You’re an open innovation analyst, so what do you actually do?
A question I get asked a lot is: ‘You’re an open innovation analyst, so what do you actually do?’ In this blog, I try to answer that question while avoiding the buzzwords as much as possible and share some secrets.
Logically, the role consists of analysing a specific part of a market. If you work at a bank like Rabobank, the focus will mainly be on food & agri, fintech, (Dutch) housing market, and the carbon market. Key activities can be divided into scouting, analysing, presenting insights, and talking to innovative companies. All this research helps our internal innovation teams learn from the market, so that they can accelerate their business proposition through adopting insights, understanding the competition, and partnering with the best parties. However, setting the main activities aside, I would like to highlight a few of the most important activities for this role.
Finding the right question
Finding the right company is like finding a needle in a haystack. I know, it’s cliché but it is what it is. Of all the 213.650.000 companies worldwide, how do you find the right partner for your new business? This search starts with a good ‘scope’ of the research question. For example, imagine you have an amazing idea for an innovative irrigation service for farmers. You decide to speed things up and partner with the most innovative player, since developing a whole new system of irrigation systems will take years to develop. How do you find that company? It all starts with a good research question and the aim is to be as specific as possible. The more specific the question, the more relevant parties we can find. Instead of using the research question ‘Finding companies with irrigation services for farmers‘, go for something like ‘Finding autonomous precision irrigation services for big farms (1000 acres and up) in the Midwest US‘. There are still lots of other questions to answer in this specific case but those usually will be covered during an intake meeting.
Becoming the Sherlock Holmes of open innovation
Once the research question has been scoped reasonably well, it is time to start the fun part: scouting! We collaborate with tech scouts from The Next Web and Unknown Group. Besides that, we also use our own databases such as CB insights and Innospot to find as many relevant parties as possible. The tech scouts use various databases and networks (on the ground in different countries) and they are also extremely good at using Google. Being good at Googling in this context means finding the most relevant parties for the business proposition of your innovation team. Over time we have developed this capability internally as well. Together with my colleague Koen de Leeuw, we have developed an excel worksheet template (I know it’s not sexy, but it works) that is made to find more parties in less time. Before working as an Open Innovation Analyst, I seriously underestimated the skill of being good and quick at using Google. There is so much information available if you know where to find it and how to interpret it. In some cases, almost the entire business model canvas of a certain business can be filled out with information found online.
Two scouting secrets: keywords & rabbit holes
So, how do you become good at Googling? A few of my best hacks to find more relevant companies are taking care of my ‘keywords’ and ‘going down rabbit holes’. In our case, the keywords are the search terms you put into Google. Start-ups and other innovative companies tend to name their service ‘slightly’ different than their peers. This means that in the case of our search for an innovative irrigation service partner the following keywords would be a good start: Irrigation services (literally Googling the most obvious stuff will feel stupid but give good results), irrigation management, irrigation as a service, irrigation systems etc. Try to dance around the initial topic to find which keywords bring up the most interesting results. If you already know one or two relevant parties, go to their websites and read what wording they use and ‘steal’ those keywords to find alternatives.
After finding the first few relevant parties you can start going down ‘rabbit holes’. This means you keep on clicking through interesting content that will link you to daughter companies, ventures, partners, clients, articles, blogs even podcasts, and YouTube. Did you find a case study mentioning an interesting collaboration with a third party that delivered an autonomous drone irrigation service? Then click through and read more about that company and its partners. While searching for companies, write down the ones you find relevant but also keep logging new keywords that come up during the search. For example, it is possible that instead of irrigation services, the industry calls it sprinkler system advice in our geography of interest. These are two of my favourite scouting hacks but there are of course tons more.
Turning it inside out and upside down
At this point, there should be a messy excel sheet full of roughly 30 seemingly random companies, URLs, and notes. This is the longlist and the aim is to go back to the initial briefing, look at what criteria are most relevant, revisit the companies and scope down to a top ten. Various criteria can help create a better overview of how companies in the longlist compare to each other if the data is publicly available. Criteria such as funding, number of FTEs, founding year, and number of clients are data points that can help say something about the maturity, scale, or traction of a company. Other criteria are also relevant to investigate such as the feature offer, type of technology, speed, pricing, and partnerships.
In our irrigation partner search, it would be interesting to know other specific requirements: how many acres they can spray per minute, whether a farmer can remotely operate the system or if the system is fully automated. Creating a small customized scoring mechanism will help create a comprehensive overview. Give the relevant criteria a score ranging from 1 to 3. For example, companies providing the irrigation service can be given a score for their technology. A score of 1 can represent a traditional system, a 2 represents an automated micro drip tubing system and a 3 represents drones that water the farms from the sky.
Then comes the time to present the results. Various types of overviews can be useful to transfer knowledge to the innovation team. Overviews such as maps, showing where the companies are based, matrices highlighting the differences between companies, and overviews of the top ten most relevant companies. But there are also a lot of small insights that you have picked up during the search itself. This can be a range of case studies highlighting interesting user behaviour or a couple of articles that all point towards a new trend or development. During this research, you’ve become a mini expert on the subject, so all these bits of information should be added to the deliverable. After transferring the insights to your innovation team, there are more steps to follow up on. It’s a continuous process of learning from what happens outside the bank. However, this wraps up the blog for now.
In short, the Open Innovation Analyst role consists of what you would expect, namely analysing a specific market. But there is a focus on learning from the outside world and passing the knowledge on to the innovation team. As partnering is a common practice in the open innovation domain, finding the right partner is a specialization on its own. Now that you have found a potential partner (or more), the real adventure starts. How to deal with that will be a topic in the future blogs from innovation colleagues. So stay tuned!