In every business, there are three major areas of work. With simplified definitions and in no particular order, they are:
- Marketing – creating the demand for the company’s product or service (examples are advertising and product development)
- Finance – providing the capital (cash or debt) to fund the company
- Operations – providing the core product or service (examples are manufacturing and logistics)
A VP Squadron doesn’t have to do Marketing or Finance – it is a 100% operations center. The goal of every operations center is always to seek efficiency. Reducing costs, eliminating wasted effort, and moving faster are all objectives of operations, however they are bounded by being aligned to the company’s product. For example, a super-high quality custom furniture maker wouldn’t want to adopt the ultra-efficient manufacturing processes of Ikea because those efficiencies are gained only because they produce a lot of the same thing very fast (i.e. they’d lose the customization which is their core offering).
The study of how best a company brings its product or service to life is called Operations Management. There are many fields of study within the umbrella of Operations Management including process improvement, process optimization, risk management, forecasting, and more. You’ve probably heard of “lean” or “six-sigma” and those fall under this category. This field of study is far too big for me to really do it justice in a blog post… But I’ll try to cover some of the big points that VP is missing.
Statistics and Bottlenecks: Statistics is something that every major corporation incorporates into their daily operations. The good ones understand that there is always going to be some statistical variation. The better companies understand how dependent events become affected by that variation. Amazon, Walmart, and Costco do this better than anyone else which is why they are so successful. They’re able to eek out efficiencies here and there better than the competition.
Operations also involves the understanding of your limitations, and good companies focus on optimizing around their constraints (also called bottlenecks). Apple used to have a big problem getting customers their iPhones on day 1 (remember all those long lines at the Apple store?). They finally figured out the statistics around product mix and improved their operations to have enough iPhones for their customers on day 1 of a product launch. But they only went as far as how many UPS/Fedex/USPS could actually deliver in 1 day. It would make no sense for Apple to continue to improve how many iPhones they can produce when their shipping partners can’t handle that volume. They improved upon a constraint until another constraint became the bottleneck.
Let’s take a typical VP squadron in Jacksonville in the Summer. They have 5 planes. They have 140 aircrew. Here are all the statistics and constraints you’d consider in developing a flight schedule:
- Some percentage of attempted takeoffs will be delayed or cancelled due to maintenance (there will be variation of this percentage among aircraft too!)
- Some percentage of aircrew will be med down
- There will be some probability of afternoon thunderstorms which may cancel or delay flights
- Some percentage of aircraft will return in a down status and affect the next mission
- There will be some variation in the length of time it will take to get the plane off-deck
- Crew rest
- Number of combinations of aircrew you can field
- Daily caps on flying and man-ups
- Number of aircrew needed on each plane depending on the type of mission
- For training events, available students and qualified instructors
We have all that data. What we don’t have is the knowledge or tools to effectively utilize it. There are techniques and tools that can help us sort through the complexity and answer a basic question like, “How likely is it for the squadron to get x flight hours or y mission quals today?” This particular problem wouldn’t be terribly difficult to model, and the benefit would be that you could understand what a reasonable expectation of performance is.
Too often, we aim for 100% mission completion, or 100% on-time takeoff, or 100% of some other metric that is easy to measure. These are foolish objectives that are reinforced when a detachment gets lucky and goes 10 for 10. That’s like expecting the roulette table to always come up black because it once went 10 times in a row.
So we end up doing some perverse things to attain these unrealistic goals. We schedule backup aircraft. We schedule backup aircrews. We increase maintenance shifts. Once we run out of aircrew, we schedule the ready crew. We do all these crazy things that consume every last drop of our resources. These are huge morale killers. Not only does it sap everyone’s energy, but sometimes the objectives are so unrealistic that there’s no way to actually be successful. Patting ourselves on the back for the ol’ college try when the goal was completely unrealistic reinforces all sorts of bad behavior and attitudes.
Sometimes it’s necessary to try to achieve higher performance outside the range of a statistically probable outcome. However, the cost of achieving that objective grows exponentially the further it gets from reality. We should be smarter about when we use the resources lever to eek out higher performance. It should be for a good reason and at an appropriate time (an ASW exercise 2 weeks after returning from deployment is not a good time for this).
I think VP is stuck in the mindset of trying to hit unrealistic goals all year round. We should invest some time and money into developing some tools to enable the OPS department to understand what a reasonable range of performance is based on the specific stats and constraints of the day/week/month/quarter. This would relieve the pressure our mindless 100% mantra causes and allow us to set reasonable expectations. It would also enable a real evaluation of squadron performance. Over time, the best squadrons would often perform near the upper boundary of the performance range and the worst squadrons would be near the lower boundary.
There’s a really good lesson to be heard about GM in the 80s. Basically Toyota had GM send its worst factory’s workers and managers over to Japan where they were shown exactly how Toyota was able to make cars of much higher quality and much lower cost than GM. Those workers came back and turned GM’s worst plant into the best plant, by far. But today, GM cars still don’t have the quality of Japanese imports, and GM went bankrupt along the way.
The difference was in culture and how it was applied to their operations. Toyota strongly enforced the idea of continuous improvement (“kaizen” in Japanese). Every person in their organization was committed to improvement – from the CEO down to the lowest person on the factory line. I strongly recommend listening to this podcast https://www.thisamericanlife.org/radio-archives/episode/561/nummi-2015 – it’s about an hour long and I guarantee you will find yourself drawing parallels between GM and the VP Navy. Toyota’s culture of continuous improvement is something that the VP Navy could adopt because our people are extremely dedicated and hard working. The only thing stopping us is our own leadership.
When I got out, I was certain that there were better ways to do things … and there are. Lots of them. Too many to list in this article. I believe that we should start by better defining our performance expectations using statistics, but we just don’t have the education or exposure in the VP Navy. But that’s my opinion and I’m biased because I like statistics. At the very least, every Operations Officer and Maintenance Officer should have to do some amount of required training in Operations Management. In the business world, similar jobs require years of experience and quite a bit of education in this field before running something as big as a VP Squadron.
Adding management education to our leadership track should be a no-brainer. While we wait, I recommend required reading for all DHs – “The Goal: A Process of Ongoing Improvement.” I won’t spoil it but it basically covers a simple idea: there are a limited number of constraints in any organization. Identify them, and then work to help them or remove them (only to find another constraint). https://www.amazon.com/Goal-Process-Ongoing-Improvement/dp/0884271951/ref=sr_1_1?ie=UTF8&qid=1489386642&sr=8-1&keywords=the+goal