The new science of prevention
If a contractor knows that certain types of subcontractors are more likely to have an injury or accident on the job, the question arises, “What can you do about it?”
In the world of advanced analytics and massive amounts of data that help create insights about us, our workers, and our behaviors, this question is being asked more and more.
Some understand the efforts of prevention to say, “If we knew that about them, we wouldn’t hire them in the first place.” This may be the ultimate in prevention, but what about the employees and contractors who are currently on the team? What about the ones who made it through the human resource or subcontracting filter and now are on the jobsite?
Although this is a critical issue, this article will not discuss how to channel these analytics into hiring practices; that is another article with legal ramifications. Instead, this article will address safety programs, training, and wellness programs to have an impact on the frequency of accidents and perhaps even the severity of those accidents.
Implementing an Analysis
Safety analytics is a detailed modeling approach to identifying groups of individuals, processes or conditions that may create an unsafe event or accident. Safety analytics uses external data, as well as observed data points, to provide a powerful tool to gain insights not previously available.
Safety analytics gives users the tools needed to assess, measure and direct an organization to better practices in all aspects of the operation, creating a safer environment for contractors, employees and, potentially, customers. This process will help identify jobs, functions, teams, locations and processes that may have a greater chance of injury or accident. This applies to all industries, including the construction industry. The analysis gives insight, assists in the creation of action plans to reduce or eliminate severity and/or frequency of incidents, and improves the overall work site.
For construction projects this is an important management tool, as detailed history with the employee base might not be available. However, with the power of predictive analytics based on external data, the general contractor can get an understanding of the workforce and its specific safety needs before the project begins. The behavioral data and lifestyle indicators, combined with credible and timely observation data, can be a powerful combination in the efforts of prevention.
Safety audits have been capturing excellent observation data for many years, but external data has been limited or, in some cases, underutilized. These data points can be excellent predictive items as managers consider where to direct the specific safety programs. As with any safety effort, the embracing of the program from the grass roots is essential to its success. Safety analytics can assist in identifying key groups where these efforts need to be directed.
Safety Analytics at a Practical Level
We have all seen the growing use of analytics in our daily lives, from purchase scans at the grocery store to the online purchase of books. How do suppliers know the public will be interested in the other books suggested? How do they know what coupons to send out? The use of insights based on data patterns affects most purchases. Certainly in the world of insurance underwriting, these data points are always used in calculating car and homeowner’s insurance options and pricing.
It seems that the basis of most safety analytics to date has been historical and observed data. The very nature of a safety audit is based on the conditions of the location and the type of procedure being performed. The human element, which is key to all safety programs, does not seem to have the same degree of data applied. In the new world of safety analytics, information on lifestyle indicators and other publicly available data can be important drivers to identify groups of employees or contractors who may have a greater chance of sustaining a workplace accident or injury.
Once identified, what should a manager do about the results of the analysis? For example, in the case of drivers who drive more than 50 miles to the jobsite every day, it has been determined that in some cases, they have a greater chance of having an accident. If the drivers know this, they might try to structure a job assignment that changes their route or reduces their total miles driven, especially as they get to the end of their shift.
Distance to the jobsite from home is just one example of the hundreds of predictive data elements that can offer insights. Targeting the response in a practical implementation is key; in fact, many would say that the implementation of the insights is as critical as the findings themselves. Cultural acceptance of the change and support for the goal of a safer environment for all must be emphasized. Many labor unions have been very supportive of these efforts, as safety programs can be the best way to protect and enrich the lives of their membership.
Other corrective actions that impact the frequency of accidents can be employed but must be updated as procedures and tasks change. The operational side of construction projects is constantly changing. It is critical to update and refine analytic models to meet these changing conditions. A dashboard to monitor the programs is perhaps another essential tool to maintain the culture of constant improvements.
Mark Charron, principal, Deloitte Consulting LLP, and David Duden, director, Deloitte Consulting LLP, co-authored this article, which was first published in Modern Contractor Solutions. TM