What comes next for library e-resource management?

A new OCLC report outlines how libraries can scale responsibly by using automation and shared infrastructure

E-resource teams are operating in an environment defined by volume and volatility. OA coverage changes. Hybrid packages evolve. URLs move. Records are updated, withdrawn, and replaced. At the same time, staffing levels remain flat and expectations for seamless discovery and access continue to rise.

Articles one and two in this series explored why metadata has become strategic infrastructure for institutions, and how OA discovery breaks down when version, rights, and link signals are unclear. Once those foundations begin to stabilise, a new question emerges. How do libraries sustain those gains over time without falling back into manual workarounds and local firefighting?

The challenge is not whether to automate, but how to combine selective automation with shared infrastructure so routine change is handled collectively, and human expertise is applied where it adds the most value.

Responsible automation is about scale, not replacement

The OCLC report Unlocking the future of e-resource management frames automation as a capacity strategy, not as a substitute for professional expertise. The aim is stability at scale.

Automation is most effective where change is frequent, rules are clear, and consistency matters. Human judgement remains essential interpreting data used to shape collections, guide investment priorities, and support strategic decisions at the institutional level.

When libraries automate indiscriminately, they risk compromising user experience. When they avoid automation altogether, skilled staff spend disproportionate time maintaining links, cleaning records, and reconciling inconsistencies that originate upstream.

“Responsible automation is about stability and scale. Machines handle volatility in workflows and across systems, so librarians can focus on strategy and users.” – John McCullough, Executive Director, Library Management Services, OCLC

Where automation delivers the biggest returns

The report highlights several areas where responsible automation consistently reduces friction without compromising quality or professional control.

Link reliability and entitlement propagation

Broken links remain one of the most visible symptoms of e-resource complexity. They often result from provider updates that do not propagate cleanly across the systems responsible for holdings, discovery, and access.

Automating the flow of updates across the metadata supply chain allows changes to be reflected consistently wherever users encounter library resources. This reduces dead ends for users and removes the need for staff to repeatedly investigate issues that originate outside the institution.

Deduplication as collections evolve

As OA and licensed content increasingly coexist at article level, duplication becomes harder to manage manually. Automation supported by persistent identifiers helps stabilise discovery as packages change and versions multiply.

This improves user experience and prevents reporting distortions caused by duplicate records competing for attention or fragmenting usage data.

Record updates at scale

Manual record maintenance does not scale in environments where collections are in constant flux. Automated distribution of record updates ensures that discovery reflects current holdings without repeated manual intervention, while still allowing libraries to apply local policies and exceptions where they matter.

Where human judgement remains essential

As automation brings greater consistency to metadata and access workflows, its real value shows up in the quality of the evidence it produces. Reliable data, gathered at scale, creates a stronger foundation for decisions that shape collections, investment priorities, and longer-term institutional direction.

Systems can surface trends, patterns, and points of friction far more effectively than manual processes. What they cannot do is determine how those signals should influence future choices. Deciding whether to deepen coverage in one area, rebalance spend, or change strategic emphasis remains a human responsibility, informed by experience and institutional context.

“Automation can make patterns and gaps visible, and reliable automation depends on quality metadata to carry those signals consistently to the point of decision. However, people are still needed to interpret that evidence and decide how collections and services should evolve.” – Ixchel Faniel, Senior Research Scientist, OCLC Research

Machine-assisted processes strengthen the evidence base by improving consistency and reducing noise. Library leaders and practitioners must then use that clearer picture to make informed decisions about direction, priorities, and change.

Shared infrastructure multiplies local effort

A central theme in the report is collaboration at scale. When libraries rely on shared infrastructure, improvements made once can benefit many institutions.

Cooperative metadata networks such as WorldCat illustrate this model. Shared maintenance of holdings, identifiers, and relationships reduces duplication of effort across the community, while still allowing local teams to control policy, presentation, and priorities.

This approach is not about losing autonomy. It is about reserving local effort for decisions that genuinely require it, while letting shared systems absorb the most volatile and repetitive work.

Turning stability into sustained capacity

Automation alone does not create capacity. Capacity emerges when libraries pair automation with evidence.

The report recommends combining multiple perspectives, including usage data, authentication-based insight, and peer context, to understand not only what is used, but where access fails, who is affected, and whether improvements hold over time.

In practice, this kind of end-to-end visibility is most effective when metadata, licensing, access, and analytics are managed within an integrated environment, such as WorldShare Management Services, where changes can be observed across workflows rather than in isolation.

What this means for libraries

To move from short-term fixes to sustained capacity, the report points to a practical next phase.

• Absorb volatility with automation. Use shared infrastructure to handle link maintenance, deduplication, and record updates at scale.
• Focus human expertise where it adds the most value. Use it to interpret evidence and make choices that shape collections, investment priorities, and long-term direction.
• Rely on shared systems, not local reinvention. Let collective improvements reduce duplication of effort across institutions.
  
• Use evidence to confirm gains. Combine usage, authentication insight, and peer context to show where automation is working and where refinement is needed.

Webinar preview: scaling what works

This final article sets the stage for a deeper discussion. Hosted by independent consultant Ken Chad, the upcoming webinar will bring together OCLC’s John McCullough and Ixchel Faniel to explore how libraries are using responsible automation and shared infrastructure to scale e-resource management without losing trust or professional control.

Expect a practical conversation focused on what to do next, what to automate with confidence, and how to ensure human judgement remains central as systems scale.

2 June, 14:00 UK, 15.00 CEST, 09.00 EDT

→ Read more: download the e-resources report: https://connect.oclc.org/eresources_unlocked
→ Register now: register for the e-resources webinar: https://connect.oclc.org/eresources_whats_next

Key takeaways

• Automation is most valuable where change is frequent and rules are clear.
• Human expertise remains essential. It connects evidence to strategic outcomes.
• Shared infrastructure allows one fix to benefit many institutions.
• Responsible automation turns metadata and OA improvements into sustained capacity.
• Evidence confirms where scale is working and where adjustment is needed.