There are three types of experiments that are common in the product management space — Proof of Concept, Prototype, and Minimum Viable Product (MVP).
I read it in one of my school textbooks but unfortunately, I don’t remember the name of the author. When searched online, I found several slightly modified versions of the above quote written by a handful of authors. Makes me wonder how much it was adored across the globe. Key point is— the idea of experimentation is old. What’s new is the art of applying it in the context of new disciplines as they emerge or evolve over time.
The advent of product management and its focus on the lean and agile methodologies during the last decade has brought experimentation to the forefront of the product innovation. About 95% of new products fail. In order to improve, product managers and similar archetypes need to champion the art of performing experiments early in the product life cycle. Obsession with experimentation is as important as empathy with the customer (highlighted below)
I believe in three keys to success — creativity, commitment, and collaboration. Experimentation originates from an act of creativity but equally important is persistence. I don’t have the statistics on how many experiments are failed. However, speaking from my own experience—while building a recent prototype, I iterated almost two hundred times before I got the approval to proceed. Patience is the virtue. We can be highly imaginative/creative but in the absence of commitment/persistence, success would look much far away. As we continue to be creative and perform experiments with strong commitment, our desire to succeed tends to increase. Here is a link that speaks to the power of persistence.
Finally, if you are both creative and committed, collaboration is the icing on the cake — makes it perfect!
There are three types of experiments that are common in the product management space — Proof of Concept, Prototype, and Minimum Viable Product (MVP). I have seen people using these types/terms interchangeably all the time. While often, we can get away by using any language but sometimes if we have a wider and distributed set of stakeholders, using incorrect language may create chaos in the end. This happens due to misalignment with the stakeholders on the expected output or the result. So, it’s important to understand the basic difference among all three experiment types.
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