Forecasting in the supply chain: How to achieve the perfect balance of supply and demand

If the supply chain is the path of goods from raw materials to the end consumer, then the accuracy of the consumer demand forecast will determine how efficiently this process will be accomplished.

This means that all chain participants, from manufacturing companies to retailers, will be able to use their resources to maximize profits and optimize costs.

In fact, the demand forecast is the beginning of the entire chain. It determines the workload and “work schedule” of all its links. It is also the beginning of production planning, and it is the basis on which distributors and retail stores rely when purchasing and transporting goods.

Any mistakes made at this stage can be very costly. A shortage of manufactured or purchased products when there is demand means lost sales or additional costs for urgent replenishment of stocks. According to RetailDive, businesses lose about $1 trillion a year due to the inability to meet customer demand on time.

Overstocking is an equally annoying phenomenon. Excessive inventory requires additional funds to store goods that are not in demand and, in the case of goods with a limited shelf life, to write them off.

You can easily calculate how an accurate forecast will affect your company’s sales using our interactive calculator.

Therefore, innovative companies are massively implementing modern forecasting solutions based on artificial intelligence; one of them is SMART Demand Forecast. These solutions allow companies to make the forecast as accurate as possible, considering a large amount of diverse data and identifying non-obvious patterns.

According to a study conducted by McKinsey & Company, 20% of companies are already using the latest technologies that plan and forecast demand in the supply chain using AI. And 60% of organizations have already planned to implement such technologies.

The rest still rely on expert analysis, considering trends in sales history and insights from business analysts. However, experience shows that such calculations are often significantly less accurate than the results provided by tools with properly selected and configured artificial intelligence algorithms. There are different types of demand forecasting in supply chain management: quantitative, qualitative, etc. But best practices usually include AI algorithms and advanced analytics.

Benefits of accurate demand forecasting in supply chain management

Forecasting tools like SMART Demand Forecast can greatly reduce all mentioned risks and increase supply chain management efficiency. Let’s take a closer look at the benefits that businesses get from an accurate demand forecast.

Minimization of lost sales

As the above statistics show, companies lose significant amounts of money due to their inability to meet consumer demand. This happens if analysts underestimate or fail to consider the factors or hidden patterns that led to a more intense spike in demand for certain groups of goods than expected.  Consequently, the supply of products was not organized properly.

Organizations find themselves in a situation where they are simply unable to sell a popular product due to its unavailability. Or they are forced to make additional efforts and funds to replenish stocks as soon as possible, overpaying for the urgency of order fulfillment.

Increase in customer loyalty 

If a customer or buyer periodically has difficulties purchasing the products they need, this can be a serious threat to the image of the supplier or store and the chain. Poor service will lead to the fact that you will at least lose customer loyalty, or in most cases, lose them completely. At the same time, attracting new customers requires much more money than retaining existing ones. In addition, if you don’t have the goods when there is demand, you will lose profit. An accurate forecast helps you maintain the required level of inventory at all times, especially during promotional campaigns.

Ability to respond quickly to fluctuations in demand

One of the difficulties in forecasting supply and demand is the changing nature of consumer behavior, which can be influenced by many factors, such as hot trends, competitors’ activities, and even the weather. It is clear that even artificial intelligence cannot take into account unpredictable factors, as it processes only the data provided to it. However, it will definitely be able to take into account all the necessary factors for a more accurate and timely forecast of demand fluctuations, which will help manage the supply chain more efficiently and flexibly.

Reduction of logistics costs 

Inaccurate forecasting of demand in the supply chain also leads to unnecessary logistics costs. For example, if a forecast for a chain of stores is based entirely on analysts’ estimates and assumptions, it means that:

• the forecast will often be less accurate and more pessimistic than realistic;
• it will usually be made for the entire network, with a further approximate distribution between different stores.

As a result, some stores will usually have an excess of products, while others will have a shortage. To overcome this imbalance, companies have to redistribute the volume of goods between outlets, which, in turn, leads to additional logistics costs. These costs increase production costs and “eat” margins.

Modern tools make it possible to forecast demand for specific items for each store separately. This helps ensure optimal stock levels in all stores of the chain.

Reduction of warehouse costs 

An erroneously overestimated demand forecast leads to the fact that some products remain unsold. These products must be stored in warehouses and become the “frozen capital” of the organization, resulting in additional costs for renting warehouse space.

Minimization of the number of written-off products

An excess of unsold goods with a limited shelf life often leads to the fact that, at some point, they must be written off. That means that all the money invested in their purchase, delivery, and storage is simply wasted. In addition, the write-off process itself involves certain costs. In order to at least partially avoid write-offs, companies are forced to sell products significantly cheaper while also spending an additional budget on marketing activities.

More effective promotions

The use of supply and demand forecasting tools can make promotions more effective and manageable. But it requires systems that can calculate both regular and promotional sales volumes. SMART Demand Forecast is one of these systems.

For example, they help you determine the optimal discount for certain items. Let’s assume you plan to reduce the price of a product by 30%. The system may find that with such a discount, demand will be so high that suppliers will not be able to meet it. Meanwhile, with a 15% discount, you will sell fewer items but earn more due to the higher price. Based on the system’s forecast, the supply chain manager will be able to make a reasonable decision on how many products to purchase, depending on the optimal discount.

In addition, tools that forecast promotions can take into account the so-called cannibalization, which is very important. When you set a discount for a certain product, the higher demand for it “eats” sales of similar non-promotional products.

Some companies forecast only regular sales, and these forecasts are always wrong because they do not take into account the cannibalization factor. Systems like SMART Demand Forecast automatically and accurately reduce the demand forecast for non-discounted products and increase it for similar discounted products.

More effective pricing policy

An accurate forecast of demand fluctuations for various items also helps to set optimal prices for them. For example, if the system “sees” that there is a demand spike for a certain product, it gives a reason to set a higher price, and vice versa. In addition, a forecasting solution will help determine what price will maximize sales.

Forecasting features for manufacturers and distributors

Demand forecasting is the beginning of the supply chain for all participants, including manufacturers and distributors. Production planning begins with the forecast. It is used to calculate the required amount of raw materials and production capacity to meet the expected demand. It considers the stock level of products and the production processes that have already been launched.

And while such companies usually make a profit from sales to distributors, the so-called primary sales, it is important to take into account secondary sales for a correct forecast: how much of your products the distributor will deliver to retailers.

For example, if a distributor plans to run a promotion for certain products in stores, it means that the distributor will buy more of those products from the manufacturer to meet the higher retailer demand.

It may also turn out that the distributor purchased less of your products than they shipped to stores during a certain accounting period. The ratio of goods purchased and sold by distributors will help you determine how much product will be purchased in the next accounting period.

Distributors engaged in secondary sales make their own forecasts based on insider information from retailers (planned store promotions, their sales forecasts, etc.). But since such information is not always available, distributors are forced to keep a safety reserve, which is determined considering the deviations from previous forecasts.

It is crucial for them to maintain a stock that, on the one hand, is not excessive and, on the other hand, ensures the constant availability of the necessary goods. If at some point the distributor does not have enough products for the retailer, the retailer will address another supplier or sign a direct contract with the manufacturer. Thus, the distributor simply drops out of the supply chain.

How artificial intelligence helps to build accurate demand forecasts

AI-based solutions for demand forecasting in the supply chain greatly simplify analytical calculations and make them more accurate. Let’s take a closer look at the benefits of using such tools.

Labor cost reduction

If a company does not use modern tools for demand forecasting, it is forced to recruit a large staff of analysts. But even an entire analytical department requires a lot of time to consolidate information, perform complex calculations, process large data sets, and identify various dependencies and trends.

Using an AI-based demand forecasting solution, an analyst only needs to upload correct and comprehensive data to the system, start the calculation process, and get a ready-made forecast. The only thing left to do is to demonstrate the result to the management, explain why this result was achieved, and suggest measures that would bring the forecast closer to the organization’s business goals.

Thus, the analyst gets rid of a large amount of troublesome and complex work and has more time to actively participate in decision-making. Instead of being stuck in an endless routine as a “computer operator,” they become a forecasting expert.

Minimization of human error

Supply and demand forecasting solutions also minimize the possibility of human error, which can cause significant losses for businesses. The analyst does not have to make any calculations. All the necessary formulas and algorithms are already built into the system. The user understands how the forecast is calculated, but the process is automatic, fast, and guaranteed to be correct.

A single database

Thanks to tools like SMART Demand Forecast, all information is stored in a single, unified database. In companies that don’t use such forecasting solutions, analysts usually have to combine information from disparate systems. They need to get master data from one system, a sales report from another, data on promotional campaigns from a third, and so on.

Using SMART Demand Forecast, all departments and all employees work in a unified system, in a single format, in a single interface. The benefits of this are especially noticeable when a certain employee falls out of the workflow for some reason, for example, by going on vacation, taking a sick leave, or resigning.

Another employee can easily continue to work with the information that the previous employee entered into the unified system. Without the unification provided by modern forecasting solutions, it can be very difficult for one employee to understand the calculations of another, thus jeopardizing the continuity of business processes.

Consideration of all necessary factors

One of the main difficulties in demand forecasting in the supply chain is that many factors, both internal and external, must be considered. This is quite difficult to do, even if a team of experienced experts is working on the forecast. Artificial intelligence solutions can do this quickly and accurately if all the necessary data has been entered into the system. The list of factors that can be taken into account by artificial intelligence is quite long. Here are just some of them:

– research results;

– data on competitors;

– macroeconomic trends;

– supplier’s promotions;

– own promotions;

– cannibalization;

– data from social networks;

– weather forecast;

– data from POS terminals;

– events in the country…

Artificial intelligence is able to take these and other factors into account, compare them, and find patterns, interdependencies, and hidden trends that are not obvious to analysts. Thus, the forecast will be more accurate and well-justified.

Chain reaction

It is statistically proven that the extra costs associated with poor forecasting in the supply chain on average make up 2% of the cost of sales. If the analyst makes a mistake, the company’s losses from such a forecast can be much higher. Systems using artificial intelligence and machine learning technologies, such as SMART Demand Forecast, are able to minimize these losses by making more accurate calculations. That’s why the vast majority of companies in the world are either already using such solutions or preparing to implement them.

Would you like to learn more about how accurate demand forecasting in the supply chain will affect sales in your company? Request a personalized presentation.