Beyond the Biobank: Modernizing Biospecimen Management for Scalable, Compliant Growth

Rick Hart, Senior Scientific Informatics Visioneer, is a veteran scientific informatics expert with a long career in consulting and delivering scientific informatics solutions

Introduction – Why Biospecimen Management Still Matters and is Actually Growing in Importance

In today’s life sciences and biotech landscape, biospecimen management is no longer a back-office function; it’s a strategic enabler of scientific insight, regulatory compliance, and revenue recognition. As multi-omics, precision medicine, decentralized trials, and global collaborations reshape the industry, organizations face increasing pressure to modernize how they collect, track, store, and utilize biospecimens. Yet too often, digital transformation efforts stall at the starting line. Leaders say, “We need a LIMS,” without a clear understanding of the operational requirements, data governance needs, or cross-functional dependencies that come with managing biological materials at scale. Drawing from years of real-world experience, we believe that successful biospecimen management begins with strategic clarity and continues well beyond system implementation. This article explores why and how organizations must reframe their approach if they want to scale responsibly and deliver lasting value.

Implementation Is Only the Beginning in Your JOURNEY

For many organizations, selecting and implementing a biospecimen management system feels like the finish line. In reality, it’s just the starting block. The true impact of a biobanking or LIMS solution is realized not at go-live, but in the months and years that follow, when the system must scale with the business, enable operational efficiencies, and support rigorous compliance.

Many projects falter in the critical post-implementation phase. Configuration decisions made early, often under tight deadlines, can limit flexibility down the road. If metadata standards, controlled vocabularies, and user workflows aren't well-defined from the outset, teams end up improvising. And in a regulated environment, improvisation quickly becomes risky.

We’ve seen it happen: a system goes live with minimal validation, limited training, and poor stakeholder alignment. Samples are entered inconsistently, data quality degrades, and confidence in the system erodes. What starts as a digital transformation initiative devolves into a workaround culture, where spreadsheets resurface and audit trails break down.

Avoiding that outcome requires more than good software. It requires committed leadership, ongoing investment, and clear data governance. It means planning for Day 2 from Day 1, with a strategy that includes training, stewardship, performance monitoring, and cross-functional accountability.

Implementation is not an endpoint; it’s a handoff. The baton passes from the project team to the business owners, and without a strong plan for that transition, even the best systems underperform. True success in biospecimen management begins after the system is live, when the organization embraces it as a living, evolving part of its scientific and operational fabric.

From “We Need a LIMS” to the Right-Fit Solution

It often starts with a familiar refrain: “We need a LIMS.” But peel back the layers, and you’ll frequently discover that what an organization truly needs is something more specific or altogether different. In many cases, they’re not asking for a Laboratory Information Management System in the traditional sense. What they need is a biobank management platform, an ELN, a specimen tracking tool, or a hybrid solution tailored to their sample lifecycle.

This is why requirements gathering cannot be a checkbox activity. Too many projects begin with a predetermined solution in mind, before anyone has mapped the business processes, interviewed end users, or clarified what success looks like. At 20/15 Visioneers and in my own consulting work, we’ve made it a rule to never begin a system selection without first understanding the “why” behind the request.

We often uncover a fundamental language gap. Stakeholders use “LIMS,” “ELN,” “biorepository system,” and “inventory tracker” interchangeably. Internal teams struggle to align on what constitutes a project vs. a program or a POC, Prototype, Pilot vs. an MVP. Without a shared vocabulary, even the best-intentioned initiatives lose momentum. 

To bridge this gap, we always begin with business process mapping and term definition. What are users doing today? What do they envision tomorrow? Where are the pain points, the handoffs, the manual workarounds? This exercise not only informs system requirements but also clarifies the broader organizational goals and encourages cross-functional buy-in.

Right-fit solutions don’t come from chasing buzzwords or buying what your peer company bought. They come from a deliberate, contextualized approach to understanding what the system needs to support, scientifically, operationally, and financially.

Sample to Invoice: Operationalizing Data Flow

One of the most overlooked aspects of biospecimen management is how deeply it connects to revenue operations. From the first conversation between business development and a prospective client to the final invoice sent by finance, each touchpoint in the lifecycle of a sample must be operationally aligned and system enabled. We call this concept “Opportunity to Cash.”

Here’s the reality: most biorepository and bio services organizations are selling complex, highly customized services, whether it's sample collection, processing, storage, distribution, or analytical support. But all too often, their internal systems treat these as discrete events. Business development tracks deals in a CRM. Operations track samples in a standalone biobank system. Finance handles billing manually in an ERP or financial system. And none of them speak the same language.

What happens next is predictable: sales commit to a timeline that operations can’t support. Services are delivered that finance can’t bill. And leadership lacks visibility into margins or performance.

This is where biospecimen management intersects with enterprise architecture. The systems must not only manage the lifecycle of a sample, but they must also align with how the business makes money.

That means:

• Defining a common taxonomy across departments (e.g., sample types, services, storage SKUs)

  
  

• Capturing key metadata at the point of intake to drive downstream traceability and billing

  
  

• Automating handoffs between systems through thoughtful integration, not just data dumps

  
  

• Embedding audit-ready documentation to meet regulatory and contractual obligations

In short, the biorepository platform isn’t just a scientific tool; it’s a revenue engine. When properly architected, it enables transparency, efficiency, and faster time-to-value. When neglected, it becomes a bottleneck that drains resources and erodes customer confidence.

Bringing this all together requires more than picking the right software. It requires strategic alignment between technical implementation and business operations. From day one, we’ve helped clients solve this challenge by focusing on workflows, integration points, and financial traceability.

Architecting for Resilience: Governance and Stewardship

In biospecimen management, longevity isn’t just about system uptime; it’s about sustaining trust in the data, consistency in operations, and clarity in decision-making. That’s why mature organizations don’t stop at software implementation. They invest in governance and stewardship to ensure their sample ecosystems can adapt, scale, and perform under pressure.

We’ve seen it too many times: a biobank system is installed, and six months later, users are creating workarounds. Naming conventions drift. Fields are left blank. Critical attributes are entered inconsistently across teams or locations. The system is still online, but its integrity is quietly eroding.

Avoiding this scenario requires more than SOPs. It demands a data governance framework with clearly assigned roles, ownership, and accountability. That includes:

• Defined data standards and vocabularies for sample types, storage conditions, assays, and service codes

  
  

• Metadata policies that distinguish required vs. optional fields, and when exceptions are acceptable

  
  

• Designated data stewards empowered to maintain consistency, resolve conflicts, and educate users

  
  

• Governance committees or working groups to align system changes with evolving business needs

This structure enables agility without sacrificing compliance for high-growth and regulated organizations. When data can be trusted, more processes can be automated, forecasting improved, and insights driven at scale.

Governance also includes the architecture itself. Instead of chasing an all-in-one platform that promises to “do everything,” we’ve found success in building fit-for-purpose systems that are integrated under a unified data strategy. Whether using middleware, APIs, or data virtualization, the goal is interoperability without unnecessary complexity.

But here’s the key: resilience is not a one-time deliverable. It’s a mindset that must be embedded in your organizational culture, supported by training, reinforced through metrics, and protected by leadership.

Open Source and Light-Touch Models: When Less Is More

If you are an industrial or at scale science-oriented organization and you’re dealing with services and high throughput, proceed cautiously with open source.  If you’re a government lab and your Capex and Opex budgets are not reliable you might think more seriously about open source with the proper support model.  This is both from a transactional/operations to an AI/ML perspective.

What’s Next for Biospecimen Management

As science moves faster and business models become more dynamic, biospecimen management must evolve from a back-office function to a strategic capability. The future isn’t just about better software but better alignment between people, process, and technology. Whether you’re scaling a global biobank, optimizing your billing pipeline, or integrating with digital health platforms, the ability to manage biological materials with precision, compliance, and agility will increasingly differentiate the leaders from the laggards.

We believe the next wave of biospecimen innovation won’t come from one-size-fits-all platforms. It will come from fit-for-purpose ecosystems that are smartly integrated, deeply governed, and built to scale with the mission. This will require a shift in mindset: from standalone tools to connected workflows, from departmental ownership to cross-functional stewardship, from “just get it implemented” to “how do we sustain and grow?” And we cannot emphasize enough the importance of proper scientific data management which is FAIR (findable, Accessible, Interoperable, Reusable).

That’s why we continue working at the intersection of science, systems, and strategy. Whether through vendor selection, project recovery, or long-term digital transformation, our mission is to help organizations turn biospecimen management into a value driver, not a bottleneck.

If this perspective resonates with you or you’re facing these challenges firsthand, we’d love to hear from you. Let’s start a conversation.