Demand Forecasting
Demand forecasting with AI
We help you to optimize the use of your company resources through precise demand forecasts
Plan your resources optimally with AI-based demand forecasts
No more reading coffee grounds and incorrect resource planning. Modern AI-based demand forecasts take the uncertainty away from you. They provide precise predictions that you can use to reliably plan your resources, such as stock levels, production, finances and personnel.
The implementation of AI-based demand forecasts is a reliable basis for decision-making. You increase your efficiency, reduce costs and increase your competitiveness.
We are a member of the
From the data to the customized product
From the data to the individual product
Would you like to establish demand forecasting with AI in your company? This is how it goes on:
Project Kick-Off
In the first workshop, we work together to gain an understanding of your use case and your business. We record your requirements and define project goals.
MVP
In the next step, we develop a minimum viable product (MVP). Through iterative processes, an AI system is created that serves as a solid foundation for future developments.
Further development
Individual extension
In this phase, we adapt to your needs. Our aim is to end up with a product that meets your wishes and requirements.
20 % less overproduction
30 % less overproduction
through improved demand forecasts
The challenge
Inaccurate predictions of energy requirements. Complex and large amounts of data. Customer and real-time data from different energy sources must be standardized. Avoid overcapacities and bottlenecks.
Solution
AI-based demand forecasting. Use of historical consumption data, weather reports, real-time sensors and economic indicators. Machine learning to recognize patterns and trends.
Result
The AI-controlled demand forecasting system improves the efficiency and reliability of the energy supply. The precise prediction of electricity demand helps to make energy consumption more sustainable and significantly reduce operating costs.
25 % less migration
through precise predictions and churn prevention
Telecommunications
- Increased churn rate leads to loss of sales
- Traditional methods are not sufficient
- High costs for new customer acquisition due to customer churn
- Need to integrate and analyze extensive and diverse customer data
Azure, Power BI
- AI-based model for predicting customer churn
- Use of decision trees and neural networks to identify migration trends
- Use and consolidation of data sources such as user behavior, customer service interactions, contract information, demographic data
The introduction of an AI-based churn prediction system effectively reduces the churn rate and significantly increases customer loyalty. Thanks to machine learning, the company is able to make predictions about potential customer churn. On this basis, it takes proactive preventative measures. This leads to higher customer satisfaction and increased customer loyalty. The use of the AI system also reduces operating costs.
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