Retail as a factory – or many factories

In the last thirty years, consumers of fashion merchandise have become spoilt for choice on where, how and when to buy. This has fragmented the retail network into a less and less predictable, omnichannel landscape, where the winners are standing out by their agility, or their ability to respond to increasingly fickle consumer demand.  

Agility in turn requires change, a revolution even, in the way we operate the supply chains to retail. Huge, complex and connected spreadsheets don’t cut it anymore. Instead, we need simple decisions. But ‘simple’ is not the same as ‘easy’. I explain: 

First, imagine all these retail points, physical and virtual, to be small factories that produce cash, and where merchandise is ‘raw material’. To make money, you want to limit the raw material and maximize the throughput. The same as in a factory, too much raw material results in a negative ROI, and too little leads to machines (cash registers) standing idle. The right amount of raw material is calculated via someone who calculates ‘material requirement’. Not a difficult job, but one that requires continuous information on things like lead-times, batch sizes and volatility of demand and supply.  

Now imagine two hundred and fifty of these factories and thousands of raw material ingredients that can be delivered at least once a week. Now it gets tricky. Especially when you know that all these factories require a slightly different raw materials input to maximize the output.  

This must be the new supply chain thinking. How to maximize retail sales while controlling the investment in inventory. Everywhere and all the time.  

Replenishment the right way

replenishment consumer goods

Since retail sales are unpredictable, the inventory in the store must be continuously fine-tuned. This finetuning is a four-step process. Each step must be applied daily to all items in all retail locations (stock keeping units or SKU’s) and to all points of distribution. (Hence ‘easy but not necessarily simple’) 

Step 1: Pareto Analysis.  The first step is to categorize items, at a store level, based on their contribution to total sales. Fast movers contribute 80% to total sales, slow movers contribute 20% to sales and non-movers are items that do not sell at all.  If a fast mover has an out of stock, the relative negative impact on overall sales is much greater than for slow moving and non-moving items.  

Step 2: Synchronize the flow of product with retail demand. To do that, we need to: 

  1. Secure Availability of Fast Movers
  2. Reduce supply of slow and non-movers

This converts the practice of PUSHING of inventory into a store to a practice of PULLING inventory to protect the sales of fast-moving items.  

Step 3: Dynamic Target Stock Calculation (Buffer Management). In any retail environment, changes occur daily. As a consequence, the system needs to recalculate the necessary buffers of each item in each retail location every day.  

Step 4: Solve Under- and Over-Stock across the Store Network. As a result of the initial allocation, or because too much stock was ordered in the first place, stock required in one location may be held in another. Therefore, repositioning inventory within the store network via transfers is essential to maximizing sales of that network.  

Expected results. Automation (read: ‘efficiency’) and focused attention on matching the flow of merchandise to consumption can drive availability of fast movers to more than 95%. This has a direct positive impact on sales and on stock turns and results in a significant improvement on each store’s profitability and that of the network as a whole.  

Jasper Zeelenberg
CEO & Founder
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