Implementing a laboratory information management system (LIMS) can be one of the most significant operational and financial investments a laboratory makes. During the 2026 Lab Manager Leadership Summit, editorial director Scott Hanton led a roundtable discussion where attendees explored a common concern surrounding laboratory informatics procurement: whether highly customized software platforms create long-term maintenance burdens that become difficult and expensive to sustain.
A primary concern among laboratory leaders is that ongoing customization requests and evolving technical requirements can eventually force facilities to repeatedly bring vendors back for additional work, resulting in significant recurring expenses.
Hanton validated this concern, warning that extensive software customization can create major long-term operational risks. When laboratories heavily modify a platform beyond its standard configuration, future software updates and vendor patches routinely require organizations to revisit, retest, or entirely rebuild those proprietary customizations.
Balancing vendor capabilities and LIMS customization
To minimize these software risk management vulnerabilities, forward-thinking organizations are developing targeted procurement strategies. For example, one participant from Maple Leaf Foods described a company policy focused on using software largely “out of the box” unless there is a compelling business reason to customize it.
Rather than rewriting software to match every existing laboratory workflow, the organization adapts some of its internal processes to fit the software’s native functionality. In situations where unique tracking requirements arise, the team relies on configurable fields and built-in flexibility instead of altering the software’s core architecture.
This distinction between configuration and customization significantly affects long-term maintenance requirements. Configuration-based approaches are typically easier to maintain through routine software upgrades, while heavily customized systems frequently require additional redevelopment work when platforms change.
However, deep customization is sometimes unavoidable, particularly when laboratories must integrate workflows across multiple departments or disparate legacy systems. One participant explained that their organization ultimately hired an experienced internal resource with knowledge of both the old and new LIMS environments because they believed it would be more cost-effective than relying indefinitely on vendor-driven updates and modifications.
The discussion also highlighted the growing ecosystem of third-party software service providers that support laboratory informatics systems independently of original software vendors, potentially offering laboratories additional flexibility and lower support costs.
The operational risk of a single point of failure
Software choices deeply impact business continuity and institutional knowledge. Hanton shared an example of a previous organization that relied on a custom LIMS developed by a single expert. When that developer retired and relocated, he took all knowledge of the system’s backend architecture with him—leaving a critical system with zero internal support.
This type of dependency is a major operational vulnerability. If only one person understands how a critical software platform functions, organizations may struggle to maintain or troubleshoot the system if that individual leaves.
Participant Joseph Torres, test laboratory supervisor at Fluidmaster, explained that his organization addresses this risk by ensuring internal IT staff work directly alongside the primary LIMS developer. This cross-training approach helps preserve institutional knowledge and reduces reliance on a single individual.
Evaluating the future lifespan of laboratory software
The conversation also expanded into broader questions about the future of laboratory informatics platforms. Hanton suggested that standalone LIMS products may eventually become part of larger enterprise ecosystems that integrate quality management, instrument data, inventory management, and other operational functions into unified software environments.
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While many laboratories still operate within disconnected software silos, several attendees noted growing interest in more integrated data environments that could better support analytics, machine learning, and AI-driven workflows.
This shifting landscape highlights the importance of evaluating the expected lifespan of laboratory software systems during early procurement decisions. While laboratories routinely assess the long-term viability of physical instruments, participants noted that organizations do not always apply the same lifecycle analysis to software platforms.
SaaS models and ongoing software maintenance
The financial implications of software ownership models require careful planning. Hanton noted that laboratories are accustomed to budgeting for hardware service contracts, which often average roughly 15 percent of an instrument’s purchase price annually, but many organizations devote less attention to long-term software maintenance planning.
Laboratory leaders must carefully evaluate whether traditional on-premises software or software-as-a-service (SaaS) models better align with their operational needs, regulatory requirements, and IT resources.
In SaaS environments, vendors typically handle much of the infrastructure maintenance, software updates, and server management responsibilities. In contrast, organizations that purchase and host software internally may retain greater control but also assume more responsibility for ongoing maintenance and upgrades.
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The push for open data formats
Proprietary instrument data formats present ongoing challenges for interoperability between laboratory systems. Since many facilities operate instruments from multiple vendors, integrating raw data into unified software environments remains a significant bottleneck.
Hanton encouraged laboratories to advocate for more open and interoperable data standards when working with instrument manufacturers and software vendors. Greater compatibility between systems could help laboratories avoid vendor lock-in and improve the usability of laboratory data for future analytical and AI-driven applications.
Although attendees expressed differing opinions about how quickly laboratory informatics systems will evolve, the roundtable revealed broad agreement on one issue: laboratories evaluating new LIMS platforms should carefully weigh not only present-day functionality, but also the long-term operational, financial, and organizational risks associated with customization, maintenance, and data accessibility.
This article was created with the assistance of Generative AI and has undergone editorial review before publishing.
