We’re looking at a quote, advanced analytics package, or analytics solution from an RCM provider. They do billing software, and they also provide clinical software. I’m going to estimate they’re doing about 100 million in revenue, but my information’s based on trends from a few years ago. They were at, I think, around 66 or 67 million dollars a few years ago in revenue, a pretty good size company.

They have come out with a new advanced analytics solution. Looking for the information they have, they talk about that they have benchmarks and how great the benchmarks are, but they don’t explain how they drive the benchmarks or what you’re going to use those benchmarks for.

I think this highlights one of the challenges that we see in a lot of marketing documents, which is not just throwing out keywords but saying, “Oh, we have this great tool for you,” like benchmarks. The problem is if you’re not careful with benchmarks, they can cause all kinds of problems.

Revenue Cycle Management Systems Analytics

I’ll give you an example. Many years ago, we saw people trying to implement benchmarks into their software systems and the revenue cycle management systems. We were billing for one of our clients and using a software application, a practice management system, for billing that they wanted us to use. We were performing quite well for them. Were averaging about 37 days from an accounts receivable day standpoint.

Again, not that its the most important metric. That’s a whole another conversation, but just in terms of measuring AR, how we were doing. Their system popped up all day, every day, front and center. Every time anybody wouldn’t get in a system, including our clients, that showed the quote, the best benchmark for this metric, and they showed the best is 23 days. All-day, every day, our client’s AR best is 23 days. The best is 23 days. You’re at 37 days. The best is 23 or 37.

What are the challenges?

The challenge, of course, is aside from the fact that it just pisses you off. I mean, assuming you’re not as good as everybody else, from a performance standpoint, do you want to have your client see that? That wasn’t really what was going on. We’re talking about your sort of lies in statistics.

If we had a client and we did have a client, it was Medicare only. We averaged about that many days for them because the payment cycle was 14 to 21 days. Pretty much almost all of them got paid right out of the shot.

We averaged somewhere in the 21-24 days. I can’t remember exactly what it was, but that’s based on that kind of a payer mix. If you’ve got a ton of BCBS or, God forbid, you know the term “workers’ comp,” and some of those payers are at 150 days, 180 days, 210 days, you’re not coming anywhere near 23 days, much less 37 days or anything else. To throw out best is so meaningless and so stupid when it’s not specific to your payer mix, the procedure types, the type of a specialty, and all kinds of other things.

The benchmarks

What are “benchmarks”? Of course, they’re saying they’ve got benchmarks. If you dig in to figure out, this company used to use SAP Business Objects. What they’re essentially doing now is they’re rolling out Tableau. They’re doing different tiers that give them more or fewer users and a certain functionality that they don’t get at other levels. So they are trying to kind of tier this to extract more value from people and giving some people explorer licenses in Tableau and others not so that they can write reports or they can only have “Read license” and so on.

That’s pretty clear what’s going on. They went from “Let’s use a hardcore reporting solution in Business Objects” to “Let’s go with a visualization tool.” They’re mutually exclusive. You’re not using both of those. You’re using one or the other.

They did do something right in this giant 16-page brochure. In this huge amount of reports they kind of show, one of the reports they show lists the question they are trying to answer, which is critical. Just showing a whole bunch of reports, somebody’s going, “Okay, I’ll look at all the reports we can do.” It isn’t that beneficial, but showing a report that answers a question that’s difficult or people have struggled with and says, “Hey, we can answer this question, and this is how we do it,” that’s great.

Force Visualization

Having said that, now knowing the question that the report is supposedly answering, it is still completely unintelligible to me. Like, I stared at that visualization and studied it for several minutes, which is hilarious. It’s a specialty that I know well, so this is not an unknown specialty. It’s a laboratory. Reporting design is tough; I get it. Sometimes, trying to force visualization onto something makes it worse. Just go with the data table, go with the results, and go with the summary. You don’t have to visualize everything.

I think the problem is we’ve moved in this world that’s like, “Oh, a pretty picture. It’s going to sell more. So we got to do visualization.” Well, analytics isn’t visualization. This is going to be a trend to hear from us a lot. They now have not just analytics. They’ve got the quote, advanced analytics. That’s the name of their package now. It’s Advanced Analytics, so we don’t just have analytics. We’ve got a one-upped analytics. We’ve got advanced analytics because somebody else’s analytics, “Mm, we’ve got advanced analytics.”

Not only that, but they have AI-enabled advanced analytics, which is great. That’s awesome when you read through. I wasn’t really clear what they’re doing. If they’re actually providing the AI and they’re actually helping develop some insights, or they’re just giving you data so that you can use it in an AI package or something like that.

Business Intelligence

Also, they seem to use business intelligence and analytics interchangeably. Even the name of the package sometimes seems like it is business intelligence. It’s a little confusing, but we’ve got to make sure we throw all the key buzzwords in to make sure that we extract as much value as we possibly can and make sure we check whatever box, “Oh, looking for BI? We’ve got BI. Looking for analytics? We’ve got analytics. Looking for AI? Oh, we have AI-enabled analytics.”

When they sort of talk about how great this package is, the solution, one of the key things that they point out is that it’s beyond spreadsheet-based analysis. They’re trying to pooh-pooh spreadsheet-based analysis. I don’t know whether it’s because some of their competitors are forcing people to take things out in Excel and do it themselves or whatever it might be.

The problem there is not that it’s in Excel. It’s that if somebody has to extract the data and do all kinds of work to clean up the data, massage the data, and do joins and all kinds of stuff to get the answers you want, the problem isn’t Excel. The problem is all the work you’ve got to do to get what you want. Excel isn’t a problem. We shouldn’t be knocking Excel.

They also knock Crystal reports. They say that they are so much different. They’re trying to dig on one of the competitors who used Crystal reports for the reporting.

A lot of this is marketing BS. I mean, do you care how the answer was derived or like what the underlying tool was to do it? I mean, the reality is it doesn’t matter how you get the answer as long as you get the answer and you can trust it. If I can trust it, I don’t care if it comes in the form of skywriting or smoke signals or pony express, although the reality is I’m anti-pony express. I mean, I like ponies, and they probably got exploited.

Software and analytics

Anyway, the reality is we build software to do analytics, and we use Excel internally. Everybody’s got Excel, and we use it. To knock categorically, Excel is nonsensical. Occasionally, it’s easier or faster to do something in Excel rather than a data workflow tool because they’re a little more cumbersome. Excel is really easy. You can fly through something.

Sometimes, we use it even like a prototype, and then we will say, “Oh, do we want to look and slice it this way or look at it this way?” or “Maybe, we should consider this when you move things around; very easily?” That can be a situation. Or sometimes, if you’re doing something one-off or there are situations like, I want to change one record. I’m going to do it in Excel, in the data table loaded into the tool rather than going and doing it through the tool. To go through all these gyrations to clean up a record is nuts, especially if you’re never going to use it again orto delete a record. I mean, come on!

There are times when Excel makes sense. Again, these are all just tools. It depends on the user and what you need to be done. If you’re saying like, “Oh, this is Objects or Oracle or Tableau” or whatever it is you’re using, it’s way better than anything anybody else has. Think of these as tools.

If you’re a carpenter and you’re building a house or whatever it might be, well, it’s like saying, “Hey! Well, we’re better than anybody else because we’ve got dynamite.” If you’ve got to, I don’t know, excavate something or, I don’t know, blow apart a rock, I’m not sure what you’re going to do in terms if you’re trying to lay a foundation of a house and you’re taking something out of the hillside or something, yeah, a hand drill really would suck. You really kind of need dynamite. At the same time, if you’re not a Seadrill, you’ve got a wall, and you’re just trying to drill a hole into one of the support beams or something like that, and all you’ve got is dynamite, I’m pretty sure dynamite is going to suck worse than a drill.

Let’s not somehow say that one tool is always better than another tool. The analysis is about getting the answers to questions you need with data, not how big your dynamite is.

 

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