Ditch the Lean Startup Methodology

Have you ever heard of boring startups?

Eric Ries’s The Lean Startup has become the jewel in the crown of many entreprises.

Countless startups swear by this methodology. Creative and passionate entrepreneurs who like to think out of the box do not quite like application of the very approach though. It is time that entrepreneurs question the usefulness of the methodology and give it a critical scrutiny.

The Lean Startup is rooted in the conception that startups should opt for a flexible approach in the phase of product development. It is an approach that rests upon the acceleration of the product creation and delivery process.

“Startup success can be engineered by following the process, which means it can be learned, which means it can be taught.” — Eric Ries

The continuous testing of a vision seems to be the basic tenet of The Lean Startup approach. According to the very methodology, startups should use the so-called “validated learning” as well as insist on getting customer feedback regularly and frequently. In the sense that the feedback is going to help in the shaping of the product according to the customers’ needs and perceptions.

Iterations and experiments are crucial components in the adoption of this approach, as they are going to help decipher the purpose of what needs to be built and what problem needs to be solved.

The build-measure-learn-feedback loop

The Lean Startup is grounded in the build-measure-learn-feedback loop. That is, the building should be minimal. A minimum viable product (MVP) is all that a startup should start with. After that, the fine-tuning comes in, and it manifests itself through two main components — measurement and learning.

Driven by the right actionable metrics, the measure-and-learn procedure should inform about the solidity of the business model. If through the question-answer and measure-learn process, the clarity about the business model is not gained or something went wrong in the process, the company should either choose to pivot or to test a different hypothesis about the product — in an attempt to correct the strategy adopted.

The following points question the validity of The Lean Startup and doubt its universal application:

MVP — ambiguous and fuzzy notion

The concept of minimum viable product (MVP) seems to lack concreteness and foundation. The idea surrounding the MVP does not lend itself to any concrete understanding. What are the criteria that can make of product a minimally-viable one?

To be able to release a product with basic features and functionalities in a timely manner presupposes that the company knows what the “minimum” to be delivered is or should be. This dilemma still haunts many startups, especially that they are trying to stand out from their competitors.

The fact that minimal products need to be released to early customers or users as soon as possible might backfire. Falling short of satisfying customers’ expectations through the MVP can lead to their disappointment about the early version of the product, which might make them lose interest in what’s coming next. In this case, disappointed customers might not guarantee to give constructive feedback for future development.

The idea of developing a product with “enough features” has to be scrutinized thoroughly beforehand. The “enough features” have to be studied from qualitative and quantitative angles, so that the product does not end up being a fragment or lacking necessary functionalities.

The wow effect matters — User Experience

The features chosen to make up the MVP parts have to make sense to the user. Customers do not really care if you are testing a hypothesis and might not know that they are presented with an MVP. What they care about is what they can accomplish with what you have produced.

It is mandatory that, whatever features you select for your MVP, you make sure to provide your early customers with the right functionalities that allow them to perform a task correctly.

Peeling off the core functionalities of a product does not make of it an MVP; it strips it of its main job, which is not something users would love to welcome. Hence, the nice-to-have features should be distinguished from the core ones.

An MVP has to offer a complete solution — one that satisfies users, delights them, and triggers their interest in consuming more of it. Your MVP should be useful and good enough to gain the loyalty of your early customers and excite them to know more about the next version of the product. Chances are only when the early clients are happy could you gain their loyalty and collaboration in making the product better.

The risk of over-fitting — customers’ feedback

To which degree should startups rely on their early customers’ feedback on the released MVP?

Many startups are driving towards failure through focusing on only one segment of clients, if not one client. By focusing on the feedback of one small number of early customers, implementing their suggestions, and tuning the engine of your product according to their needs and preferences, you are indeed excluding the real market picture mirrored by all the segments — early adopters, early majority, and late majority.

That being said, The Lean Startup places a disproportionate value on customers’ feedback. Early adopters’ feedback seems to play a central role in the product development.

Early customers’s feedback cannot govern the decisions about the next version and features of your product simply because the early adopters’ limited number does not represent the real picture of your potential users.

Therefore, Eric Ries’s proposed approach limits the importance of users’ feedback to the early adopters and the initial stage of the product development, leaving startuppers confused on whether or not to implement their early customers’ ideas and suggestions. Falling into the trap of model over-fitting might be the undesired consequence of blindly applying the build-measure-learn feedback loop.

“Overfitting is a modeling error that occurs when a function is too closely fit to a limited set of data points. Overfitting the model generally takes the form of making an overly complex model to explain idiosyncrasies in the data under study.” — Investopedia

The Lean Startup could inform your decision making and team growth. However, at some point, businesses have to choose whether to walk the path of creativity and passion or to stick to a boring and shy fashion of improvement. Startups need to throw caution to the wind. Skating on thin ice can be exciting!

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