The gap between good and great labs lies in how they embed innovation into their workflows. During Lab Manager’s Innovating the Future Digital Summit, Laura Sievers, clinical director of pathology and laboratory medicine at Washington University School of Medicine, explored what it means to stay “ahead of the curve” in laboratory innovation.
Through a vivid comparison of two fictional laboratories, Riverside and Evergreen, Sievers illustrated how proactive and reactive approaches to innovation yield vastly different outcomes. Her insights offer a roadmap for labs seeking to embed innovation into daily operations while maintaining balance, efficiency, and sustainability.
The three Rs of sustainable laboratory innovation
Sievers introduced the “three Rs” of laboratory balance—routine, relief, and resilience—as a compass for integrating innovation without disrupting essential functions.
- Routine anchors a lab’s core reliability: specimen handling, data integrity, and compliance. Before layering on new tools, leaders must ensure these foundational processes remain stable.
- Relief represents the tangible benefit of innovation—simplifying work, reducing manual effort, and giving staff time to focus on critical thinking and collaboration.
- Resilience prepares teams and systems for change through cross-training, flexible workflows, and scalable infrastructure.
By protecting what works, lightening the load where possible, and strengthening systems for the future, Sievers emphasized that innovation becomes an evolution rather than a disruption.
From status quo to continuous improvement
Sievers contrasted the experiences of two laboratories—Riverside, which takes a reactive stance toward innovation, and Evergreen, which approaches it as a continuous process. Riverside maintains stable but stagnant operations, waiting to adopt new solutions until required by regulations or crises. Evergreen, by contrast, dedicates five percent of its operational time to staff-led improvement projects. This small investment fosters creativity, ownership, and steady progress.
At Evergreen, brief weekly process reviews and microlearning sessions help staff explore small, meaningful improvements. These routines embed innovation into the lab’s DNA. As Sievers explained, “Balance doesn’t come from avoiding innovation. It comes from embedding it.”
Building a culture of innovation
Most innovation failures, Sievers noted, stem not from poor ideas but from poor integration. To make new tools “stick,” laboratories must first cultivate a culture of innovation—one that is open, iterative, and connected to organizational goals.
Every investment should tie to a specific purpose, such as improving turnaround time, sustainability, or quality metrics. Structured implementation pathways—pilot projects, review committees, and clear success metrics—allow staff to test ideas confidently. Identifying “innovation champions” across lab sections further helps teams adapt by sharing feedback and fostering peer learning.
Sievers visualized this as an innovation culture cycle: ideate, pilot, implement, reflect, and scale. Each iteration strengthens confidence and capacity, transforming innovation from a one-time event into an ongoing habit.
Partnerships as a force multiplier
Innovation, Sievers stressed, rarely succeeds in isolation. Both internal and external strategic partnerships expand a laboratory’s ability to innovate and sustain change.
- Academic-industry collaborations bridge research insight with practical application.
- Vendor partnerships evolve procurement into co-development, aligning tools with real operational goals.
- Cross-institutional collaborations accelerate standardization and shared learning.
Internally, strong collaboration with IT, supply chain, and executive leadership ensures seamless data integration, sustainable procurement, and organizational alignment. “Innovation thrives in connection,” Sievers said. “It’s about the network of partnerships we keep.”
Measuring what matters
To prove value and sustain momentum, laboratories must measure innovation’s impact. Sievers outlined four categories of key metrics:
- Operational: turnaround times, automation uptime, workflow efficiency
- Financial: cost per test, reagent use, and energy savings
- Quality: error reduction and data integration improvements
- Sustainability: waste diversion, energy reduction, and use of eco-efficient materials
She encouraged labs to combine quantitative metrics with qualitative feedback from staff to capture both performance outcomes and human impact. “Numbers matter,” she said, “but stories connect.”
Innovation in action: AI scheduling and sustainability
The session’s “Evergreen” lab illustrated how small innovations drive measurable results. By adopting an AI-driven scheduling system, Evergreen reduced manual planning time, cut labor costs, and improved morale. Freed capacity allowed staff to pursue larger goals, like partnering with vendors on a reagent take-back program that reduced waste and saved 15 percent in material costs. In contrast, Riverside’s surface-level sustainability efforts—recycling bins and lightbulb swaps—added work without impact. The difference, Sievers concluded, lay not in resources but in integration.
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The future-ready lab
Sievers closed by highlighting three overarching themes shaping tomorrow’s laboratories:
- Workforce evolution: Upskilling staff in data, automation, and digital systems to complement technical expertise.
- Integration focus: Connecting data, people, and processes for unified, real-time decision-making.
- Regulatory alignment: Treating compliance as a strategic advantage by anticipating evolving standards around AI, data security, and sustainability.
The labs that will thrive, she noted, are those that view innovation as intentional, measured, and human-centered. “Being ahead of the curve,” Sievers concluded, “isn’t about predicting the future—it’s about preparing your lab to shape it.”
