This article is initially available on our podcast. Click here to listen.
If you were trying to predict which sports team would win, what metrics would you use? We know that there’s a whole thing about Moneyball and things like that, but let’s take a few examples to think about how this might apply to something like revenue cycle management.
In American football, like the NFL, I used to have a friend who picked which team was going to win based on the color of the jerseys. Whichever color she liked better, she chose that team to win.
My thought was, “If you don’t have any scientific method here, it’s as good a way to do it as anything else, I think.” And another friend used to pick which team was going to win, based on which butts of the players she liked better. Let me repeat that. I did say “butts,” meaning the anatomical portion of the body. As hilarious as that sounds at the time, there might be something to this.
Who’s at their peak?
Once upon a time, I was a sponsored bike racer. You train basically throughout the whole year, and you race about nine months out of the year. But there are certain times that you try to peak and engage in what’s called periodization, where you will try to have your peak performance at certain times of the year, like in May for the state championship or September for the regional or national title.
In doing that process, though, just as bodybuilders will try to cut through the competition, you can see who’s in better shape for that particular race. So we used to engage in what was called “butt checking,” although we used the worst word than “butt.” The reality was, you’re staring at other guys’ butts because your head’s down on the handlebar and stuff like that.
Does physical size matter?
I identified who looked like they were in better shape and were more likely to be at the top at the end, winning the races, and stuck to their wheels to have them be my lead-out person. Often, I’d stick with them to place well and win money in these races. So there is something to butt checking. Maybe, she was really onto something.
If you were an NBA team, and you wanted to put together an all-star team, or you ever wanted to predict whether or not you’re going to win games. Further, this is a presumably essential criterion. If someone told you to measure the height of players to select who should be on the team, would you do it? And would it help you? And if you wanted to win games, would you join the taller team or look at some other criteria?
I think we can all agree that just sticking the tallest players on the basketball court will not win you the most games, all other things being equal. That doesn’t mean there isn’t some relationship between height and winning what’s known as a correlation. Again, the recent small-ball Warriors NBA thing does not apply here.
Here’s how it works…
There is some correlation between size and winning because, all other things being equal, if we took a bunch of six-foot-tall great basketball players and six-foot-eight great basketball players, I’m betting on the six-eight guys. I’m using US measurements here. For anybody who’s in the metric world, we’re focused on the US here.
Determine the scope for revenue cycle management performance
Even if we believe that height has some impact on winning games, how would you measure it? If I said all the players are five feet tall, would that be good? Well, your immediate answer is probably “No,” but I didn’t tell you their league. If I said these were all like seven or nine-year-olds, five feet tall, they’re probably crushing it. They’re probably keeping the other team from even making any shots, blocking everything, and getting all the rebounds. But if they’re adults, five feet tall, they’re all going to be crushed.
It all boils down to this…
How is this related to revenue cycle management? I mean, you knew I was going to bring it back around at some point. Correlation and causality are accounts receivable. Measuring accounts receivable, whether in the form of something like accounts receivable days, is this predictive of revenue cycle management performance.
We come back to that kind of question, which is, “What’s the definition of performance and success?” We talked about winning games in something like a sport of basketball or American football. What are the criteria for success in RCM? Everybody says it’s fewer AR days. All other things being equal, yeah, sure. I mean, I’ll take my money faster rather than not as fast. But if I’m choosing, I’d rather have more money than have it more quickly. There’s no question about having more money than faster. So that’s not the criteria.
Define the criteria
The criteria would be like, “How much money do you collect?” There’s a whole separate conversation we’ll have about how to quantify what that is. But back just a simple concept of, “Is lower accounts receivable or fewer AR days predictive of collecting more money or more revenue? And would you measure that? Or is lower AR days just more like measuring how many players on your team have mustaches?” Generally speaking, I’m more in the camp of it’s more like measuring mustaches.
Here’s the important part…
That doesn’t mean it isn’t correlated. There is some relationship between those two things. Generally speaking, there’s some relationship between lower AR days and collecting more revenue, although it’s correlated more than causation. The correlation is nowhere near one. It’s not even remotely close.
The moral of the story is, don’t just stick a bunch of eight-foot-tall people on the basketball court because they’re going to be ungainly. I mean, it’s going to go badly. I’ll put a bunch of six-foot-tall people on the court, and they’ll probably run circles around them. Focus on what’s important, which is collecting more, not just reducing AR. That’s the moral of the story and what basketball players’ height and mustaches, and butts have in common with revenue cycle management.