With unemployment low and consumer confidence reportedly stable, many retailers are hoping for a strong holiday season. But a shorter holiday season due to a late Thanksgiving and a year of less-than-stellar earnings has many retailers approaching the season with tempered expectations. At the macro level, global trade and tariff uncertainty, geopolitical volatility, and an inverted yield curve have economists and financial planners continuing to issue warnings for a recession or semi-recession in the near future.
In order to control costs, retailers have already been forced to close nearly 10,000 stores this year alone. Despite actions by the Fed to curtail a potential recession, retailers must still pursue innovative cost-cutting strategies to weather the potentially troubling times ahead. Below, we’ve outlined several use cases for retailers to leverage their data to identify opportunities for reducing costs with analytics and better managing the risks of ongoing financial uncertainty.
Workforce Optimization: Retail companies invest in training in-store employees to curate their desired customer experience, but do they have the right number of people with the right skills to service customers at various levels of busyness? Dynamically staffing the right number of customer service and retail personnel is a great way to cut costs and begins with accurate forecasts of activity, be it foot traffic or customer service points of contact. Considering the appropriate skillset mix will also avoid underutilization or lost sales, which can be complex in a retail environment where call-outs or substitutions are common. Do you know your organization’s optimal metric for shoppers-to-associate-ratio or how it affects in-store conversion during peak traffic hours?
Fraud Detection: Identifying fraud in retail can be difficult amidst millions of transactions and undefined fraudulent activity. Analytics can help bring attention to unusual scenarios through anomaly and outlier detection, as well as establish KPIs and alerts around typical employee or customer purchase patterns to identify fraud in discounts or returns. Putting the technologies and processes in place to identify recurring customers and analyze employee logs at the cash register and clock-in systems enables retailers to address theft and fraudulent activity that may otherwise go unnoticed.
Merchandise Planning: Simplification of SKU selection can reduce costs by focusing efforts on the most profitable products in a dynamic way. Trimming the tail items can simplify depot operations and streamline in-store replenishment. In an environment with thousands of products, analytics can quickly identify products as near-duplicates or substitutes cannibalizing sales. Forecasting and analyzing consumer demand signals will keep you ahead of the curve and offering the right selection of products. Analytics can help you understand not just which SKUs or product families sell well with certain consumer segments, but also which components or features are selling well across products.
Robot Process Automation (RPA): RPA is the technology that allows you to configure the automation of tasks. It is great for repeatable tasks like data entry and can offload tasks so that employees can focus their energy on more impactful work. RPA can reduce costs for retailers in a number of applications: automatically process returns through inventory and billing, communicate with customers about shipping status or delays, or manage rebates. Vodaphone is supercharging its processes through an analytics control center which utilizes RPA to simplify procurement tasks. RPA is additionally a solid way to prove out the value of analytics in an organization, as it is focused on taking action based on insights and analytics.
Reducing costs with analytics can not only help retailers realize short-term savings but create a platform for continuous financial returns. For many retailers, the effects of the Great Recession are still felt today. As we look to the future, advanced tools and capabilities are enabling a more strategic, data-backed approach to planning for the near-term economic climate. Leveraging data that your business may already be collecting can unlock new paths to savings, efficiency, and growth.
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Coauthor and contributions by Eric Gardner