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.
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