The business world of the 21st century has grown and advanced so fast, that it is difficult to run a company without business intelligence to assess where one stands against the competition. Business intelligence aids companies by collecting the unstructured raw data from their transactions and transforming it into information which enables the company to be active instead of reactive.
Consider a company operating in the retail industry, which has a large assortment of different products in its inventory and a dozen stores. Now suppose that management wants to compile a list of most sold products for each store. The BI analyst working for the company can use their knowledge of BI tools to compile a report. However, where the BI analyst really adds value is in the quality of the analysis. For example, the top sold products could differ from store to store. The analyst could attribute this to the fact that customers in different locations like a different set of products. They could go further and attribute this to certain cultural differences in different regions. This sort of analysis can help a company streamline logistics by accurately forecasting future demand and ensuring that the company orders, stores, and ships the top products for each store.
How BI Aided a Large Kosovan Retailer
When I worked as a Data Analyst at one of the largest retailers in Kosovo, we managed 36 stores across the whole country. One of the issues plaguing our stores was the large amount of inventory which was considered dead stock. A product is considered dead stock when a single unit cannot be sold for a specified number of days. This is a major problem because if products cannot be sold, they have to be disposed of in accordance with local laws and regulations. This reduces assets on the balance sheet and increases expenses on the income statement, resulting in a decrease in net profit.
To begin with, we classified products by assigning letters based on their level of sales (A, B, C, D, X), with A being the best and X being the worst. The way letters were assigned was by dividing the sales of a selected product by the number of days in a specified period of time. For example, if a product sold 100 units in 3 months (~91 days), then we divide these two numbers (100/91) to calculate that 1.09 units of the product was sold per day. Based on our criteria, this level of daily sales would have a specific letter assigned to it. In our case, the product would have been assigned the letter A. After classifying each product by daily sales, we listed each product’s cost per unit. Keep in mind this is the cost of buying the products from the supplier, not the sales price. After doing so, we multiplied each product’s cost per unit by the stock level currently in inventory to get the total cost for each product. In doing so, we were able to report the percentage of products for each letter that were currently in the company’s inventory.
In order to improve inventory management and increase the overall quality of inventory in stores, the company’s goal was to stock products with assigned letters of A and B while decreasing the number of products classified as C, D, or X.
The idea of this Business Intelligence was to just see which products were dead stock, or not selling that well. In deciding what action to take and whether to discontinue certain categories of products, senior managers would of course need to examine the root causes of sluggish sales. For example, changing customer preferences, high prices, low quality products, inadequate retail displays, poor store location, or strong competition.
Final Thoughts
In today’s fast paced business environment, a company without access to business intelligence is like a ship navigating uncharted waters without a compass. Business Intelligence can aid companies in any industry by highlighting where customers are spending their money. This in turn enables management to make well informed decisions and be more proactive in decision making.
Loredan Emini graduated from Rochester Institute of Technology in Economics & Management. He currently works as a Power BI specialist for a German company, and as a lecturer of Power BI.
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