The asset value of stores is set to surpass inventory as the biggest investment on the balance sheets for most Indian retailers, given the improving supply chain efficiencies. Optimal utilization of this investment implies minimizing empty shelves. Strategies for doing this in India are more fundamental than in a developed market.
Supply chain text books have traditionally pointed out that inventory is the biggest asset of a retailer. Well, that has changed, at least in the developed markets. The assets at stores (real-estate plus furnishings) have become the biggest investment, as a result of more efficient supply chains in developed markets. With organized retail still developing in India, many retailers have not optimized supply chain efficiencies. Once the efficiencies are achieved, CFOs will realize that stores and store space is the biggest investment on their balance sheets.
Some retailers, such as a certain leading department store chain in India, already have store assets as the biggest investment on their balance sheet. An extract from their 2007-2008 annual report is presented below:
(All amounts in Rs. Millions)
Assets at Stores
Air conditioning and other equipment
Furniture, fixtures and other fittings
Computers (apportioned to stores)
For mature and near-mature retailers, the strategic focus should be on improving the ROI on this biggest asset – assets at store. Empty shelves imply an under-utilization of this asset and therefore affect its ROI adversely. Empty shelves also negatively affect a shopper’s store experience.
At the corporate level too, empty shelves lead to higher items costs (COGS) and therefore reduced net margin (the bottom-line). This impact will likely become more prominent as real-estate and associated costs continue to increase. This relationship is shown in the diagram below.
Empty shelves could also represent a process issue – that merchants under-estimated consumer preference for specific items, that store personnel had sufficient inventory in the back-room but have not replenished the shelf, that supply chain managers couldn’t effect proper service levels at store or that the visual merchandisers have under-allotted shelf space in the planogram. Empty-shelf situations also skew the historical data used for forecasting, which results in reduced forecast accuracy for later seasons.
To solve this problem, retailers can obviously over-stock items. However, that would increase the working capital costs to an unprofitable level. The solution lies in first understanding consumer preferences and then planning to effectively supply the right amount of inventory to each store. We have devised a roadmap for the typical issues at an Indian retailer. This roadmap needs to be altered to meet the specific requirements of any situation. The solution for empty shelves is provided in steps two through four of that roadmap (see diagram below). These steps fall within the demand flow.
The demand flow starts from customer touch-points and ends in customer orders with the resulting orders being placed on the higher echelons of the supply chain. However, the steps that are pointed out (two through four) are improvements that might suit most retailers in the Indian marketplace. Our recommendations are to first identify the customer decision tree, a tool to visualize how customer needs link to specific items. This tool is drawn out as a tree with the trunk starting from the customer’s high-level needs like hunger, entertainment, exercise, etc. It then extends through the branches of categories and sub-categories and ends in the leaf nodes of items. Since every retailer’s typical customer profile is different, this tree would differ for every retailer. It is important to understand the customers shopping at your various geo-demographic store clusters before drawing this. The result of this exercise is a deeper understanding of customer-visit scenarios, customer needs and consumer preferences. This understanding should then be used to redefine merchandise hierarchies. Redefining the merchandise hierarchy is a big change, but based on deep analysis of the customer decision tree, retailers would certainly benefit from the intuitive floor layouts, clearer category roles and effective promotions.
To make sure these objectives are met, it is important to execute these strategies properly at the store level. With store personnel in India having one of the highest attrition rates in any industry, this presents challenges in training costs and compliance for retailers. Simple technologies to capture random questionnaires could be used to encourage compliance and quickly identify training issues and opportunities.