Blog
Data management: Start global, scale local
How to create an organization-wide data management environment.
Phyllis Imparo, Practice leader, Data Governance and Stewardship, IQVIA
Jun 03, 2022

The enterprise information management (EIM) ecosystem isn’t a static system. As data management technologies evolve, new data assets are introduced to the environment, new users are added to the system, new technologies are incorporated, and how the environment is managed will need to evolve. This is where managed services become an integral part of maintaining quality, consistency and usability.

Many life sciences organizations roll-out their data environment on a small scale with goals to expand it to support local teams and add new data sources. This allows them to test operational assumptions, fix small problems, and adapt the environment to accommodate all types of data and users so they can constantly generate new value.

But as they expand these platforms to new users, and add new kinds of data, they need to be sure they have agility in their technology, good business rules and talent to adapt the data management process based on local regulations, languages, business unit needs, and relevant data.

If a company is building a master data management system for a global organization, they need a clearly defined data management strategy and data stewards designated to each location who understand global standards and procedures, and how they must be adapted for local end users.

These needs will vary, depending on the project and team, but there must also be a set of data governance policies and procedures that every team follows in order to maintain consistency in the global system. For example, if a medical information team in the UK asks for a change of customer address, the data stewards will have a set of rules allowing them to meet global procedures while adhering to local data privacy regulations. Those steps will differ if the same request is made in China, or Brazil, or the US.

Data follows the sun

Establishing global standards that accommodate local adaptations is essential for big companies, because these kinds of changes will come from every corner of the data ecosystem. If they do not properly govern and steward their data, all the effort spent building a centralized repository and data management system will suffer, and the database will fracture into a collection of untracked versions of the data. It pollutes the data lake, introducing risk and uncertainty to the entire data system.

A strong program management team can prevent these risks. This team is dedicated to building global rules for the data, and tracking variabilities in each country, working with local experts to help core team to adapt their functionalities for each region, language and time zone.

At the same time, the back office processing of the data must continue to ensure changes flowing into the organization can be processed as they arrive, and errors and variations identified and fixed immediately. That may require teams located in multiple time zones to provide a follow-the-sun model to avoid delays in data updates.

This way when a business user has a query, there is a team in place to respond, and the changes trigger an immediate corrective action ensuring the data is always up to date.

Efficiency requires planning

Companies cannot wait until their basic operational services are in place to determine how they are going to configure the system, govern changes, and roll out updates. It needs to be part of the broad data management plan, and part of the agreement with any service partners who support this data landscape. Choosing a single vendor who can provide the spectrum of services required to create an end-to-end EIM environment, can eliminate many of the risks that emerge in a data rich environment, ensuring the established standards for data best practices remain intact.

Companies can still start small, with pilot data projects for local roll-outs, and a broad set of rules for governing the data. But these pilots should follow a structure, lead to templates, and capture lessons learned, so every subsequent roll-out benefits from the prior deployment. Those rules and templates will become the central framework for the data environment with guidelines for how teams can adjust them to accommodate local laws, regulations, and timeframes.

Such up-front planning and strong data governance & stewardship ensures companies will be able to scale their EIM system across regions achieving speed, efficiency and rapid adoption with every new deployment.

IQVIA provides the gold standard for pharmaceutical market data as well as clinical research. IQVIA employs thousands of data scientists, healthcare professionals, technology experts, and Data Governance & Stewardship professionals who oversee processing of more 100 billion healthcare records annually. To learn more about IQVIA’s data services, contact us here.

 

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