The “dark side” of retail: industry challenges and specifics of inventory management for dark stores

  • Feb 1, 2023
  • 10 min read
Cover: The “dark side” of retail: industry challenges and specifics of inventory management for dark stores

Since Tesco launched its first dark stores in the United Kingdom in 2009, the format has grown rapidly in Europe, eventually taking over the world. According to the Future Market Insights report, the average annual growth rate for the global dark store market from 2018 to 2022 was 24.5%.

The quarantine restrictions of Covid-19 gave a powerful boost to the development of Q-commerce in general and the dark store format, in particular.  When customers were "locked up" and supermarket floors were empty, some chains developed this format in parallel. In contrast, others decided to go "to the dark side", seeing in it fantastic opportunities. Therefore, when people talk about dark stores, they often mean one of the varieties of this business model:

  1. Classic dark stores. In this case, there are no physical stores for customers, only a website/application for customer orders and warehouses with picking operators for delivery/self-delivery. Distributors can also use this option to enter the retail market without intermediaries.
  2. Dark stores based on operating supermarkets. Here there is no separate warehouse, and orders for delivery to customers are formed directly from the existing store. This is convenient if the chain has an extensive system of stores in different areas and has the ability to make a quick delivery, which is critical for dark stores.

In 2022, there were already more than 6,000 dark stores worldwide. In addition to industry pioneers Tesco and Sainsbury's, the industry today is represented by significant players like Amazon, Walmart, Ocado, etc., as well as local chains and startups. And from 2023 to 2033, FMI predicts an average annual growth rate of 38% for this market.

Today's article will focus on classic dark stores, their features, and the challenges retailers face in this relatively new industry.

The features and challenges of the dark store industry

Along with the obvious benefits and prospects of this quick commerce model, there are several significant challenges for dark stores to overcome for businesses to grow and make a profit. 

Time is a critical variable in the dark store profitability formula

Being able to "curb" time is an essential key to a dark store's success. In an increasingly competitive environment, with the development of online stores and rapid delivery services, providing the right product to the customer at the right time can be an important factor in the fight for customer loyalty. Two factors are fundamental here:

  1. Speed of delivery.

Today, customers are increasingly less willing to spend much time shopping for groceries. From what used to be a weekend family ritual, this activity  has turned into a quick selection of goods on a smartphone screen with the expectation of a quick checkout and delivery. Many dark stores guarantee delivery within 45 minutes, and some even guarantee a 10-minute delivery (like Gorillas or Flink).

To keep such a "promise," retailers can resort to the following measures:

  • automate all processes for ordering, accounting and delivery of goods to the customer to reduce manual operations and the possibility of errors;
  • optimize the location of goods in the warehouse to make it easier for operators to collect and ship orders;
  • develop an extensive chain of warehouse stores directly in residential areas;
  • make the process of selecting and moving goods during order picking as automatic as possible;
  • optimize/standardize cart size to speed up order picking and use bicycle/scooter delivery;
  • use optimal loading of delivery vans combined with GPS and data analytics to implement centralized route planning. 
  1. Convenient delivery slots.

The growing demand of customers makes it necessary for dark stores to provide them with a choice of convenient delivery times – the so-called time slots. If customers don't find a suitable slot on the site, they may cancel the purchase even if all the items they want are available. Such lost sales can significantly impact the retailer during peak hours, the hot season, and before weekends and holidays. As a result, goods are not sold, creating a surplus. In addition, it will affect the average daily usage (ADU) and, consequently, the correct calculation of orders for replenishment. 

To minimize this problem and partially redistribute the load at peak times, retailers are using additional resources for order processing and delivery, introducing a 24/7 operating mode and practicing "happy hours" when customers can get additional benefits by choosing "unpopular" delivery times. 

While preserving customer loyalty, these measures still lead to additional costs. That's why cost and inventory optimization is the second critical "argument in this equation" on the way to dark store efficiency.

According to experts from PwC, significant investments in technology and automation, as well as operational excellence in order to reduce costs are essential factors in improving the profitability of fast home delivery market players.

Dark stores’ inventory management challenges

1. Ensuring maximum product availability for customers with minimal surplus

Some might argue that this challenge is not unique to dark stores, and that is true. However, for online commerce, the availability of the product the customer needs is critical. In other words, if the required item is out of stock, the online customer is more likely to switch to another online "store" rather than when visiting a "brick-and-mortar" store.

For most products, and especially for the fresh and ultra-fresh categories, 100% availability will always result in significant write-offs unless sales forecasts are accurate enough for each day and store. That is why more and more retailers prefer to solve this problem with the help of specialized systems because manual calculations are quite time-consuming and have a significant error percentage. 

Machine learning-based demand forecasting, such as in the LEAFIO Inventory Optimization system, takes into account most of the factors influencing demand: seasonal and intra-week fluctuations, holidays, promotions, etc. The automatic replenishment system, considering this data, will order exactly as much product as is needed on a particular day to meet the expected demand. Algorithms will take into account lead time, goods in transit, package size, expiration date, and remaining goods in stock. The system will also automatically calculate the necessary safety stock depending on the supplier's reliability level. With such an "autopilot", the retailer minimizes surplus and missed sales, and customers always receive the expected goods and quality service.

According to Accenture research, 47% of customers would be willing to pay more for the products and services of companies that adhere to sustainability principles. Thus, reducing waste not only means lower costs for dark stores but also increased customer loyalty if properly communicated.

2. Efficient use of warehouse space and assortment management

The average U.S. retail store is just under 50,000 square feet, and a typical dark store ranges from 100,000 to 200,000. It doesn't need the wide aisles between shelves like a regular supermarket, and shelves can be much taller. The extra storage space allows dark stores to place not only more stock in the warehouse but also to have a wider product assortment. 

Unlike a physical store, a dark store doesn't need safety stock for display which not only takes up space but also an extra number of turnover days. Therefore, dark stores can return funds invested in goods more quickly.

Unfortunately, these advantages are often offset by errors in demand forecasting or improper assortment selection. In this case, dead stock accumulates in warehouses, which leads either to the freezing of funds or to spoilage and write-off, as in the case of fresh products. 

We have already mentioned that you can easily avoid forecasting errors with modern inventory management systems. In addition, such a system would help manage the assortment efficiently. For example, the BI module from LEAFIO gives comprehensive analytics on product management within the assortment matrix. ABC analysis tracks changes in the sales dynamics of each SKU. The system prompts which goods should be removed from the assortment and helps to do it softly and without losses. When introducing new products into the range, the system will predict demand based on automatically selected similar products and order exactly as much as necessary to ensure availability but avoid excesses. 

3. A high share of promotions

Intense competition and the specifics of online shopping dictate the need for retailers to provide customers with a wide range of promotions and bargains. That's why dark store apps usually have not only a separate section with special offers but also notify customers about current and upcoming promotions. In other words, we can say that promotional offers are an important driver of dark store sales. Therefore, a lack of promotional items will not only be fraught with the loss of one sale but possibly the loss of a customer. On the other hand, the desire to provide the chain with promotional items often leads to write-offs and the spoiling of goods.

Retailers can avoid this problem with a system such as LEAFIO Promotion Intelligence, which can: 

  • forecast sales and automatically generate orders for future promotions;
  • calculate order deadlines for on-time preparation for the start of the promotion so that the goods arrive at the warehouse no earlier and no later than necessary;
  • quickly replenish the stock of goods during the campaign, adapting to the current demand;
  • complete promotions in a timely manner according to the adopted strategy and evaluate their effectiveness.

4. Seasonality, along with sharp fluctuations in demand

As in any FMCG retail business, dark stores also have pronounced fluctuations in demand for certain goods, depending on the days of the week, season or holidays. To prepare for such fluctuations, it is necessary to forecast and purchase an increased volume of goods in advance, taking into account the planned promotions. When dealing with seasons, the challenge is not only calculating sales forecasts and factors correctly but also applying them correctly when calculating orders based on delivery schedules. 

Modern solutions such as LEAFIO Inventory Optimization can automatically calculate and apply seasonality coefficients for regular assortment (demand for which may fluctuate during the season), specific seasonal goods and goods added to the assortment matrix only for a limited time. 

At the same time, we should not forget about unpredictable factors affecting customer demand. These include, for example, sudden changes in the weather during the season or major sporting events. Abnormal heat, for example, increases sales of drinks, and orders of beer and snacks increase many times during broadcasts of major soccer championships. Since such events are difficult to predict and put into system parameters in advance, it is important for purchasing managers to take them into account when adjusting orders just before they are sent to suppliers. 

Thus, seasonality, along with unpredictability, suggests that the ideal of dark store inventory management is a hybrid symbiosis of up-to-date software and knowledgeable experts who can properly adjust system parameters and promptly make the necessary adjustments. That's why we at LEAFIO provide our clients not only with training services for personnel involved in procurement but also offer a long-term partnership and advice in solving arising problems. 

AI-powered solution for building an efficient system of inventory management


As retailers adjust to skyrocketing customer expectations, they still face the old, familiar challenges of introducing new products, forecasting demand for slow movers, managing seasonal and promotional assortments, and more. Fortunately, they can easily solve these problems with high-tech solutions (including the use of AI), even in an increasingly unpredictable and demanding market. According to PwC, technological innovation will be a crucial factor of success in Q-commerce in the medium and long term. And the LEAFIO team is doing its best to bring these innovations even closer and more accessible to our clients.

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