Knowledge is power. It’s what we were told growing up – that we needed to gather knowledge in order to succeed. The trouble with that advice today is that we’re surrounded by knowledge. The computing power in our pockets is pretty incredible, and knowledge is so easy to come by that it can be difficult to know where to begin.
From the safety perspective, we often talk about the importance of data, and it’s worth pointing out the difference here between data and knowledge. More importantly, making a distinction between knowledge and intelligence is crucial. In the image, it’s easy to see that data, information and knowledge aren’t power. They are simply building blocks to gain insight and wisdom – intelligence, you might say – that gives us something to act on.
So often in the world of ground service, we tell ourselves that when things aren’t going wrong, they must be going right. Logically, that just doesn’t hold up. Not being bankrupt doesn’t mean we’re flourishing any more than not having a stroke means I’m the picture of health.
Data can help form a foundation for knowing not just that things are in fact going well, but it can help understand why. That last bit is critical.
W. Edwards Deming famously said, “If you can’t describe what you are doing as a process, you don’t know what you are doing.”
Not surprisingly, Deming also said, “In God we trust, all others bring data.”
Data can help us unravel the things we do that make us successful every day. That’s a much different approach than simply hoping to avoid mistakes, and working to identify enablers of safety performance is something that takes practice.
If we agree that safety is broadly defined as our ability to succeed despite uncertainty, and that safety management is really just a set of tools to support decision-making that helps to realize that success, then the need for data-based intelligence is clear. To move beyond simply reacting to failure, we have to seek wisdom within our daily operations.
Reactive tools aren’t bad, but it is important to remember that they can only describe something that’s already happened. To move beyond that – to inferential methods – we have to look at data a bit differently.
Accidents, injuries, incidents, and spills are all lagging indicators. That is, they describe a past event, and generally a negative one. While there may be something to be gained by understanding how a failure happened, it’s hard to support decisions – and to identify what enables performance – by simply looking behind us.
Instead, lagging indicators work best when they are balanced with leading indicators. Leading indicators speak to those beliefs and behaviors in our business that help us succeed, build resilience, and understand risk.
Where lagging indicators are often quantitative (generally numeric) measures like incident rate, lost workdays, gallons lost to spills, etc., leading indicators often take on qualitative characteristics. Qualitative data is interesting because its context is built in via narratives, observational information, stories, and so on. Neither is better than the other, but balance is crucial.
Unless we can support decision-making (wisdom and intelligence do this), collecting data is just an uninteresting hobby. Statistics are the key that unlocks data’s power to inform, and though you may have heard that statistics can be manipulated to say anything, rest assured that like any tool, they have a purpose. I can hook up a tow head improperly, drive too fast in a refueler or even select the wrong settings on a GPU – and yet we don’t discount the tool.
Used properly, and with healthy doses of skepticism and humility, statistical analysis can help us to uncover trends, themes and patterns that aren’t visible by simply looking at the data from a system. That ability moves us to the realm of inferential statistics, where we can shift our thinking from reactive methods to more proactive and predictive decision-making.
Balancing lagging and quantitative data like gallons sold, aircraft movements, employee turnover and accident or injury rate with leading, qualitative information like responses to climate surveys, training feedback, observational data, interview notes and comments from audits can help provide a balanced perspective on what we’re doing well, and what can be improved.
Having trouble gathering enough data on your own? Join forces with other operators to aggregate the data you collect so that tools that rely on larger data sets, like regression analysis, are possible. Plenty of government agencies and trade groups also publish data sets you might use to supplement your own experience.
Operating successfully despite the dynamic aviation environment requires that we deeply understand risk, safety and resilience. Getting there means digging into our operations purposefully, and analyzing data in search of intelligent answers to questions that have a meaningful impact on our performance.
The advantage? Not only can data enable better-informed decisions about safety, it can support more efficient operations. In industries like aviation ground services, where competition is high, and margins are not, being more efficient – and supporting safer, more resilient operations – may just equal survival.
Dr. Benjamin Goodheart is the Managing Director of Versant, a global safety and risk management firm based in Colorado. Benjamin has extensive experience in aviation safety management, planning, and accident investigation. He is an ATP-rated pilot and flight instructor, and he holds a Ph.D. with a research focus on aviation safety and organizational performance. To learn more about how Versant can help you manage risk, call 833-VERSANT or visit Versant on the web at versantrisk.com.
