Beyond Sweaters and Ballet Shoes
By Sean Jackson, Sean.Jackson@actian.com
In recent weeks, there have been some well-publicised examples of retail giants whose financial performance has been severely impacted by breakdowns in the supply chain. As salt in the wound to these behemoths of retail, there are just as many examples of organizations that have exceeded market expectations due to an ability to behave nimbly and respond quickly to changes in consumer demand.
For example, leading U.K. retailer Marks and Spencer recently announced that it could have sold three times more sweaters, had it paid closer attention to data generated by its own stores. This had a major impact on its share price, making it the second biggest faller in the FTSE 100 for the quarter. At the same time, John Lewis (another retailer) predicted consumer demand and provided the right stock to the right stores. Sales of its ballet shoes were up 129% year-on-year and profits were big.
This news made me wonder what the root of this issue was; which factor could cause success for one and failure for another. Was it just a case of getting lucky with the right stock at the right time or was there something buried deep in the DNA of the organization that gave some retailers a crucial advantage?
The answer is simple -- success comes from the ability to distill actionable intelligence from data gathered from a range of internal and external sources. This data consists of diverse factors including: the demographical characteristics of your main customers; their psychological state and purchasing patterns; how they plan to use your products; the macro economy; even what the weather is doing that day. Investigated quickly enough to catch the trend at its birth, these all come together to define crucial business decisions such as: what to stock; when and how much of it; how to position it in the physical environment of the store and how to package and market it.
Having access to a fast and affordable analytic database platform can unite all the data from operational systems (EPOS, stock, merchandising, loyalty, ERP etc) and give business managers access to the right information at the right time, helping them to drive growth, performance, competitive advantage and, ultimately, profits. With a fast and cost-effective analytic database engine, retailers can optimize their merchandising and product range by understanding buyer behavior and identifying trends immediately. They can also refine supply chain management by co-coordinating stock deliveries and replenishment, meeting the demands of each potential customer.
Cross-purchasing behavior analysis can also be calculated using a fast analytic database engine, which allows for large datasets to be joined together. Such intelligence can then be used for marketing purposes, product range decisions, promotional planning and evaluation, shop floor layout. The opportunities are endless.
Nevertheless, success is not just based on speed or high performance; any analytic solution needs to be cost-effective. There is no point in a retailer investing in analytics if the system to be deployed involves a stack of new hardware that needs to be powered and then cooled, as well as configured and maintained. Retailers will be far better off with systems that leverage off-the-shelf hardware and have as little a footprint as possible.
Savvy organizations, such as US retailer Sheetz, are using analytics to adapt product selection and availability to the needs of their customers faster, to improve customer service and tailor the shopping experience to the individual in a cost-effective way. In today’s competitive retail market where the slightest negligence renders giant chains out of business, it is no longer just about survival of the fittest, but survival of the fittest and quickest. Retailers cannot afford to be anything but ultra-responsive; they need a business intelligence system that provides analysis without prompts or delays. By ignoring this key need, they stand to lose out on opportunities that can make or break their business. And that is something that goes beyond the ability to analyze sweaters and ballet shoes.
Sean Jackson, marketing director, Actian Corp., which enables organizations to transform big data into business value with data management solutions to transact, analyze, and take automated action across their business operations. He can be reached at Sean.Jackson@actian.com.