Life sciences firms are used to an on-going stream regulatory hurdles, and the upcoming ISO IDMP compliance is another to add to the list. But ISO IDMP is also a little different, and promotes the kind of structure and discipline needed if organisations want to really break new ground and take their businesses forward.
How can organisations use ISO IDMP to change the way they operate, and to transform their master data management?
It all begins with data
Data is at the core of such a transformation, and with assumptions about its quality, completeness, and reliability as an accurate record of operations. As EMA’s IDMP requirements near finalisation, the scale of the standards’ impact on managing regulatory data becomes more apparent.
The transition from the current xEVMPD submission requirement to the more extensive and rounded demands of IDMP will involve extensive work. Data is extracted from a wider range of sources than just regulatory affairs and the same high levels of data integrity and data quality need to extend across many business areas, so that the combined data can be relied upon as a definitive reflection of product reality.
The next stage – master data management
After the initial IDMP data analysis the next stage should move to a broader plan for ‘master data management’ (MDM), that will set the company in good stead for that wider transformation. EMA’s own ambition for ISO IDMP supports this effort to improve the data’s quality and integrity, thereby increasing its value. This requires getting the underlying data (the master data) in order, using agreed upon standards.
Companies can enhance and add to this source data for their own internal purposes. The idea is that building on the right foundations and using agreed upon terminology will make the complete data set more meaningful and easier to repurpose.
Beyond compliance requirements, companies should be striving for a 360-degree view of product data. This includes a global, integrated view of product information, which supports business processes throughout the product lifecycle and provides a definitive master data set servicing multiple applications.
Master data management best practice
The journey to MDM should be viewed as an evolutionary one, though the scale of the transition could be construed as daunting. The important thing is that companies start somewhere and treat developments as a continuum – with people, processes, and technology brought on in parallel.
The starting point should be data governance, so with this in mind, it is important to establish early on how quality and consistency will be managed, who owns the data, and who is accountable for its quality and integrity.
Data policies and processes should then provide the documented guidelines, procedures, and tasks to direct data stewards and other stakeholders, enabling them to ensure the integrity, consistency, and sharing of enterprise data resources.
Data stewardship will be critical in extracting value from MDM and IDMP investments. This involves proactive management and oversight of an organisation's data assets. Operationally, the remit can be broken down into a number of clear steps, from initial data profiling/discovery/scoping, and data modelling, to data cleansing, profiling, enriching, matching, consolidating, and relating.
IDMP compliance will require solid data governance and use of MDM principles and processes for data stewardship, irrespective of whether an organisation plans to implement MDM technology to support IDMP or not. Ultimately, ISO IDMP’s main focus is master data. As such, it makes business sense to harness this master data for maximum effect.