Introduction
Welcome to our business-friendly guide on Demand Driven Forecasting in Empress. This powerful feature allows you to predict future sales and business trends based on past data, aiding in strategic decision-making and planning.
Introduction to Demand Driven Forecasting
Demand driven forecasting is an essential tool in business for predicting future trends, which informs strategic planning and decision-making. Empress uses the Exponential Smoothing Method, which leverages past Sales Order, Delivery Note, or Quotation data to compute forecasts.
Accessing the Forecasting Report
To access the Forecasting Report, follow these steps:
- Navigate to the Home page.
- Click on Manufacturing.
- Select Reports.
- Choose Forecasting.
Once you’re here, you’ll see a comprehensive forecast report generated by Empress.
The Exponential Smoothing Method
The Exponential Smoothing Method is a statistical technique used to predict future values based on past results. It uses an average calculation to assign exponentially decreasing weights over time. In simpler terms, it’s a formula that helps us figure out what might happen next based on what has happened before.
When forecasting, the method uses the same data to predict future periods. The first month’s forecast is calculated from the average of all total orders. From the second month onward, the system calculates the forecast for the next month by adding the difference between the last month’s Total Order and Forecast Value (multiplied by the Smoothing Constant) to the current month’s forecast value.
How to Utilize Filter Features
Empress offers several powerful filter features to customize your forecast report:
- Company: Filter your forecasts by specific companies.
- From Date and To Date: Set a specific date range for your forecasts.
- Based On Document: Choose whether to base your forecast on past sales order data, delivery notes, or quotations.
- Based On: Select whether to display forecast data based on quantity or amount.
- Based On Data (in years): Determine how many years of past data the system should consider for forecasting.
- Periodicity: Choose to view your forecast data on a Monthly, Quarterly, Half-Yearly, or Yearly basis.
- Smoothing Constant: Adjust this constant to change how sensitive your forecast data is to changes in past data.
Understanding and using these filters empowers you to generate the most relevant and useful forecasts for your business.
Conclusion
Demand Driven Forecasting in Empress provides a powerful tool for strategic planning and decision-making. By using past data to predict future trends, you can make informed decisions that drive your business forward. For further assistance with this feature, or any other aspect of Empress, please refer to our additional resources or contact our support team.