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Recordable incident rate decreased by 76%
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Lost time injuries decreased by 88%
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Lost work days decreased by 97%
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Property damage cases decreased by 22%
Challenge
From 2006 to 2008 Cummins Rocky Mountain (CRM), a Distributor for Cummins, Inc. with 14 locations and nearly 1,000 employees across nine states in the U.S. Rocky Mountain region, had a safety risk management program based on lagging indicators that returned inconsistent results. They recorded high incident rates in 2006, lower rates in 2007, but then higher rates again in 2008.
In the fall of 2008, CRM implemented a leading indicator JSA (Job Safety Assessment) Process to focus on predicting and preventing workplace safety incidents. This process has three main components: first, all employees assess workplace hazards prior to starting their work and then manage those hazards throughout their work; next, all levels of management verify that hazards are being managed by observing and engaging with employees while they work; and finally, management resolves uncontrolled hazards in a timely manner.
However, throughout the early implementation phase of the process, because they utilized a manual data collection procedure that was difficult for frontline employees to adopt, CRM was only able to record about 100 JSA audits per month. Not only was this not enough safety leading indicator data, CRM had no way to perform advanced and predictive analytics. CRM realized they needed an automated safety software system that would enable the processing of a larger volume of data as well as provide more advanced analytical tools if they wanted to more consistently prevent injuries and manage their risk.
Solution
In 2009, CRM implemented SafetyNet, Predictive Solutions safety software system. The SafetyNet software system was easily configured to fit their existing JSA observation and safety checklist process, allowing for easy adoption by their frontline workforce. SafetyNet also delivered advanced and predictive analytics capabilities that CRM’s data driven, Six Sigma based management team could use to prevent workplace injuries.
Results
Within just 12 months of implementing SafetyNet, CRM increased its JSA observation rate by 700% to over 800 observations per month. With this larger data set, SafetyNet’s advanced and predictive analytics helped CRM trend its safety leading indicator data and predict and prevent workplace injuries. CRM’s recordable incident rate decreased by 76%, lost time injuries decreased by 88%, lost work days decreased by 97%, and property damage cases decreased by 22%.
Interestingly, now that there are so few lagging indicators (e.g. incidents) being recorded, CRM must rely even further on safety leading indicator data to sustain their injury prevention and risk management process. In the year after initial implementation of SafetyNet, CRM recorded 21 lagging indicator data points, while recording nearly 3,000 leading indicator data points using its JSA observation process in SafetyNet.
In addition, CRM’s use of SafetyNet has modernized its safety function, which is now being used as a model for how to employ leading indicators to manage other CRM business functions.
Finally, CRM’s success was recognized by the Board of Directors of Cummins Inc. As a result, its JSA Process and SafetyNet software are now being deployed globally by Cummins Distribution Business Unit across its more than 600 locations in 190 countries and 16,000 employees.
