Tag Archives: data

What do my kids know about collaboration that you don’t?

4 Jan

Collaboration is everywhere these days–especially within the pharma industry. But getting it to work well relies on proper planning and co-operation that spans disciplines to allow better use of, and access to, data.

A while ago we were planning a family trip to an adventure park. However, no one was going anywhere until my two boys had tidied their rooms! Faced with this herculean challenge I was impressed to see the planning that went into the collaboration that would achieve the task. My eldest quickly realized that he could reach high shelves more easily than his brother. While my youngest used the fact the he could crawl under the beds faster to great effect. That preparation helped get the job done more efficiently and successfully.

What’s more, they had worked out exactly what they needed to achieve and had evaluated their individual talents to get the job done fast and well. Once done they were more than happy to gauge their success by sharing their results and then receiving feedback. In turn it brought them a reward in the form of a great family day out.

That’s what I call successful collaboration. And dare I say that the life science industry could learn a lot from my two young ones.

True, the days of going it alone are, thankfully, behind us. Organizations have finally learned to play to their strengths and look outside for specialists with the skills they don’t have. The reason is simple–the job gets done faster with costs firmly under control, all of which leads to far better returns for your investment. What we now have to get past is a fear of using and sharing data with ‘the competition’. Keeping data hidden simply hinders collaboration.

The social media model makes it easy to share the lifeblood of collaboration: facts, information and –vitally – ideas. Adopting that approach means that the sheer number of people who can contribute (once the appropriate levels of interaction have been defined and put in place) can result in conversations that would never have normally taken place.

Virtual interaction also speeds up the process. Thanks to electronic laboratory notebooks, for example, paper becomes a thing of the past, as do transcription errors and misinterpretation. IP can be simply protected at the touch of a button. The right application can then select the correct data and analyze it with complete traceability of input from all parties to make reporting simpler than ever. All of which speeds up informed decision-making, leading to innovation.

Now I’m not saying that internal and external collaboration has suddenly become child’s play. It will doubtless require a shift in the collective mind-set of R&D teams. But if you are willing to share your data and analysis openly so that your findings can be assessed, and if the knowledge you have generated can be easily retrieved, true innovations will get to market faster and more cost effectively.

My young lads have already shown how open collaboration can accelerate a positive result up in their bedrooms. Now it’s up to us to follow their lead to see how we can make it work across the world.

R&D Informatics – 3 Strategies for 2012

23 Nov

This is part III of a series of blogs analyzing the results of our recent R&D Collaboration trends survey. See R&D Informatics – are you ready for 2012? and  R&D Informatics – It’s  all about reducing complexity, improving collaboration & protecting IP for the earlier posts.

R&D INFORMATICS: READINESS CHECKLIST

Based on our analysis of the survey findings and the input of dozens of leading R&D organizations that we work with at IDBS, we’d like to propose the following practical strategies to help you tackle R&D Informatics in 2012.

Step 1: Reduce Complexity:

  • Legacy system de-cluttering – can you identify systems you don’t want to interact with anymore?
  • Explore where you can use flexible, multi-purpose, multi-domain systems. Take steps to future proof your systems for inevitable business change
  • Don’t think that removing a system removes capability, it may enable implementation of better processes
  • Don’t accept “we can’t do that, the system won’t let us”

Step 2: Improve Collaboration:

  • Think data, not documents – all data (yes, even raw data) should be easily accessible in real time, accessed controlled, searchable and reportable
  • Who are your partners in the ecosystem? Consider who are the consumers and contributors of your data. Where do you fit? Can they see your data?
  • Maximize online access to data – employees expect to be able to collaborate as easily with their work systems as they do with their social media tools. A reliance on summary level information only allows superficial collaboration
  • Don’t use different systems for internal and external collaboration – you’re just creating more silos

Step 3: Maximize Capture of IP & Innovation:

  • Explore how IP capture can be automated from existing data capture process – can you make it an inherent element of every stage of research, so that it is not an additional activity?
  • Where are the opportunities to harvest IP from your existing processes? Don’t create a new IP capture activity – this simply makes more work for the scientists
  • What are the barriers to current IP capture?
  • Can you share your innovative processes with others?
  • Don’t think it’s someone else’s problem – it is the responsibility of everyone to capture and share their innovations

Discover more by listening to our ondemand webinar.

WHAT’S YOUR PLAN OF ATTACK FOR 2012? 

Let me know your thoughts on these approaches and your own strategies for addressing R&D Informatics in 2012.

R&D Informatics – It’s all about reducing complexity, improving collaboration & protecting IP

31 Oct

This is part II of a series of blogs analyzing the results of our recent R&D Collaboration trends survey. See R&D Informatics – are you ready for 2012? for the first post.

Reality of the R&D Informatics landscape

It is often easy to assume the majority of organizations have had the opportunity to address basic data management and reporting requirements. For example, report production and tools for compiling data are a “must have” for today’s organizations who want to stave off the competition. The general assumption is that everyone has solved this problem, but the survey reflects a different reality. There is strong need for enterprise-level data management systems that collect and store information and make it readily accessible to multiple layers of users within an organization. Read on…

What are researchers concerned about?

It’s not just the voice of analyst and executive management, but this survey exposes that at researcher level three main themes cause respondents the most concern:

80% think the IT environment is too complex – they cited issues with existing tools, too many systems and lack of informatics staff as causing the most concern. There is a clear need for the capability to better manage data consistency across multiple domains.

Comment: This means organizations must simplify the desktop and make the data ecosystem less complex.

55% cannot collaborate effectively – they cited the ability to effectively share and collaborate through data, both internally & externally as an area of concern.

Comment: This means organizations must make data searchable, rich in context and digital – delivering the ability to align data, gain insight and make it usable across the enterprise.

37% believe that they are losing intellectual property – they voiced concerns about effective IP capture, management and security.

Comment: This means making sure researchers capture and securely share their innovation, without having to add to their workload. Their systems should seamlessly capture innovation and make IP auditable.

Top collaboration challenges:

Drilling down the topic of collaboration, the survey found that a staggering 91% of respondents surveyed reported their number one collaboration challenge is managing data to ensure the consistency of research results and avoid rework.

The top three collaboration challenges reported were:

  1. 91% are worried that they cannot align results with their colleagues
  2. 80% are worried that they cannot share their data with their colleagues
  3. 78% had problems recording and tracking intellectual property

Comment: If you can’t manage and align data easily then you can’t collaborate with it or secure the IP – which becomes a vicious circle. Document centric approaches just make this problem worse.

What are people’s responses to these issues?

In the next year, R&D organizations are planning to address these data challenges by creating a simplified environment which captures innovation, enables collaboration and provides insight.  Initiatives organizations are focusing on include:

  • External collaboration
  • Systems consolidation
  • Open innovation
  • IP capture
  • R&D governance

So now we know the issues, what are we going to do about it?

Discover more at IDBS seminarsR&D Informatics: Strategies for 2012” during November in Paris, Frankfurt & Boston, or attend our webinar on November 17.