Is there a ‘silver bullet’ to solve the problem of Out of Stock in retail?
Everyone understands that the problem of Out of Stock (OOS) in retail exists. It irritates customers and negatively affects financial results of retail chains and their suppliers. However not everyone equally understands what a term Out of Stock encompasses.
What is Out of Stock?
It is an event when the product was not available for sale to customers as intended. This includes situations where the item is completely out of stock in the store, or the item is in the store but not on the shelf, or even the item is on the shelf but not as intended by merchandising standards – customers cannot see or find it.
What is the size of the problem (or rather, the opportunity)?
The average level of OOS in retail in developed countries is about 8% and this is the reason for the loss of about 4% of sales. That means, a 2-percentage point improvement in product availability on the shelf leads to 1% increase in sales.
Additionally, this negatively affects customer loyalty:
8% OOS level means that 1 out of 13 items was not available for sale on the store shelf when the customer wanted to buy it. In addition, data analytics and market research company IR found out that 20% of OOS events are not resolved for more than 3 days.
IHL Group research shows that shoppers experience out of stock issues one in three times they visit a store.
Nielsen IQ research shows that 30% of shoppers visit new stores when they cannot find the item they want, resulting in a loss of long-term loyalty.
The rise of e-commerce is making product availability even more important. Customers who encounter an out-of-stock item in a brick-and-mortar store may not purchase the originally planned item, but often they will purchase another item in the same store. Buying online means they can simply switch to another seller. For example, a grocery store will lose about half of its sales when a customer does not find a product on the shelf, while a ‘dark grocery store’ will lose all sales.
This situation has persisted and has not changed for about 20 years. What actions should be taken to reduce both – OOS events and OOS duration?
What are the causes of OOS?
About 75% of OOS events are driven by internal retail chain processes and about 25% by various external factors. The pie chart below details the causes for the shelf OOS.
Given that there are different causes of OOS, there is no one ‘pill’ to solve all problems.
So, what to do?
1. Create a desire to do something
This means it is necessary estimate OOS level and lost sales by products and by stores. The goal is to determine the “size of the pie” without even delving into the root causes of OOS.
2. Know where to focus
This means understanding the root causes of OOS. At this stage, ‘divide the cake into pieces to eat it’. It is very important to separate the root causes into two parts:
order related causes that affect store OOS,
in-store execution causes that affect shelf OOS.
There are 6 key areas for OOS solution.
As a result of this step, the following will be discovered:
categories (products) with a high-level of OOS,
stores with a high-level OOS,
root causes of store OOS and shelf OOS.
Half of the work is done at this point of the time. What's next?
Gaining knowledge will allow to focus on the biggest problems first. It is not enough to act once; it is very important to act constantly. Obviously, the usual methods of dealing with OOS have reached their threshold, and new tools and solutions are needed:
to solve the product OOS – it is necessary to have tools targeting the problems associated with the store OOS,
to solve the store OOS – it is necessary to have tools targeting the problems associated with the shelf OOS.
Assortment planning and optimization
Planogram execution monitoring
Identifying data accuracy and in store execution issues (On-Shelf Availability)
OOS solution areas in details
Inaccurate demand planning
Out of Stock distort true demand. Ideally, the demand forecast should be the same as the sales forecast, however, they are invariably different, mainly because of sales variances caused by OOS. Demand forecasting is mostly based on checkout data, but it only shows what customers actually bought, not what they intended to buy if the item were in stock. OOS distorts true demand in the following way:
When a product is in the OOS state, it cannot be bought and thus sales decrease in the checkout data showing less than true demand. This leads to subsequent underestimation.
In about half of the cases customers replace an out-of-stock item with another item in the same store. Such situation results in over-sales of in-stock items (above their normal demand), while sales of out-of-stock items decrease (below their normal demand). Thus, the cash register data do not accurately reflect the true demand for both goods.
In about 15% of OOS cases shoppers delay purchases. The purchase intervals shown in the checkout data become biased. In this case, the availability of OOS products will create a situation in which the actual rate of sale is rarer than the actual demand.
Inaccurate product data. Product data inaccuracy occurs when data synchronization between suppliers and retailers is lame. The main reasons are:
Consolidation of previously independent databases. This occurs during a merger or acquisition of retail chains or due to the consolidation of previously separate data.
Introduction of new or termination of production of old products. Manufacturers regularly make minor changes to many of their products (for example, reducing the juice package from 1L to 0.95L).
Management of seasonal or temporary goods. Manufacturers often introduce seasonal items or temporary product changes (such as bonus items with a new code) and then revert to the old code.
Inaccurate stock balances lead to inaccurate orders. The actual balances differ from the balances in the system. Conducted studies show that the level of coincidence is only 35-45%. The discrepancy between actual balances and the balance in the system is approximately equally divided into two parts:
Balances in the system are larger than the actual ones. This is because of damaged or expired products not written off on time, re-sorting between similar products during checkout scanning, unknown losses when buyers forgot to pay for goods, inventory counting errors. This cause is the main contributor to 47% of OOS events associated with product orders.
Balances in the system are less than the actual ones. It is surplus of the product. These goods do not negatively affect the OOS, however, freeze excessive working capital.
Not synchronized order and delivery schedules. This happens when the order is placed before the arrival of the early order (for example, according to the schedule, the order is formed at 9.00, and the delivery occurs in the afternoon). When ordering, assumption is made that the early order will be fulfilled in full. However, it often occurs that the supplier does not fulfill the order in full, and an underestimated order is formed accordingly.
Manual adjustment of order which was generated by the system. Many chains have specialized ordering tools, but they also give the store or ordering employees the right to correct orders. This practice often reduces the accuracy of the order.
Promo orders. It is necessary to divide orders into two parts - regular orders and ordering goods for promo. A common problem is that too few items are ordered during the promo and too many right after the promo. When choosing an order tool, make sure that there is such a separation.
Goods delivery to the store
A large block of OOS causes is associated with store suppliers (both direct deliveries to stores and deliveries from the chain’s distribution center). The main reasons are:
Too rare deliveries to the store. Such a problem arises when there is little or no storage space in the store, all the goods are placed in sales area and there is not enough inventory from delivery to delivery.
The delivery schedules are not synchronized with the replenishment schedules of the goods on the shelf. Such a problem arises when the goods after delivery are in the receiving area, do not move to the sales area because the internal processes are set up so that replenishment in the store occurs much later the day of arrival of goods or even on the other day. Various studies show that the problem of synchronizing the schedule of delivery and shelf replenishment is more often observed in the case of direct deliveries to stores compared to deliveries through the distribution center, especially if external merchandisers handle the replenishment of the shelf.
Too many stocks in store backrooms. You might think that the more stocks in the store backrooms, the less the shortage of goods on the shelf. In fact, there is usually no such correlation - there is often a mess in store backrooms, the goods are hiding each other, the employees do not remember which, where the goods are, and no one really tries to look for them.
Supplier service level. Two problems can be distinguished here - late delivery and non-delivery - partial or complete. Safety stock should solve such problems, but often it is not correct itself - too small or too large.
Allocation of shelf space
Fast-moving goods very often have too little shelf space. This problem is very popular and occurs during assortment planning for three main reasons:
Shelf space for SKUs is allocated depending on the size of the secondary package. Thus, fast-moving goods get too little space, they need to be replenished very often or even during the day, which leads to a constant shelf OOS. Using this shelf allocation methodology, about 85% of the goods will exceed the weekly stock, which can be reduced in favor of fast-moving goods.
Too much space given to a brand or supplier. Very often, chains ‘sell’ shelf space, and the problem arises when they ‘sell’ too much. Then all the supplier’s slow-moving items are listed into the assortment, or the goods are merchandised with too many facings. Thus, it will pick up space for well selling SKUs from other brands resulting them permanent shelf OOS.
There are too many SKUs in the assortment. This happens when retail chains are highly influenced by suppliers in assortment management decision. Suppliers try to ‘shove’ as many SKUs into their limited space as possible, or multi – category suppliers, ‘scaring’ retail chains with so called ‘package contracts (all or no categories)’, overload stores with a bunch of unnecessary assortments. More SKU does not mean better assortment. Many different studies have been conducted to analyze the reaction of customers to a decrease of SKUs in the stores. Often, a modest reduction in the number of SKUs was perceived positively by customers, since there is less clutter on the shelf, the product is more visible and seems to be larger assortment in the store.
To comply with planograms, it is necessarily to have them first. Not all retail chains have had them yet. Various studies show that a 10% change in planogram compliance results in a 1% change in OOS levels. Accordingly, stores need to focus where the risk of non-compliance is high. It is higher where the service level of the supplier is lower or supplier's merchandisers ‘fight’ for shelf space hide shelf holes’, moving price tags, or there are no clear processes and synchronization when listing and de-listing SKUs from the store’s assortment.
On-shelf item management
One thing is to draw the merchandising planograms sitting in the office, and the other thing is consistently implement it in the store. Below are the most popular four erroneous practices that lead to increased OOS:
Closed “shelf holes”. Some chains use the ‘item in transit’ label, but most chains move adjacent items apart and close ‘shelf holes’ with other products. This practice has two negatives - employees waste time on unnecessary work and deceive themselves about OOS, since not seeing ‘shelf holes’, they forget to order goods or replenish the shelf, even when the goods are already in the store.
There is no price tag on the shelf. This is often related to the practice described above – when the ‘shelf hole’ is closed, the price tag is also removed. Later, the product appears on the shelf, but the store employee forgets to return the price tag. This limits the sale of the product as customers do not see the price for it.
Wrong price tag. The product is not in its place, it confuses customers and limits their intention to buy the product. This is very common when the assortment is too big, and everything can hardly be placed on the shelf.
Product is ‘hidden’ on the shelf. A product is often hidden by other products or is placed deep on the bottom shelf. This is often a sign of poor assortment planning. The situation is aggravated by the ‘struggle’ of external merchandisers for shelf space.
Having many years of experience in working with retail chains, the SUMATUS team has developed artificial intelligence tools that allow systematically deal with about 75 percent of root causes of OOS, and dramatically improve store performance and customer satisfaction.