For research and development (R&D) decision-makers, the ‘lab of the future’ invokes images of huge cost and resources diverted to new and complex systems. Some cite automation and AI as harbingers of the futuristic lab although, fundamentally, these will support scientists — not replace them. Others see mobility as the key issue, but this is not a panacea and, instead, should form part of a multi-platform approach.

At a recent event, I challenged the audience to think about what this futuristic vision means to them. A universal definition is yet to emerge. However, we can agree it is not about finding a use for technology. Instead, it is about better serving key business drivers through operational changes that are augmented by technology. This has wide-ranging implications across the organization’s infrastructure, processes, people and business models.

As this ‘lab of the future’ becomes more realistic, teams will increasingly look to establish ‘best practice.’ It is vital that this is driven by striving to achieve the business’ key goals, not by empty futurism. After all, R&D teams are under increasing pressure to ramp up innovation, cut operational costs and increase speed to market.

With those drivers in mind, forward-thinking organizations will shape their strategy around three key areas:

1. Ergonomics: physical layout is critical to productivity in the lab. This is about using the right tools to solve small problems — and good informatics systems should support whatever application interface is best-suited to the job. These can be further augmented by use of location and hardware beacons — meaning the software knows where you are and what’s nearby.
2. Automation: mapping out existing processes, identifying bottlenecks, and moving towards a paperless approach. The importance of R&D teams having one searchable, accessible, single source of knowledge cannot be overstated. This is the best-case example of automation — rather than simply automating the past process which is, typically, on paper. Taking this one step further, you can use automated systems to conduct laborious tasks. This is not new, but the cost and availability of robotic technology is dropping, making it more amenable to simple tasks.
3. Virtualization: outsourcing is increasingly prominent among global R&D companies. As large R&D organizations shift towards becoming research hubs and the guardians of intellectual property, they must be able to support numerous teams and data streams. Technology will be intrinsically linked with the concept of ‘working together’ in an increasingly virtual and globally distributed manner.

While the lab is changing, the world around it is changing even faster. In fact, it’s likely that the ‘lab of the future’ will be rooted in the consumer technology of today. We have seen first-hand, when designing the latest iteration of E-WorkBook, that consumer habits and expectations are increasingly influencing the behavior of researchers in the lab. As the students of today become the scientists and R&D leaders of tomorrow, ‘social’ features in lab software, such as the ability to comment and discuss others’ findings, will grow in prominence. This will drive acceptance and uptake of new technologies among R&D organizations.

R&D leaders must focus on the continuous improvement of processes to meet business goals rather than technology for technology sake. A strategy shaped around ergonomics, automation and virtualization, could make elements of the R&D lab of the future a reality today.

Paul Denny-Gouldson is VP of Strategic Solutions at IDBS. He may be reached at editor@ScientificComputing.com.