Digitizing manufacturing with an MES is a big step, especially in regulated spaces like pharma and biotech. But alongside innovation comes responsibility—especially when it comes to compliance. Since MES sits at the heart of production, enforcing process controls and managing real-time data, it’s essential to validate the system to ensure it performs reliably, consistently, and in line with GMP expectations.

But validation isn’t just a one-time box-ticking exercise during go-live. For MES, knowing what to validate and when is just as important as the actual testing. Let’s dig into some real-world CSV considerations that come up before and during MES implementation—especially the ones the validation lifecycle charts don’t quite capture.

Strong Processes Make MES Work Better

One of the biggest mistakes teams make is jumping into MES design before the underlying process is well-defined. MES enforces your manufacturing process—it doesn’t create it. So if steps are unclear, inconsistently followed, or handled differently across shifts or sites, the MES will end up magnifying those gaps.

For example, imagine you’re digitizing a batch process for a sterile injectable, but the current SOP is vague on how to handle a filter integrity test failure. In a paper world, operators might flag it and wait for QA input. But MES needs clear logic: does it halt the batch? Send an alert? Allow a retry? These decisions need to be nailed down before validation begins.

Good Master Data Sets You Up for Success

Master data often gets lumped in as just an IT task—material codes, equipment models, recipes—but it plays a much bigger role when it comes to MES. But in an MES, master data is the process. It defines what materials are acceptable, what steps are required, what equipment can be used.

Let’s say you’re producing oral solid doses and define a mixing step in the MES without linking it to specific blender models. Without validated equipment rules, the MES might allow production using a blender that’s out of qualification—or worse, wrong for the formulation. During validation, testing this logic is crucial, but even before that, it’s important that the business owns the quality of that data.

A Solid Infrastructure Foundation Pays Off

It’s tempting to focus validation efforts on MES functionality—batch workflows, data capture, electronic signatures—but it all rests on infrastructure. If MES runs on an unqualified virtual server, or backups aren’t validated, everything above it is compromised.

In some MES projects, testing gets well underway before anyone catches something like a time mismatch between the app server and the database. Suddenly, timestamps are off, records don’t align, and test results need to be redone. Infrastructure qualification (especially in cloud-hosted or hybrid setups) needs to happen before MES scripts are ever executed.

Validating Real-World Workflows Builds Confidence

Every MES system is built around electronic workflows—those digital instructions that tell operators what to do, when, and how. These workflows translate real SOPs into structured, enforceable steps.

During validation, it’s not enough to check that the workflow runs. You need to test that it enforces the right behavior. For instance, if an MES is supposed to require QA signoff before starting a fill line, your test case should prove that a user without QA credentials cannot bypass it—even if they try to skip steps or backdoor the system.

Take a scenario where line clearance verification isn’t included in the MES workflow. If validation scripts only test standard process flows, it might pass without issue—until someone skips clearance in production and the system doesn’t catch it. It’s the kind of gap that often shows up in post-go-live monitoring—costly, but preventable with the right test coverage.

Integrated Systems Need Integrated Testing

MES almost never operates in a vacuum. It talks to ERP systems for order management, LIMS for test results, and sometimes even SCADA or PLCs for equipment data. Each of those connections brings CSV implications.

Let’s say your MES automatically pulls material status from your ERP. If the ERP flags a batch lot as “on hold” but the MES doesn’t stop the batch, that’s a compliance failure. You’ll need to validate not just the data flow, but also what the MES does with that data.

Here’s a scenario: an MES is integrated with LIMS to ensure a batch is only released after passing microbial testing. During validation, a failed test result is simulated—but the MES still releases the batch. The issue? A small logic error in how the system read the LIMS flag. Catching that during validation avoided what could’ve been a serious compliance risk.

Smart Access Controls Strengthen Data Integrity

Access control in MES often seems straightforward—until you dive into the details. Users need the right permissions to do their jobs, but not so much access that it compromises compliance.

A validation-worthy question: can a production supervisor approve their own work? Can an operator access quality records they shouldn’t see? These scenarios don’t always appear during initial testing, but they’re critical for 21 CFR Part 11 and Annex 11 compliance.

Example: During validation, it’s uncovered that any logged‑in user can reassign batch steps—even those without the proper training. Fixing this didn’t stop at tightening up user roles; it meant redesigning the MES’s training‑verification logic so that only qualified personnel can make those changes.

In Summary

Validating an MES system isn’t just about writing and executing test scripts. It’s about understanding how the system touches every part of manufacturing, and making sure those touchpoints are locked down, compliant, and trustworthy.

By focusing on real-world considerations—things like process clarity, master data, infrastructure, interfaces, and user roles—you’ll catch issues early and avoid painful rework down the line.

Whether you’re mid-implementation or just starting to plan, it’s worth pausing to ask: are we validating what matters most?