In this article
Whilst consultants fantasize about Pharma 4.0 and wonder when AI will replace humans, most pharmaceutical manufacturing teams rely on paper batch records — partially or entirely. For a reason: implementation of MES with integrated sensors and data is a costly and lengthy transformation process.
However, the drawbacks of paper-based processes are significant: repetitive basic checks, poor collaboration functionalities, no possibility for simultaneous work, zero data for analysis, no reusable data for other documents. This leads to lengthy reviews, delayed error spotting, extended cycle times, and bored teams who miss errors.
In 2026, digitalisation and automation are no longer an all-or-nothing, multi-million dollar question. It is a large, diverse landscape of solutions that bring different combinations of digitalisation, automation, and required investment.
In this article we outline the different options and our own view on the investment/reward trade-offs.
The batch record digitalisation landscape: from document management to fully integrated EBR.
Not all digital solutions address batch review challenges in the same way. To compare them effectively, pharmaceutical companies should evaluate each option across two key dimensions.
1 — Implementation Complexity & Costs
2 — Efficiency Gains & Quality Impact
Low complexity, low impact
Fast to deploy, but limited automation value
High complexity, moderate impact
High effort for incremental review improvements
High complexity, high impact
Transformational but resource-intensive
Low complexity, high impact ⭐
The "sweet spot" for fast, measurable ROI
💡 Key Insight
Machine-learning-powered document automation delivers high impact with relatively low complexity by targeting batch review bottlenecks directly — without disrupting existing MES or shop-floor operations.
EBR systems replace paper batch records with structured, digital workflows at the shop-floor level. They guide operators through manufacturing processes in real time while capturing data electronically, improving execution accuracy and reducing transcription errors.
EBR deployments are powerful but require substantial commitment:
As a result, EBR projects deliver long-term value but require considerable upfront investment and multi-year implementation timelines.
✅ Pros
⚠️ Cons
Machine-learning-based batch record automation focuses on streamlining the review process without replacing existing manufacturing execution systems. This targeted approach addresses the primary bottleneck while enabling further digitalisation steps, such as paper-on-glass or EBR adoption. These solutions typically:
This combination of high impact and lower complexity makes ML automation an attractive entry point for batch review digitalisation.
✅ Pros
⚠️ Cons
See batch record review automation in action
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See it in action →Book a free consultation →Document management systems provide a digital foundation by enabling centralised storage, version control, audit trails, and electronic review and approval workflows. They are often the first step in the digitalisation journey, replacing physical archives with structured digital repositories.
While valuable for compliance and organisation, document management systems do not fundamentally change how batch review is performed. Manual checks remain the dominant activity — reviewers still read through records page by page, just on a screen instead of paper.
✅ Pros
⚠️ Cons
Enterprise backbone platforms provide a comprehensive foundation for quality and manufacturing operations. They typically support:
These platforms are often central to long-term digital transformation strategies.
Despite their strengths, backbone systems come with significant challenges:
✅ Pros
⚠️ Cons
The right choice depends on your organisation's maturity, resources, timeline, and strategic priorities.
Automate Batch Review with ML Document Automation
Target the primary bottleneck first to achieve rapid efficiency gains with minimal disruption. Prove the value of digitalisation, structured data, and incremental change — before committing to larger investments.
Improve the Overall Process with Digital Workflows and Integrations
With digital review in place, assess opportunities to optimise the whole review process for maximum efficiency, speed, and quality. Build integrations into other systems such as QMS and SAP.
Expand into Digital BR and Full EBR
Deploy Paper-on-Glass based on the digitalised Master Batch Record. Over time, connect MES and laboratory systems for complete digitalisation and real-time automation.
💡 Key Insight
Software is a space where incremental learnings and roll-out tend to be more rewarding than rigid all-or-nothing implementations. Starting with ML automation builds internal confidence, proves the business case, and creates the structured data foundation every subsequent step depends on.
There is no one-size-fits-all solution for digitalising batch record reviews. Each technology category comes with specific trade-offs between cost, complexity, and impact.
The key is to match technology choices to your organisation's specific needs, maturity level, budget, and strategic timeline. Software is a space where incremental learnings and roll-out tend to be more rewarding than rigid all-or-nothing implementations.
Start here → ML Review Automation
Fast to deploy, high ROI, no shop-floor disruption. The ideal first step for any organisation regardless of size.
Scale to → Full EBR & MES
Once the business case is proven and data foundations are in place, the path to full digitalisation is far smoother.
Not sure where your organisation sits on this map?
Talk to an Acodis expert — free 30-minute consultation. We'll assess your current process, identify the fastest path to ROI, and help you build a digitalisation roadmap that fits your budget and timeline.
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