Methods to Gather Information

Why retailers need a centralized data hub

We will explore some of the key technologies retail businesses have adopted to meet their goals. How do retailers keep track of all of the products they sell? What are the benefits of data-driven information technology? What are the key information systems that can support better business decisions? What are data warehouses and how are they used?

One of the challenges of a retail business is the need to purchase inventory well in advance of customer demand. Traditionally, retailers have relied on observation and even intuition to guide their purchasing decisions. Retailers can do this by listening to customer comments while they shop, noticing out-of-stock conditions on store shelves, visiting competition, and conversing with suppliers to receive (somewhat biased) information.

Beginning roughly in the 1960s, the evolution of marketing as a discipline presented retailers with more interactive techniques to gather information about their customers. They began using surveys, interviews, and focus groups.

Before sophisticated information technology, retailers relied largely on prior activity and this “anecdotal” information on which to understand their customers. Technology was kept in the back room and used for simple business operations. Now, data-driven technology is at the core of retail business.

To run a successful retail business, management must be able to answer questions that only information technology can provide. Which are our most profitable store locations? What products are selling best and are the most profitable? How is our customer base changing its buying pattern? Is our flow of inventory in line with anticipated sales?

Today, the latest data-driven technology has even changed the paradigm from asking what all of our customers will want to asking what EACH of our customers will want.

Retail Information Systems

Retail information systems have evolved in similar fashion as business computing in general. More data has created the need for larger storage and faster processors. The need to give wider data access to more employees, so-called “data democratization,” has necessitated de-centralizing information platforms and increasing ease-of-use. We have seen platform evolution from mainframe systems to client/server to cloud and now to mobile platforms in retail information systems.

Today retail information systems (RIS) vary in platform, cost, and functionality–and range from simple to complex. Simple systems can support point-of-sale (POS) transactions and keep track of sales activity. Complex systems, designed for large enterprises, can manage all aspects of the business: POS, Supply Chain, Finance, HR, CRM and more. Whether simple applications or complex systems, modern retail information systems all utilize databases and provide access to stored data through Graphical User Interfaces (GUI).

POS informs retailers of the details of sales transactions: what item was sold, where the transaction occurred, at what price, what employee performed the sale, and information about the customer making the purchase. Supply chain management systems (SCM) track the product’s origin even before it arrives at the store or warehouse (and will be discussed in more detail in the next section). Financial data systems provide management with data concerning the organizations’ profit and loss factors. Human resource systems (HRS) keep track of employees: status, title, employment type, salary, address, etc. Customer relation management systems (CRM) track customer information and will be discussed in a later section.

Data Warehousing and Data Mining

All of the RIS we have discussed so far have one major thing in common—an underlying database to store their unique data. Through the process of mergers and acquisitions, most large retailers inherit duplicative systems that continue to exist independent of each other due to the large cost of consolidation. With data “everywhere,” retailers turn to the latest IT techniques.

Data warehouses (DW) are created to bring related information from disparate databases to one large database so that it can be easily analyzed.

In computing, a data warehouse (DW or DWH) is a system used for reporting and data analysis, and is considered a core component of business intelligence. DWs are central repositories of integrated data from one or more disparate sources.

Once the data has been migrated to the DW, data scientists can begin to provide retail management with meaningful information through the practice of data mining. Data mining is the process of discovering patterns in large data sets and involves methods at the intersection of machine learning, statistics, and database systems.

With the mining of information in the data warehouse, management can gain valuable insights as to how best to run the business. This is usually accomplished through queries and reporting.

Queries are business questions translated into code to bring results from the DW. What is our best-selling product line? What is the profit margin on our private brand versus the name brand products? Who are our best customers? How do our online sales affect our inventory position for our stores?

Business reporting is simply scheduling the most common or requested queries at regular intervals and pushing the information out to the organization’s information consumers on a regular basis.

One of the most notable data warehouse success stories comes from the healthcare industry in the 1990’s. A large national health management company had more than nine regional centers, each operating semi-independently. Each regional center had its own management and business infrastructure, including information technology.

The company’s top medical experts noticed that the care being delivered for its diabetes patients was inconsistent across the regions. Some regions claimed that certain treatments were more effective, but came at a higher cost to the business. But the real problem was that the clinical data needed to understand what was the most effective treatment was locked up in 10 different databases, many of which were using different database software.

A data warehouse was constructed, pooling the data from all of the regional warehouses and providing access for the first time for national clinical research analysis. Out of hundreds of different treatment programs, three were found to be the most effective, and of those, two were found to be the least expensive. These data warehouse results were a win for the patients, doctors and the business.

UPC, RFID, and QR Codes

There are three common technologies retailers use to identify and track individual product units in retail sales transactions, inventory management and distribution, or supply chain- UPC, RFID and QR codes. Most of these symbols are quite familiar as we see them on a daily basis.

The Universal Product Code (UPC) is a barcode symbology that is widely used in the United States, Canada, United Kingdom, Australia, New Zealand, in Europe and other countries for tracking trade items in stores.

Radio-frequency identification (RFID) uses electromagnetic fields to automatically identify and track tags attached to objects. The tags contain electronically-stored information. No line-of-sight is required to receive information from RFID which makes it better suited for inventory flowing through a warehouse conveyor system, for example.

A quick response code (QR code) is a matrix barcode made up of dots. Because it is two-dimensional, it can hold substantially more data than one-dimensional barcodes, such as UPC. It can be read by a QR scanner or by a smartphone with a camera.

This YouTube video does a fairly good job providing some background information on this technology. It discusses the origin of bar codes, describes how they work, and helps us understand the evolution to QR codes.

You can view the transcript for “QR Codes and Barcodes as Fast as Possible” (opens in new window).