With ever-increasing demand for greater efficiency, scientific organizations are turning to data-intelligence systems to provide visibility into lab operations and help drive decisions.

As the complexity and interconnectivity of scientific systems continues to rapidly change the laboratory environment, there is an ever-increasing demand for higher efficiency with diminishing bandwidth to achieve it—this often results in too much time being spent on operational issues rather than science.

Advanced data-intelligence systems in concert with expert guidance are quickly becoming the mainstay for all laboratory operations. The demand for operational excellence is growing rapidly, even to the level of machine learning, where artificial intelligence is currently being explored to expand lab-wide visibility and efficiency with unprecedented refinement.

Advancing lab operations can be viewed as three distinct phases: simplification, optimization, and transformation. Simplification requires an assessment of all laboratory assets to know where things stand.

As we have seen, data-intelligence tools help to visualize the entire fleet and allow better control over assets. Optimization combines utilization data with other instrument attributes, such as service history, age of equipment, and end-of-service terms. A risk score can be developed to measure the ‘health’ and viability of each instrument.

Finally, transformation of all lab operations to a lab-wide, data intelligence management system ensures that all instrument utilization and expenditures achieve maximum efficiency. Data-driven decisions are becoming the standard for best-in-class laboratories and organizations.

The ability of scientific organizations to react swiftly to changing scientific, financial, and business conditions is of paramount importance in today’s rapidly evolving scientific landscape. The global pandemic exemplified how rapidly and explosively conditions can change.

The ability to adapt quickly to such monumental shifts is necessary and achievable by optimizing lab performance using new digital technologies and expert analysis to enhance the visibility and utilization of assets.

The first step in achieving operational agility is to deploy an asset performance program that maximizes the utilization of instrumentation while simultaneously reducing operating costs. The aim of asset performance management is to optimize lab efficiency and productivity for any given condition by improving the reliability and availability of all assets.