Business analytics can help retail organisations be more competitive and improve revenue. Sudipta K Sen elaborates Competition characterises the retail industry more than any other business driver. Today, globalisation, changing consumer demand and the current state of the economy have resulted in cautious spending which has brought about a cutthroat retail environment.
Every day, leaders of retail organisations ask themselves two related questions: How can we maximise revenues from our product offerings, retail outlets and customer relationships? How can we maximise profitability without eroding the quality of our products and services, the shopping experience or overall customer satisfaction? Traditionally, answers to these questions have been forged using simplistic query and reporting tools coupled with instinct and intuition. Optimised answers to these questions have been all but impossible. Many retailers still rely on operational and transactional data to determine future outcomes in the hope that hindsight can generate useful insights and foresight. But knowing how many transactions took place is not the same thing as understanding why they took place, which factors influenced the outcome and how to optimise the result in the future. This is where business analytics can be very useful. Business analytics stands where human intuition meets analytic intelligence. Gone are the days when retail operations could be governed by the instinct and intuition of shopkeepers who knew customersí names, buying behaviour, seasonal trends, product preferences and likely future purchases. The complexity of todayís global, multichannel retail environment makes it impossible to glean that kind of knowledge only from personal experience and common sense. Retailers have turned to a variety of technologies in their quest to improve revenues, customer service and operational efficiencies. However, customer, transaction and market data collected from different channels often reside in disparate systems, leaving no practical and consistent way to analyse information for personalised customer insights. As a result, important decisions about merchandise selection, pricing, promotion, positioning, allocation, inventory replenishment, staffing and other aspects of retail operations are made and executed based on incomplete or inconsistent information. This leads to sub-optimal actions and in some cases even costly mistakes.  To endure and flourish in competitive markets, retailers need more. They need to readily access and analyse data whenever needed to gain comprehensive, accurate and forward-looking retail intelligence. Retailers need to synthesise the sea of data and derive the most significant information to provide a window into the future, necessary for proactive decisionmaking. They need business analytics to distinguish meaningful trends from ënoiseí, clarify why events occurred, and identify the significant factors that lead to repeatable successes or accurately predict future outcomes. In short, they need intelligent information that delivers strategic analytic insight. Delivering such advanced insights requires advanced capabilities based on true analytics. The following two key circumstances have opened up new opportunities for retailers to exploit analytics like never before: Retail automation systems yield more data than ever. The burgeoning popularity of loyalty and credit cards, the growth of the internet as an alternative sales channel, the proliferation of automation systems and RFID are creating a wealth of data that retailers are beginning to apply to better understand and optimise their businesses. All this data can be used more readily than ever. These factors, combined with spiralling costs and competitive pressures, are driving the adoption of a new level of information technology based on retailspecific analytics. Analytics can be applied to optimise many areas of the retail business, such as customer relationships, merchandising, operations and overall performance. Business analytics give retailers robust ways to understand what is happening and what could happen with quantified accuracy within stores, among stores and across chains. Leading retailers around the globe have begun using business analytics to make an array of strategic decisions; for example, where to place retail outlets, how many of each size or colour of an item to put in each store, how much square footage to allocate to a category, when and how much to discount, etc. The effects of better decisions in these areas can generate millions of dollars for retailers. What are the rewards of business analytics for retailers? Many retailers today rely solely upon capabilities that draw on simple descriptive measures and additive capabilities: summaries, weighted summaries, averages, percentages, minimum and maximum values. This may provide some insight into the past trends and performance, but it is difficult to determine the significance of these trends. Navigating a retail enterprise with hindsight reporting is like driving a car while watching the rear view mirror. You know very well where you have been, but the road ahead is still paved with uncertainty. More so in volatile economies, with so many dependent factors at play, past history can be a poor predictor of future events. In contrast, analytics can span not only the past and present to distinguish significance from happenstance, but also predict specific future outcomes. Analytic insight is like possessing an onboard navigation system. It predicts the road ahead and offers the best path to reach the destination, in spite of constantly changing circumstances.  The following scenarios reveal how analytic capabilities can enhance success in four key areas of retail business management: Marketing and CRM: It involves targeting the right customers with the right messages at the right time to maximise the value of each customer relationship. The essential foundation of successful retailing is a deep understanding of current and prospective customers. Consumers should not only be perceived as market segments but also as individuals whose circumstances and preferences change over time. Merchandising: Merchandising comprises optimising the selection, placement and promotion of merchandise among geographies and store locations and displays. When retailers align supply and demand chains with accurate demand forecasting, they can deliver the right product at the right place, time and price to fulfill customer demand. Operations: This involves optimising the behindthe-scenes aspects of retail business, such as real estate decisions, staffing levels and IT portfolio management. Once analytics has given an accurate forecast of demand, this knowledge must guide decisions for inventory replenishment and for staffing all store floors, catalogue call centres and fleet crews. Performance Management: This entails assessing the performance of individual stores and whole enterprises and understanding where changes will yield the greatest progress toward strategic goals. A consistent performance management process enables the organisation to fully understand how business processes are performing and where trouble is brewing. Retailers can therefore better align investments, which include people, infrastructure and capital, with the overall business strategy in ways that deliver expected results and meet overall objectives. What should retailers look for in business analytics solutions? The portfolio of available analytic processes targeted at retail organisations is extensive, but the real intelligence story is much more than a shopping list of discrete point solutions. The retailers who get the most significant returns on their investments will be those who take a purposeful, pragmatic approach by establishing an intelligence platform. Business analytics solutions should turn data about customers, merchandise and operations into knowledge that provides greater insight into performance and empowers retailers to make more informed decisions, gain a competitive advantage, strengthen customer and vendor loyalty and improve profitability. Business analytics solutions should provide an integrated, open and extensible foundation for creating and delivering accurate and in-depth retail intelligence. The future retail landscape will be defined by the retailers that know how to maximise customer satisfaction and profitability with the right combination of quality products, friendly and efficient service, unique value, differentiated shopping experience and a business model that truly serves logical and global communities. How will this be accomplished? It starts with understanding the customer, and then linking that insight into every decision thereafter, from merchandising and marketing to distribution, store operations and finance, so retailers can predict how best to serve their customersí ever-changing needs. The author is CEO and Managing Director, SAS India. |
