1. From your experience, where does Data Governance sit within an organization? Is it more within Data Management/IT or more on the business side? Who drives these operating models?

   It depends on the organization’s structure and culture. The foremost point to appreciate is who benefits from Data Governance being in place. The answer should unequivocally be – business. That means that it is the business which needs to ensure there is sufficient data literacy across their organization – meaning, business teams need to be able to ‘ask’ for the right data to be able to make day-to-day decisions. IT and Data teams only react to those requests (although this reactiveness, if codified, can help them respond proactively). In short, business team guides, and IT/Data team enables. Therefore, organizations need to strike a fine balance where business teams define the ‘why’ and the ‘what’, and IT/Data teams define the ‘how’.

   Could IT own the data governance program? Sure, but only if business is actively involved. Could business own the data governance program? Sure, but only if IT supports business teams at every step of technical implementation. Our experience shows that IT or business working in isolation have struggled implementing Data Governance. Some organizations are creating a Data Office and assigning a Chief Data Officer (CDO) whose role is to drive governance in an organization as well as bring business and IT together. This strategy can be costly and culturally driven, but it can add a lot of value.

   Who drives the overall Data Governance programs depends on who has the motivation to take on the accountability, the bandwidth to operationalize, and/or the money to finance the program. Whether it is IT or business or data functions or a combination driving the data governance program, one needs to ensure that accountability remains with just one function.

2. Where do I start when it comes to creating a Data Governance strategy?

   The very first step is to understand the status quo at your organization. We advise setting up a taskforce of diverse stakeholders who have a strong understanding of the data-related challenges across processes, people, and technology. This information will be vital in allowing you to then stand up your data governance framework. The next steps would be to align this framework with your organization’s overall business strategy. It is critical to socialize and align this framework with senior executives to get their endorsement. Having this top-down approach is critical in terms of bringing awareness and buy-in for data governance.

3. What are key challenges in operationalizing a Data Governance Operating Model for life science organizations?

   There are a wide range of challenges we have observed across the various clients we have supported. Here are the three that have been the most common:

   • Quantifying the value of data governance for the organization/ articulating the value of data governance to the business.
   • Lack of support from Business or IT when the other function is driving data governance.
   • Making it stick - embedding data governance in the organization’s DNA to ensure the change becomes an overall part of the data management culture.

4. Can you provide a few tips to bring Data Literacy within an organization?

   In its simplest form, Data Literacy refers to the ability to effectively communicate, use and understand the value of data. Note that the level of data literacy may vary across the various role types in the organization, but here are a few ways to establish a strong data literacy foundation:

   • Embed key messages around the importance of data and data quality within your organization’s data policy.
   • Create persona-level data communications. It is imperative that each persona/ role in the organization understands the role of data in their day to day lives; how it impacts their performance and ability to do their job; and what their responsibilities are in terms of supporting in the maintenance of data. We have seen roadshows and newsletters being used effectively as communications tools to get these points across.

5. It is difficult at times for application teams to quantify the business value of implementing data management solutions due to cost of implementation as compared to benefits. Can you provide an example of how this situation was overcome in an organization?

   The most effective strategy is to create a quantitative business case, which of course can be rather challenging for a data management solution. To do so, we first recommend understanding the capabilities of the prospective technology and map them to compliance & risk management, cost savings and revenue generation. Our suggestion would be to start with the most important lever: compliance & risk management. The focus here should be on identifying

   • The financial costs due to the fines & penalties associated with a regulatory breach and
   • The costs associated with loss of business continuity.

   As you proceed to identify the remaining benefits across the other two levers, keep in mind that some may not be possible to quantify. In those situations, ensure that you still include them in your business case but with a strong qualitative rationale in place to justify their inclusion.

6. Data is an extremely broad term – do you have any advice on how to break it down into domains and focus on the domain with the highest impact for a biopharma company to invest in first?

   Based on what we gathered partnering with top biotech and pharma organizations globally, IQVIA believes biotech organization should focus on three data domains: customer, patient, and product.

   Customers represent the interface between the product manufacturers and the consumers, representing a pivotal element in the pharma ecosystem. In an industry where competition is more and more fierce, customer data elements must be centrally designed to support business strategies. IQVIA also highlights the importance of enriching the standard customer data points with extended data elements e.g., web data, medical, regulatory.

   Patients are the individuals who ultimately need treatment, thereby representing the ultimate ‘customer’. It is important for biotech organizations to understand what patient pain points are, the physical and mental barriers to overcoming them, and the perceived value of doing so. Based on these factors, the process prior to commercialization can be more streamlined and optimized

   Products represent the commercial assets for biotech organizations, who therefore need to understand how to differentiate their pipeline and the corresponding branding from the competition. IQVIA has seen several occurrences where global biotech organizations having put in place a solid data management strategy in the products domain saw significant increases in the bottom line.

7. At what maturity level should an organization consider adopting any Data Governance tool? Is there a Data Governance tool/application for Life Science commercial data management that covers all tenets of Data Governance?

   Organizations at any level of maturity must consider exploring the value that the technology brings. Technology serves as the backbone of your governance framework. By incorporating its use early on, you can define your processes, roles & responsibilities around the technologies you choose to implement. Early data governance technology implementation can also serve as a powerful change management tool. Technologies that effectively automate data governance and management tasks, like managing data quality, will ultimately create a lot of first-hand value for data users, making them more likely to support your broader change management efforts.

   There is unfortunately no single technology or application that covers all the tenets of data governance. However, there are platforms, like IQVIA’s self-service 360-degree Data Platform, that does deliver the core data governance capabilities of ingesting, cleaning, and transforming data, along with automated data stewardship workflows.

You can learn more about IQVIA’s Data Governance and Stewardship capabilities on our website, as well as by watching the on-demand webinar here.