At Mergeflow, we get asked this question a lot, particularly by our software platform customers. It is a very important question. After all, getting the most value out of our software platform requires a certain skill level on the part of the analyst using our software. Of course, this is true for any tool used by anyone to accomplish anything in any craft. For example, I may decide that I want to become a world-class radiologist. In order to achieve my goal, I could obtain a state-of-the-art MRI machine. But just getting the machine would only get me so far, of course. I would also need lots of hard-won skills and experience as well in order to “see” anything with my new fancy machine (not to mention that I should probably go to medical school). Some of these skills would probably require a certain type of talent or trait. Other skills could and would have to be acquired. This would require continuous access to and practice with my new MRI machine because skill comes with practice. Not just any practice, but what the psychologist Anders Ericsson in a seminal study called “deliberate practice”.
Let’s get back to our question, “What makes a good innovation intelligence analyst?”. Most people would probably agree that a useful proxy to this question would be to ask, “What do I need in order to become a good innovation intelligence analyst?”. Like with my radiologist example above, this question has a traits and a skills component.
What traits do I need in order to become a good innovation intelligence analyst?
Traits tend to be a lot harder to learn than skills. Many traits you either have, at least to some extent, or you don’t. For example, based on my observations of people doing innovation intelligence, it seems that those people who are familiar with but do not necessarily follow conventional ways of asking questions certainly have an edge over people who “always do things by the book”.
I find it difficult to pinpoint these required traits more exactly. But a few months ago I watched a 2008 TED talk by Charles Elachi, who at the time of the talk was head of the Jet Propulsion Laboratory. In his talk, Charles Elachi used the photograph I used as title image here. Point of the photograph was to illustrate what makes the typical JPL employee (hint: only one of the people in the photograph is a typical JPL employee…). I find this to be a perfect image for illustrating the required traits of an innovation intelligence analyst as well.
Now, let’s move on to the second component of our question, the skills component:
How can I learn innovation intelligence analyst skills?
Whenever I want to learn a new skill, I usually look for books, hands-on experts, and all kinds of online materials (papers, websites, tutorials, videos, interviews, forums, etc.). In my opinion, books, particularly those written by hands-on experts, are often a great start because they simply have more space for contextualization than do the usually shorter and more dispersed contents available online. However, this is situation- and goal-dependent, and my preferences may vary accordingly.
Some years back, when I first started looking for innovation intelligence books, I could not find any. So I thought about adjacent subject areas where I might find more material. The most immediate adjacent area that came to mind was intelligence analysis as it is practiced in government agencies (not to mention that these organizations reportedly have innovation or technology intelligence capabilities as well). Just like innovation intelligence analysts, government intelligence analysts also need to address questions that cannot be addressed directly (directly as in “OK, [insert-name-of-your-favorite-personal-assistant-here], what is the population size of New York City?”). Instead, they need to find much more creative, indirect ways to address their questions if they want any kind of useful answer. Also, just like innovation intelligence analysts, government intelligence analysts have to keep track of many fast-paced and disparate sources of information; they deal in probabilities rather than certainties; and they also somehow need to get their message across to decision makers if they want their work to have an impact.
So I was happy when I found that in fact there are some books on government intelligence analysis, written by hands-on experts. Here are my personal favorites so far, along with very brief comments:
Fingar, T (2011). Reducing Uncertainty.
What I find particularly interesting about this book is its emphasis on the purpose of intelligence, i.e. how to have an impact on decisions, how this may be achieved — and also how things can go wrong, even if intentions are good. All of this from a world class and hands-on expert, Thomas Fingar.
Heuer, RJ & Pherson, RH (2014). Structured Analytic Techniques for Intelligence Analysis.
This is a real workbook, in the sense that you can use it for and during work. It describes a range of techniques for different circumstances, as well as those techniques’ strengths and weaknesses. The book’s spiral binding keeps it open at any page you want, which makes it convenient to use it as a reference on your desk (no, I did not get the Kindle version of this book).
I learned a lot from these books, and still do when I re-read them every once in a while (I highly recommend re-reading; the new things you learn between re-reads make you discover new things with each re-read). Even though both books are more geared toward geopolitical than toward technology or innovation analysis, I can transfer many things to my own domain. Having to make this knowledge transfer is probably good. It keeps me from treating the books as mere “instruction manuals”, which, given the domain, would be counterproductive (cf. the “traits” section above — real innovation intelligence analysts do not always do things by the book, even though, or precisely because, they know the book).
What else is there?
At Mergeflow, we regularly train customers in innovation intelligence. Many strategies we use and teach there are rather specific to our software platform. But just like the books mentioned above, there are many other materials that are platform agnostic. For example, I often read articles etc. coming out of the RAND Corporation. In particular, I recommend keeping track of their Emerging Technologies and also their Science, Technology, and Innovation Policy publications. Also from RAND, there is a great talk that Steven Popper gave at Tecnológico de Monterrey. You can watch Steven Popper’s talk on YouTube.
None of these materials provide cookbook instructions. But they provide very interesting examples and new perspectives. And making the transfer from these perspectives to one’s own questions, discovering new angles, and questioning your own assumptions are all part of why this is an essentially human and fun activity, right?