The Lean Startup toolbox is great for taking innovative products from idea to scale. However, within large companies, our innovative products are developed within a broader context. This talk explores how intrapreneurs can take innovation beyond sticky notes, creative ideation and running experiments to ensure that their work is aligned with corporate strategy. Such alignment can help avoid our innovation projects becoming ‘orphans’ with no company support for scaling. The notion of an innovation thesis to guide innovation with large companies will be presented along with examples and case studies.
In 2009 I was a research fellow at Stanford University. A time which I enjoyed greatly. I remember sitting in one of Steve Blanks early classes and being struck by a thunderbolt of inspiration. I knew right then, that somehow I wanted to be part of what was going on.
A few years later Eric published The Lean Startup, a book that spawned a moment. The Lean Startup gave us a great toolbox for taking innovative products from idea to scale. And at that time we were all convinced that startups owned the future, and if corporates wanted to keep up they had to start acting like startups!
And that created a lot of innovation theatre. The problem was that everytime people think of startups they imagine a group of four your hipsters changing the world. And so companies had to have that, plus the bean bags, whiteboards, sticky notes, standing table and canvases. It has not yet landed that startup are not the artefacts they use. Rather startups are a methods for creating new products under uncertainty. Startup aare a set of principles and practices that can be codified and adapted by any organization of any size.
And these principles outline a hierarchy of questions that every innovation team must answer. With some questions being preceding others in importance. Our value assumptions around making stuff people want, should be tested before our growth assumptions. We have to first crack the code on problem-solution fit, before we crack the code on product-market fit. This is simply because one doesn't happen without the other. If you are making stuff nobody wants then you are not going to get to product-market fit. At the heart of the process is this idea that startup teams can avoid the mistake of premature scaling by doing the right things at the right time.
And this what we are growing to understand. Large companies are not startups, nor should they strive to be. Instead, they can adopt startup methods and apply them in a way that is relevant to their context. And within large companies, our innovative products are developed within a broader context that includes core products that managed using traditional metrics like ROI. And this poses a challenge.
And so we have been working with corporations to think more deeply about how they can apply startup practices to how they make investment decisions in new ideas. What you see here is the build-measure-learn loop for making investment decisions. This is based on Dave McClure’s Moneyball for startups. The principle is that rather than invest a large amount of money as a one-time shot based on a business plan, we have found that it is better to engage in incremental investing. Invest a little bit, track and review the team’s progress, and then double-down on those ideas that are showing the most promise.
And this is connected to our hierarchy of questions. From our perspective, innovation accounting provides us with the criteria of what we mean by “showing promise”. This is not a flowery concept but a rigorous process that can be measured. So we invest a little to allow you to figure out the customer needs and jobs to be done. We invest some more to give you the runway to create the right solution. Double down with a larger amount for you to crack the code on on your business model and provide even more resources when you are ready to scale. At any point, we can iterate with small investments or stop failing project without investing too much.
And even after leadership understands The Startup Way and Innovation Accounting we still face challenges. Lets not forget why we do this, the ultimate goal is to have our innovations leap into main company and help the company achieve long term success and meets its strategic goals. This means we means we need scale. And this is a problem - really at the strategic level.
There are innovation leaders who believe that innovation is about letting a “thousand flowers bloom”. But a recent report by PWC shows that such ‘random acts of innovation’ do not produce great returns
At this point it is important to note that strategy is distinction from vision and tactics.
Vision - Where we want to go.
Strategy - a heuristic for taking decisions under uncertainty.
Tactics - Decision we make in the immediate moment, guided by strategy and with the available options.
Believe it or not, for a lot companies their work on innovation exist at the tactical level only - loads of random acts of innovation.
We believe all the innovation work happening in a company should be guided by an innovation thesis or strategic goal.. So we feel that companies need to analyse their portfolio, the business environment around them and the key trends that are going to impact their business. Then they need to create a theory (a point of view) about how we are going to use innovation respond. This innovation thesis becomes the lighthouse that guides our investment decision making, and what our teams ultimately end up working on. Whether it's in a lab or within the business, having this strategic guidance is great for alignment.
This is the process we are building in Pearson.
Budget allocation are done by a portfolio council.
This is SparNord Banks Innovation Thesis
But from a lean startup perspective, our innovation strategy in a thesis not a law. And we will test this thesis via our investment decisions, review what’s working and iterate on the thesis if we need to.
But from a lean startup perspective, our innovation strategy in a thesis not a law. And we will test this thesis via our investment decisions, review what’s working and iterate on the thesis if we need to.