Manufacturers have invested heavily in Manufacturing Execution Systems (MES) to bring greater control, consistency and visibility to batch execution. The promise is compelling: replace manual processes, standardize workflows, capture data electronically, and create a more controlled path from production to batch release.
Yet even with MES in place, batch execution can still face deviations, delays, rework, and extensive review cycles.
The reason is simple: technology alone does not eliminate execution gaps.
An MES can enforce workflows and capture information, but it cannot compensate for unreliable master data, disconnected equipment, poorly designed processes, unclear exception handling or inconsistent practices across sites. When these underlying gaps remain, organizations can end up digitalizing inefficient processes rather than eliminating them.
The result is a familiar set of challenges: operators rely on workarounds, manufacturing teams spend time resolving avoidable issues, quality teams perform extensive manual reviews, and batch release takes longer than expected.
So, what causes batch execution to fail even when MES is already in place?
1. Poor Master Data Discipline
MES execution depends heavily on the quality of the data behind the workflow. Materials, equipment, recipes, process parameters, instructions and other master data elements must be accurate, complete, and properly governed.
In practice, master data can become outdated or inconsistent. Changes may not be implemented uniformly; ownership may be unclear, or teams may work around governance processes to meet production timelines.
The impact: Hidden execution risks
When data driving execution is unreliable, even a well-designed MES workflow can produce inconsistent results. Errors may only become visible during execution or review, creating deviations, rework, and additional investigation effort.
What should change?
Organizations need clear ownership of master data, defined change-control processes, and regular data reviews. The goal is not simply to maintain data, but to ensure that the data driving every batch of execution is trusted.
2. A Paper Mindset Inside a Digital System
Moving a paper process into MES does not automatically make the process more efficient.
Many organizations digitize existing workflows without first questioning whether every step is still necessary. Paper forms, approval layers, and redundant checks can simply reappear as electronic screens and system transactions.
Operators may then focus on completing the prescribed system steps rather than understanding the process of intent behind them.
The impact: Digital execution without process improvement
The organization gains an electronic record, but not necessarily a better process. Unnecessary steps remain; execution becomes cumbersome, and operators may look for workarounds when the system does not reflect how work is actually performed.
What should change?
Processes should be reviewed before they are digitised. Redundant activities should be removed, critical control points should be clearly identified, and workflows should be designed around how manufacturing actually happens—not around how a paper form was previously structured.
3. Weak Integration with Shop-Floor Systems
An MES becomes significantly more valuable when it can reliably exchange information with equipment and other manufacturing systems.
However, integration gaps remain common. Where equipment data cannot flow reliably into the MES, operators may still need to enter information manually. This introduces another opportunity for transcription errors, delays, and inconsistent data.
The impact: More manual work and longer reviews
Manual data entry increases the burden on operators and creates additional work for reviewers. Quality teams may need to spend time verifying information that could otherwise have been captured automatically.
What should change?
Manufacturers should prioritise automated data capture wherever practical, validate data flows early and ensure that equipment and system interfaces are designed around critical execution requirements.
The objective is not integration for its own sake. It is to reduce manual intervention and create a more reliable flow of execution data.
4. Over-Customization of MES
Every manufacturing site has unique requirements. But responding to every local requirement with custom MES logic can create another problem.
When organisations heavily customise their systems, different sites can end up operating on different workflows, configurations and business rules. Over time, the system becomes increasingly difficult to maintain and adapt.
The impact: Rigid systems and slower change
Standard upgrades become more complicated. New requirements require more development. Lessons learned at one site may not easily translate to another.
What should change?
Organisations should use standard MES capabilities wherever possible and challenge customisation requests that address local preferences rather than genuine process or regulatory requirements.
Standardisation across sites can make systems easier to maintain, upgrade and scale.
5. Poor Exception Handling
MES workflows are often designed around the expected sequence of events. Real manufacturing, however, rarely follows the happy path every time.
Equipment issues, unexpected process results, material problems and other deviations can require operators to make decisions outside the standard workflow.
The impact: Workarounds outside the system
When exception workflows are unclear or difficult to navigate, operators may escalate issues through email, paper notes, calls or other informal channels. This creates gaps in traceability and makes it harder for quality and manufacturing teams to understand what happened and why.
A controlled happy path is not the same as controlled execution. The real test is what happens when the batch leaves the expected path.
What should change?
Exception scenarios should be designed into the workflow rather than treated as unusual afterthoughts. Operators need clear resolution paths, appropriate approvals and the ability to capture relevant deviation information within the controlled process.
6. Inadequate Operator Training
Technology cannot replace process understanding.
Training that focuses primarily on which buttons to click and which screens to complete may help operators use the system, but it may not prepare them to respond when something unexpected happens.
The impact: Workarounds undermine system control
When operators do not understand the process logic behind a workflow, unexpected situations can lead to hesitation, escalation, or workarounds.
What should change?
Training should combine system knowledge with process understanding. Scenario-based training can help operators understand not only how to execute a batch, but also how to respond when execution moves outside the expected path.
7. Review by Exception Is Not Fully Implemented
One of the major opportunities of digital batch execution is reducing unnecessary manual review.
Yet many organisations continue to perform extensive reviews of every batch record, even when much of the information has already been captured, validated and controlled electronically.
The impact: Digital records, manual release
When confidence in system-generated information remains low, quality teams continue to review large volumes of routine information manually. This increases review time and can delay batch release.
What should change?
Organisations should clearly define critical parameters and establish where validated system controls can be trusted. This allows reviewers to focus their attention on exceptions, critical events and information that genuinely requires human judgement.
8. Fragmented Governance Across Sites
A global organisation can have multiple MES implementations, but that does not necessarily mean it has a consistent manufacturing execution strategy.
Different sites may use different templates, data structures, workflows and practices. Without central governance, improvements made at one location may remain isolated.
The impact: Inconsistent execution at scale
Fragmented governance makes it difficult to compare performance, replicate improvements and establish consistent execution standards across the organisation.
What should change?
A central governance model can establish common data standards, process templates and performance measures while still allowing justified site-specific requirements.
What Should Pharma Leaders Focus On?
The answer is not simply to add more technology.
MES can provide the digital foundation for controlled batch execution, but the quality of execution depends on the processes, data and people surrounding it.
Pharma manufacturers should focus on eight priorities:
- Govern master data with clear ownership and change control.
- Redesign processes before digitising them.
- Increase automated data capture from the shop floor.
- Minimise unnecessary MES customisation.
- Build exception handling into the execution workflow.
- Train operators to understand process decisions, not just system steps.
- Establish genuine review by exception.
- Create consistent governance across sites.
Building a More Predictable Path From Execution to Release
Batch execution does not fail simply because an MES lacks features. It fails when the organisation’s processes, data, integrations and governance are not strong enough to support consistent execution.
This is where modern electronic batch record management can complement the broader manufacturing technology landscape.
CaliberBRM helps organisations bring batch execution, documentation, review and approval into a controlled digital workflow, supporting standardised execution, real-time visibility, exception management and more efficient batch review.
In a CaliberIPQC implementation at Zydus, digitalisation addressed two issues closely related to this article: shop-floor instrument connectivity and review effort.
66
IPQC instruments integrated30–40%
Reduction in review time through review by exception776+
Batches generated using IPQRThis is a CaliberIPQC manufacturing implementation rather than an MES benchmark. It demonstrates what changes when execution data is connected and reviewers can focus their attention on exceptions instead of routine information.
Explore the Zydus digital manufacturing case study →
The objective is not merely to replace paper with electronic records. It is to create a more connected and disciplined execution-to-release process.
Because ultimately, predictable batch execution depends less on how many features a system has and more on how consistently the organisation uses technology to enforce well-designed processes.
For pharma leaders, that is the real opportunity: move beyond simply digitising batch execution and build a process that is controlled, consistent, visible and designed for release.
