Rapid advancements in fields like drug discovery, biotechnology, and materials science are pushing laboratories to produce results faster while maintaining precision and compliance. This surge in innovation places greater demands on lab operations, requiring seamless workflows, optimized equipment use, and streamlined processes. As research timelines tighten and budgets face increased scrutiny, lab managers play a pivotal role in reducing inefficiencies and controlling costs to ensure their teams can meet these growing expectations.

A new survey conducted by Censuswide on behalf of MachineQ, a Comcast company, sheds light on key challenges facing laboratories and highlights opportunities to optimize operations through emerging technologies like the Internet of Things (IoT) and artificial intelligence (AI).

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The survey included 400 US-based laboratory professionals at life sciences companies with over $1 billion in annual revenue and functional roles in lab operations, asset management, and maintenance and calibration.

Unplanned downtime and asset tracking challenges

One of the most significant challenges revealed in the survey is unplanned downtime. Nearly 60 percent of lab professionals reported experiencing operational disruptions due to equipment failures, missed calibration schedules, and difficulties in locating critical lab assets. Among labs with annual revenues between $1 billion and $10 billion, this issue was more pronounced, with 62 percent reporting downtime-related setbacks.

Despite these challenges, many labs continue to rely on outdated asset tracking methods. The survey found that:

• Fifty-six percent of lab professionals manually track equipment utilization.
• Fourteen percent have no system in place for monitoring assets.
• Only 30 percent use real-time monitoring technologies.

Without accurate asset tracking, labs struggle to optimize equipment use, leading to inefficiencies and unnecessary costs.

According to Steve Corbesero, Jr., senior director of product and solutions at MachineQ, the primary barriers preventing labs from adopting real-time monitoring and other efficient systems are the associated costs and the challenges of integrating new technologies with existing legacy infrastructure.

“Many labs have relied on manual tracking for years, and shifting to real-time monitoring requires investment and change management,” he explains. “However, as labs recognize the benefits—immediate data access, better resource allocation, and improved efficiency—we're seeing growing adoption. The industry is moving toward connected labs, and real-time monitoring is quickly becoming the new standard.”

The case for real-time monitoring

The survey highlights a strong correlation between technology adoption and improved lab operations. Among respondents who use real-time monitoring for asset tracking, 62 percent feel confident in their ability to justify equipment investments, compared to 51 percent of those without monitoring systems. Additionally, 68 percent of labs using automated tracking believe they have the right amount of equipment to meet their needs—whereas only 35 percent of labs without utilization tracking feel the same.

These findings emphasize the need for lab managers to move beyond manual tracking and embrace digital solutions that provide real-time insights. IoT-enabled tracking systems, for example, allow for automated equipment audits, predictive maintenance, and enhanced resource allocation—key factors in optimizing workflows and reducing costs.

Looking ahead: Investing in the future

Despite the benefits of IoT and AI/ML technologies, only 29 percent and 28 percent of labs, respectively, are currently using them. However, the survey indicates a strong shift toward adoption, with 85 percent of respondents planning to implement IoT and 87 percent planning to integrate AI/ML into their lab strategies over the next two years.

“As AI and ML advance, they'll unlock deeper insights—predicting maintenance needs, optimizing equipment usage, and even automating complex workflows,” says Corbesero, Jr. “The future of lab operations will be increasingly data-driven thanks to IoT, AI and ML, with real-time intelligence improving efficiency, reducing downtime, and enabling smarter decision-making.”

As lab managers prepare for the future, investing in advanced technologies will be critical in driving efficiency, reducing costs, and maintaining a competitive edge. By adopting real-time monitoring, predictive analytics, and automated asset tracking, laboratories can transform their operations and ensure they are equipped to meet the demands of modern research and development.