🍽️ The Data Dish #9: Setting the Table for Data Integrity

Welcome back, compliance connoisseurs! We’ve been serving up some tasty insights on data integrity, and this week, we’re bringing out the main course: Data Governance. Because if ALCOA(+) is the secret sauce, governance is the recipe that keeps everything running smoothly.

Let’s dig in! 🍽️

🍛 Main Course: Data Governance – Who’s Running This Kitchen?

Ever walked into a kitchen where nobody knows who’s in charge? Chaos. The same goes for data integrity. Without clear roles, responsibilities, and accountability, things get messy—fast.

Data governance is your organization’s rulebook for managing data integrity. It defines who’s responsible, what processes must be followed, and how data should be handled to avoid breaches, inconsistencies, and regulatory nightmares.

Real-World Example: When Governance Goes Missing...

A pharmaceutical company was cited by regulators because different departments had conflicting data on batch records. One team updated information, but the changes weren’t properly communicated, leading to discrepancies in final product release reports. The result? Delays, compliance issues, and a very unhappy QA team.

The lesson? When governance is weak, data gets lost in translation—and so does compliance.

🍽️ How to Set the Table for Data Integrity

Just like a Michelin-starred restaurant follows strict kitchen protocols, a pharma company must have well-defined data governance structures to ensure compliance. Without clear guidelines, things start to slip—data gets lost, records become inconsistent, and regulatory scrutiny increases.

📜 What Do Regulators Expect?

Regulators like PIC/S, the FDA, and the MHRA have clear expectations when it comes to data governance:

🔹 PIC/S Guidance (PI 041-1, Good Practices for Data Management and Integrity in GMP/GDP Environments):
✔️ Companies must establish a documented data governance system that defines responsibilities, processes, and oversight of data throughout its lifecycle.
✔️ Governance should be risk-based—focusing on critical data that impacts product quality and patient safety.
✔️ Data governance should apply to both paper and electronic records, with periodic reviews to ensure compliance.

🔹 FDA Guidance (Data Integrity and Compliance With Drug CGMP, 2018):
✔️ Companies must have written procedures that define how data is recorded, reviewed, and stored.
✔️ Data governance policies should ensure that data is attributable, legible, contemporaneous, original, and accurate (ALCOA+).
✔️ Senior management is responsible for ensuring a culture of quality and compliance that supports data integrity principles.

🏗️ How to Build a Strong Data Governance Framework

🔹 Step 1: Write It Down – Formalize Data Governance Policies
Regulatory Expectation: PIC/S states that all GxP-relevant data must be governed by clear policies that establish ownership, handling, and retention rules.

Your Data Governance Policy should cover:
📌 Roles & Responsibilities – Who is responsible for data integrity (e.g., QA, IT, Production, Lab Managers)?
📌 Data Ownership – Who owns the data at each stage of the lifecycle?
📌 Change Control – How are changes to data managed and documented?
📌 Data Security & Retention – How long should data be stored, and how is access controlled?

🔹 Step 2: Assign a Head Chef – Create a Governance Structure
Regulatory Expectation: The FDA expects executive management to take responsibility for ensuring data integrity policies are followed and enforced.

📌 Assign Data Integrity Leads within key departments (Lab, Manufacturing, IT).
📌 Establish a cross-functional Data Governance Committee to oversee data integrity initiatives.
📌 Implement regular audits and reviews to verify compliance.

🔹 Step 3: Train the Team – Make Governance a Daily Practice
Regulatory Expectation: PIC/S requires data integrity training for all personnel handling GMP/GDP records.

📌 Conduct regular training on data governance policies.
📌 Use real case studies of data integrity breaches to highlight risks.
📌 Perform mock audits to assess adherence to governance protocols.

🛠 Action: Build Your Data Governance Playbook

Step 1: Develop and implement a formal data governance policy aligned with regulatory expectations.
Step 2: Assign clear responsibilities and ensure teams know who oversees data integrity.
Step 3: Train employees on how governance applies to their daily tasks and conduct internal reviews to verify compliance.

🔍 Self-Assessment: How Strong Is Your Data Governance?

Ask yourself and your team:
❓ Do we have a formal, documented data governance policy?
❓ Can we demonstrate who is responsible for each stage of data integrity?
❓ Are we performing regular audits to ensure compliance?
❓ Would an FDA or MHRA inspector say we have a “culture of data integrity”?

If you’re not sure, your governance structure needs reinforcement!

🔜 Next Week: Training for Data Integrity – Sharpening Your Skills 🔜

Having strong policies is great—but does your team actually know how to follow them? Next week, we’ll explore the must-have training strategies to ensure data integrity becomes second nature in your GMP environment.