With the focus of regulated information processes shifting toward structured data exchange, pharma companies are investing heavily in systems to help them capture, collate, analyze, and manage that data in smart and efficient ways.
But in their keenness to digitally advance their operations, companies need to be careful they don’t unwittingly create new complexity and costs for themselves.
1. The pursuit of end-to-end regulatory information management/the rise of best-of-breed
It makes perfect sense that companies want to streamline end-to-end RIM activity, so they can view and manage data consistently and harness it efficiently.
But if you become locked into a single vendor’s software in the process, this could create new risk. If any single brand effectively has control over your company’s data, you’ll need to maintain that relationship no matter what, and absorb any changes in that vendor’s direction or cost structure over time.
Emerging best practice is to maintain strong master data, and then take a platform approach to mixing and matching the best applications or ‘modules’ for each set of tasks (e. g. Clinical, Regulatory, Quality, Safety & Pharmacovigilance).
By emphasizing the data as an asset in its own right, and optimizing modern plug-and-play application integration to allow this to flow seamlessly to where it’s needed, companies can benefit from the best of both worlds – optimal functionality, without lock-in.
And modern, cloud-based deployment makes this easier than ever.
2. Progress beyond IDMP: the extended roadmap
By now companies generally know what they’re doing with ISO IDMP to comply with EU/EMA expectations.
But if you really want to innovate and drive new efficiencies internally, you’ll need to look beyond the immediate requirements around regulated product data. You might want to establish a clear line of sight across your ERP system too, for instance, to create a seamless data trail right the way through to manufacturing.
Otherwise, you’ll end up with new silos which, as ever, are a source of cost and risk.
In 2023, it’s time to ask ‘What’s next?’ and form a roadmap that extends beyond EU IDMP for its own sake.
3. A recalibration of data projects, learning from outsourcing mistakes
In any large system project, it can be tempting to downplay the ‘data’ detail and make it a target for offshoring to contain costs. But this is at odds with the importance of data and its quality in ensuring that every other element of a project and its goals can be delivered.
All too frequently we see statements of work being repeatedly tweaked in an attempt to control costs. And, more often than not, it’s the critical data tasks that are the focus of those ‘efficiency savings’.
Procurement KPIs seem geared to insisting on these cuts, which is immensely short-sighted. Data is the most complex and skilled part of any system project and, if that data work is skimped on to save money, the chances are that the system will fail and ALL of the associated investment will have been in vain.
Just as you would never compromise on a Class I Project Manager, you should never scale back on the required data expertise – especially in complex areas where a certain talent density and experience is needed (e. g. across IDMP, Clinical, Quality and other specialist disciplines).
In 2023, as data becomes intrinsic to almost every strategic systems initiative, business owners really need to push back against pressure to ‘best shore’ data work, to ensure that the project as a whole delivers. This is no time to be squeezing specialist service providers in favor of low-cost, low-touch commodity offerings whose output can’t be guaranteed.
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