An automated metrics system to measure and improve the success of laboratory automation implementation

The authors describe a system for collecting usage metrics from widely distributed automation systems. An application that records and stores usage data centrally, calculates run times, and charts the data was developed. Data were collected over 20 months from at least 28 workstations. The application was used to plot bar charts of date versus run time for individual workstations, the automation in a specific laboratory, or automation of a specified type. The authors show that revised user training, redeployment of equipment, and running complimentary processes on one workstation can increase the average number of runs by up to 20-fold and run times by up to 450%. Active monitoring of usage leads to more effective use of automation. Usage data could be used to determine whether purchasing particular automation was a good investment.