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6 Myths About Lean Startups

Lean helps entrepreneurs refine those hunches, create actionable hypotheses to test, and record learning for future decisions, all the while targeting key success metrics for the business.
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I can't get enough of Lean Startups, opposite the stance that Michael Sharkey recently guest blogged about on Venture Beat.

In the following, I try to contend with a few misconceptions that I have experienced at Twin Engine Labs, as well as in the executions for many startups for which I've advised (full disclosure: my company helps startups execute, using lean concepts to do so).

Myth: The Lean Startup model encourages features vs. whole products

Ash Maurya has done some amazing work combining the core aspects of lean methodology along with what the Business Model Canvas accomplished, originally by Alex Osterwalder. The product he has created, LeanStack, is a growing list of tools to quickly allow entrepreneurs to capture their business model and focus on the correct priorities for the business.

What the Lean Startup methodology teaches us is that the dichotomy between "feature by feature" and "my product is a massive behemoth of everything the customer could possibly want" is a false one. Rather, it is about allowing the metrics that matter and the business goals associated with those metrics to drive the priority of development tasks. Customer development and build-measure-learn feedback loops are what determine how a product is developed in the Lean Startup methodology. Not the false dichotomy of features and complete products.

Myth: It prematurely burns out our team

Continuous innovation is here to stay. Leading development practices incorporate far more automated testing and more continuous integration today than ever, making it easier for engineering staff to maintain constant iterations.

But simply because we are now free to "fail fast" doesn't mean you test everything. Part of the art of starting up is identifying the key insights gained through customer development and the build-measure-learn feedback loop. Smart entrepreneurs use those insights to craft the next set of assumptions that come out of that learning.

By attaching actionable metrics to each experiment, decision making can be transparent and organic, allowing the organization as a whole to be more confident in their next initiatives because they are based in fact and tied to key success metrics the product and business as a whole should be focused on.

I contend that anything that is prematurely burning out a team is a matter of over-committing the team or spreading them thin. Experiments should always be designed with timing in mind, particularly with regard to the capacity of the team and the needs of the business. Managed well (just like any process), the pace is very sustainable and new ideas and innovations can be tested much more confidently.

Myth: These are hard products to love

The reasons that some of these products may not be considered deep (initially) is that the purpose of lean methodology is to hone and refine your value proposition to your customer (ie. find product-market fit) more quickly and with less risk. Why build a "deep" product if it does not present the correct solution? Once lean helps your company find product-market fit, then the company will more quickly discover ways to make your product "deeper" and provide more value.

No matter what methodology is used, there's no silver bullet to good execution. Lean doesn't assume anything about the team behind the product or their capabilities, it's simply a framework for bright entrepreneurs to gain real insight more quickly, in a manner that also happens to easily accommodate startups.

Myth: It devalues architecture

This is also a misinterpretation stemming from the idea that lean focuses on shipping the bare minimum required. Again, lean is a process for establishing actionable insights quickly. If your product support infrastructure requires a long build loop, then the full development cycle will naturally be longer also. But often, these decisions are prematurely made, and a company should not be building out an architecture prior to gaining customer validation. However, the lean startup method can be scaled to support products with robust architecture as proven by Palantir Technologies and Shutterstock.

What lean does force the company to make early choices about are exactly what architecture will be required to support the feature sets that are being shipped because of the customer validation. Because those features are tied to experiments and testable hypotheses, the architecture that is built is focused on providing the best experience possible to test those hypotheses.

Once problem-solution fit is obtained, that is the more appropriate time to begin planning an architecture to support the growing and anticipated needs for when you obtain product-market fit.

Myth: It leads to the wrong discussion with your investors

Having heard first hand accounts from my own company as well as many of my customers who are seeking funding, what investors want to see is a cadence of internal growth and learning within the founding team members. Real traction is found through validated or invalidated experiments that contribute to the key success metrics you are tracking. Differentiating from a startup that is really close to breakthrough from one that is not can't be done without the tracking and measuring that lean methodology bakes into the company.

This makes conversations much easier with investors, showing why a founder thinks the way they do about the direction they're taking with their product, and that they aren't simply going with their instincts alone. An experiment board should become a board of lessons learned, and should read like a novel to any investor wanting to get to know a startup better.

To me, this steers the conversations towards the right direction, not the wrong one. This is where companies which have real traction can easily differentiate from those that do not.

Myth: It distorts the Valley's hiring model in weird ways

The hiring model across the technology industry as a whole is hugely distorted because of the lack of trained talent in the industry (both from the private and public education sectors), and the incredibly high demand for good employees. The valley in particular has odd (acqui-)hiring practices that have nothing to do with lean, and more to do with an area and industry that is talent starved with capital to spare. Lean, agile, or any other methodology has very little to do with the systemic problems that cause the hiring practices mentioned in this myth.

Why Lean is often misunderstood

To be truly familiar with lean, as with all other skills, takes time, practice, and understanding. Observing from the outside is generally not enough. The great part about lean is that it is easy to try out, even internally inside an operational company.

Whether a company is starting from a blank slate or wants to tighten up its own initiatives that drive the business goals, I would encourage any founder or product manager to at least try creating a lean canvas. This will help in understanding some of the bedrock principles behind lean.

Lean is Good Business

The great part about all of this is that I've found that entrepreneurs generally think about these questions and answers intuitively anyway, and without any guidance, end up incrementally improving their products and value propositions. Lean helps entrepreneurs refine those hunches, create actionable hypotheses to test, and record learning for future decisions, all the while targeting key success metrics for the business. With lean, iterative improvements are grounded to key insights and objectives, and that just seems like good business to me.

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