Why improve product availability on the shelf?
The availability of products on the shelves of physical sales points or in storage facilities for e-tailers depends on the various players in the supply chain. Delivering the right products, at the right time, in the right place and in the right quantities is therefore a problem that concerns both the company's internal operations and external mechanisms. The unavailability of products sold on the shelves has an impact on the turnover of the brands as well as on the reputation of the business concerned. The consequences of the absence of products on the shelves can thus be quantified and described in the short and long term.
How do customers behave when faced with a lack of products on the shelf? What tools and processes can be used to predict or even anticipate the unavailability of products on the shelves? How can we anticipate stock shortages and mitigate delivery delays? Here we look at the causes and repercussions of product and merchandise unavailability on the shelves of retailers, distribution chains and hypermarkets.
The consequences of the unavailability of products on the shelf on the turnover
Meeting customer demand means ensuring timely sales means ensuring the availability of items and products at the point of sale on a continuous basis. The losses that can be generated by stock-outs or the non-shelving of products can be immediate, but also have a long-term impact. Indeed, occasional product shortages may cause customers to wait or choose an alternative brand, or even to go and get the product in question from a competitor. However, when the absence of articles or products becomes recurrent, it can lead to the customer changing the brand permanently.
Therefore, calculations of the loss of turnover caused by the unavailability of products cannot be limited to the loss of a one-off sale. The company must consider the customer's departure as a whole: frequency of visits to the store, price of the average shopping cart purchased by this same customer during his visits, etc. The worst case scenario to anticipate in these calculations is the customer's permanent departure if they decide to go to a competitor with a higher service rate.
Another type of negative impact on store finances can be seen in the case of departmental service failures: the cash flow losses associated with products that are left in the stockroom because they were forgotten and not offered for sale on the shelf. The stagnation of these items in storage causes capital to be tied up and significant unaccounted financial losses.
Impact of lack of product availability on customer satisfaction
The repeated absence of products on the shelf can affect the relationship between the business and its customers. The behavior of visitors to a point of sale in response to the temporary absence of a given item varies between:
- substitution: use of a similar product of another brand or purchase of the same product, but in a different format;
- deferred acquisition of the product: waiting for a second visit to the store;
- travel to another store to fill the need;
- decision to cancel the purchase.
In addition, the recurrent unavailability of items in the store's shelves damages the image of the business in the eyes of regular customers. The store's reputation can suffer in the long run. Customer loyalty within a sales unit depends on various criteria, including the customer service rate. In order to ensure customer loyalty, employees within the same store must work to implement the right processes to ensure the continuous availability of items on the shelves.
Factors limiting the availability of products on the shelf
There are many factors behind the limitation of product availability or even stock-outs in stores. They can be linked to supply chain management, to the company's operational teams or to external hazards. We will distinguish here a few scenarios that can lead to stock-outs:
- forecasts often made manually by operational teams lack precision and can lead to approximations that are more or less distant from the reality on the ground when orders are placed;
- delays in delivery by suppliers combined with unreliable estimates of minimum and safety stocks make it impossible for the organization to meet customer needs during the replenishment period
- problems affecting the supply chain at the level of the suppliers of the suppliers (supply of raw materials necessary to the elaboration of the products) block the supply chain in its totality;
- the total number of human resources allocated to the various sales areas is insufficient to ensure the functions of stock management, shelf-stocking and accounting of goods.
There are many reasons why products are out of stock on the shelf. In addition to supplier-induced delays, stock-outs can occur even when the product in question is in stock. A retailer can use an audit to identify all the processes or functions that may be the cause of defective supplies on the shelves.
Methods for detecting product shortages on the shelf
The methods mainly used to detect ruptures are statistical or manual techniques. Their main drawback is that they are not anticipatory. Indeed, statistical tools aim to detect out-of-stock situations once they have occurred, generally based on sales receipts and the history of product purchase frequency.
Manual methods, on the other hand, require the team in charge of a department to make verification passes at different times of the day. However, these records cannot cover all products and do not include any closed stock that may have occurred between two checkouts. In addition, they require a large number of staff to be effective and diminish the value of the solution from an economic point of view.
The advent of predictive tools based on machine learning makes it possible to envisage the implementation of an anticipatory follow-up of the insufficiencies of articles in the shelves of the stores. Artificial intelligence ensures the development and learning of algorithms that provide forecasts of product shortages on the shelves, in real time. In addition, these algorithms are able to generate product assortment proposals that increase customer substitution behaviors rather than cancelling the purchase or acquiring the reference from a competitor.
Machine learning and product availability on the shelf
Machine learning algorithms take into account historical and continuous data flows internal to the store, linked to all the actors in the supply chain, as well as exogenous data that can have an impact on the operation of the store. Internal data includes receipts (baskets), available SKUs (stock-keeping units), busy hours, work shifts, etc., while external data can include information about weather, strikes, econometric data, regional and local events.
The ability of data science tools to capture and ingest large volumes of data allows for a multidimensional picture of the phenomenon or variables being studied. For example, in the case of product availability on the shelves, forecasting and machine learning tools generally provide predictions concerning all the references in a store. They allow teams and department managers to free themselves from manual surveys that cannot follow all the SKUs on sale in the store. In addition, predictive applications help to understand the phenomenon of product availability and unavailability, and even to take into account delivery delays on the supplier's side, by proposing optimal product assortments that can push the customer to substitute the product and thus avoid the cancellation of the purchase, among others.
To conclude, ensuring a quality service rate to the consumer depends on various logistical factors. Taking into account the loss of turnover, the degradation of the image and the notoriety of the brand, the rate of customer loyalty, the consequences of a faulty shelving affect the points of sale at different levels. In addition, various tools are emerging thanks to artificial intelligence in order to better anticipate these problems and avoid financial losses, even if they are temporary.