnson was named the new CEO of struggling midlevel department store J.C. Penny’s (JCP). Johnson quickly set about making drastic changes at JCP—a significant shift toward upscale mini-Martha Stewart in-store boutiques, the elimination of traditional coupons, and major pricing changes. In spite of several initial indications of customer nonacceptance to the changes, the CEO pushed ahead with the mega-changes across the entire chain simultaneously. By the end of the first year of Johnson’s turnaround strategy, JCP had amassed nearly a $1 billion in losses and a 25 percent drop in its revenues. In April 2013, Johnson was fired.
- In Feb. 2013, an online Internet course offered by Georgia Tech and hosted by the leading online learning firm Coursera promised to teach 40,000 students how to create their own massively open online course. The online platform asked participants to sign up using Google Docs. When the crush of students tried to sign up, the system crashed. According to Google, apparently Google Docs allows only 50 people to edit a document simultaneously. A small detail, that seemed to have been overlooked by the planners.
- In March 2013, the high-flying Canadian yoga apparel maker and retailer Lululemon Athletica had to recall more than $60 million worth of a women’s yoga pants for being too see-through. Within a month, there was an announcement stating “product chief to exit.” The following month the CEO announced that she was “stepping down.”
- On Oct. 1, 2013, the much-anticipated healthcare.gov went live. And, almost immediately, it crashed. Unanticipated surge in Web traffic was blamed for most of the problems. Even those who were able to get through faced a multitude of issues and errors—confusing instructions, missing drop-down tools, unexpected hang-ups and puzzling design. Those who gave up and called the customer service reps didn’t fare any better. The reps couldn’t access the online market place either. In April 2014, Kathleen Sebelius, the Health and Human Services secretary, resigned because of the healthcare.gov website’s troubles.
All these above examples have one thing in common. I call it the “Big Bang” approach to going into the future—introducing new products, innovation, and change management in general. I call the firms, organizations, and individuals who principally use this strategy as “Planners.” Unfortunately, most large firms, governments, and institutions predominantly still prefer this Big Bang mode of going into the future. This approach to change and project management makes a bunch of assumptions: (1) all process and outcome variables are known and can be accounted for ex-ante, (2) existing data from past projects can be used to predict the process and outcome of this project, (3) some variation to projections can be accommodated along the way using managerial judgment, (4) all projects will be launched at full scale and (5) failure is not an option.
Traditional approaches to minimize and manage risk in Big Bang innovation and change management projects is by doing a lot of analysis before taking action. BHAGs (Big Hairy Audacious Goals) are announced with much fanfare. Then, the future is approached by performing an environmental scanning (SWOT, STEP, Value Chain Analysis) and followed by the setting of a project plan to execute strategy. Trend lines are predicted based on IRRs and WACC or projected cost benefits; KPIs and milestones are set and budgets are allocated. When project performance does not meet projections, money and energy is spent to get the project back on to the predicted trend line. Unfortunately, heads roll when the predicted future fails to materialize.
Unfortunately, a website like healthcare.gov is a massive and complex undertaking—too many variables and too many unknowns. So are major change initiatives like at J.C. Penny’s. When you are dealing with unknowns, one is talking about uncertainty and/or ambiguity. The only way to uncover unknown variables is through action—experimentation, trial, and error. There is no other way. Any amount of analysis will not uncover some of the hidden variables.
Hence, seasoned entrepreneurs, innovators, and VCs use a very different approach to go into the future. They test out their ideas predominantly through Analysis after Action. They think big, but start small. They start several small projects to test their hypotheses. They prototype rapidly and try to establish proof of concept by quick feedback from the market—voice of customer, voice of technology, voice of supply, and voice of demand. They try to fail fast, fail cheap, and fail smart. In doing so, they learn quickly by uncovering hitherto unknown variables and/or create data where there is none. With this new knowledge, they refine their hypotheses and business models. They iterate this process of prototyping, failing, uncovering unknowns, and establishing a viable business model. They pour in more resources only after a positive proof of concept has been established and the successful business model is replicated and scaled slowly. I call this approach to going into the future as “Start Small;” as against the Big Bang approach described previously. I call the firms that employ this technique as “Testers.”
To summarize, Planners usually follow the traditional Big Bang approach that is characterized by the following sequence: Analyze → Predict → Plan → Act → Full Scale Launch. Testers on the other hand follow the Start Small approach that is characterized by the following sequence: Design → Build → Test → Learn → Redesign → Scale Slow Launch.
The basic tenets of Lean Startup and the Start Small methodologies have been around for some time. In fact, the fundamental concepts come from some noteworthy intellectual progenitors. In 2009, this method of going into the future was termed “discovery driven growth” by Rita McGrath. Decades earlier in 1978, Henry Mintzberg termed this as “emergent strategy” as against “intended or deliberate strategy.” In the mid-1990s, software developers started using Agile Scrum (Start Small or emergent techniques) vs. the traditional Waterfall methodology (Big Bang or deliberate techniques) based on the work of Takeuchi and Nonaka in the mid-1980s. Most of the concepts, principles, and frameworks professed by today’s Lean Startup folk came out of this Agile Scrum software development.
Many entrepreneurship educators have been teaching, preaching, and practicing lean concepts for several decades now. All this Lean Startup stuff is pretty much de rigueur for them. Apart from the early dot-com crazy days when even the VCs lost their way for a few years, good startups have always started out “lean.” The only recent thinking and trend has been the toning down of the over-reliance on business plans. Again, this is about balancing deliberate vs. emergent strategies for going into the future, i.e., more action before analysis as against an over-reliance on analysis before action.