Safety Big Data sets can be used to predict workplace injuries with accuracy rates as high as 80-90 percent, according to a white paper based on research conducted in collaboration with a team from Carnegie Mellon University, one of the leading institutions in the field of Big Data analytics.
Safety Big Data sets can also be used by organizations to create leading indicators to improve safety outcomes:
• A Fortune 150 energy company reduced its injury rate by 67% within 18 months
• A Fortune 150 manufacturer reduced its lost work day rate by 97% within one year
• A top five public U.S. university saved more than $20 million in insurance fees by reducing injuries across four years of on-campus construction projects
• A top 20 construction company achieved significant safety improvements including 90% of worksites experiencing no lost-time incidents
• A top ten specialty contractor reduced its workers’ compensation fees by 57% and 66% two years in a row even while total hours worked was increasing
Big Data is making its case as the most effective tool at our disposal to reduce workplace injuries and save lives.
Drowning in data
According to IBM, 25,000,000,000,000,000,000 (that’s 2.5 quintillion) bytes of data are created daily and 90% of the data in the world was created in the past two years. We are clearly in the era of Big Data.
The world of workplace safety is no different. Every day, safety managers and other company personnel collect safety data in the form of safety inspections and observations, near misses, incident reports, JSAs (job safety assessments), and audits. Companies are also collecting machine-based data from portable gas monitors, GPS devices, vehicle dashboard monitors, biometric systems (like heart rate monitors), and accelerometers.
However, rather than expertly navigating the sea of Big Data, many companies and individual safety professionals feel as if they are drowning in it.
The direct result: many companies are getting very little, if any, value from their investment in their data collection initiatives. The indirect result: they are frustrating their team members who they ask to spend significant time collecting data.
This results in what Dr. Chuck Pettinger, a leading safety expert, has coined a “vicious cycle.” A vicious cycle occurs when a company can’t provide any meaningful insights from their data. Data collectors become disillusioned and either begin “pencil whipping” the data, or just give up and stop collecting it altogether.
Navigating the sea of Big Data
Just as we are in the era of Big Data, we are also in an era of massively expanding computing power. The smartphone you carry around today is nearly as powerful as the computer that sat on your desktop in the early 1990s. In part, this is the result of Moore’s Law which states that the number of transistors on integrated circuits (those that power computers) doubles approximately every two years.
With more powerful computers, we can effectively navigate the sea of Big Data rather than drown in it by harnessing the power of advanced and predictive analytics. Advanced and predictive analytics help us move up the Analytics Pyramid to answer more important business questions than basic data access and reporting systems will allow.
Rather than just using data to answer simple business questions such as “what happened,” or “where, when, and how often,” we can transform raw data into leading indicators. These leading indicators help to answer the more difficult business questions that leaders want answers to, such as “why is this happening” and “what if these trends continue”?
By using predictive models, we can even answer the penultimate question of “what will happen next?” Once we do that, we can answer the ultimate and most important question on the minds of senior leaders – “how do we achieve the best outcome?” In the case of workplace safety, this means aligning people and resources optimally to achieve zero incidents.
To effectively answer these more important yet challenging business questions, more and more complex data analytics strategies should be employed. Basic data access and reporting methodologies represented by simple reporting tools can only return lagging indicators. The massive computing power available to us today must be harnessed to perform statistical analysis, forecasting and extrapolation, and even predictive and optimization modeling.
This creates a “virtuous cycle.” This is when team members who are collecting data are rewarded for their efforts. As a result, they want to collect even more data to feed the analytics programs that are returning valuable leading indicator and predictive information. As you do more with your data, the folks collecting it see the positive outcomes of their efforts and invest even more time in the data collection process, which allows for deeper analytics, which allows for more positive outcomes, and so on; until a “flywheel” effect takes hold.
Sink or swim
Are computers, machines, and data the most important elements in eliminating workplace injuries and fatalities in this era of Big Data? Absolutely not.
First, people must realize that to NOT employ data analytics in workplace safety is to ignore one of the most effective ways to improve safety outcomes. Next, people should be motivated to go out and collect the data needed to move up the analytics pyramid to ultimately predict and prevent workplace injuries. Then, something must be done with the data collected so that a virtuous cycle, rather than a vicious cycle, can be achieved. Next, savvy analytics and safety professionals are needed to team up to interpret the results of our analytics efforts.
But most importantly, and in the final step of the process, leaders are required – at all levels of an organization – to take the results of the analytics and do something with them that leads to safer outcomes. Only people can effectively use the findings from leading indicator and predictive analytics programs to change human behavior and physical conditions in the workplace.
A recent study by Bain and Company found that “early adopters of Big Data Analytics have gained a significant lead over the rest of the corporate world.” They are outperforming their competitors, are twice as likely to be in the top quartile of financial performance, and are five times as likely to make decisions faster.
One key question has already been answered; Big Data and analytics tools are both available and proven. One key question remains – who are the safety leaders who will adopt them most effectively?
