Design Experience That Matters, Book Review: The Other Side of Innovation

We love Vijay Govindarajan and Chris Trimble’s Other Side of Innovation, specifically the second half of the book. For anyone who has ever resented being asked to write a business plan, Govindarajan and Trimble’s book will at last explain the profound difference between planning and prediction.

Consider that at the moment you decide to explore a new product, you will never be dumber about your customer, their needs and your opportunity. The big idea in Other Side of Innovation is how to manage product development as a “disciplined experiment.” Applying the scientific method to design thinking involves establishing a “hypothesis of record.” This tool helps the product manager answer their two most important questions: what are we spending money on, and why?

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When trying to figure out whether our new product is a good idea, to paraphrase David Hume, our confidence should be proportional to the evidence.
An example “cause and effect” diagram.  What are the steps necessary to take our product idea through to production?  Then, consider the assumptions built into that process.  What has to be true for steps A and B to lead to step C, and so on?
Given all of the assumptions we identified through the cause and effect diagram, consider a framework that weights assumptions according to our confidence (reasonably certain, educated guess, wild guess) and the consequences if the assumption proves false (minor problem, serious problem, catastrophe).
We might imagine a hierarchy of assumptions, the most dangerous ones being low confidence and high stakes (the top right box). 
At DtM, we use this framework to determine program priorities.  The first dollar we spent on product development must go towards emptying that top right bucket (low confidence, high risk).  We might increase our confidence by conducting user and market research, or by building a physical prototype, or by recruiting new partners with the necessary expertise onto the team.   If this approach allows us to falsify a critical assumption, hooray!  We haven’t wasted much time or money.

To build a hypothesis of record, the team must first create a “cause and effect” diagram, a simple flowchart of the steps necessary to reach the ultimate objective (in DtM’s case, saving millions of lives in poor countries). The team then identifies the most critical assumptions embedded in the plan, stated in a way that meets Karl Popper’s standard for “falsifiability.” The team then defines a set of experiments that will test those key assumptions as quickly and cheaply as possible. When an experiment proves a key assumption false, you know it’s time to update your hypothesis of record.

Every design firm brags about “failing as fast as possible.” Govindarajan and Trimble’s book explains how to do it with rigor. This approach has become the basis for all of DtM’s strategic planning. Check it out! And if you buy the book through the links in this email, Amazon will send part of the proceeds to DtM! [Other Side of Innovation]

Source: core77

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