There’s nothing new about the notion of using leading indicators to manage safety. What’s new though is the availability of powerful business intelligence (BI) tools to identify and track predictive metrics and to transform that data into powerful insights to power more effective decision making and improve environmental, health and safety (EHS) management.
Business Intelligence, or BI as we know it today, has a longer history than you might think; one that predates computers and other technological advances. In fact, the first term of ‘business intelligence’ appeared way back when in 1865 by Richard Millar Devens in his Cyclopaedia of Commercial and Business Anecdotes in that year.
Devens used the term to talk about how a banker, Sir Henry Fumese, used “business intelligence” to gain a leg up on his competitors. Through careful study, he gained knowledge of the political issues, risks, and general market conditions of that time. And there you have the first recorded use of BI.
It wasn’t until the 20th century with the emergence of computers that BI really started to gain recognition. The 50s, 60s, and 70s came and went and with them the development of various enterprise applications but when it came to accessing data from multiple sources, they were one-dimensional reports. The problem was that the underlying data in these reports was very siloed; there wasn’t a single, consistent view of the data.
Fast forward a decade and hello, data warehouses! With the likes of Ralph Kimball (one of data warehousing’s original architects) and Bill Inmon (considered by many to be the father of the data warehouse) data warehouses were born and with them came the opportunity to bring together disparate data sources and store them in one place. Over the next two decades the number of companies using BI exploded and vendor numbers mushroomed. More and more companies were starting to understand the true value of the BI currency, and how it could help them.
Today most large organizations use BI as a key instrument to identify, among other things, patterns in customer buying behavior, predicting future stock requirements and detecting fraud. To do this, they have collected large volumes of transactional data and have applied sophisticated statistical algorithms to find patterns. All of this made possible due to process automation making more data available and the continual decrease in the cost of computing power.
Your Employees’ Safety, in 1s and 0s
When it comes to the EHS realm, with its large amounts of data stored across organizations surely there is a need for “health & safety data warehouses.” Buried in these warehouses are patterns, awaiting discovery and analysis that could assist with decision making when trying to determine where future incidents could occur.
EHS professionals are looking for ways to predict and prevent significant incidents. Traditionally, using statistical methods on historical data to determine what happened and why gives them a good indication of past performance, such as how many incidents of each type have occurred. This allows them to establish what has caused them. Using this information, an organization can learn from previous events and put controls in place to eliminate or reduce hazards and mitigate risks.
So EHS and BI are the perfect bedfellows!?
Moving Towards Operational Excellence
EHS is a highly-regulated realm. Organizations need to measure and record significant amounts of data to ensure, and prove their, compliance to governing authorities , such as incidents, near misses, absence due to health & safety accidents, safe behaviour observation, inspections, and root cause analysis investigations, just to name a few.
Traditionally, this information has been stored for compliance reasons and mainly used in isolation to tactically improve business operations. However, by using BI techniques, it is possible to significantly reduce EHS incidents and help organizations move towards operational excellence. Ultimately bringing greater value to the organization over and above just meeting compliance requirements.
When it comes to more mature organizations, they will use predictive analytics whereby they will apply rules to their historical EHS data. This can then be combined with external data to predict incidents that may happen in the future along with probabilities. When implemented properly with employees being able and willing to report near misses and incidents, this is a good method of predicting certain types of incident.
However, to actually prevent the incidents from happening, EHS professionals have to digest the results of the predictive analysis and determine the correct courses of action that need to be taken.
To fully benefit from BI predictions, EHS systems should ideally go one step further than just forecasting what could occur by suggesting actions that should be taken along with any associated consequences of each option given. This prescriptive analysis can help an organization make decisions around maximizing future opportunities or give the best chance of mitigating any risks with which they are faced.
More Data, Fewer Incidents
Advanced BI provides many potential benefits to EHS. One example is more reliable hazard detection processes: rather than relying solely on human expertise, advanced analytics and machine learning can be used to detect issues resulting in potential improvements in accuracy.
BI also gives organization a more reliable way of sharing best practices. If we look at best practices in risk detection as an example, they can be codified into computer algorithms and easily shared across multiple geographies and divisions. This results in greater consistency across the organization, as employees do not have to be relied on to share best practices anecdotally.
These all result in an increase in the detection of risks that will lead to a decrease in the number of serious incidents.
The Road to a Safer Working Environment
EHS BI should involve sifting the huge amount of EHS data that is collected by organizations, finding the relevant information, and turning it into prescriptive actions that will lead to a safer and more compliant working environment.
Having the ability to quickly turn raw data into actionable information can make the difference between smart EHS decisions and costly mistakes. But making sense of all the information from different data sources can be a challenge. That is why it is imperative to have the right BI tools in place to put data to work enabling easy identification of insights and the confidence to act, ensuring focus remains on performance improvement.
For information about how SAI Global can help you manage EHS risks contact us.