In the build-up to our Innovation in Practice 2018 conference, we interviewed Chris Lees, from Serendipity29, one of the speakers at the conference.
What will you be talking about at the conference?
I’m going to be talking about the past, present and future of data. To me that’s about the journey organisations take on their data journey. As they take that journey, there are opportunities for data and data standards to impact on their ability to innovate.
What’s your experience around innovation?
When I worked at Zurich Insurance, I was part of a global task force looking at how you can encourage innovation. One takeaway from that experience was how people struggle with the idea that you can simply make people innovate. What I believe is that all you can do is to provide the conditions where innovation can take place.
Can you explain what you mean by that?
If you have a seed and you want it to grow into something, then you have to provide it with soil, water and sunlight, and nutrition, all the things a seed needs to germinate and grow. Then, who knows, you might grow a great oak tree out of that one seed. Or the seed might grow in completely unexpected ways. What’s critical is that you have the right conditions in place so your seeds have the best opportunity to grow.
What does this mean with regards to data?
There’s a couple of issues here. First, it’s around having the ability to interpret data. This has never really been valued before in the workforce. All too often people have made dumb decisions on data that they’ve not had the ability to interpret.
The second issue, though, and this is potentially worse to your business, is that you might be very skilful in interpreting data, but the data you’re using is very low quality. You might be great at drawing inferences from the data, but if the data is wrong, then you’re screwed. This is where data standards play the biggest role, because they allow us to be clear about what we mean and be confident that the data we’re using is correct or fit for purpose.
What does this mean in practice?
Take the example of office occupancy: I conducted a study about office occupancy with a colleague from Cambridge University. People talk about occupancy as if it’s a standardised metric. They’ll say things like, “we’ve got 60% office occupancy” and expect to be able to compare that with a competitor. Our research showed that even with just the mainstream terms used, there are over 60 different ways of defining occupancy. So to state that your office occupancy is 60% becomes entirely meaningless and misleading. Once you have data standards, you can then compare like with like.
A lot of the time, we tend to interpret data relatively superficially or perhaps worse of all, we look at the data after the fact: we make a decision and then look for the data that supports that decision. Having data standards means you can make business decisions based on data that everyone understands. And that, in turn, helps to enable or catalyse innovation, as I’ll explain in more detail at the conference!
Any thoughts about the conference itself?
I’m really excited about it. What’s always great at these conferences is the range of people you meet. There will be those people who are at the heart of innovation, who are engaged in innovative projects, creating cultures where innovation thrives. Hearing from them is always energising.
And then there will be those people who are not quite there yet. They know that innovation is a good thing, but they don’t understand how to get there. Talking with them often stimulates new and surprising ways of thinking. It’s in the unexpected conversations that take place at the conference that some of the most enlightening discussions happen.
There’s a word for it: serendipity. It’s one of my favourite words, and the name of my business, Serendipity29, and one of the wonderful things I love about innovation.