Since publishing my last essay critiquing the representation of startups and innovation as an experiment, I have been racking my brain thinking of what the equivalent of innovation within the sciences might be. This representation would have to be large enough in scope and impact to represent the unique contribution that a truly successful innovation makes to the lives of people and society in general. Then it suddenly struck me:

                                                    Innovating is actually a lot like doing PhD thesis or dissertation.

This may not be as catchy as calling startups and innovations experiments, but the similarities are so strong that it’s strangely uncanny. It also provides a way to fully align innovation management  with the scientific method. Below I outline four core similarities to illustrate my point:

1.  A Path for Searching
Here an interesting etymology. The term “thesis” comes from the Greek word meaning “study”, and the term “dissertation” comes from the Latin word meaning “path” (Wikipedia, 2012). The word “study” is consistent with Steve Blank’s proposition that startups should be designed to “search” for a sustainable business model through customer development and customer discovery. Steve’s proposition is simply that the job of innovation teams is to “study” the market and discover two main things: 1) What customers want and; 2) A profitable business model for delivering value to customers. In science it is the same; scientific study is really just a “search” to understand how the world “really” works.

Within science there are clear guidelines of what constitutes a good “path” for researchers to follow when conducting their thesis (i.e. the scientific method). Within innovation Eric Ries has developed a similarly powerful concept. The build-measure-learn loop provides a clear “path” for innovators to take as they conduct their “search” for a sustainable business model. The power of the build-measure-learn process is that it acknowledges that you will go through various iterations of your initial ideas before you find the “truth”. In science, it is the same. There is an acknowledgement that during your thesis, you will go through various permutations and conduct several studies until you reach your destination.

2. Research Project
The power of the thesis metaphor lies in the idea that innovation can actually be viewed as a research project. Rather than a business plan, the innovator’s idea is a research proposal. The problem with the business plan is that it orients innovator teams towards execution because it is, after all, a ‘plan’. And we love it when a good ‘plan’ comes together. The term ‘research proposal’ is much more tentative. It is just a proposal; meaning ‘we could be wrong’. This orients innovation teams toward learning whether they are on the right path. This is exactly parallel to the orientation that scientists take at the beginning of any new research project.

3. Research Team
Within the thesis metaphor, innovation teams can start to view themselves as research teams, rather than teams set up to deliver a product. A few months ago I had an argument with the lead engineer of a startup who viewed his role as being; “to build the best technology possible”. So he spends all his time reading software books and writing code. What he didn’t realise is that technology cannot be “the best technology possible” in a vacuum. The question for an innovation team to answer is; the best technology for who? The ‘who’ in this equation is defined by two factors; people who want the technology; and are willing to pay enough for the technology such that the firm can build a profitable business. So the job of the lead engineer in an innovation team is not to just build excellent technology. They are part of a research team, and their main job is to operationalize their innovation hypotheses as minimum viable products designed to maximise learning.

4.  A Significant Contribution
In science, a thesis is considered successful when the researcher makes a new and significant contribution to knowledge. For innovation teams, there are similar pressures. An innovative product is successful when the team has discovered a profitable, sustainable and scalable business model. In a PhD thesis, you have to convince may be five to ten people, who constitute the toughest audience on earth, of the value of your work, before you can graduate. But customers are equally tough as an audience. In a democracy, you can’t make customer give you their money; they have to part with it voluntarily. So unless you are creating real value in their lives and solving real problems for them, your business is doomed to fail. So upon achieving product-market fit, an innovative product graduates.  

Innovation as a Managerial Science
Just like calling startups experiments, the thesis metaphor emphasises learning. The difference is that an experiment sounds like a single event, whereas it’s implicit in the term thesis that you are involved in a process that involves several research studies and iterations.  What I also like about the thesis metaphor is that it opens up innovation teams to learn more about the whole tool box of scientific methods that are available to them as they develop their products. As I noted in my earlier post, the scientific method is not just experimentation. There are several other methods including surveys, interviews, customer observations, user testing and case studies. The thesis approach fully aligns innovation with the scientific method and prepares ground for the development of a managerial science that can be taught as a learnable and repeatable process to innovation teams; just like scientists have been doing with PhD students for centuries.