In the mature and highly competitive European retail sector, ensuring that the right product is on the right shelf at the right time is critical, yet the problem of shelf out of stocks remains as stubborn as ever. Could the loss prevention team be the key to unlocking this new sales opportunity?
This blog explores the problem of out of stocks, the relationship between this problem and loss, share some new ideas for loss prevention teams to consider, and to be pragmatic, identify three next steps any team could take to help improve on-shelf availability (OSA).
To understand the scale and nature of the out of stock problem in Europe, the article will draw on two studies, the ECR Europe study on Out of Stocks, conducted in partnership with Roland Berger and a global study on the extent of out of stocks published by Professor Daniel Corsten and Thomas Gruen .
But before all that, this blog will start by defining what is meant by a shelf out of stock, and the inverse, OSA, and how it is measured.
Defining and Measuring Shelf Out of Stocks
The prevailing industry view is that the problem should be defined through the shopper’s eyes. A shelf out of stock incident is defined as when the shopper does not find the product they want, in the right condition (undamaged, in-date, etc), at the location (shelf) they expect, at the right time. However, there is no perfect way to measure against this definition, so in practice what retailers adopt are some of the methods listed below:
1. Independent third party audits – is the product on the shelf?
2. Internal audits conducted by store associates – how many gaps are there on the shelf?
3. Distribution service levels – was the product ordered by the store sent by the Distribution Centre (DC)?
4. Perpetual inventory records – how many items have zero on the stock file?
5. Maximum shelf quantity – how many items have perpetual inventory records less than 70% of maximum shelf quantity?
6. Daily sales rate – how many items have less than one day’s sales on the perpetual inventory records?
7. Sales exceptions – how many items have a daily or hourly sales rate significantly below the average that would be expected based on previous sales history?
8. Store service levels – was an item ordered online successfully picked in the store and delivered to/collected by the shopper?
9. Customer survey at checkouts – did the shopper get everything they wanted on this trip, Yes/No?
10. Customer survey on the till receipt – shoppers are asked to complete an online survey and let the retailer know whether they got everything they wanted on their last visit, Yes/No?
Each of these ten methods have their own limitations, leading to many lengthy debates inside retail organisations as to the true extent of the problem and based on that, who should then be held accountable. In a survey of retailers and manufacturers attending an ECR event organised in Brussels in May 2012 to relaunch an initiative on out of stocks, 48% of the attendees said that their organisation did not have an out of stock metric that was respected across their organisation and was considered helpful in driving better results. Further, in this same survey, while 70% of the retail respondents said that either the Supply Chain or Store Operations were the single accountable function, 30% of the retail respondents said that there was no single function accountable for OSA.
Impact of the On-Shelf Availability Problem on Sales and Profit
Despite these limitations to how the problem is measured and managed, academics and industry associations have managed to complete multiple studies to quantify the scale of the problem. In 2003, Professor Daniel Corsten and Thomas Gruen were tasked to bring together the data from all these multiple (there were 50+) studies to produce a global overview of the problem.
In their report, the average out of stock rate in Europe was reported at 8.6%. This was found to be slightly higher than the global average of 8.3%. Put in simpler terms, what this number represents is that for a typical shopping trip and an average basket of 100 items, the shopper could expect just over 8 of those items to be out of stock. Said differently, shoppers could be expected to purchase only 92% of everything they wanted to buy.
While the average is interesting, the real value comes from understanding the variances from the average. In the ECR Europe study, these were some of the differences they reported:
• Day of the week: Empty shelves were more likely to occur on a Friday and Saturday.
• Promoted Items: Items on promotion were found to have up to a 75% higher level of out of stocks than items not on promotion.
• Categories: Ready-made meals and confectionary were found to be nearly twice the average out of stock rate at 15% while dish washing products were recorded at just 0.5%.
• Size and format of store: Supermarket format stores were less likely to be out of stock than the larger hypermarket format.
Another source of variance of out of stocks emerged from another ECR study, this time from the ECR Retail Loss Group's study entitled “Making the Link: the role of employee engagement in controlling retail losses”, published in 2014. What this study reported was that the quartile of stores with the lowest level of employee satisfaction had twice the shelf out of stock rate than the average of the stores in the other three quartiles: https://ecr-shrink-group.com/research.
Important information, but the more critical question for retailers to understand is the scale of the lost sales from these empty shelves. In other words, if this problem was to be fixed entirely, how much would sales grow? To date, the approach taken to answering this question has been to understand from shoppers what they would do if they were to find their favourite brand/item/size was out of stock. Table 1, based on the data published by Corsten and Gruen, displays the responses from European shoppers across eight categories.
Shopper Responses to Out of Stocks - Europe:
% of Shoppers who:
Do not Buy Anything 9%
Buy the Item at Other Store 27%
Delay Purchase 17%
Substitutes - Buy Different Brand 32%
Substitutes – Buy Same Brand 16%
For the retailer, Corsten and Gruen determined that the retailer would incur a sales loss when the shopper takes one of the two following actions:
• The shopper does not buy anything (9%)
• The shopper buys the item at another store (27%)
They also estimated, evidencing a study by Data Ventures, a value loss of 7% when the shopper substitutes items, and buys alternative brands at a lower retail price or smaller sizes of the same brand.
Together, these actual losses total to 43% meaning that if shoppers were faced with 100 incidents of a shelf out of stock, 43 of those incidents would lead to less money in the till, with the retailer losing no immediate sales value on the other 57 incidents as consumers switched to other brands.
Table 2 illustrates the impact on net income for retailers reducing out of stocks, with two scenario’s, first the brilliantly optimistic one that the problem is completely eliminated and then more pragmatically, the impact if the problem was halved.
In the first step of the analysis, the sales increase rate is calculated for both scenario’s. For the first scenario, the full out of stock rate (8.6%) is discounted by 57% to get to the sales growth potential (3.7%). In the second scenario, the sales growth if the problem was eliminated completely is discounted by 50% to identify the increased sales if the problem is halved (1.8%)
The second step, the gross profit improvement that these lost sales would generate is identified by assuming an average gross margin of 30%. This calculation shows that the retailer could add profit that would be the equivalent of 0.54% of sales by halving out of stocks.
A way to express this profit increase would to view it as a percentage of retailer net income, which has been assumed at, based on research by the Cranfield School of Management, 3% of sales. When viewed this way, improving out of stocks by half, could grow a retailer’s net income by 18%. A very attractive proposition for most retailer CEO’s.
Impact of Improving Out of Stocks - Europe
Target 100% improvement in Out of Stocks (Zero Out of Stocks) 50% Improvement in Out of Stocks
Sales Increase 3.7% 1.8%
Gross Margin % 30% 30%
Improvement to Gross Margin 1.1% 0.54%
Current Net Income 3% 3%
Improvement to Net Income 36% 18%
Clearly, there are two big limitation of this analysis, first, it is based on the claimed behaviours for just eight categories and second, it ignores any possible cost to achieve these goals, such as higher waste or labour hours. Nevertheless, in the ultra-competitive retail sector, the analysis does point to the potential of a very attractive growth opportunity.
Drivers of Out of Stocks
While much of the academic research has focused on the sources of the loss, for example, how much is caused downstream and therefore the “fault” of the stores versus upstream and therefore the “fault” of the supply chain, head office and the manufacturer, the more instructive analysis is to understand the breakdown of the causes by work process.
Corsten and Gruen looked at five broad work process areas that they reported accounted for 91% of the sources of the causes of out of stocks, namely store stocking, store forecasting, store ordering, planning and supply. In Europe, the breakdown is displayed in Table 3.
Causes of Out of Stock by Work Process
Work Process Attribution
Store Stocking (too few staff, not found in back room, etc) 38%
Store Forecasting (Too little, slow response time, etc) 22%
Planning (incorrect master data, wrong category planning, space allocation, etc) 11%
Store Ordering (not enough ordered, not ordered on time, etc) 11%
Supply (not sent, not sent on time, etc) 9%
Other (Manufacturer supply problem, storms and floods, etc) 9%
What is most instructive about these work processes to loss prevention is that it shines a light on the connection between loss, loss prevention practices and on-shelf availability. For example:
Store Stocking – stores can generate shelf out of stocks incidents when they minimise the shelf quantity in store to accelerate the sales of items with sell by dates close to expiry, to maintain item freshness or to reduce the quantity that thieves could steal on any one occasion.
Store Ordering – items not correctly coded as waste, damaged or simply stolen, will not be written off in the perpetual inventory records until after the lack of recording or incident has occurred. The consequence is that sales-based ordering systems will continue to “think” that those items are still on the shelf, leading to replenishment orders not being generated on time and/or until a correction is made and the missing inventory is written off. Thus, a major cause of shelf out of stocks for some high loss products can simply be that no one knew that they had not been ordered.
Planning – incorrect master data can be both a cause of loss and a shelf out of stock. For example, when a store is shipped a case of what the master data believes to contain 40 units but in fact, due to an input error, only contains 20 units, those 20 items will be recorded as a loss and at the same time will not be available to sell, even though the system thinks they are on the shelf.
These are just three examples of where a shelf out of stock can be caused by a response to shrink, can be a consequence of shrink, or be both a cause of shrink and a cause of out of stocks.
This inter relationship between these two priorities can in turn lead to tension between functions, especially between buying and store operations, and inconsistency in the delivery of the intended shopper promise and ultimately store and shopper loyalty.
Responses to the Problem of Shelf Out of Stocks
The ECR Europe report produced in association with Roland Berger recommended that the industry adopt a coherent shopper-centric approach to the problem, that started with better measurement, that in turn would lead to increased management attention, both in the store and in the head office across all functions. From these two foundational elements, the report then made a series of recommendations focused upon five improvement levers, namely; improve the replenishment systems (from collaborative forecasting to improved labour schedules), to simplify the merchandising strategy (range, layout, etc); to improve inventory record accuracy; better manage promotions; and to develop more automated and collaborative store ordering systems.
The ECR Europe report then illustrated through case studies how these different levers were being used by retailers such as Auchan, Sainsbury’s, Spar, Delhaize and DM, providing evidence of the benefits of:
• Adopting a Point of Sale-based measure of on-shelf availability.
• Moving to an automatic store ordering system.
• Reducing and simplifying the assortment.
• Ensuring that planograms are fit for purpose with the right shelf holding capacity.
• Removing the errors in master data file and store book stock systems.
• Improving case and consumer packaging.
• Sharing data on sales and inventory with manufacturers.
Above all, the report illustrated that there is no one “silver bullet” and that for each item, category, store format, store location and time of year there will be different specific reasons that explain poor on-shelf availability performance, from a lack of supply through to poor store management.
Like with the problem of shrink, the most important response to the problem is to adopt a structured and systematic approach to problem solving that includes the following steps.
1) Call to Action – a clearly stated problem statement with a compelling financial benefit that can ensure that the right resources are allocated to ensure that there is capacity to deliver change.
2) Project Plan – the right stakeholders are identified, recruited and a clear charter for the project established with approvals and sponsorship from top managers. Focus the project on the 80 for 20.
3) Measure and Map – identify where to focus by reviewing the data to then to zoom in on the vital few products, stores or processes, with a joint group following and noting the flow of product and information from the moment an order is placed through to the shelf.
4) Analysis – from the process maps and the data available, identify the possible causes of an out of stock incident, then brainstorm and prioritise possible root causes.
5) Develop and Pilot Interventions – pilot and test possible interventions.
6) Implement – deploy proven interventions in the organisation, supply chain operations and stores.
7) Review and Reapply – document and independently review results post deployment and reapply learnings to other categories, stores, etc.
Sustainable and successful responses to the problem rest on the level of senior manager commitment to the improvement goals and good measurement, hence these are the very first requirements for change.
The Link to Loss Prevention
Hopefully you will have followed this blog so far, and concluded great information but this problem is not in my scope of work. However, to challenge the status quo, is there not a case for the loss prevention team to play a more leading role in improving on shelf availability in the future?
For example, while general management would still hold the final accountability, why could the loss prevention team NOT take on the extra responsibility for developing and championing the overall company OSA improvement strategy, the metrics, the capabilities and a multi-functional rapid response team to go after the biggest opportunities?
A possible rationale to management for such a proposal could be as follows:
1) If your organisation is typical, responsibility would be split and there would no one single team clearly identified as responsible for the strategic oversight of the OSA problem, the metrics, the interventions, the tools and techniques and importantly, management reporting. By putting themselves forward, the loss prevention team could be meeting a large unmet need for the organisation.
2) Since there is this trade-off between OSA and loss, by appointing one team to find the right balance between two problems, your organisation can be in a better position to find the “sweet spot” between too many lost sales though OSA and loss, especially on fresh and high margin categories.
3) Finally, it can be argued that many of the core capabilities of your loss prevention team and their investments in data analysis can be transferred over to and scaled against a problem that could be 3-5 times greater than shrink alone, thus your team’s return on investment could grow exponentially.
Maybe this approach would be too controversial for your team right now but maybe something to consider for the longer term?
What can you as loss prevention leaders do next?
So, with the thought that becoming the lead support function for general management on OSA being for the longer term, the next steps outlined below are some that any loss prevention team could take tomorrow to be more involved in OSA, helping the organisation drive sales and net income growth.
Step 1: Call to Action: To illustrate the relationship between loss and OSA for your organisation, review the OSA and loss data for the top ten most out of stock items across some key categories.
Does your analysis show that some of the most out of stock items are also the most lost (waste, error or damaged) items? If yes, and by using the methodology described earlier, aim to calculate the sales and profit improvement of a 50% improvement in OSA and a 50% loss reduction. What would this improvement represent as a percentage improvement on current profits? Is this growth potential large and compelling enough for the organisation to initiate a project?
Step 2: Map and Measure: From store visits, the loss prevention team should seek to understand the extent to which high levels of out of stocks could be attributed to the measures the stores are taking to tackle the problem of loss. For example, are the stores restricting the quantities of the items they create, put on the shelf or indeed order, to manage waste and loss? If they are, could these choices be “dampening” the overall profitability of this item or category? Put another way, if OSA could be improved, could the sales and margin grow at a faster rate than the losses?
Step 3: Cross Functional Teamwork: Typically, retail merchants or buyers are accountable for sales, with the stores accountable for shrink/waste. And herein lies the crucial problem of competing priorities. The role of the loss prevention team could be to initiate joint projects inviting the buyers, the stores and potentially the product manufacturers to jointly investigate new interventions that can improve OSA while at the same time controlling loss to an appropriate level, leading ultimately to a higher level of category profitability.
The aim of this blog has been to explore the relationship between on-shelf availability and loss by sharing some of the currently available research from ECR and other industry associations. What the research shows is that out of stocks is a significant problem to the shopper, the retailer and the manufacturer. Improving OSA can grow the bottom line significantly; just a 50% improvement can potentially lead to an 18% increase in net income.
A deeper understanding of the causes of shelf out of stocks, reveals that losses themselves and the actions organisation’s can take to control losses contribute to the extent of shelf out of stock problems.
Finally, this blog makes the case that the loss prevention team could play a bigger role on OSA supporting general management in their efforts to reduce shelf out of stocks, while at the same reducing losses due to theft, waste and error.
To get started, the loss prevention team could take time to better understand, through data analysis and store visits, how loss and loss prevention controls contribute to the OSA and loss problem on the ten most often out of stock items.