posted on September 25, 2025

This FAQ addresses common questions about electronic lab notebook replacements, including costs, alternatives, and results from real-world implementations. It expands on the POV article “Today’s Best ELN May Not Be Another ELN” with additional insights for life sciences organizations.

1. Should I replace my current ELN with a new electronic lab notebook?

Most organizations discover that ELN replacement doesn’t solve their core problems. The issue isn’t the ELN tool itself; it’s that the ELN functions as just one isolated component in a fragmented ecosystem of LIMS, MES, and other point solutions. When you replace one ELN with another, the underlying architecture remains unchanged, and the same frustrations typically resurface.

2. What question should organizations really be asking about ELNs?

Rather than “which ELN should we buy,” the critical question is “how should ELN function within our broader digital strategy?” The path forward requires moving beyond tool selection to architectural thinking, building a foundation that unifies data, contextualizes it across functions, and enables AI-driven analytics.

3. What hidden costs should I expect from ELN replacement projects?

Beyond license fees, ELN replacements typically require substantial investments that often exceed incremental gains:

• Data migration of historical records and experiments
• Integration expenses with instruments and enterprise systems
• Retraining costs across multiple user groups
• Revalidation efforts for regulatory compliance (GLP, GCP, GMP)

Industry analysts consistently show that swapping like-for-like systems rarely moves the ROI needle; organizations invest heavily only to recreate the same limitations.

4. Why don’t new ELNs eliminate data silos in life sciences?

ELN exists as “just one cog in a much larger machine.” ELN, LIMS, MES, and scheduling tools form a patchwork of point solutions, each optimized for narrow functions but not designed for harmony. Data continues living in silos, scientists still export to spreadsheets to connect experiments, and context gets lost between research, development, and manufacturing.

5. What is a digital unified platform approach to laboratory challenges?

Digital unified platforms, such as L7|ESP®, treat ELN as a native capability within a broader digital architecture rather than a standalone system. This approach delivers:

• Automatic data contextualization linking experiment records with LIMS, MES, and inventory
• End-to-end workflows spanning research through manufacturing without manual handoffs
• AI-ready data structures that eliminate downstream transformation requirements

6. What’s the difference between ELN integration and true platform unification?

Integration maintains separate data models and requires ongoing maintenance of connections between disparate systems. True unification provides ELN functionality as a native platform capability, eliminating integration complexity while ensuring consistent data contextualization. L7|ESP® exemplifies this approach by delivering ELN alongside LIMS, MES, and other capabilities within a single architectural foundation.

7. How do digital unified platforms support AI and advanced analytics in pharma?

Digital unified platforms eliminate data fragmentation and structure information for immediate AI readiness. McKinsey research shows that biopharma companies consolidating software and migrating to modern architectures can free up to 30% of their R&D IT spend. These freed-up resources can then fuel innovation, automation, and AI initiatives rather than maintaining system integrations.

8. What should life sciences leaders prioritize: replacement or transformation?

The choice is fundamental: continue the cycle of point-solution replacement or invest in a digital unified architecture designed for longevity. Sustainable ROI comes from platforms that unify data, orchestrate workflows, and position organizations for AI-driven operations, rather than perpetually swapping tools.

Transformation delivers a lasting impact through workflow orchestration, data contextualization, and operational intelligence, capabilities that incremental ELN replacements simply cannot provide.