Wartime Analytics: How Two WWII Geniuses Influence Today’s Customer Experience
November 11, 2015
By Paul Fowler, Director, Global Partnerships, Clarabridge
Each November, many countries around the world pause in remembrance of the sacrifices and contributions of those who laid down their lives in conflicts across the world. One chapter of World War II history particularly resonates with us here at Clarabridge because it involves creative and insightful ways to gain a new understanding of the truth.
The advent of airpower and the use of long-range bombers presented many opportunities and challenges to the Allies. Long range bombers were an important part of the Allies’ World War II strategy, but protecting them on their long and dangerous flights into the heart of Germany and Nazi-held Europe presented many challenges. Struggling to cope with the massive losses and a lack of resources and aircrews, the RAF and USAF turned to statistical analysts including Patrick Blackett and Abraham Wald for guidance on how to protect their aircraft and their crews.
Working for the Ministry of Defence (MoD), Blackett used data analysis to make recommendations on the best ways to allocate resources for a variety of military operations (an all-around genius, he would later win a Nobel Prize for physics). Meanwhile in the US, Abraham Wald was making surprising suggestions about how and where to allocate the armour on planes taking off on their long, dangerous sorties over Europe.
Many bombers were coming back from Germany with bullet and flak damage, while tragically many others were not coming back at all. The top brass wanted Wald’s and Blackett’s advice on where they should place the armour to prevent this.
The obvious answer to the DoD and MoD was to protect the parts of the plane that were most heavily damaged. However, much to the amazement of the military, Wald recommended the armour should go where there was no anti-aircraft damage.
Upon examination, the logic was sound. If the planes came home, then it was OK for them to get hit where they had been hit. The planes that didn’t come home most likely had been fatally hit in the places where the returned planes showed no damage. Therefore, it made perfect sense to armour those parts of the aircraft that showed no damage
However, there was a big caveat – Wald said he couldn’t be sure that his results were accurate because the sample he was examining wasn’t complete. He couldn’t examine the anti-aircraft damage on the planes that didn’t come back because they were in pieces in Germany. Therefore, his conclusions could be erroneous.
This was a classic case of selection bias: because the data Wald had was incomplete, the conclusions he could make were naturally limited (and biased). Statistically, he could only make an accurate decision if he had access to ALL of the data (the planes that returned AND those that did not).
So why as a customer experience professional am I talking about two of the 20th century’s brightest statisticians and physicists?
Well, Clarabridge takes a very similar approach to customer analytics. Like Wald, we take our core belief that you need as many different sources of data as possible in order to get a complete view of your customers’ experience. Digging deeply into one source revealed an insight that the air forces could take action on, but he was keenly aware that with more data, his results would be more accurate. Wald didn’t look at the damage to the wings in isolation to the damage to the fuselage, engines, or tail. These were all vital components that help to create a single functioning aircraft.
Customer feedback is similar. Let’s imagine an aircraft and all its individual components are similar to today’s corporations and their multiple divisions and functions. Clarabridge customers recognise that just focusing on one source (or component) won’t help the corporation to function alone. They are co-dependent.
Here’s my analogy: imagine the wings are survey feedback, contact centre data is the cockpit, Social is the engines, and live chat is the tail—for that plane to fly you need to appreciate all of those components as they all influence each other and the bigger picture. Together they help keep that plane in the sky. If you analyse them collectively, it will allow you to make that plane fly higher, faster, and better.
As we stop to remember and thank all those who have served, we also remember these analytical pioneers. They contributed not only to the war effort but also to our ability to think again, look at the big picture, and truly understand problems to take correct and decisive action.
Lest we forget.