Gas Station Merchandise Planning: Tackling 7 Challenges with Advanced Software Solutions

global retail
  • Aug 4, 2023
  • 9 min read
Cover: Gas Station Merchandise Planning: Tackling 7 Challenges with Advanced Software Solutions

Gas station inventory management has much in common with convenience stores. For starters, the merchandising challenges are similar, and effective merchandise planning is often the key to increasing productivity and developing retail stores sustainably. Nevertheless, there are also some peculiarities that we are going to discuss today.

Merchandise planning challenges of gas station chains can be dealt with using traditional methods, but a lack of in-depth analytics and manual operations often complicate things. However, owing to advanced software based on artificial intelligence algorithms, most functions in inventory, product mix, and shelf space management (such as ordering, category management, product display, etc.) can be performed more efficiently or even be fully automated. So, let’s take a look at the seven most common challenges in merchandise planning that can be met by utilizing artificial intelligence:

1. Limited storage and shelf space

One of the peculiarities of gas station stores is the small footprint, which often leads to problems with inventory storage. To ensure that goods are always in stock, purchasing managers often resort to increasing the volume of orders, which often leads to overstock, write-offs, or even forced sales. On the other hand, if the stock is not replenished in time and the store faces high demand, no goods on shelves will mean lost sales. So, either result will be unprofitable for the retailer.

Solution: Set up the "empty warehouse" inventory management system while ensuring an adequate stock reserve for showcasing. 

This approach requires precise product ordering and logistics to maintain optimal stock levels without constant inventory storage. To efficiently set up an "empty warehouse" system, gas station chains need to use specialized software to ensure optimal availability of each SKU through accurate forecasting and flexible supply chain setup.

For instance, the cutting-edge LEAFIO AI Retail Platform currently helps gas station chains such as WOG, VIADA, Baltic Petroleum, Avias, and others with complex merchandise planning and solving the following tasks:

  • forming a flexible supply chain and efficient distribution of stock between locations in the network while minimizing balances and "frozen" goods;
  • making accurate forecasts and ensuring optimal availability of each SKU;
  • creating product displays based on current balances, ensuring the proper level of stock on the shelf for the next delivery;
  • creating planograms that help to effectively use every bit of shelf space available and maximize revenue.

2. Limited product mix on the shelves

Due to space constraints, the product range at gas stations is limited. If the selection of goods does not meet customers' needs, you risk losing sales or overstocking. Therefore, all available space must be used wisely, and each SKU must be carefully selected and occupy the optimal place on the sales floor.

Solution: ABC analysis of the available product mix, demand analysis, elimination of passive SKUs, and timely assortment rotation.

It is crucial to perform the following actions regularly to ensure that the optimal product mix is put on the shelves:

  • Analyze the assortment performance considering the location, supplier, product category, and SKU;
  • Identify the driver products and those that require more promotion;
  • Based on analytics data, remove ineffective SKUs from the shelves and select better alternatives;
  • Forecast demand for new products to minimize risks and, if necessary, make changes.

For example, the LEAFIO platform offers the Assortment Performance solution, which allows you to build your assortment management strategy and simplify this process with the help of accurate calculations and artificial intelligence recommendations. The system constantly analyzes changes in the product mix and offers improvements that will increase your sales.

3. Time spent in the store 

Most gas station customers spend only a few minutes in the store and do not intend to stay longer. Therefore, the space should be organized so the customer gets to the right products quickly and makes additional purchases simultaneously. It is essential not only to choose the right product mix but also to provide such an attractive layout that you prevent empty shelves.

Solution: Analyze layout and macro space development, consider sales data, margins, and customer journey.

To effectively respond to this challenge, it is essential to:

  • Quickly identify passive categories and SKUs and remove them from the shelves or change their placement;
  • Select the optimal placement for related products to ensure  additional sales and, as a result, increase  the average check of the store;
  • Quickly rotate the product mix and replace sold items in the planogram.

Fast and intuitive design process

Currently, there are cloud-based solutions that help to create practical and smart planograms, set tasks for staff, and monitor their implementation online. For instance, the LEAFIO Shelf Efficiency solution includes a mobile application that allows store staff to receive assignments quickly, update the display, and send photos to confirm changes.

"A cloud-based system that is constantly evolving is the key advantage. LEAFIO meets the price and quality requirements, as well as all merchandising management needs. It is much more than just planogram modeling. It is a comprehensive tool that has provided a new approach to merchandising management in the WOG chain of stores," says the WOG Project Manager.

4. The need to expand the gas station chain

Profitability in the industry can commonly only be achieved through the opening of new permanent locations and targeted network expansion

According to a report by BCG, a global consulting company, 70% of retailers plan to expand their networks. 

However, every retailer knows that opening a new location is a costly and complex process fraught with many difficulties. In addition, new managers have to be hired to work on opening new locations, which always involves additional costs.

Solution: Streamline the store opening processes based on data from the experience and sales across the network.

Thanks to advanced software, most of the processes involved in network expansion have become automated. The system simply copies all the necessary data and supports the opening of a new location. The POS opening does not require new purchasing managers, which lowers costs. 

The software expands the capabilities of managers when opening new points of sale by:

  • Standardizing the processes of planning promotions, stock replenishment, and control over the product mix and shelves;
  • Forecasting demand in the first stages of opening a location while taking into account data collected in similar locations;
  • Creating format planograms with the ability to make the necessary changes instantly online.

5. Balancing the management of fresh and ultra-fresh products

Fresh goods are one of the most challenging categories in inventory management. They have a short shelf life, so they need to be constantly restocked.  The ultra-fresh category is even more complicated. It requires daily deliveries, and if you stock the shelves fully,  it will inevitably lead to overstocks and write-offs of expired products. Still, if you don't order enough, empty shelves will disappoint customers and lead to lost sales.

Sharp demand spikes during the week are another problem. Today, you have full shelves and expired products, and tomorrow, you have empty shelves and unsatisfactory demand. You must also consider the minimum acceptable delivery and sales time for fresh products. This is usually specified in the contract with the supplier, and the terms may vary depending on the delivery or type of product.

Solution: A detailed analysis of changes in consumer behavior, as well as the creation of a flexible supply chain and its synchronization with demand.

When placing orders, you should consider the following information:

  • existing restrictions and agreements with suppliers, product packaging, and reserve stock;
  • product shelf life and the number of days it can stay on the shelf before it expires;
  • changes in demand during the week to change orders following expected sales volumes;
  • delivery times during the day to create the most accurate forecast.

The LEAFIO Fresh Inventory functional module considers all of these parameters. It allows you to balance the supply of fresh products, preventing the formation of surplus or empty shelves. The system calculates orders with high accuracy owing to the implemented simplified analog of LIFO batch accounting. In addition, the system minimizes product write-offs by automatically setting an acceptable level of availability.

6. Forced markdowns to sell goods

Sales are often necessary to quickly move stock, but implementing each promotion takes time and hard work. Therefore, it is vital to deal with the causes of shelf delays rather than the consequences. If you minimize stocks, you can reduce the number of forced promotions.

Solution: Ensure the most accurate ordering, which will provide optimal turnover and minimize the need for forced sales.

Accurate ordering is possible when you use reliable analytics data and forecasts that consider fluctuations in demand. The more precise your orders become, the less often you need to make additional sales and markdowns. Manual calculations without software naturally cannot guarantee such accuracy. Note that specialized software can also exclude atypical sales from analytics data, as they affect the indicators.

If you still need to plan promotions, the whole process can be implemented more efficiently and conveniently through the LEAFIO Promotion Intelligence functional block, which includes all the necessary tools for preparing and implementing sales, such as:

  • promotion calendar,
  • planning, warnings about related actions and possible errors,
  • automatic creation of a forecast of results using artificial intelligence,
  • adaptation of the inventory to actual promotional sales,
  • estimate of the necessary stock for promotion,
  • productivity analysis based on turnover, balances, plan-fact, etc.

7. Frequent and multifactorial demand fluctuations

Consumer activity in stores at gas stations is very volatile and depends on many factors. Demand is affected by location, days of the week, time of day, holidays, etc. If you only calculate these fluctuations and create forecasts manually, critical errors and lost sales are inevitable.

Solution: Analyze consumer activity and generate forecasts using AI tools.

In a multifactorial and volatile demand environment, it isn't easy to formulate a strategy based only on manual analysis. Artificial intelligence is more effective, as it eliminates the human error factor and allows the processing of large amounts of data. 

Thus, with  AI, you  can:

  • calculate the index of demand fluctuations and use it to form more accurate orders during the week;
  • create orders based on data on the current level of stock, size, and type of packaging, goods in transit, etc.;
  • use accurate data without taking into account atypical consumer activity;
  • create an optimal inventory level based on supplier reliability.

"We chose LEAFIO because we liked the energy and expertise of the team. They already run successful implementation projects for gas station chains in countries with good performance indicators. We realized that we could trust them because their team not only implements solutions but also helps to build more accurate and efficient business processes," Edwin Bakhshiyan, CEO of Baltic Petroleum, said.

Utilize the power of artificial intelligence to optimize inventory and grow your network

AI-powered software will help retailers better manage inventory and shelf space, forecast demand, and efficiently use limited store space. Implementing an intelligent product planning system will significantly reduce costs and boost business performance by improving order accuracy, creating an efficient "empty warehouse" system, deep analytics data, and automating most of the routine tasks of managers.

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