Sales forecast

What is a sales forecast?

A sales forecast is an estimate of a company's future sales over a certain period of time. It is used to plan and manage expected revenue and is therefore also a basis for sales forecasting. Sales forecasts are also an essential component in the financial planning, budgeting and strategic decision-making of companies. They support the assessment of the company's financial performance and growth potential.

How do you calculate a sales forecast?

There are various ways to calculate a sales forecast, depending on the industry, the available data and the desired accuracy. There are various methods of calculation:

1. Historical data analysis: Analysis of historical sales data to identify trends and patterns that indicate future sales.
2. Market research: competitive analysis, investigation of market trends and customer behavior.
3. Statistical methods: Application of various statistical models.
4. Expert opinions: Consideration of assessments and experiences of experts in the respective industry.
5. Technological approaches: Use of artificial intelligence (AI) and machine learning to recognize complex data patterns and create more precise forecasts.

Example of calculating a simple sales forecast

1. Collect historical data: Collection of sales figures from the last 12 months.
2. Calculate average: Calculate the average monthly turnover.
3. Consider trends: Analyze seasonal trends or other patterns evident in the data.
4. Create forecast: Using the calculated average and recognized trends to create a sales forecast for the coming months.

How do sales forecasts behave in different sectors?

1. Food retail (LEH)
   • Seasonal fluctuations: Seasonal trends, including public holidays and the harvest season, must be taken into account in the forecasts.
   • Customer preferences: Eating habits and consumer trends can change and should therefore not be neglected in the course of optimal product availability.
   • Use of AI: AI can help to create accurate forecasts based on sales data, weather information and social trends.
2. Bakeries:
   • Time of day-dependent demand: Bakeries often have peak times, such as mornings or afternoons, which must be taken into account when forecasting and ordering according to demand. Demand can therefore change during the day depending on the time of day.
   • Differences in the day of the week: Demand and therefore sales can also change depending on the day of the week. At weekends in particular, sales can differ from those during the week.
   • Product diversity: Bakeries have a wide range of different products with different sales cycles, which have an impact on the sales forecast .
3. Gastronomy:
   • Reservations and walk-in customers: The sales forecast is mainly influenced by the fact that both pre-reserved seats and spontaneous guests are possible and work in combination.
   • Events and functions: Local events and public holidays can have a significant impact on sales and, depending on the event or occasion, can significantly increase or decrease revenue. This is particularly related to purchasing optimization.
   • AI and data analysis: Tools for analyzing customer feedback and ordering behavior, but also for analyzing external factors such as the weather, can be used to refine sales forecasts . Possible tools are AI and those for data analysis in general.

How is artificial intelligence (AI) used in sales forecasting?

Artificial intelligence can significantly increase the accuracy and efficiency of sales forecasts. With the help of machine learning, algorithms can analyze large amounts of sales data and identify patterns that are difficult for humans to recognize. AI-powered forecasting can take into account seasonal fluctuations, market trends and even external factors such as weather conditions and social media to enable more accurate predictions.

What are the advantages of precise sales forecasts?

A precise sales forecast is a decisive factor for companies, regardless of their size and sector. It enables sound planning and helps to minimize financial risks. Accurate sales forecasting boosts a company's profitability because, among other things, it reduces inventory costs by allowing the optimum order quantity to be determined. A further increase in the accuracy and reliability of forecasts can be made possible through the use of modern technologies such as AI, giving companies a competitive advantage.