Next-Generation Analytics: Actionable Insights on Tap

Feb. 23, 2017
On-demand access to the latest business intelligence is the key to almost every strategic priority life sciences organizations are working towards. But it can’t be delivered without the right groundwork.

The ability to perform timely analytics and to access reliable, up-to-date business intelligence at the point of need is a priority for just about any business in 2017. On-demand decision support is the key to operational efficiency, to competitive advantage, and to an organization’s ability to respond to new market conditions and new business opportunities. Without reliable insight, companies might easily miss something, and teams will not be fully confident in their decisions.

In life sciences the barriers to achieving information clarity are particularly high - despite the fact that regulatory scrutiny requires companies to be vigilant in capturing and reporting a lot of detailed information. The issue isn’t a lack of data, so much as a paralysis caused by information management complexity.

Aim for a whole that is greater than the sum of its parts

While the life sciences industry already makes good use of business intelligence and analytics tools, typically this is for a very specific use case, and data is confined to a function-specific system silo, limiting its broader value. This piecemeal approach to information management is now hampering attempts to collaborate more broadly across the organization, as companies try to foster a more creative, innovation-oriented culture. This situation needs to change as altering market dynamics force companies to reassess existing business models and operating norms.

Ultimately companies need to work towards a consistent, continuous information management strategy that transcends department, location and data type. One that allows all the data threads from across the different parts of the organization to be drawn together, and at speed, so that they can contribute more tangibly towards the more pressing priorities of the business. These might range from improving transparency, and managing increasingly onerous regulatory requirements globally, to repackaging product portfolios, and collaborating in new ways across and beyond the business.

Processes need to be aligned too, of course: accruing timely insight is worthless if steps are not in place to exploit it. Such processes need to be enterprise-wide in nature and scale, appropriately design and supported by suitable change management, complemented by incentives and personal accountability.

Supporting technology must be fit for purpose too – able to be integrated seamlessly so that different data sources can be combined and mined as needed to support the current need.

Taking practical steps in the right direction

A practical way forward is to plan and build real-time analytics into broader data management initiatives, eg those already underway to support regulatory compliance. That’s because much of the

content involved can serve a range of broader commercial purposes if given the right treatment from the outset.

Whether initiatives are designed to improve existing analytics capabilities or to introduce analytics into new business areas, it is important that companies take a long-term view as doing this properly will require both sizeable investment and a significant change to established processes.

But above all, companies should prepare to do something – and soon. Inertia is not an option. Business transformation based on predictive analytics and real-time insights will be crucial to a secure future for any company in and beyond 2017 – not least for life sciences organizations.

If you achieve nothing else in the months ahead, resolve to develop a roadmap that plots out progress milestones – one that, in due course, will allow the business to leverage both live and historical information for tangible operational and competitive advantage.

If it contains the following elements, you won’t go too far wrong:

  • Engage external experts & take a holistic approach to data management and analytics
  • Standardize and streamline the way data is captured, stored and management, to enable integration and cross-analysis
  • Address data duplication
  • Improve content accuracy, completeness and currency, ensuring regulatory compliance and patient safety
  • Think beyond single applications towards building a master pool of (business, product, operational, financial) knowledge – even if this is achieved virtually
  • Aim to create a ‘single version of the truth’ – ie the fuller picture of a situation as a whole, based on complete and up to date detail
  • Make information easy to share, and quick to access and to mine for analysis
  • Reduce reliance on month/quarter/year-end reports, empowering business users to discover the intelligence they need on demand

About the author

Elvis Paćelat is a business and technology executive with more than two decades of international experience in the Life Sciences market. With detailed technical understanding and expertise in compliance and regulatory content management solutions for Life Sciences, Paćelat is a specialist in business impact analysis. As AMPLEXOR Life Sciences's vice president, compliance management, he is responsible for driving the corporate strategy and market success of the AMPLEXOR Life Sciences' suite business. Paćelat is committed to delivering benefit for clients, partners and shareholders, whilst supporting client-centric strategies and spearheading groundbreaking innovations.

About the Author

Elvis Paćelat | VP of Compliance Management