Connecting the Dots: What Did You Learn from Connect?

Connecting the Dots: What Did You Learn from Connect?

What struck you most about this year’s IDBS Connect? Was it the news about the new collaboration, search and inventory management tools announced on the first day? Was it hearing customers in both the life sciences and industrial sectors share their experiences of going paperless?

With so much to take away from IDBS Connect 2015, it’s hard to narrow down our number-one take home message from this event. But here’s our attempt to get to the bottom of the key learnings.

For us, one of the most striking questions came out of Michael Elliott’s talk looking ahead to lab informatics in 2025; has informatics improved science? Over the last decade, the informatics industry has certainly delivered a range of products for managing scientific data but have they really delivered on the promise to boost innovation? It was a tough question and we found hints as to the answer in another talk, this time on day two by innovation guru Stephen Shapiro – have we been asking the wrong question? In essence, Stephen explained that the number one-barrier to innovation is misinterpreting the problem at hand and attempting to answer the wrong question.

Asking the right question

It’s an invitation to all research stakeholders to pause and think about whether we’ve defined the problem we want to solve correctly. What we’ve seen over the last decade is an explosion in the number of players in the research ecosystem. There’s been a boom in the number of small to mid-sized biotech and pharma organizations handling specialized sections of the research pipeline. Advances in biologics and precision medicine, to cite a further life sciences example, have also increased the volume and complexity of data. And as our own, CTO, Pete Murray highlighted, the amount of knowledge available to mankind is doubling every 12 to 13 months.

So where does this leave lab informatics? What is the problem that we need to answer? Hearing some of our customers describe scenarios where 80% of an analytics project is spent just gathering data highlights the limitations of paper-based working. The merits of replacing paper notebooks with their electronic counterparts are clear and demonstrable. But when we’re defining the innovation challenge we want to overcome, the one message that seemed to ring out the loudest from every talk and every breakout debate and every informal meeting was putting people first.

Adding the human touch

At the highest level, we all – whether it’s IDBS developing software or a research organization – need to remember that innovation comes from human beings. At the heart of the ecosystem of research majors and CROs, CMOs and outsourcing partners across every domain and industry are people. While integrating data from different sources in the research ecosystem can be seen as a technical challenge, we have to remember that it’s the people that have to make sense and interpret the information they’re given. If data isn’t made easy to manage and systems aren’t straightforward to use, then lab informatics has failed.

For lab informatics to meet the challenges of 2025, we must approach data management from more than just a technical point of view. We must remember first and foremost that our mission is to make researchers’ lives as simple as possible so that they can take the data our systems make available and use them to innovate.

On the flipside, we heard time and again that successful change management when going paperless is founded on listening to the voice of the user. Because it’s only when the end users see the benefits of change that they will embrace it and advocate for it. Again, people are the key.

Building tomorrow’s research

Our main take home from this year’s IDBS Connect is that the amount of data created by research is only going to grow and the business models underpinning innovation are only going to get more complex. It means that we’ll be focusing on championing the people behind every innovation story in every new product that we design and build and in all our training and support. And by building people-oriented solutions, it’ll give all research stakeholders the courage to go beyond automating the past and build a technical framework fit for the 2025 innovation ecosystem.

In essence, we’re carrying on our mission to help you bridge the gap between data and people.