Give the customer what they want when they want it. It is the oldest retail axiom out there, but you cannot overstate the importance of getting it right.
More than two-thirds of shoppers have walked out of a store because it did not have the product they wanted. The result is lost sales, potentially wasted stock and a dent to the bottom line. The spread of COVID-19 across the globe has brought on-shelf availability into sharp focus as grocery retailers struggle to keep up.
For grocery retailers, optimal on-shelf availability boils down to having the right product on the shelf, in the right quantity, of the right quality, and at the right time. Sounds simple.
It is, however, deceptively complex, and finding the sweet spot with on-shelf availability remains a major headache for retailers, from those with just a few hundred stores to those with thousands of stores, several of whom and have had more than a century of practice.
Here are four reasons why on-shelf availability is a considerable challenge for retailers.
It is not enough to have the right stock on a shelf somewhere in the store. To maximize sales conversion retailers have to think fastidiously about category assortment on shelf and placement in the broader store layout. Take the classic example of confectionery strategically located near the till or where shoppers queue. It undoubtedly drives sales, as one in five shoppers in the UK have bought these impulse items. The subsequent push to eradicate supermarket ‘guilt lanes’ more than halved sales, even though the same products were only meters away. It illustrates the considerable power of position and assortment in driving sales.
The impact of this spans everything from the whole store layout to individual category management. That is because item level on-shelf availability acts as a microcosm of broader shopper behavior. Assortment planning requires an understanding of the bestsellers; how many lines to stock to provide choice without waste; which lines offer sufficient variety of price points; and which are gateway or cross-purchased that are fundamentally important to win large basket sales. Get assortment planning wrong, and retailers have product occupying space without generating sufficient sales and with a significant replenishment challenge as fast-selling lines have insufficient facings to cover purchases.
A hike in the National Living Wage and the ongoing burden of business rates, compounded by a harsh economic climate and intense competition, have all served to see retailers stripping labor from stores.
A leaner stock replenishment team can neglect replenishment tasks and inventory checks or, as is more often the case, have labor hours misaligned with demand. That is because the distribution of staff hours have always concentrated around peak sales periods, such as at weekends. Optimal on-shelf availability, on the other hand, requires standard and consistent routines throughout the week, offset by when customers demand the product.
While retailers know that labor hours should broadly match their sales over time, getting into the detail of specific tasks and offsetting them to sales is a complicated exercise. Added to that, the challenge of affording to run the operation, inflexible contracts, and tight labor markets with potential employees not willing to work according to the ever-changing pattern of demand, and you can see why stock replenishment will not always be perfect.
These issues are compounded further by the fact that many in-store management roles have been stripped out too, with these managers having acted as overseers for ensuring tasks around on-shelf availability and stock replenishment are delivered.
In light of this, there is a compelling need for retailers to make use of data-driven insight on the shop floor that ensures the limited staff resources have the maximum commercial effect, by using data to prioritize tasks, that maximize on-shelf availability. Focusing on products that matter, which varies by day and by store, ensures stock replenishment teams make the most significant difference to the operation. All too often, routines are static from day to day and do not adjust for the latest data and insight that should form part of the operational plan.
If you cannot measure it, you cannot improve it. So goes the famous Peter Drucker saying. And it is undoubtedly true for optimizing on-shelf availability and ensuring that shoppers are not left with empty shelves or product past its sell-by date. Which strategy to adopt when it comes to measurement, though, can be a significant source of confusion and debate for grocery retailers. There is the perpetual inventory (PI) approach - assuming where PI is >1, it is in stock. There is the gap scan, a technique used by most retailers; or there is the traditional mystery shopper audit, which checks a limited number of items as on the shelf. An ePOS velocity model is a more sophisticated approach, taking value from cash registers to monitor the availability of all products. And these are a mere handful of the options out there.
Each approach has its strengths and weaknesses, but in deciding, retailers should consider three crucial aspects. First, duration. Does the approach track availability at only one point in time, or does it boost the quality of its assessment by tracking on-shelf stock at multiple times? Is data available in real-time, rather than waiting for overnight processing? Second, accuracy. Is the software used consistently and reliably accurate? Can it be manipulated? How much staff training is required? And third, cost. Does it deliver value? Does it require too much manual input? Can you see and track the economic benefits to the business?
Shelf-life is a problem unique to grocery retail. While fashion retailers can keep out-of-season stock stored in a DC to be re-merchandised during a summer sale, if grocers fail to convert sales within a product's shelf-life then it automatically becomes waste, with all the economic and environmental implications that bring. Of course, most major grocers have partnered with charities to donate end-of-life stock, but the financial loss to the retailer is still the same, albeit without the cost of disposal.
Managing on-shelf availability is a significant component of waste prevention. Namely ensuring that short-dated stock sells first, and all stock sells before its sell-by date by providing availability, and assortment and merchandising all work in tandem with shelf-life. There has been the promise of data embedded barcodes or RFID as the long-term strategy for dealing with waste. Still, with only small-scale trials undertaken so far, there is a way to go before retailers can rely on this as a solution.
With the shortest shelf-life and often sold unpackaged, fresh lines are arguably the most challenging category in ensuring on-shelf availability. Tackling this challenge is multifaceted and complex, but maintaining on-shelf availability requires stock replenishment systems to calculate the expected freshness of the product in-store so that new stock arrives in to store at the right time. This ‘assumed freshness' metric is fraught with error – caused by customers or e-commerce pickers selecting the freshest product at the back of the shelf, or as every seasoned retailer knows, the constant challenge of ensuring product rotation by stock replenishment colleagues.
As a result of forecasting error, mis-rotation, or lack of freshness checks, there can often be stock that customers are not willing to buy, at least not at the full retail price. One way to respond is to replenish with newer, fresher stock. Another robust response is to reduce the retail price to stoke demand and sell through the aging stock faster. The theory behind what discount to apply to a product varies widely between retailers and geographies. From the day-to-day whim of the colleague, to fixed markdown policies, all the way to optimized prices powered by advanced analytics. These decisions are at the heart of the delicate balance between on-shelf availability and waste.
Retailers can simultaneously maximize revenue and minimize waste, but to do so requires some of the decision-making to be automated and based on thousands of data points. Retailers that do this are developing a competitive advantage over those that rely on more traditional methods. In essence, both can work, but those that embrace operational optimization powered by analytics will win in the long run.