Innovation — but why, and how

Innovation is such a positive word. We can slap it onto almost anything, and make it look good. There is a magical mist around innovation and how it comes into being. We observe bright minds churning out good ideas that become disruptions in the market. We try to be as cool coming up with crazy ideas that we cram into our products. Very few of these become disruptions, if they solve any real world problems at all.

As Peter Drucker wrote in Innovation and entrepreneurship: “Innovation is work”. There is nothing magical about it. Innovation requires investment and hard work, coupled with the ability to identify opportunities. If you are a successful company with a few products on the market, making good money, why should you invest in innovation? After all, research and innovation work is never guaranteed to pay off. Would it not make more sense to invest in new features in existing products, fighting with competitors over market share and making customers happy?

Why?

I believe there has to be a balance. Too much investment in innovation and you end up chasing the next big thing without delivering value, now. Zero investment in innovation is a sure path to becoming extinct. Every organization has to build their muscles to deal with the unknown. If you are doing something in the complex domain, the only way to navigate is to experiment and learn[*]. When you are on a mission to delivering value, you need to find out the best way to consistently deliver that value. We need to continuously learn because the world is continuously changing. Eventually the market you act in will be disrupted. Without the ability to learn your products will become irrelevant to customers as you no longer are delivering value and solving their problems.

How?

One of the cornerstones of my vision in creating an innovative organisation is internal entrepreneurship. A system of lean startups, run inside the enterprise, inspired by Eric Ries The Startup Way.

To make this possible I believe we first need to build a team of people that are comfortable in the complex world. Train people to do small experiments, measure and then rerun the experiment. Apply scientific methods of creating a hypothesis, trying to prove it through experiments and learn. Validating assumptions as we experiment and build upon existing research on the topic.

This team will then be able to help a startup from the line organization by assisting them in methods, tools and mindset. With all the data such a startup can gather, it should be easy for management to make decisions whether to keep funding, incorporate into existing products or kill the startup. We need to get addicted to data collection and become fully data driven.

It is important to remember that the data for a startup will be completely different than the data for a new feature created by a line organisation. We need to be talking about what Ries calls Innovation accounting. A good example of this is Dave McClure’s Pirate metrics (AARRR — Acquisition, Activation, Retention, Referrals, Revenue). What and how we actually measure is very context dependent, but the decision we make must be data driven. The success of an experiment is judged by whether it delivers value or not and whether we have learnt more by running the experiment

In the utopia I envision we can eventually have the whole organization working this way. Spinning up new startups when we want to try an idea, be addicted to the measurement and giving management a transparent way to make decisions whether to keep funding or shut down. A startup in this context is an autonomous team that takes full responsibility for what they are building, from idea to created value and outcome.

If we can do this well people that work in roles like product management and product owners can transition into doing more valuable things than deciding on and prioritizing work. If we really get good at running small, cheap experiments, measure and learn, we do not need anyone to tell us what to do. Instead we get addicted to always trying out new ideas and quickly shutting initiatives down if they are not adding value. People that know the product and market well can help us deciding on larger visions, identifying disruptions and supporting innovation.

The path to fulfilling a vision always has a first step. I believe that is to create a team addicted to discovering, learning and making data driven decisions. They can then invite and involve others, as well as giving management the tools needed to make decisions around future projects. This team will start building the organisations ability to experiment, learn and adjust, focusing on delivering value. Just as with any other change I believe we have to start small, try things out and adapt. This is precisely what I am setting out to do.