Business Intelligence in Retail Industry

Retail industry is a highly competitive market with new players entering the fray every once in a while. Rapidly changing customer demands and mounting pressure from suppliers, effective management of information is imperative to make good business decisions.

Target Corporation is the second largest retailer in the US having its sales through store fronts as well as digital channels. It differentiates itself from other discount retailers like Walmart and K-mart stores by offering more trend-forward, upscale merchandise at lower costs. A typical Target store offers clothing, beauty products, electronics, health products, groceries, home and hardware supplies.

Along with popular brands Target also sells its own branded labels such as Archer Farms, Market Pantry, and Simply Balanced; Sutton & Dodge, their premium meat line; Threshold, their premium furniture line; and the electronics brand Trutech. Target also has a separate e-commerce operations through the target.com domain. From its aesthetically designed store fronts to an award winning i-Phone app, Target aims to make their customer’s shopping experience memorable and unique.

Target with its operations across 1,801 locations throughout the United States has large volumes of data, right from its supply chains, warehouses and store operations. With this myriad information at their disposal Target wishes to make leverage this data to develop actionable insights and deliver value. The CEO of the company Mr. Brian Cornell wishes to use Business Intelligence to have insights into the various facets of his business. At a very basic level he wishes to see the performance of the companies from the perspective of the following parameters:

• Customer : Who are the type of customers that typically prefers to shop at Target stores.  What would be their average annual income? How many customers are enrolled for reward programs and how can they be segmented based on their spending. What is the age group of people shopping at the stores and the number of people preferring store fronts vs online shopping. 
• Sales Channel: Which are the different channels that are more profitable to the company. While their standalone retail stores are their main source of income, alternate channels such as online shopping, TV shopping networks, mall stores etc. are also channels that Target is interested in.
•  Promotional events/Discounts: What is the increase in sales during special promotional events such as Black Friday or Cyber Monday. How much discounts is to be provided as part of the reward program, which are the products on which discounts should be offered, for what duration should they be offered are some of the parameters the CEO would like to look into.
• Vendor/Supplier Payments: Which are the vendors and suppliers that provide the best raw materials and at what price? what has the performance of the vendor been in terms of timely delivery of raw materials and if quality of the products have been consistent.
• Employee Payments: Employees include clerks at the checkout counters, warehouse workers, delivery workers and other managerial and administrative employees. Information on the number of employees at each store, customer to employees ratio, salary paid to employees are different location and the working hours of employees are some of the parameters that the CEO would be interested in looking into.

      How Dimensional Modelling helps?

a     Using Data Dimensional modelling will help Target to understand its revenue model better by giving valuable insights on the sales it generates. By defining various dimensions such as store, product, date, promotion etc, the CEO will be able understand the granularity of its sales generation. Data dimensional will help understand that for a particular product, at a particular store at a particular location, what was the daily or monthly sales that occurred.  By observing the high cardinality, numeric measure of entries in the fact tables we would be able to get clear measure of various business event such dollars sales for a particular transaction by a customer. Additive and semi-additive facts will also help in aggregating various facts together to give the stakeholders the necessary level of granularity.

      Accumulating Snapshot Dimensional Model:

      Considering that there are many milestones in the entire process of obtaining the inventory, storing it in warehouses and delivering it across various stores across the country, an accumalting snapshot would be the ideal type of dimensional modelling for understanding the sales revenue for Target corporation.

  

     Below is a sample dimensional model that can be used for the Retail Industry. Some of the key dimensions are Product dimension, payment dimension, store dimension etc.

Thus through the use of dimensional modelling for data warehousing, key stakeholders of the business can get an idea of how Target is performing through implementation of various parameters.

References:

• http://flylib.com/books/en/4.65.1.20/1/
• https://www2.microstrategy.com/download/files/whitepapers/open/Business-Intelligence-and-Retail.pdf
• https://en.wikipedia.org/wiki/Target_Corporation