R&D Software: Out-of-the-Box and into the Lab

When it comes to research and development (R&D), money talks. More specifically, cost will always play a role in the type of technologies used in the lab – and the way those technologies are used. As the media has often highlighted this year, R&D organizations are under pressure to reduce costs, increase speed to market and drive innovation. That will have a profound impact on the technology they choose to support their scientists in the lab.

In years past, the research giants built their own bespoke systems – the money was flowing and the budget was big. The technology was custom-built with a key principle in mind: their team did things differently. With hindsight, it’s clear that much of the work these companies do – at least on a basic level – is the same. This realization, coupled with ongoing cost pressures, are driving a change in fiscal dynamics. The change will see the perceived need for perfection give way to a more cost-conscious, measured approach. R&D organizations will increasingly turn to off-the-shelf systems that cater for their domain-, but offer less scope for customization.

These custom, expensive systems were also built with the assumption that the technology need only work internally. Fast forward a few years, and things couldn’t be more different – R&D is an increasingly collaborative, multi-stakeholder endeavour. That means the old approach is no longer fit for purpose. Systems must now integrate out-of-the-box. This is a significant step forwards, but is not brand new – we are seeing the same change take place in our home lives, with applications like Facebook readily integrating with other applications. ‘As a service’ will become the norm, in an environment where public APIs and data exchange play a key role. That is a big change from the custom, behind-the-firewall approach of the past.

A third adjustment is also taking place. With the cost factor now key and time of the essence, it will be more and more important for end users to self-manage the informatics infrastructure – not relying on IT to manage users and projects. To support this, user experience should be a central concern for those designing new R&D software. Intuitive systems that allow the scientists themselves to bring new team members on board, and set their security privileges accordingly, will no longer be a nice-to-have – they’ll be an operational necessity.

As the design and use of informatics tools adapts to the changing requirements of R&D organizations, we can expect these three factors to play a significant role. Organizations will strive for user-friendly systems, designed with scientists in mind, that work and integrate out-of-the-box – and we look forward to responding to that challenge.