In the Star Trek series, the crew of the USS Enterprise boldly and resourcefully devised creative solutions to the challenges in the universe. Inventory management, too, must have its own bold solutions to meet the challenges in a complex and ever-evolving retail universe.
Shoppers are becoming more demanding and less loyal. Sixty-eight percent of shoppers list instant gratification as one of their top three reasons for shopping in stores. While 75 percent of shoppers still prefer to shop in brick-and-mortar stores, their brand loyalties are fast eroding (e.g. 12 percent drop in Beauty and Apparel segments). In a survey of retail shoppers, over 35 percent walked away completely from a sale when they could not find the right product. While the other 65 percent indicated that they might try another time or look at another location, the original selling opportunity was lost.
Internally, retailers are awash in transactional data, sales histories and category management plans, but have low confidence that their current toolset and inventory systems are allocating the right assortment of products to the right locations. In addition, collaboration between departments – sales and planning, supply chain and allocation, merchandising and planning, is an alien concept in many organizations.
While the USS Enterprise could beam their team to the right place at the right time to save the universe, retailers cannot beam the right assortment and selection of their products into retail stores to save the sale; or can they? With the right approach allowing retailers to deliver their product at the right place, and at the right time to maximize sales and gross margin, inventory management may be poised to boldly go where it hasn’t gone before.
Retailers can accelerate their revenue using an approach that involves deploying inventory in a predictive way. It starts with a deep understanding and acknowledgement of a product’s true demand and lost sales opportunity, based on detailed analysis of prior season inventory and sales data. From this, in-season decisions are made to deploy more accurate inventory at each point of sale and inform next pre-season merchandising and assortment.
Understanding true demand and lost sales opportunity
All the data to evaluate the full sales opportunity is readily available for analysis, if teams know what to look for and how to calculate the gap between predictive sales and actual sales at a store-item level. Predictive sales consist of products sold, ghost demand (items that should be carried but aren’t) and lost sales (items that are carried, but weren’t placed accurately). Complement the analysis with robust yet efficient shopper perspective (e.g. surveys, intercepts, field tests and competitor tactics) to understand what shoppers want to buy, how they want to shop, how they buy and when they walk away. It may appear tedious on the surface, but surprising insights can be gained.
Exhibit 1: Visualizing Sales Potential
In Exhibit 1, a baseline is established (the red line). Data analysis can predict potential sales (the green line) and identify opportunities for improved placement of in-season store-item level inventory to alter the full price sell through rate for current inventory and prepare for post-season planning.
In-season predictive inventory deployment
Exhibit 2 illustrates the key in-season interventions and pre-season insights in predictive inventory deployment. Retailers can create immediate value via three differentiated activities to manage in-season inventory deployment.
Exhibit 2: Predictive Inventory Deployment
- Store-item level inventory injection starts with historical sales and transaction data. When viewed at granular item level detail (along with major pricing and promotional changes) retailers can identify important differences in likely demand between relatively similar SKUs to establish the initial allocation of inventory.
- Rate of sale based read and response uses real time mapping of in-stock levels for high velocity vs. low velocity items on a weekly basis, at a store-item level, allowing more accurate deployment of inventory to each point of sale.
- Right inventory trade-offs and replenishment hierarchy requires periodic and frequent redefining of allocation priority based on channel/customer revenue, profitability, and strategic criteria to ensure best use of available inventory and protect both near term and long term growth.
Analyses that used to take days and weeks is now available in hours—rapid enough to actually impact weekly inventory replenishment. By predicting when and where the sale is most likely to occur, the right inventory can be “beamed” to that precise store-door or e-commerce DC.
Pre-season merchandising and assortment insights
Granular findings from analysis of in-season lost sales can provide valuable insights for next pre-season inventory planning and merchandising, creating a lasting advantage.
- “Ghost Demand” and white space opportunity can shed light on evolving customer wants and opportunities (e.g. size combinations, ticket prices) that can help gain share.
- Informed buy plans and chase readiness can be activated via hindsight analytics on actual demand versus actual sales, which can also be used to modify buy plans and the depth of buy needed behind each SKU.
- Store planning and store clustering uses patterns of customer buying behavior to create a bottom up store plan that can better link pre-season Plan with in-season Allocation intent, while improving speed to market and reducing inventory waste.
At this level of detail, retailers can best identify patterns of product performance within and across channels and build an omnichannel view of product demand that serves as an input to more effective inventory allocation. Used correctly, these pre-season insights can provide a significant upside: the potential to spark a mindset of continuous improvement that can dramatically improve merchandise assortment for each subsequent season.
Static rules that were once true are very quickly insufficient and inaccurate in today’s fast-moving, fast-changing omnichannel environment. Functional and organizational hierarchies superseding channel/customer hierarchies invariably lead to suboptimal inventory deployments. Dynamic inventory allocation requires frequent and periodic redefinition of these rules of inventory engagement to maximize sales and margins. A predictive inventory approach forces all departments to share a single view of inventory, in real time, and encourages a laser focus on a single organizational goal – fulfilling customer demand. This shared focus helps to address many of the obstacles to true omnichannel capability such as lack of clarity around inventory ownership between stores and online, confusion around which regions, stores or wholesale customers get priority on limited inventory, and misaligned incentives that create wasteful dialogue on who should get the sales credit if one channel makes the sale and another channel fulfills the sale. Omnichannel capability requires an omnichannel organization.
Visualizing predictive demand
Some retailers are so confident in the power of their Brand that they feel customers will find their products regardless of how they are distributed. Others rely on their omnichannel (ship from anywhere) capability to correct “wrong place, wrong product” mistakes. These views are very likely costing the retailer in product margins while significantly shortchanging their true selling potential.
Exhibit 3: Visualization of predictive demand
Visualizing predictive demand (Exhibit 3) can identify specific solutions to influence lost demand by recommending when and where inventory is redeployed to reduce out of stocks of the “right inventory” and less overstock of the “wrong inventory.”
In a recent case study (Exhibit 4), one retailer was able to realize a 5 to 7 percent lift in sales by leveraging a tailored lost demand methodology to guide allocation decisions, enabling inventory with higher turns to be deployed more effectively across all channels.
Exhibit 4: Potential Revenue Lift
Delivering on omnichannel’s promise to sell better requires retailers to boldly rethink how to create a truly demand-driven inventory management capability that fuels a continuous improvement approach to pre-season planning and in-season merchandising with long term sustained payout. As Captain Kirk would surely say, “Beam me up, Scotty.”
About the Authors
Adheer Bahulkar, is a partner with global strategy and management consulting firm A.T. Kearney, specializing in strategy and operations in the consumer and retail sector. He is based in Washington, D.C. and can be reached at email@example.com.
Manik Aryapadi, is a consultant with A.T. Kearney specializing in retail supply chain planning and technology. He is based in Chicago and can be reached at firstname.lastname@example.org.
The authors would like to acknowledge Kevin Wang, John Adams and Roth Nelson for their significant contributions to this article.