Market Validation Is the Only Validation

June 19, 2019 Focus area: Continuous Innovation
"A system learns by removing parts, via the principle that we know what is wrong with more clarity than what is right, and that knowledge grows by subtraction." ~ Taleb, N. N.

In this third part of my blog series on innovation practices that will enable continuous innovation, I discuss why market validation is the only validation. The previous posts can found here in case you missed them:

  1. Turn problems into actions
  2. Innovation requires a flowing system

Innovation validation is a process where an innovative idea or concept is transformed into something that is worthwhile bringing to the market or bringing into the experimentation phase. Therefore, a first hypothesis about the customer value of the idea needs to be tested in a real-life environment. When I say: "needs to be", I indeed mean you cannot go without it. As long as you haven’t tested your hypothesis in a real-life environment, you are still only guessing and assuming. If you were a decision maker would you prefer:

  1. A perfect product that nobody wants, or;
  2. A perfect market fit with a concept that requires optimization. 

Validation over verification

One of the key challenges in the innovation process is reducing uncertainty. Hence the key question to be answered is, especially in corporate innovation: is there a market for my innovation? Validation and verification are two ways to reduce uncertainty. Where validation aims to check whether the solution will meet the customer’s needs and answers the question: are we building the right innovation? Verification is concerned with whether the system is well-designed, of high quality or in other words: are we building the innovation right? Even though verification is an essential part of uncertainty reduction, it is only worthwhile after you really know whether there is a market for your idea. And again, would you prefer a perfect product that nobody wants or a something that the market wants but needs to be optimized? 

Ask, ask and ask again

In addition, if we break uncertainty reduction further down, one can say that the most effective way to reduce uncertainty is by continuously delivering fast consumable feedback. So, why not go out there and ask? Techstars program director Conrad Hollomon states that start-ups that participate in the Techstars Accelerator program are obliged to talk to at least 100 customers in order to validate market fit as soon as possible. Furthermore, it helps to reduce the psychological and emotional distance between the ideas and confidence of the innovator on the one hand, and the expectations and opinions of the market on the other hand.

Conclusion

So, start reducing uncertainty by formulating hypotheses and testing them repeatedly in a real-life environment. This knowledge will enable you to make the right go/no-go decision when needed, or as the Lean-Startup calls these moments: pivot or persevere. This data driven learning cycle will help to stop guessing and start knowing, which will help you to make the next step towards continuous innovation.

In my next blog I’ll explain the fourth practice: "Stimulate Interdisciplinarity". Meanwhile, if you want to know more about continuous innovation, visit the Continuous Innovation Framework website.

References

  • Ries, E. (2011). The lean startup: How today's entrepreneurs use continuous innovation to create radically successful businesses. Crown Books
  • Taleb, N. N. (2018). Skin in the game: Hidden asymmetries in daily life. Random House.
  • HarvardX (2019). Launching Breakthrough Innovations