The essentials of inventory forecasting
Determining the exact quantity of products that will be sold at a specific time of the year offers a company the opportunity to optimize its inventory. Inventory forecasting has become a necessity to improve the performance of the supply chain and the overall performance of a company.
For this purpose, an innovative tool has been developed: the predictive intelligence platform which allows to make sales forecasts and stock shortage forecasts.
But what is the precise role of sales forecasting in inventory management and optimization? What are the most effective inventory optimization methods? We offer you a complete analysis of the fundamentals of inventory forecasting.
The role of sales forecasting in inventory optimization
Companies have to face many problems related to inventory management. Indeed, when not optimized, inventory management can degrade the performance of a company. Thanks to sales forecasting and artificial intelligence tools, stores can implement a real inventory optimization strategy.
Avoiding overstock and out-of-stock situations with sales forecasting
In inventory management, overstock and out-of-stocks are major issues. Companies need to know the exact amount of product they need to store in their warehouse area.
Overstock penalizes the company which must find solutions to sell, in spite of everything, its surplus of products. Promotions can be put in place. However, some products simply cannot be sold. This is particularly the case for perishable products that are past their use-by date. This overstock then becomes a dead loss. Finally, the overstock represents a more important storage cost since the references which do not generate sales occupy a storage space.
Concerning the stock shortage, it also penalizes the results of a company and can harm its position on the market. Firstly, customers faced with an out-of-stock situation may decide to switch to another company and order from the competition. An out-of-stock condition degrades the customer experience. Second, production of an out-of-stock item must be restarted in a hurry. Raw material purchase costs are no longer negotiated. Similarly, delivery costs can be higher because they are not optimized.
So, to optimize storage, innovative tools allow to make sales forecasts. Sales forecasting is essential to determine in advance the quantity of references needed in the stock. A supply chain that integrates sales forecasting is an efficient supply chain that is able to avoid stock-outs and overstocking.
Reducing storage costs by taking into account the sales forecast
But sales forecasting also plays a key role in reducing storage costs. Depending on the business, a company may need to store high volume SKUs, high value items, hazardous products, food products, etc. All of these characteristics result in additional storage costs.
By knowing in advance which products will be sold and in which quantities, logistics optimizes its storage in a global way. Indeed, the inventory forecast allows the company to anticipate its storage needs. It has total visibility over a week, a month, a year, etc.
In addition, the predictive intelligence platform integrates data external to the company, such as the weather, the economic and health context, etc. It can therefore determine future stocking trends. It can therefore determine future consumption trends. Combined with the company's internal data, these trend indications refine sales forecasts and inventory forecasts.
The human factor in inventory management
Storing items represents a financial cost for the storage warehouse. But stock management is also about the men and women who work in the warehouse on a daily basis. The costs related to human resources can penalize the performance of the supply chain in the case of poor inventory management.
Once again, the data provided by sales forecasts optimizes resource requirements. For example, if machine learning predicts a peak in sales for the month of October, the company knows that it will need to mobilize more human resources. Similarly, depending on the type of products sold, small or bulky items, it will be able to adapt the composition of its logistics team. The management of the logistics team is also optimized thanks to the sales forecast.
The different methods of inventory forecasting
Inventory forecasting is at the heart of inventory management, as it addresses many of the challenges of optimized inventory management. Inventory forecasting methods are tailored to certain industries, product types, etc. However, we will see that the last method, the one based on machine learning, is the only one that includes anticipation and provides reliable predictions.
The ABC method and the 20/80 law
The 20/80 law is also called the Pareto method. This method proposes to identify the 20% of references that represent 80% of the global value of the stock. It should be noted that the Pareto method is used in areas other than storage. For example, in sales, 20% of customers generate 80% of the turnover.
In order to forecast the inventory, it is therefore necessary to start by identifying the 20% of the inventory, in terms of number of products, which represent 80% of the total value. The ABC method applies this reasoning to the rest of the inventory:
- Category A contains 20% of the products that represent 80% of the value of the stock;
- Category B contains 30% of the products that represent 15% of the value of the stock;
- Category C contains 50% of the products that represent 5% of the inventory value.
Then, according to this ABC classification, the stock level of category A products will have to be monitored on a more regular basis. The replenishment order should be given early enough to avoid any shortage. These products must also be located in the immediate vicinity of the picking areas in order to increase efficiency.
The FIFO method: First in, first out
Let's see the FIFO method, First in first out, is called FIFO in English: First in first out. It consists in managing its stock according to the date of entry of the various parts in the storage space. Thus, the products having generated the last production costs or the last purchase costs must be sold first.
This inventory management process is a method that tends to valorize costs. It is one of the most common methods used in the automotive industry, where the FIFO method prevents spare parts from becoming obsolete. The storage of food products can also be done using the FIFO method. In this case, the products are consumed before they reach their use-by date.
The FIFO method therefore allows the management of replenishments according to the date of entry of the references in the stock.
The forecasting and artificial intelligence method
To optimize its inventory management, the company can opt for the inventory forecasting method and for artificial intelligence. In this case, it chooses optimization, but also anticipation. To be efficient and effective, inventory forecasting includes:
- analysis of sales receipts, cancelled orders, abandoned baskets, pending orders;
- the local economic context and the level of competition;
- psychological factors;
- sports and cultural events;
- weather conditions;
The machine learning takes into account both the traffic and the number of orders placed on a Tuesday morning. It analyzes the days of the week when orders are most numerous and which promotions generate the most sales. It is thus able to offer a complete and real vision of the future orders of a local store, an online store or a retail store.
Thanks to the simultaneous analysis of all these data, the prediction system provides quality forecasts in real time. Companies are therefore able to know exactly how many orders will be generated during a given period. Controlling the flow of future orders allows them to better manage replenishment and storage.
Similarly, they will be able to analyze the sales of a product during a season. This allows them to optimize their storage, better negotiate with suppliers and better plan replenishments throughout the year. Finally, by relying on innovative artificial intelligence tools, companies can anticipate their decision making in complete security.
In short, inventory forecasting is an integral part of a successful business strategy. Optimized action plan, data security, customer satisfaction or resource management, inventory forecasting becomes essential to optimize inventory management.
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