Most computer systems provide a lot of information. Management and employees depend on the analysis provided by the computer software to make critical business decisions. But do you know how the numbers appearing on your reports and screens were generated? Before you respond, “Of course I do, it’s only common sense!”, let me describe some surprises several of my customers have experienced in the last six months:
Episode #1 – An English food distributor was perplexed. Sales of a particular frozen food item had dropped off, but his computer system was maintaining a high level of inventory of the product. We investigated. Here is the usage history we found:
| Month | Usage (Cases) |
| December, 2000 | 35 |
| November, 2000 | 52 |
| October, 2000 | 76 |
| September, 2000 | 94 |
| August, 2000 | 128 |
| July, 2000 | 137 |
Notice how usage for the item decreased rapidly from July to December. Yet his system was predicting demand for January 2001 of 175 cases! The current purchasing parameters were based on this expected demand. We called the software support team of the computer company and asked what was going on. They responded that predictions of future demand were based on an average of what was sold in the past. Looking at usage over the previous six months, I still didn’t understand how the system was predicting demand of 175 pieces. The support technician explained that average usage of the product was calculated over the entire time it had been in inventory. The item had been stocked for a little less than 10 years (3,554 days, or about 118 months). During that time the company had sold 20,650 cases of the product, or about 175 cases per month.
I tried for half an hour to explain that considering average usage over a ten-year period was not a logical way to forecast future demand of a product. The support person continually repeated a phrase that has nearly caused me to commit murder several times over the past 21 years: “The system is performing as it was designed.”
Episode #2 – An industrial distributor was looking at a ranking report produced by his computer. This is a report that lists items in descending order based on cost of goods sold. He was perplexed. He had actually sold $4,000 worth of a product (at cost) this year, but the report showed a value of $24,000 for the product in the cost of goods sold column. What happened? We called the support department of this computer company. The support person told us that:
- The distributor had just completed the second month of his fiscal year.
- In the first two months of the fiscal year he sold $4,000 worth of the product.
- The system annualized sales over the first two months and projected that he would sell $24,000 for the entire year.
Unfortunately this was a seasonal item that was sold only in January and February. I explained to the support person that many products do not have consistent usage throughout the year. I further said that it was not logical to project sales over an entire year based on two months usage. Again, I was told that the system was functioning according to the design specifications and the documentation. Had the customer not carefully scrutinized the report, he would have treated the item as though it had greater than actual sales.
Episode #3 – A distributor called me and said that his computer system was projecting a 10% increase in demand for the items of in a certain product line this year. He said his system based the increase on a trend calculated by comparing sales recorded during the past several months this year to the sales recorded in the same months last year. The system’s methodology sounded logical, but he too was perplexed. Neither he nor his sales department thought these products had been selling well in recent months. The distributor and I looked at the usage history and found that most products had experienced a 3% to 5% decrease in sales. Again we called the support department.
The support technician explained that the system was designed to calculate trend factors based on the cost of goods sold of all items in the line. And this year there had been a 10% increase in cost of goods sold over the previous year. Unfortunately the cost of goods sold increase was due to a 13% price increase in the early part of the year. If we had followed the suggested trend factor and increased the stock quantity of each of these products, we would probably been faced with an overstock situation.
These examples involve three very popular, widely used distribution software packages. In each case the customer did not understand how the system calculated some critical inventory-related information. – information on which they relied to make important business decisions.
There is a very good chance that you are unaware of some (though perhaps less dramatic) “quirks” in the information provided by your computer system. You need to be aware of them. This data confusion may be caused by a feature that was designed for a specific customer or industry, and your company may do business a different way. The other firms may experience different patterns of usage, cost their inventory differently, obtain material from different sources, process transactions differently, etc. Yes, there is a possibility that a feature was not well designed and is a “bug” that needs to be corrected. But keep in mind that every business is unique. Even companies in the same industry buy material and process transactions in very different ways. No single computer system can meet the precise needs of every business.
Take the time to be sure you understand how your computer system derives the information it presents on inquiries and reports as well as the computations it follows in calculating replenishment parameters. Examine every critical field! Remember that even fields that seem to have a clear definition can be computed in several ways. For example:
On-Hand Quantity – Some systems reduce the on-hand quantity of a product when material is shipped. Other systems update this quantity when material is invoiced.
Cost of Goods Sold – Is the cost used in your financial statements based on an actual cost, replacement cost, average cost, or some other cost? If it is an average cost, how is this amount calculated? We know of four different methods for calculating average cost.
Demand/Usage – Some systems consider customer requests in demand or usage. Other systems consider only actual sales. How does your system consider warehouse transfers in determining total demand or usage?
Occasionally we find a customer being misled by a system providing incorrect information. But more often we find mistakes made because a customer incorrectly assumed they understood the meaning of a field. Don’t fall into this trap. If you understand how your system derives information, you can interpret the data correctly, or you can determine how the system must be modified or enhanced to provide you with the information you need to run your business.