How are predictive analytics tools changing safety reporting best practices?
What is predictive analytics?
Predictive analytics refers to any software that can extract information from existing data and use it to predict trends and behavioral patterns. It's usually implemented to predict future outcomes but the same technology can also be used to explain or understand any type of unknown pattern in the past or present.
In addition to making forecasts about the future based on available data, this kind of software also analyzes hypothetical scenarios and recommends courses of action based on their likely outcomes.
What is safety reporting?
Safety reporting is the collective processing of all information regarding incidents, accidents, work-related illnesses, absences, near misses, hazards, and property and environmental damages. Safety data is collected in order to facilitate investigations, identify causes, understand trends, learn from past failures, and prevent future occurrences. Reports are also used to notify relevant authorities both within and outside an organization about an occurrence, which may be required by law. Accurate and comprehensive safety reporting is a crucial part of successful workplace health and safety management.
How is safety reporting being impacted by predictive analytics?
Robust analytics tools are changing the following aspects of safety reporting processes:
Risk assessments: a traditional risk assessment follows a series of systematic steps that rely on a prescribed matrix to calculate the probability of an incident occurring. Predictive analytics can enhance the risk assessment process by identifying functional, procedural, potential, and even obscure hazards and failures, like in the event of a sudden plant breakdown. This may be one of the most important breakthroughs in the field of safety.
Health and safety policies: until now, organizations had to formulate and draw up generic policies based on a variety of assumptions. With predictive analytics, those assumptions can be replaced with data-driven facts and trends that management teams can use to draft more effective EHS policies.
Data collection and communication: one reason employees shy away from reporting incidents is the cumbersome and excessive paperwork involved. The reasons vary—some employees aren't comfortable filling out forms, some get impatient with the task, and some may simply be irritated at having to interrupt their routine tasks—but whatever the reason, it can lead to poor record keeping. Predictive software can analyze user habits and behaviors in order to determine which employees might benefit from a mobile inspection process for example, and which employees may require additional inspection training.
Incident mitigation: the primary goal of safety reporting is to collect data, learn from it, and apply controls to prevent repeat incidents. Traditional safety reporting methods focus on gathering information, but predictive analytics tools go further by analyzing all available information to uncover the causes of incidents and proactively identify new trends and behaviors for EHS teams to monitor and manage.
Enhanced analytics is an emerging technology every organization should leverage in order to build a more efficient safety reporting system and ultimately, improve workplace safety by predicting risk and preventing incidents.
To get more out of your safety data, check out the EHS Professional’s Guide to Improving Safety Outcomes with Data.
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