Improved Leadership. Competitive Advantage.

People died.

That’s an attention grabber, we know. But it’s that time of the year again—hurricane season—and we’d like to do a quick compare and contrast exercise using two mighty hurricanes.

In one corner, weighing in at 125 mph, we have Hurricane Audrey. Audrey struck an unsuspecting Cameron, Louisiana, with a surrounding population of about 12,000, in the summer of 1957. Since Audrey, only Hurricane Katrina has killed more people; at least 416 were confirmed dead.

In the other corner, weighing in at a whopping 155 mph, we have Hurricane Floyd. Floyd walloped the Carolina Coast in September of 1999 with the eye of the storm passing directly over Wilmington, North Carolina and its surrounding population of a quarter of a million people. Hurricane Floyd killed 57 people—mostly North Carolinians.

But how do you explain this? Floyd was 30 mph stronger than Audrey and hit an area that was 20 times more populated. But, despite the potency and more populous area, Floyd resulted in only 57 deaths compared to Audrey’s 416. How can one account for this? Surely, a more vicious storm hitting a more populated area should result in more dead. But, that’s not what happened here.

Answering this question should help us in our management and leadership of high-risk/high-hazard organizations.

Without question, the answer to this riddle involves preparedness and foresight. In 1957, the population of Cameron, Louisiana was ill informed and, quite frankly, most were ignorant of the danger fast approaching. Actually, because of Audrey, we’re a lot better at prediction and emergency response (although that doesn’t necessarily seem true if we look at Katrina…more below). But Wilmington and the Carolinas, in general, were much more informed and got prior warning. Armed with this advance notice and some time to prepare, most were able to find safety.

Within this context, we offer the following as it relates to high-risk/high-hazard organizations.

Trending and Monitoring. Trending and monitoring matters. Tropical storms are now captured by advanced weather technology immediately. Actually, meteorologists are sophisticated enough that they trend and monitor for just the conditions that would spark a tropical storm. Once a tropical storm forms, it is closely tracked and monitored. Trend paths are computed. If a tropical storm does metastasize into a true-blue Hurricane, more robust models are built and tracking becomes fanatical. We can learn a lot from this practice. Just like the weather, valves, systems, equipment, and machinery can act up in both predictable and unpredictable ways. Like the very best meteorologists, engineers, operators, and maintenance folk should commit themselves to trending and monitoring. This is not an activity that should be ignored, or worse, pencil-whipped. When we trend and monitor, we head off danger before it ever surfaces.

Predictive Maintenance is Potent. Every organization that we partner with embraces preventive maintenance. Coincidentally, preventive maintenance is exactly the activity that feeds the trending and monitoring that we mention above. However, there are precious few organizations that really GO ALL IN! as it relates to predictive maintenance. Predictive maintenance involves capturing and storing large quantities of data and building stochastic, probabilistic, and regression models that will help predict the next equipment failure. Tough to admit, and as attacked at the weathermen are, they tend to have most of us beat—they use data to make informed predictions and, more often than not, they get it right. Building a strong predictive maintenance program requires investing in some IT infrastructure and getting some smart people on board—statisticians, mathematicians, and/or engineers. Not surprisingly, getting this off the ground often takes a corporate champion to drive this effort. And patience matters. Because after you build the team and build out the IT platform to make data capture possible, you need some run-time to get an adequate sampling of events/observations. We’ll say this, though—that an investment of hundreds of thousands of dollars now could save many millions later. For one of our clients, one day of not producing energy is a direct hit to the pocketbook of over $1 million. If predictive maintenance can save a station from one unplanned event, how could it not be worth the investment?

Aggressive Response. Lastly, how we react to data and forewarning matters. Let’s look at Katrina, for instance. Here, on the surface, this seems like an easy win. After all, we had the predictive tools and did all the trending and monitoring. We knew that danger was lurking. But some sociologists claim that in 2005, as a society, we found ourselves in a complacent mood. Others suggest that we ignored the bad warnings because earlier predictions failed to materialize so what made us think this one was going to be right? Other historians and sociologists offer that we were just dead numb to bad news given the Global War on Terror and the wars in Iraq and Afghanistan. Regardless of the reasons, the historical fact remains—we knew what was coming, but didn’t act. And as we approach the anniversary of Katrina, that may be the most tragic part of this story. But, respectfully, back to our discussion. In high-risk, high-hazard organizations, we need to react with force. Strong Fix-it-Now (FIN) or Rapid Response teams are a must. Sadly, in general, we’ve found organizations that were either good in trending/monitoring and maybe prediction, but not good at reacting (that’s Katrina). Conversely, we’ve seen organizations that just love a crisis and react with gusto, but it could’ve been prevented in the first place (that’s Audrey).

Be the leader. Be the organization. Be the team that invests in the capacity to predict, trend, monitor, and react. After all, there could be big waves ahead. Should we be battening down the hatches? The safety of your employees and the public, at large, may depend on how well you can answer that question.