VALUE VS. WASTE

 

In other words, which of our efforts are value-creating and which are wasteful? This question is at the heart of the lean manufacturing revolution; it is the first question any lean manufacturing adherent is trained to ask. Learning to see waste and then systematically eliminate it has allowed lean companies such as Toyota to dominate entire industries. In the world of software, the agile development methodologies I had practiced until that time had their origins in lean thinking. They were designed to eliminate waste too.

Yet those methods had led me down a road in which the majority of my team’s efforts were wasted. Why?

The answer came to me slowly over the subsequent years. Lean thinking defines value as providing benefit to the customer; anything else is waste. In a manufacturing business, customers don’t care how the product is assembled, only that it works correctly. But in a startup, who the customer is and what the customer might find valuable are unknown, part of the very uncertainty that is an essential part of the definition of a startup. I realized that as a startup, we needed a new definition of value. The real progress we had made at IMVU was what we had learned over those first months about what creates value for customers.

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Anything we had done during those months that did not contribute to our learning was a form of waste. Would it have been possible to learn the same things with less effort? Clearly, the answer is yes.

For one thing, think of all the debate and prioritization of effort that went into features that customers would never discover. If we had shipped sooner, we could have avoided that waste. Also consider all the waste caused by our incorrect strategic assumptions. I had built interoperability for more than a dozen different IM clients and networks. Was this really necessary to test our assumptions? Could we have gotten the same feedback from our customers with half as many networks? With only three? With only one? Since the customers of all IM networks found our product equally unattractive, the level of learning would have been the same, but our effort would have been dramatically less.

Here’s the thought that kept me up nights: did we have to support any networks at all? Is it possible that we could have discovered how flawed our assumptions were without building anything? For example, what if we simply had offered customers the opportunity to download the product from us solely on the basis of its proposed features before building anything? Remember, almost no customers were willing to use our original product, so we wouldn’t have had to do much apologizing when we failed to deliver. (Note that this is different from asking customers what they want. Most of the time customers don’t know what they want in advance.) We could have conducted an experiment, offering customers the chance to try something and then measuring their behavior.

Such thought experiments were extremely disturbing to me because they undermined my job description. As the head of product development, I thought my job was to ensure the timely delivery of high-quality products and features. But if many of those features were a waste of time, what should I be doing instead? How could we avoid this waste?

I’ve come to believe that learning is the essential unit of progress for startups. The effort that is not absolutely necessary for learning what customers want can be eliminated. I call this validated learning because it is always demonstrated by positive improvements in the startup’s core metrics. As we’ve seen, it’s easy to kid yourself about what you think customers want. It’s also easy to learn things that are completely irrelevant. Thus, validated learning is backed up by empirical data collected from real customers.