Dell products l.p. (20240202750). SYSTEMS AND METHODS FOR GENERATING REVENUE FORECASTS simplified abstract
Contents
SYSTEMS AND METHODS FOR GENERATING REVENUE FORECASTS
Organization Name
Inventor(s)
Anna V. Popova of Murphy TX (US)
Vinod Babu Palani of Leander TX (US)
SYSTEMS AND METHODS FOR GENERATING REVENUE FORECASTS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240202750 titled 'SYSTEMS AND METHODS FOR GENERATING REVENUE FORECASTS
Simplified Explanation: The patent application describes a method for generating composite prediction data by combining conventional prediction data with distributed prediction data obtained from a sales pipeline model.
- The method involves obtaining conventional prediction data based on historical revenue data.
- It also includes generating first distributed prediction data using a distributed model based on sales pipeline data.
- The composite prediction data is obtained by aggregating the conventional prediction data and the first distributed prediction data.
Key Features and Innovation:
- Combination of conventional and distributed prediction data.
- Utilization of historical revenue data and sales pipeline data.
- Aggregation of prediction data to generate composite predictions.
Potential Applications: The technology can be applied in sales forecasting, revenue prediction, and business planning.
Problems Solved: The method addresses the need for more accurate and comprehensive prediction data by combining different sources of information.
Benefits:
- Improved accuracy in prediction data.
- Enhanced decision-making for businesses.
- Better insights into revenue forecasting.
Commercial Applications: The technology can be used in various industries such as retail, e-commerce, and finance for better forecasting and planning.
Questions about the Technology: 1. How does the method improve upon traditional prediction models? 2. What are the potential limitations of using composite prediction data in business decision-making?
Frequently Updated Research: Stay updated on advancements in machine learning models for sales forecasting and revenue prediction to enhance the accuracy of composite prediction data.
Original Abstract Submitted
a method for generating composite prediction data, the method that includes obtaining, by a computing device, conventional prediction data based on historical revenue data, generating first distributed prediction data, using a first distributed model, based on first sales pipeline data, and obtaining a composite prediction data by aggregating the conventional prediction data and the first distributed prediction data.
