In the darkest days of World War II, the US Naval Air-force faced a serious problem. Airpower had come to play a major role in the conflict. Fighter aircraft had proven decisive in a string of critical naval battles and that trajectory looked set to continue. But aircraft were going down fast. So many brave pilots were lost.
The outcome of the war itself was at stake. But the rate of loss simply couldn’t continue indefinitely.
Put like that, the term “problem” seems an understatement. “Intractable and deadly dilemma” might be a more accurate description. But whatever words you use to describe the challenge, it was the Center for Naval Analyses — a nonprofit research and analysis organization that thrives to this day — that was tasked with finding a solution. And the answer the CNA’s team of analysts and researchers arrived at seemed almost ridiculously simple at first glance.
Planes needed better armor.
More specifically, they needed strategically placed armor that would protect the most vital parts of a plane without adding so much weight that the aircraft couldn’t get off the ground. It was a precarious balance of protection, on the one hand, weight on the other.
So the CNA arrived at an ingenious method. To figure out where the armor should be fortified, the team carefully analyzed bullet holes in planes returning from missions. Painstakingly, after analyzing every bullet hole in the fuselage of hundreds on hundreds of planes, they arrived at a clean, clear visual map of where planes were taking the most bullets.
Here's what that map looked like:
And they had their solution: Armor on planes should be strongest where bullet holes were most concentrated. The solution was elegant, the way forward clear. It was a triumph of careful forensic analysis over the chaotic fog of war.
There was one small problem. This was precisely the wrong answer.
A Hungarian mathematician and statistician named Abraham Wald happened on the CNA’s research and saw one glaring detail the research team had overlooked. They had only been analyzing planes that returned. It was the areas without those scary red dots that represented a plane’s most vulnerable areas.
The CNA team had fallen victim to survivorship bias – a logical error that supports false conclusions by concentrating only on variables that persist after an earlier selection process.
And now the bit about supply chains
This little story demonstrates a lot of things. One of them you can boil down to an oddly repetitive maxim: You don’t know what you don’t know. Like the poor inductivist turkey of philosophical legend, our species seems doomed to incorrectly assess risk based on an incomplete data set.
But the solution Abraham Wald’s brilliance unearthed says something important too. And it reveals an interesting truth about business intelligence, what it does, and why it’s so important.
Let’s take another look at the CNA’s rigorous yet flawed initial methodology. The first approach CNA military scientists leaned into was to analyze their problem in microscopic, forensic detail for a solution. They minutely surveyed each and every bullet hole as though lives depended on it. Because they did. Their approach was fueled by an assumption that every torn scrap of fuselage had the potential to be the one crucial defining data point — a smoking bullet hole of insight that could save lives and win a war.
But that approach blinded them.
Each bullet hole in a returning plane was something they knew. Each bullet hole that took a plane down, on the other hand, was unknowable. In other words, yes it all gets back to that maxim: They didn’t know what they didn’t know. The answer the naval research team needed only popped onto their radar of comprehension when Wald stepped away from the plane. From a distance with a data guy’s detached eye, Wald was able to see the forest for the trees and a solution came into view.
Wald successfully quantified what wasn’t there. And that allowed a leap of imagination that turned data into intelligence, ragged bullet holes into insight.
And now the bit about you and IL2000
We aren’t the company that’s going to pretend that BI conclusively solves supply chain fallibility, let alone the fundamental fallibilities that so complicate the human condition. That’d be disingenuous. Worse, it’d be dumb.
No management retreat, self-help program, online transcendental meditation course, or transportation management system (even IL2000’s extremely powerful, quite possibly quasi-omniscient TMS) can immunize a company against not knowing what it doesn’t know.
What BI can do though is tear you away from the analytical impasse that comes when you get lost down in the data points. The right BI tools will help you step away from the daily complications that riddle your supply chain like so many bullet holes. And from that perspective, you gain your first real chance to get a handle on all the stuff you don’t know.
And all of this also goes to show that insight about how to build a better supply chain doesn’t arrive neatly packaged at your front door with a fresh-faced delivery guy requesting your signature as proof of delivery. Gonna put the next bit in bold and center-aligned because it’s important. And some companies will try to tell you otherwise:
No methodology, tool, or software makes a company smart.
People make business intelligence.
And that’s why IL2000 is different. Our approach to business intelligence isn’t just to sell you a software platform. By working with IL2000 you gain access to people — smart people — skilled managers, consultants, analysts, and veteran transportation personnel with decades of unique insight across every corner of the supply chain.
And it all converges into a bubbling tank of human-driven supply chain intelligence.
Like the CNA and its intractable problem, supply chain insight is often hard-won. Solutions to rising above uncertainty require big leaps of imagination – especially in 2022. But with IL2000’s supply chain business intelligence, you have a real shot at seeing through your data points to find prescient insight about what’s coming next.
Learn more about our unique perspective on BI by reading our Taming your supply chain isn’t a data problem white paper. Or contact us to schedule a no-obligation consultation.