Essential Components of Data Governance – Part 2
These are 2 of the essential principles that ResultWorks believe are essential to any data governance program’s success.
Strive for Continuous Improvement
The rollout of a data governance program is a significant milestone that enables the foundational framework and structure for an organization’s journey. But achieving the ultimate objective of proactive and effective data governance is a long-distance journey, not a sprint.
A strong data governance program will ensure continuous improvement as an objective in perpetuity. Just as with all other areas of business, mistakes will be made, and lessons will be learned along the way. The key is to apply those lessons to refine and enhance your data governance standards and processes as the program evolves and matures. Establishing feedback mechanisms and metrics to measure and monitor the ongoing health of the data governance program is an essential aspect of ensuring continuous data quality improvement.
Building a Shift in Culture
Data governance has not historically been embedded within the culture of most life sciences organizations. As with any strategic objective, the commitment to achieving greater data quality must be driven from the top down. Leadership must ensure that accountability for data quality becomes an inherent part of the organizational culture. Data quality cannot be viewed as optional and done on a “best-effort basis.” Instead, it must become an expectation as part of everyone’s day-to-day responsibilities. Otherwise, there will never be enough energy to make it stick.
The preferred approach may vary by organization, but regardless of whether you decide to employ a “carrot” or a “stick” approach to driving conformance, strong change management will be needed. It’s important to educate stakeholders and champion the cause to help everyone appreciate the need for data governance and understand the negative impact that results from poor data quality. In some cases, resources in the trenches may not fully be aware of downstream impacts and tend to think about the data they are generating as “my data.”
Another needed shift in mindset that some may face is the heavy reliance on consensus-driven decision making. Driving for 100% consensus on every data governance decision is not a practical approach and can result in organizations stalling and churning on key decisions needed to move forward. Individuals should be identified and empowered to make decisions that best serve the cross-functional interests as a whole, while objectively evaluating the perspectives of each impacted function. Without this type of framework, the amount of standardization, and thus the ability to leverage or re-use the data, will be limited.
These shifts in culture will happen over time not overnight. As perspectives evolve, the right behaviors are instilled, and the organizational mindset is shifted from that of “my data” to “our data”
Summary
One of the essential components to a successful data governance program is to apply what is learned to refine and enhance the standards and processes as the program evolves and matures. A feedback process and metrics to measure and monitor the ongoing health of the data governance program is an essential aspect of ensuring continuous data quality improvement.
There must be accountability and leadership must set the tone so that data quality becomes an inherent part of the organizational culture. Data quality must become an expectation as part of everyone’s day-to-day responsibilities.
Educating stakeholders on data governance is needed for it to make an impact on poor data quality. Key individuals should be empowered to make decisions that best serve the cross-functional interests as a whole, while objectively evaluating the perspectives of each impacted function.
Why It Matters To You
The ability to benefit from advanced technologies like artificial intelligence, machine learning, and analytics relies on solid data governance. Having a strong plan data governance program in place is imperative to ensure success with these tools. In this blog we discuss:
- Several key principles and themes that are essential to any data governance program’s success.
- Why continuous improvement in the data governance program is vital.
- How the culture and leadership of the organization can impact data governance success.
Case Study: LabWare Centralized Data Review for a Global Biopharmaceutical Company
Overview A global biopharmaceutical company specializing in discovery, development,... LEARN MOREWhite Paper: Managing Data Integrity in FDA-Regulated labs.
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