In the March 2019 edition of the Marine Corps Gazette, Maj Amber Coleman introduced us to the A-Rating. Also referred to as operational availability, the A-rating is simply the amount of time a piece of equipment is available divided by the total time measured. In this post, we are going to expand on that idea to give you some tools to improve the A-Rating. We will start by flipping the equation around. Simply stated, maximizing uptime is accomplished by minimizing downtime. Our new equation is downtime over total time. For the sake of an attention-grabbing title, we are shamelessly calling this downtime equation the A-hole. The key to fighting this A-hole is based on improving some basic time-driven-metrics.
Backing up for a moment, equipment readiness or R-rating is a warfighting metric that commanders at all levels are understandably concerned with. Knowing exactly what combat power we have available for the fight at any given time is a very valuable insight. Unfortunately, the Marine Corps has been grappling with less-than-satisfactory R-ratings for years and has not identified a solution within budget realities. We know that more funding helps knock down some choke-points, but it is hard to explain what an extra dollar buys the Marine Corps in terms of R-rating.
The problem with chasing R-rating is that it only represents a single point in time, and there are only two components of the math that can be affected: How many items we own, and how many of them are ready to fight. Every Marine who cleans a rifle knows there are more than two factors contributing to readiness. Preventative maintenance, parts availability, funding, the number of techs, operational tempo and many more factors influence this elusive metric. In fact, the problem is so complex that there is no known or accepted model to accurately predict equipment readiness. The Marine Corps has been looking for one for decades, but the problem stumps researchers.
The A-rating allows us to look at the problem differently and explore trends over time. When we consider a time driven approach our problem set gets simpler, or at least easier to explain. The A-rating is well-defined using some simple mathematical equations. In 2008 Gary A. Pryor from the U.S. Army Training and Doctrine Command published the following equation for estimating A-rating in the International Test and Evaluation (ITEA) Journal:
A-Rating = (Total Time – Downtime) / Total Time
This is pretty simple stuff, but Pryor went on by breaking downtime (or the A-hole) into its largest contributing factors:
- Time for Preventative Maintenance (TPM)
- Time for Corrective Maintenance (TCM)
- Time for Administrative and Logistics Delay Time (TALDT)
There was a lot more to his paper. This is not an all-encompassing list as we can deconstruct any of these factors into more components. What this approach illustrates is a methodology that allows us to reduce an elusive metric like R-Rating, into something manageable, and more importantly actionable. If we minimize the downtime factors in the A-hole by shortening process times, we improve A-rating and in turn we improve R-Rating.
The beauty of this approach is that these time driven factors lend themselves to process improvement that can be affected at any level of the organization including our battalions in the operating forces. Simple adjustments at the unit level can have a huge impact. For example: A unit supply shop is currently allowed 72 hours to approve a service request and release funding for the parts on that order. By shifting the target to a same-day approval at the unit level, a unit can reduce the A-hole by three days. This will require some communication between supply and maintenance to prevent late nights on Fridays, but better internal comms is a good thing that we should pursue anyway. Making the warehouse receipt for parts immediately on arrival and notify maintenance can buy back even more time. Speeding up the delivery of parts on an installation buys back even more time. Predicting and scheduling lets us get ahead of maintenance requirements, resulting in faster maintenance times (no waiting for parts or tech availability) which again buys back even more time. There are probably hundreds of other improvements that buy back small increments of time. Hours add up to days and days add up to weeks. By shaving increments of time off processes across the factors of A-hole, in aggregate we build tangible time savings that improve readiness.
The higher up in the organization we move, the more we should focus on A-rating instead of R-rating. With R-rating, we are not always sure if more is better. For instance, do more technicians equate to better readiness? All A-hole factors are measured in units of time. Using A-Rating justifies investing in faster transportation, processes, techniques, and tools. With time metrics of A-rating, faster is always better. Using A-Rating justifies investing in faster transportation, processes, techniques, and tools. A-rating also allows for enterprise wide synchronization of efforts. Investing in better forecasting techniques, can result in better responsiveness from industry. Improving our warehouses and modernizing our supply practices have measurable effects on A-rating. R-rating is very difficult to tie back to a funded action, but A-rating is easy to explain in comparison.
General Al Gray once told us the “it doesn’t cost any money to think.” Let’s start thinking about how we conduct business. Its all about getting faster. R-rating is still important, but if we look at longer time horizon than R-Rating and focus on gradually improving A-rating the math clearly indicates that readiness will follow. Minimizing downtime factors in the hole of the A-rating allows for enterprise wide process improvement. We do not need to wait for funding or approvals to start making progress. Let’s fight this A-hole and start improving our equipment readiness.
Does anyone know of an efficient way to track reductions in "A-holes" in GCSS-MC or figure out the availability ratings across commodities? GCSS-MC provides MTBF and MTTR data points; however, it is much harder to ascertain other variables.
This week I was in yet another logistics forum, listening to a Marine Corps Systems Command brief about additive manufacturing. At the end of the impressive brief, a senior leader asked if we had seen an impact on readiness. The answer was: "no...or not yet sir." This was not because, AD doesn't save time in some cases, it is because we aren't tracking readiness in a way that we can control.
The question is really have we seen an impact on average readiness, which is roughly equivalent to operational availability (A-rating). Until we understand our metrics and goals, we will not be able to answer this simple question that is fundamental to logistics.
Additionally, to the SYSCOM briefer s credit,…