By LCDR Sean Blackman
I often hear people say things like, “We wouldn’t have this problem if we were at Google or Microsoft or Amazon. Why can’t we do things like that here?”
I definitely understand the sentiment. The IT environment within DoD is challenging to say the least. Add that fact to the idea that we play with some of the most advanced machines ever built while we are in the aircraft, and you can understand the frustration that our systems on the ground should be equally advanced.
There is, however, hope on the horizon. If companies like Google or Amazon have taught us anything, it is that data must be viewed as a commodity. They have made untold piles of cash by leveraging the insights they have into their customers, and they make it easy to use their products. How can we use that within Naval Aviation? Well, first-off we have to stop collecting data just to “feed the beast” and start collecting “data as a byproduct.” If we can orient ourselves around making our work in the Navy easier and faster to perform through technology, we can generate high quality data as a byproduct of making it easier for our people to do their jobs. It’s a complete 180* from how many of our systems were designed, but it is how these companies have succeeded. People don’t use Facebook for the sole purpose of giving them their data. Data is generated as a result of people using that platform out of perceived “value.” We need to emulate that within our organization. It will make life better for the deck plates and provide leadership the data they need to lead effectively through Data-Driven Decision Making.
Eight months ago, the CNAF Office of Data Science was stood up with one objective in mind – to use our data to help fix our readiness shortfalls. Well, it shouldn’t be a surprise to anyone reading this that we learned one thing very quickly – much of our data was not of high enough quality to act upon. Luckily, we have some really smart people across the country that helped us gain some critical insights regardless of that, so our efforts were not in vain. The question that really kept us up at night was how to fix our data quality issues. No amount of “training” will ever force us to produce high quality data – it has to be done by being as least burdensome as possible to the Fleet and we must provide something back to our users anytime we impose a cost of data collection on them. Going forward, we plan to build our systems around that tenet.
We’ve also been heavily involved in the concept of Data-Driven Decision Making (D3M). In order for data to be effective, we need shared insights across the enterprise – from the ready room to the Flag Briefing Room. If we can use data to serve both those customers effectively, we will have created something really special. When we talk about D3M, what we are really saying is that we are applying rigorous common sense across the enterprise. Flight Hours is a great example. For each flight in an F/A-18, the post-flight process of recording flight hours occurs THREE times – once by the aircraft itself (FAME), once in Maintenance (OOMA), and once by Operations (SHARP). Guess how often these three recorded flight times match (even with some business rules applied) …. They don’t match and they never will as long as we keep doing business this way (stovepiped systems that don’t talk). The days of repeated manual processes needs to come to an end NOW, and we are taking steps to do just that. D3M is simply doing what makes sense by treating our data as an asset rather than a liability.
From Maintenance, to Supply, to Ops, we are actively looking for ways to use data to make our lives better. From Predictive Maintenance, to Supply Chain Optimization, to Automated Flight Debriefing, we are investing in technologies that will allow us to be just as efficient and innovative as the Googles and Amazons of the world.
Have an idea for a data driven project? Please reach out! The CNAF Office of Data Science wants to hear from you. Contact LCDR Sean “ButterBean” Blackman at sean.blackman@navy.mil.
LCDR Sean “Butterbean” Blackman is an F/A-18 Super Hornet pilot and the Office of Data Science Lead at CNAF. When he’s not busy crunching numbers and geeking out reading new tech articles, he enjoys tending to his three horses, nine chickens, two parrots, and two dogs.
コメント