IDBS Blog | 18th October 2011
R&D Informatics – Are you ready for 2012?
In July 2011 we worked with Scientific Computing, R&D, and Drug Discovery & Developmentmagazines to survey almost 700 R&D professionals.
The survey aimed to uncover the top challenges R&D centric organizations face in the quest for R&D collaboration, IP protection, and effective data management. It also explored the key initiatives planned to support R&D Collaboration and Data Management in the coming year.
EXPLORING THE SURVEY FINDINGS
88% of R&D organizations lack adequate systems or practices to automatically collect data for reporting, analysis and decision making. An essential part of collaboration is how effectively individuals and organizations share data. The survey found that today’s researchers still rely on manual processes and non-scientific applications, such as Microsoft Office applications, for report production. The task is particularly difficult in the Defense & Aerospace, Manufacturing & Engineering, Energy & Utility, and Academia and Government sectors.
Comment: The R&D world is moving to a data centric environment rather than a document centric environment. Report writing is on average taking 25% of researchers’ time. It’s not about reporting it is about developing insights and understanding from other’s data, enabling everyone to be more productive.
As Jay Galeota, SVP Strategy & Business Development, Global Human Health, Merck explains in a recent Ernst & Young report*: “The most important thing is what you can actually do with the data. It’s one thing to have interesting information, but it’s the insights that are important to guide smarter, better decisions…”
6 out of 10 respondents relied on manual compiling and searching of data. The survey explored how researchers shared data and found that 60% are unable to compile relevant R&D data without manually searching through documents and reports. This results in a static document-centric view of the data.
Comment: This results in a document rather than data centric approach. Each respondent is both a consumer and generator of data – the collaboration challenge is as much about internal person-to-person collaboration, as external business-to-business sharing of data. It also results in significant time lost/taken away from actual research because people are busy searching through documents for info. For streamlined research, people need to put hands on relevant data immediately, not spend time recreating it and certainly not spend hours looking for it.
57% R&D organizations are relying on in-house systems to manage R&D data. Survey respondents across all sectors are predominantly using legacy in-house, home grown/built, solutions.
Comment: We know that change occurs in R&D organizations on a 12 month basis, but it is fair to say that few in-house systems can effectively evolve or be upgraded in synch with this timeframe. This causes an ongoing burden to businesses and their IT support systems. In talking with industry insiders we hear that this is leaving an unsustainable graveyard of systems. Where software development in-house does have a role is in configuring best in class systems to confer a competitive advantage. Does any R&D organization have building software as part of their vision?
As Chris Thoen, MD Global Innovation Office, Proctor & Gamble commented*: “Only do what only you can do.”
Less than 25% of responding organizations have deployed foundation technologies such as ELNs, LIMS, KM, and PLM systems. This leads to a R&D data ecosystem – data flowing from idea to product – that is fragmented and siloed. The survey reflects the proliferation of third party process applications.
Comment: Many organizations are using a combination of multiple data and knowledge management applications across their business. This makes management of IP/data from early research through to commercialization challenging. And while point solutions have been implemented to solve particular issues, there is a resulting duplication within the IT landscape (e.g. data analysis and reporting tools). In many organizations, multiple similar category products are used by different parts of the enterprise.The result is that there is no end to end solution for data management that integrates into existing data silos
Watch out for the next blog post in this series – I will explore what the R&D Collaboration survey tells us about IT complexity, collaboration & intellectual property protection.
* Source: Progressions: Building Pharma 3.0 – Global Pharmaceutical; Industry Report 2011 from Ernst & Young.