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Back in the mid-2000s, when I co-founded a billing company Cobalt Health with a partner, we ran into something that I found a lot confusing at the time. That was this issue of the closing period, or the end of it took to close out a period. We frequently get these questions in the sales cycle, like, “How long does it take you to close out a month?” I was always perplexed about this because they’d ask like, “Is it three weeks? Or is it a month? What is this timeframe?”
Waiting in vain?
We essentially set up the business to be a quick close from the company’s inception, meaning at midnight, the month closed. So you could go in, see the data at 00:01, and see precisely what we did for the month. There wasn’t this waiting period.
It was bizarre because we always get this question. It was so consistent: How long, how long, how long? And we would answer like, “Well, it’s instantaneous.” We got these confused looks, and people wanted to talk about it. And we thought, “God, this is so strange.” We thought, “Well, we’re new to this industry. Maybe, there are some things we don’t understand. I mean, certainly, we understand finance and accounting pretty well.”
What about enterprises?
We had two Ivy League MBAs who started the company. So we had a reasonable understanding of finance. It’s just that it seemed so strange, and we could never quite understand it.
Even at the time, we remembered that there were some substantial sophisticated organizations. I mean, we’re talking about multi-billion dollar companies like Cisco, who would close out their quarter or fiscal year in a matter of days, meaning they would publish the results of their financials for stock market purposes publicly in something like five days.
Now, if you think about that, five days, they had to be just auditing the results and looking at all the information and things like that, making sure things were categorized quickly. They weren’t entering any data. They couldn’t have been because there’s no way you could load all that data and review it all in a couple of business days. That means, essentially, they were dealing in real-time data at that time and then added it and dropped it out. For a multi-billion dollar publicly-traded company, that would make sense to take a few days to do that. Still even then, it was only a couple of days, like five days.
Let’s discuss accruals
For us, we were instantaneous. Even now, I kind of wonder, like, “Is there some reason for this?” I mean, we understand accrual versus cash. So you might think, “Well, you’re all maybe on an accrual basis rather than cash.” I can’t think of a reason that it would make sense to do this even if you’re on an accrual.
If you’re on an accrual, you’re essentially going to book the revenue, not the total revenue but some allocation towards what you expect to collect for that month and then the cost again and things like that. Then, at some point, in the future, you’re going to adjust to that, but you’re not going to alter in five days or three weeks. Indeed, not for everything. There’s going to be some for the product in the future. So I can’t even see a good reason from an accrual standpoint.
The competitive edge
Maybe, we were just ahead of our time in the mid-2000s. Certainly, we were on some other things related to technology. Even at that time, we didn’t take any couriers. We refused to do any courier with any clients.
That’s not a massive revolution in the mid-2000s, but it was still pretty common at that time to have couriers. We didn’t have any physical file cabinets, like the paper that came into our company. We did not keep paper files ever.
Document all of it
From day one, we did electronic document storage of everything, and we shredded everything. So we didn’t keep paper files. We didn’t even do fax. Most organizations even now still have a physical fax machine, and this is 15 years from that period. But at the time, we refused to do physical faxes either. We had electronic faxes for our clients. They were in the ER or in the facility or something like that.
You could drop them in a fax machine, and they would load directly into our systems. So we didn’t have to have a paper printout and all those kinds of garbage and problems.
Some reasons are more legitimate in terms of waiting and lag time, things like that.
We’ve brought up some now that are not legitimate, and I still don’t understand, but there are some check dates. If you’re going to try to reconcile and look at the check dates, it might take a couple of days to post when a check is received. So you might have some period issues across that. Something that’s received on the 30th-31st doesn’t get posted until the 1st or the 2nd. Okay, great! We can understand that.
You may also even experience longer-term delays related to those types of issues like you can’t post a payment for several weeks, sometimes four, five, six weeks, because the payer didn’t give you any documentation around that payment, and you can’t figure out what patients to apply it to. That happens with much frequency, and it takes quite a bit of time to track that down, chase the payer, and get that information.
We understand that there were legitimate issues, but that still doesn’t mean you have to wait to close out a period essentially. Depending upon how you’re slicing and dicing, data is just a lens on how you’re looking at things.
How long is too long?
There are some easy solutions to certain things like accounts receivable, where people are trying to figure out, “Okay, do we count it, or do we not count it towards the AR outstanding?” Okay, it’s pretty easy. If the balance is zero or not zero, then you can filter it out and do calculations around AR days and other things. So there are relatively easy ways to deal with that.
Some others are much more complex and don’t have quite an easy solution. Even if you can do something instantaneously, you may want to wait to get a little further up that Pareto. But we still don’t understand this mindset. Further, that’s the issue, I think, where we’re trying to focus.
There’s this concept of “Oh, we can’t really know stuff for a long time, and so we should wait six months or only look at data that is six months old to have some level of confidence in it.”
We think there are better ways to do that and better ways to approach it certainly, if the goal isn’t financial reporting (because you should be able to do financial reporting much faster.) Yet, performance analysis, again, you shouldn’t have to wait that long to get some indications of how things are performing and trending over time.
We’ll come back in another podcast and talk about some specific examples and how to deal with this. But we have to change our mindset towards being instantaneous, data-oriented now in real-time data, not “We’ve got to wait a long period to know anything.”