A data cube is an example of the RAN function, which stands for Regularized Automatic Numbering. This function takes an input (the fact measure or survey) and creates a series of output (fact blocks). In a data cube used at a retail chain store, the fact measure is printed on the vertical columns and the product information is printed on the horizontal rows. The fact block numbers are used to identify the product category and the store can then group the items into groups. For example, if there are ten facts in a data cube and they fall under the product “Apparel,” then it would be wise to group the products by the type of apparel.

An example data cube used at a chain retail outlet would look something like this: Product Name Facture Retail Price Category Code Number. It would then be followed by an item number. The groupings could then be further divided into smaller groups such as men’s clothing, ladies clothing, accessories, shoes, handbags, and etc. The fact that more categories would be grouped together and labeled together could aid in identifying more product categories. This would in turn lead to more revenue and improved profitability.

• The fact measure itself is an important metric to use when determining profit margins for inventory.
• It allows for the reduction of costs and thus enables the calculation of an effective ROI.
• The most commonly used and effective fact measure tools are the bar and column charts.
• Bar charts display a normally distributed data set on a column.
• When used with a data cube used at a chain retail business, it would be practical to group products based on their type.

The usefulness of the fact base would also be useful when working on the inventory front. A data cube used at a chain retail business could have product categories mixed up. If one category is overstocked and the other under stocked, it would be useful to group the over-stocked items in another category in comparison to the under-stocked items. By grouping similar products together, the fact that there is a high profit margin can be determined.

A final application of a fact measure is when dealing with customer service. An example of this could be where a customer calls up the customer service desk only to be told that they cannot process their order at that particular store. The process that was used previously was to process the order by hand and then call the customer service desk. However, with the metric system, the fact that the order cannot be processed is translated to an effective and accurate statement instead of calling the customer service representative. As well, by grouping similar products together under one metric, the chain retail business can improve its overall efficiency.

Metrics are crucial to a chain retail business. This fact applies not only to the products themselves, but to the entire operation. If one fact is substandard, it can greatly affect the overall profit margin. The metric system can translate the statistical data, turning it into a tool that can positively impact the overall bottom line. By using a metric when calculating profitability, the chain retail business can improve its bottom line profit figures.