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Let's Go Fishing for Data

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July 06, 2017
Financial Systems
Ron Strecker

©2017 Hospitality Upgrade
This work may not be reprinted, redistributed or repurposed without written consent.
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Winter is gone and the fish are getting active. 
 
Have you ever wondered how a fisherman knows the right bait to use to catch his favorite fish? It takes practice, patience and learning from all those who’ve gone before you. Field guides explain fish behavior and you can learn how to catch the fish you want.

There are numerous field guides out there that explain fish behavior, their favorite foods, and their preferred environment. Keep at it and you’ll learn how to catch the one you want without using trial and error.
 
Now picture all these fish as important pieces of data. Some fish are isolated in PMS Lake, a few more are over in POS Pond. Occasionally, you’ll see a few that look like they came from PMS Lake but later you realize they hatched in S&C Swamp. Look closer and you’ll find time and attendance tadpoles bumping into purchasing poles in all these locations. Small streams between these remote fishing destinations allow various species to coexist. Think of this as data from one system being shared with another system through interfaces.
 
In my previous article, I took you on data’s journey from its creation in our front-line systems, through a few twists and turns as daily management information, before it reaches its final destinations – general ledgers and boardroom presentations. The takeaway was to keep that data path free from interruptions by letting interfaces do the work.
 
The data that makes it to the boardroom is only a fraction of what’s being generated constantly by the property management system (PMS), point of sale (POS), and sales and catering system (S&C). The mountains of data available need to be harnessed into accurate, actionable and timely management information – revenue, payroll, booking pace, arrival and departure patterns, guest demographics, menu sales mix  – each byte is important to someone.
 
Sooner or later, some ingenious fisherman will figure out how to find all his desired fish in one single, easy-to-reach location. No more traveling here for one fish or there for another. No more looking for the optimum lure. Fishing for data is a bit trickier, but not impossible. It simply requires us to be more precise in our language and description of the data we seek. The process of building a massive warehouse to house all your data in one location isn’t for the faint of heart.
 
Lucky for us, the industry already has a field guide of sorts when it comes to the data we commonly encounter. The Uniform System of Accounts for the Lodging Industry, Eleventh Revised Edition (“USALI”) is more than just a resource for how to build a financial statement. It includes extensive discussion on common statistics used in operations and the detailed formulas required to calculate important metrics. Your accounting office most likely has a specific general ledger account assigned to many of these measures. 
 
The other data floating around our primary applications is a great deal like general ledger data. In fact, you’d swear it was identical. Over time, data that looks similar has been studied, tested and differences documented. This discovery process will help identify the correct data for any specific use. It may be a single purpose statistic or it might be used many times more for other reasons. Some data will make its way to the general ledger while similar-looking information will be discarded or used for other special reports. 
 
Every scenario described above can actually happen. It doesn’t mean any single report is right or wrong. The key is to know why they’re different. Application deficiencies or interface design limitations are usually part of the problem. Other times the difference is rooted in a process that needs to change. Communication is key. 
 
Developing a common language is critical when multiple applications have data elements that sound like they’re the same. USALI is a great way to start creating this common language. Every member of the executive committee should have a copy. You can use it to teach  your rising stars how to read financial statements. If you’re selling software or helping corral data inside your company, you need a copy, too.
 
[The real danger is that sometimes, and maybe not all the time, what you believe to be accurate data may have fallen victim to Christie Davies’ Theorem: If your facts are wrong but your logic is perfect, then your conclusions are inevitably false. Therefore, by making mistakes in your logic, you have at least a random chance of coming to a correct conclusion.”]

 
If you’re making plans to use data warehouses and cubes to streamline your management and analysis efforts, do so cautiously. Study all the applications closely to identify the critical data available and what pieces it’s OK to ignore. The goal is to identify that single source of truth for the data you need to manage your business.
 
One last fishing analogy as you dive deep into your data pond: There are many times where the data, like fish, may look like the big catch. But if you aren’t 100 percent sure that what you caught is what you want, don’t hesitate to throw it back!
 
Ron Strecker is the chief financial officer for the Al J. Schneider Company.

Two of the most common data points you hear in the hospitality business are occupied rooms and room revenue.
You can run a PMS report with this information just as a sales and catering system report. But proceed with caution, since the two reports may not be the same.

 
Here’s an example that could happen to you:
 
It’s bright and early on a Wednesday morning in a busy convention hotel. The revenue team is meeting to discuss the most recent weekly results from Smith Travel Research. The report contains important daily performance specs compared against your competitors. In short, it’s a report card on how well your revenue strategies are performing.
 
Within moments there’s disagreement around the table. The numbers don’t match up with the information everyone printed from their applications. The sales director is looking at her S&C report, front office has a PMS report, the revenue manager has an RMS report, and the controller has a general ledger summary. Each counts room nights and room revenue from the past week. Some pieces of some reports match the Smith Travel report, but no two are exactly alike. Sound familiar? Have you lost time trying to figure out why such basic information is different in each system?
 
Let’s look at each report and see what could get in the way of accuracy. Of the four, the controller’s general ledger summary is the one that will wind up in a board presentation, so it better be right. After all, most general ledger entries for room nights and room revenue come directly from PMS transactions by way of an interface. But even the general ledger summary and the PMS report don’t match up.
 
Your sales director relies on a sales and catering software report. Many of these software packages receive data directly from the PMS each night showing group rooms consumed and group revenue generated. However, if a group room is occupied in a room type defined in PMS but not in S&C, there’s nowhere for the actual data to go in S&C. If rebates were included in the room rate but calculated as a total after checkout, it’s likely this revenue adjustment won’t interface to S&C. There’s a good chance the sales director’s report is too low on room nights and too high on room revenue.
 
The front office manager’s PMS transaction report should be identical to the controller’s general ledger summary. All transaction codes go to a specific general ledger account through an interface. Perfect. No human intervention. No chance for error, right? Wrong. Someone recently set up a new rate plan and assigned an incorrect transaction code. The room night and the room revenue from reservations on that rate plan went to non-room statistics and revenue.
 
Maybe the revenue manager has a better answer. After all, the revenue management application is constantly refreshing its database with actual and future activity. Those reports are driven almost entirely by rate plans. Too often though, some information isn’t incorporated into a standard revenue manager’s report. Often adjustments are made to a group’s master account days or weeks after that group checked out.
 
We end up back at the controller’s general ledger summary. It creates the financial statements. If setting up new rate plans in the PMS can cause an undetectable error of this magnitude in the general ledger, then your checks and balances aren’t working. Luckily, the ability to establish rate plans in the PMS is usually limited to a few users.


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