Prognosis

What is a forecast simply explained?

One prognosis is a prediction of what could happen in the future. It is based on the analysis of past and present data. Using mathematical models or expert knowledge, attempts are made to predict future events or developments. For example, a company could have a prognosis Create to estimate how many products it will sell in the next year.

Why are forecasts important?

forecasts are essential for making well-founded decisions in a wide range of areas. They enable companies to predict future developments and trends, which is particularly important for planning resources, finances and strategies. forecasts help to minimize risks, identify opportunities and prepare for changes in the market or environment. As a result, companies can increase their competitiveness and operate successfully in the long term.

What forecasting models are there?

There is a wide range of forecasting models. These include the following, which can be divided into three main model groups:

1) Time series models:

• Arithmetic mean: Calculate the average of past data.
• Exponential smoothing: Weighting current data more than older data.
• Arima (Auto-Regressive Integrated Moving Average): More complex model that takes trends and seasonalities into account.

2) Causal models:

• Regression analysis: Investigating the relationship between independent and dependent variables.
• Econometric models: Using multiple independent variables to explain economic phenomena.

3) Qualitative models:

• Delphi method: Interviewing experts to reach consensus.
• Market research: Surveys and interviews to collect opinions and expectations.

Why do forecasts make sense?

forecasts and planning are inextricably linked and together offer numerous advantages:

• Risk management: By predicting future developments, companies can identify risks at an early stage and take appropriate measures.
• Resource allocation: Companies can achieve resource efficiency by knowing when and where the respective resources are needed.
• Strategic planning: Die forecasts support long-term strategic planning and help define and achieve corporate goals.
• Cost control: Through precise planning, companies can reduce costs and increase profitability.
• Competitive advantage: Companies that make well-informed decisions are better able to compete.

How does Excel generate forecasts?

Excel provides various tools to forecasts to create:

• Trend lines in charts: Insert a trend line into a chart to show the trend in the data. This can be linear, exponential, logarithmic, polynomial, or a moving average line.
• Forecast function: Use the FORECAST () or FORECAST () function to calculate a future value based on existing data series. The function requires known x and y values as well as the new x value for which the forecast is to be made.
• Data analysis tool package: Activate the analysis tool package and use the included features, such as regression analysis, to provide detailed forecasts to create.
• Forecast sheet: In newer versions of Excel (from Excel 2016), there is the forecast sheet tool, which allows users to create a complete prognosis be able to create for their data. This tool automatically generates charts and tables that represent the predicted values and confidence intervals.

Influence of artificial intelligence (AI) and technology:

Modern technologies and AI are playing an increasingly important role in making forecasts:

• Data analysis: AI can analyze large amounts of historical and current data to produce more accurate and detailed forecasts to create.
• Machine learning: Machine learning algorithms can recognize patterns in the data and continuously improve predictive models.
• automation: Technologies automate the forecasting process, saving time and resources.
• Personalized recommendations: In the food industry, AI-supported forecasts help create personalized product recommendations for customers based on their buying behavior and preferences.

Forecasts in the food industry:

In the food industry, forecasts particularly important to make production and sales efficient. Here are a few specific applications:

• Demand forecast: Companies are forecasting demand for various foods to avoid overstocks and shortages.
• Inventory management: Die forecasts help to optimize inventories and minimize the perishability of food, so that food waste is also prevented.
• Seasonal planning: Predictions help you plan seasonal products and special promotions, such as holiday offers.
• Pricing: Market forecasts can be used to develop pricing strategies and anticipate commodity price fluctuations.

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