As retail markets become increasingly competitive, the ability to react quickly and decisively to market trends and to tailor products and services to individual clients is more critical than ever. A business intelligence system can be a very effective means of organizing and analyzing the vast amount of information generated in a retail business, and help you generate a more effective business model for keeping your business profitable.

To achieve these goals, retailers must be able to successfully manage inventory, product mixes, promotions, supply chain dynamics, and a number of other factors. Furthermore, as retail markets become increasingly competitive, the ability to react quickly and decisively to market trends is more critical than ever. Lack of information is not the problem—data to assist in making these kinds of decisions is readily available from a variety of sources. On the contrary, the problem is that the volume and complexity of information available to organizations is overwhelming. Increasingly, successful retailers will be those that can effectively categorize and utilize these data for category management, client loyalty programs, promotions, etc. in short, Business Intelligence.

Category management software applications have traditionally focused on the first category of data, with occasional forays into the second. While these are certainly critical metrics in determining profitability and product mix, companies are increasingly taking a more client-centric view of their business, and are looking to the third and fourth categories of data to provide new insight into marketing and sales.

Now that we have discussed the decision support capabilities that will be crucial to surviving in tomorrow’s retail business landscape, let’s take a look at how these capabilities align to the classic needs of the business. Consider the case of adding new products to the inventory. A new product is under consideration for introduction into a chain of grocery stores. When introducing a new product, we want to know whether it is expanding the category or merely cannibalizing sales of existing, higher margin products. Retailers frequently introduce products into one or two markets to gauge their success before rolling them out to all of the stores.

To judge success of the new product, we want to compare sales and margin of the entire category in the test store to a control store where no new product was introduced. This could be accomplished using Business Intelligence. We would look at percent changes over a specific time period, and be able to drill down to greater detail once we have formulated a hypothesis

For example, let’s say we introduced the product at a significant discount. Consider this scenario: Overall sales in the category did not increase relative to the control store (both stores increased absolute sales by about five percent.) Drilling down on product suggests that sales of the new product cannibalized sales of existing products, rather than driving increased demand and expanding the category. Furthermore, the discount on the new product is shrinking the category margin. The combined effects of cannibalization and aggressive discounting have seriously hurt the bottom line in this category. Depending on the goal that has been defined for this category, this may not have been a successful product introduction. Drilling down to the product level highlights the results of new product introduction on the sales and margin of existing products. Based on this analysis, we may choose not to introduce the new product at other stores. Or, depending on the products that it competes with, we may choose to introduce the product but maintain margin by pricing it more competitively. Insights from the Business Intelligence system enable us to accurately assess the true impact of this business event, and evaluate its effectiveness.

As retail markets become increasingly competitive, the ability to react quickly and decisively to market trends and to tailor products and services to individual clients is more critical than ever. Although data volumes continue to increase at an astounding rate, the problem is no longer simply one of quantity; at the heart of the issue is how companies are using their information.

Increasingly, particularly in the retail industry, it is important to understand client preferences and behavior. A business intelligence system can be a very effective means of organizing and analyzing the complex barrage of information generated in your business, and helping you generate a more effective business model for keeping your client base happy and profitable.