Deloitte’s Patrick Middag and Dennie van de Voort provide some practical steps to creating and entrenching effective data governance practices which in turn can help elevate the quality and value of regulated pharma data – not just for the immediate use case, but also for other critical applications beyond the regulatory function.
Key insights:
- Maintaining data quality and consistency holds the key to critical pharma production and regulatory processes.
- Establishing a data governance structure, including appointing a Data Governance lead, an interaction model and company awareness would help provide that clarity and direction.
- There is the potential for mass-scale market disruption by the Big Data players, which have all the skills and resources to challenge the Life Sciences & Healthcare industry head on with their strategic use of data and analytics.
The impact of any digital process transformation program relies heavily on the quality and reliability of the data that feeds into those processes. If that data is patchy, inconsistent, out of date, or incorrect, risks will be magnified each time someone re-uses that data. Operationally, inconsistent information exchanged with the regulators will lead to non-compliance risks, risks of poor quality and ultimately patient safety and public health risks. More strategically, it will limit companies’ ability to perform useful data analytics and to increase their business efficiency, reducing the time to market and patients.