This article first appeared in the Summer 2017 issue of The Record.
In 2002, general manager of US baseball team Oakland Athletics Billy Beane noticed something that no one else did: players were being evaluated based on gut feelings, folk wisdom and outdated standards of measurement. Facing limited spots on the team’s roster and significant budget constraints, Beane used statistical methods (sabermetrics) to objectively evaluate baseball players. Seeing the value of players where others did not, Beane recruited the best players and Oakland Athletics became a competitor of top teams like the New York Yankees – despite its low budget.
Retailers and consumer packaged goods (CPG) companies need to treat every inch of shelf space like a spot on Beane’s roster, using statistics to ensure that all stock keeping units (SKUs) positively contribute to weekly sales.
Today, 35-40% of retailers’ total inventory is stuck in non-performing SKUs that contribute less than 5% to total sales. To eliminate waste and optimise their inventory, retailers and CPG companies should implement SKU rationalisation, using analytics to determine the merits of adding, retaining, or deleting items from a shelf.
Currently, most retailers and CPG companies analyse SKU performance at a top level – such as by region or channel – on a biannual, or annual basis. However, this only gives a blurry picture of SKU performance so they don’t get detailed insight into what makes their products desirable in particular markets, making them slow to adapt inventories to customer demand. Instead, companies must make frequent SKU decisions across an entire channel.
Built on Microsoft cloud technology, Neal Analytics’ Inventory Optimization solution offers a new way to manage dynamic, responsive product portfolios by providing granular visibility into individual SKUs.
Inventory Optimization enables retailers to analyse product characteristics and market preferences to provide merchandise managers with quantitative forecasts that precisely predict sales lift for every possible product mix. CPG companies can use the solution to analyse which SKUs perform best in each market, identifying peer groups of outlets for every channel, region, or market demographic.
Armed with accurate insights and future sales projections, retailers and CPG companies can tailor a product portfolio to individual stores or markets, satisfying customer demand. Meanwhile, merchandisers can harness the guidance generated by Inventory Optimization’s machine learning capabilities to move under-performing SKUs to more appropriate markets, or eliminate them. By doing so, they can devote every inch of shelf space to products that are successful in that market. This lifts sales and profits, improves product availability, reduces stock-outs and eliminates unsold products.
Luke Shave is global industry marketing lead for CPG and Retail in Microsoft’s Cloud and Enterprise Group and David McClellan is practice director for CPG and Retail at Neal Analytics