1. Challenge and selection: Describe your challenge, including all relevant

information.

I work for a municipality in the Netherlands. Like many cities in the world, the  municipality is trying to develop to a smart city (we prefer to call it smart  society because it is all about the people and businesses and not about  techniques)). A few years ago, I was working on a project called “smart  lighting”. Basically, this project was about upgrading our public lighting system  to a smart and interconnected lighting grid which serves as a carrier for  innovative services. At a certain stage of the project we came across questions  on ownership of data processed by the sensors of the public smart light grid.  Should we treat it as open data that belongs to the public or as proprietary data  that only belongs to the private company? The private company we talked with  experienced a lot of uncertainty when data should be treated as open data. They  thought that this would have a negative impact on their business model, which  was based on selling of data. At some stage of the project we had endless  discussions on legal aspects of ownership of data. This led to a serious deadlock  of the project. We decided to take a step back and look at the vision on open  data and open innovation. We decided to “re-scope” (test) this vision: which  beliefs did we have to be tested? Where are our blind spots? I choose the method  of storytelling for this re-scoping of the project.

2. Application: Describe how you applied the tool you selected to your challenge

(e.g., what you did and how the tool was applied effectively or ineffectively).

We decided not only to involve people who were directly involved in the  project. We also invited outsiders. The audience I had to speak to was very  broad: there were business developers, light architects, lawyers, policymakers  and financial experts. I decided that if I wanted to create an impact I should  present a real-life case which really impressed me. I started by putting the next  question to the table “Who owns the data?” Then I presented some hard facts  on the growth of data. I asked the audience, how many times you should fold a  piece of paper with a thickness of 2 cm’s to bridge the distance to the moon? I  did this to express that tremendous growth of data with figures you can’t  imagine. There is an abundance of data and it is ubiquitous like air (and nobody  asks the question: “who owns the air?”). Then I presented this real-life story. It  is about a girl who, at the age of 17, was confronted with breast cancer in her  family. The diagnosis of breast cancer can be very painful and sometimes even  inaccurate. This 17-year-old girl just finished classes on coding (writing  computer algorithms). She decided to write an algorithm that could detect  breast cancer. She used data on cellular characteristics from the internet and  research institutions (open data). She managed to write a prototype that was  really powerful and promising. It turned out that her algorithm was pretty

accurate when it came to predicting breast cancer. She now studies at a  university where she is perfecting this algorithm. I then asked the audience  what they think would have happened if the data feeding her algorithm was  monopolized by a few research institutions or companies. And I asked the  audience the question on what level the real value was added: at the level of  data or at the level of the intellectual capital of this 17-years old girl? I then I  answered the question on ownership of data: this question is not relevant: the  value of data is in the flow not in the source!”

3. Insight: Describe the insight you gained from applying the tool you selected to

your challenge (e.g., how an insight affected your thinking about the challenge  and about design thinking more broadly).

The most important insight was that storytelling led to a meaningful discussion  on possible business cases on open data. We decided not to ask the “boring”  legal question on ownership of data anymore. Another insight I got is that, like  Einstein said, a problem can’t be solved in the context in which it arose. We  therefore took the problem out of its context and asked outsiders to help us  unlocking the deadlock, by re-scoping (testing) our vision on data (using the  story).

4. Approach: Describe what you might do differently next time -- applying the

same tool you selected or a different one -- and the reason(s) why.

The first thing I would do different is obvious: focus on aligning mutual  interests. Telling a meaningful story can be helpful by defining problem field  (extensive legal discussions on ownership of data) and solution field (finding  new business cases). In our case we came in the end to the conclusion that  problem and solution were actually interconnected. We could have saved  ourselves time if we recognized this at an earlier stage of the project.

Franz Richter, January 21, 2018

