Personal Protective Equipment

Picture this—an electronic employee self-service compliance system, a web-based field safety observation system and a completely integrated management access self-service electronic incident reporting system all linked together, giving your company the tools to discover trends in knowledge, behavior and accident specifics.
If that sounds like next-generation technology to you, think again. NSTAR Electric & Gas, based in Boston, Massachusetts is currently in the final phases of implementing such a system.

Information is power
Harnessing the power of data for the purpose of determining circumstances, including how, where and when accidents have occurred, is nothing new. Lagging safety information has been available for nearly 100 years. Companies have used this data to make comparisons against their own performance as well as serve as an indicator of experience against other similar industries.
Using predictive-type designs is a newer concept that utilizes analysis of gathered data to indicate where problems may be most likely to occur. As the information matures, a predictive model can be designed into the system. Using that model, utility safety professionals can flag potential problems when one, two or more predetermined criteria correlate with one another.

Analyzing and processing
Gathered data has powerful benefits in quickly discerning where issues have a strong positive correlation. For example, let’s say an employee has difficulty passing an electronic, web-based safety lesson. Email alerts are sent to a safety compliance officer. Inquiries are made about the employee’s time on the job, progress, etc.
Simultaneously, the safety supervisor corraborates the information by reading field safety observations about the affected employee.� Perhaps the employee may have had an unsafe observation while performing work in the field. Safety and compliance looks for those positive correlations where both variables increase together or where specific markers are set and triggered.
Frequency, percentages, score, behavior and severity are all current criteria in both operating applications. NSTAR utilizes the online training and field observation component systems data to assess each case. Each data set is immediately evaluated to determine what underlying issues (behavior, knowledge or skill) may need intervention.

Moving the system to integration
NSTAR is now in the development phase of completing its electronic data acquisition and data management system segment. The program is being provided by SIGMA Corporation of Massachusetts and, once lagging data is integrated into the system platform, historical data will be added to the matrices.
A self-service accident reporting system will enable NSTAR supervisors and managers to enter accident information on-line in real time. Accident data is then transmitted to corporate safety, risk and claims, and medical and higher-level management in the affected business unit.
With this system, the benefits going forward for NSTAR are clear. If all parties can use the information it will provide to take immediate, positive and effective action, the company can continue to drive down unplanned events and improve safety. iP