Rapid response to change is a matter of business survival in a period of maximum adaptation to consumer desires. A sudden change in demand for your product can either destroy your business, or it can strengthen your position by outperforming your competitors.

Today, when people are quickly drawn to a new product or idea, they are just as quick to forget about it. The era of fast dopamine rewards is significantly impacting demand and creating new challenges for businesses.

Inventory management is one of the biggest challenges, because it's not only frozen assets, but also storage space and the risk of product spoilage. How can you avoid these losses and stay competitive? In this article, let's look at demand forecasting techniques and how to optimize inventory balances.

Causes of unsuccessful demand forecasting in retailing

Out-of-stock or overflow shelves indicate an unsuccessful purchasing strategy. Perhaps the manager ordered goods at random, without accurate calculations. But an experienced business knows that deliveries can be delayed, customer tastes can change dramatically, and political events can affect sales. Accurate demand forecasting helps minimize the risks of shortages and surpluses.

1. Incorrect evaluation of marketing activities.
   A manager may not account for the impact of future marketing campaigns, resulting in shortages of promotional or advertised goods. Inadequate communication between marketing and purchasing departments may lead to a mismatch between demand forecasts and actual sales. With a single source of truth, misunderstandings can be avoided and each department will have access to the data. 2- Lack of historical data analysis. Analytics services collect and analyze data on sales, seasonality, promotions, price changes, and other factors that affect demand. Analyzing historical data helps to identify demand trends and avoid previous mistakes. This analysis is especially important during peak periods when demand changes every year, especially before New Year's holidays and during seasonal changes.
    
2. Ignoring external factors.
   Demand is influenced both by historical trends and the current market situation. You need to consider political and natural factors that influence consumer behavior. Perhaps an abnormal heat wave? Or a pandemic and quarantine? All are just examples of reasons that influence consumers' purchasing power and choices.
    
3. Human Factor.
   Purchasers may make decisions based on personal experience rather than real data. In such a case, it is very easy to fail to take into account holidays or upcoming promotions, resulting in severe shortages. The possibility of data entry error and over-reliance on historical data from the previous month, without taking into account seasonal market changes, must also be considered.
    
4. Local variation in demand.
    There are significant differences in demand for goods by region and location. One location may have a product lying around while another may run out of stock too quickly. Use local sales data and optimize inventory according to the target audience of the location.

Mistakes in demand forecasting can be very costly to a business. Implementing advanced analytics solutions can help you mitigate risks, optimize inventory, and stay one step ahead of the competition. Is your company ready for effective demand management?

Tools for demand forecasting in retail

1. Store-by-store reporting.
   This reporting is invaluable in forming a sales strategy for a chain of stores. A manager can identify patterns and nuances that cannot be observed when analyzing aggregated data. Each store serves a unique customer base with different tastes and needs. Individual store reports can reveal which products are in high demand in a particular region or neighborhood. For example, a bedroom community may have a higher demand for children's products, while a business center may have a higher demand for prepared foods and coffee. Using such a report, the analysis of store indicators (turnover, profit, number of checks and sales, average check and others) for different interval (hour-day-week-month-year) is performed. It is also possible to visualize your data with line or bar charts.
    
2. Combination of ABC and XYZ analysis.
   ABC and XYZ analysis are basic analytical tools that allow you to not only categorize products by importance and profitability, but also to assess the stability of demand. This combination allows strategic decisions to be built for the long term with the goal of increasing store profits in mind.
    

3. Statistics of problematic products.
   This information can be found in the goods report. This block shows information on all current problems among products, statistics of their occurrence and solutions. Which product and which store has become problematic is the necessary data to start acting. The advantage of analytical store data in one service is that you can find the true cause of the decline in sales of specific SKUs. The following actions should help bring back past product positions: new planogramming; additional demand stimulation; product replacement.
    

4. Quadrant Analysis is a tool for analyzing demand during seasonal peaks, holidays, and promotions. This report will allow you to trace changes in what factors caused the decline or growth of demand, as well as show problematic or promising products.Important clarification: the truthfulness of the information depends on the choice of metrics for the axes. Price changes are an additional way to react to product demand, especially if competitors have offered something new. The effectiveness of new pricing depends on the elasticity of demand for a given product, brand positioning, and overall market conditions. Quadrant analysis helps to identify potential problems in demand forecasting, make assortment decisions, and better understand the impact of factors.

Effective demand forecasting is part of a strategy aimed at increasing sales, avoiding shortages and surpluses, and planning a marketing campaign. To improve accuracy, it is advisable to use a combination of different forecasting methods and analyze the historical data already available. One should take into account the local characteristics of each store to improve the accuracy of purchases.

Successful demand forecasting is not a one-time task, but an ongoing process that requires attention, analysis and adaptation to changing market conditions. Investments in quality forecasting are strategically important to ensure competitiveness and sustainable development of retail business.