Demand Forecast
What is Demand Forecast?
Forecast App with Artificial Intelligence (AI) is an innovative web application designed to assist companies in making accurate demand forecasts for their products and services.By utilizing powerful classical machine learning algorithms, the tool analyzes historical sales data, considers factors like variability and seasonality, and predicts future demand with great precision.
Users can easily upload data sets from Excel and choose from a selection of estimated models like ETS, ARIMA, Prophet, Random Forest, and SVM.The tool's intelligent algorithm automatically selects the best model for each product, providing clear visualizations and interactive graphs to showcase demand predictions over time.
This aids companies in making well-informed decisions regarding production, inventory, and supply chain management, ultimately enhancing efficiency and cutting down on operating costs.With features like historical data analysis, outlier detection and imputation, model competition algorithms, and KPI forecast systems, this tool is ideal for small to mid-sized companies initiating digital transformation processes and seeking optimized resource utilization for improved business performance in today's competitive market landscape.
KEY FEATURES
- ✔️ Utilizes classical machine learning algorithms.
- ✔️ Allows uploading data sets from Excel.
- ✔️ Automatically selects the best model for each product.
- ✔️ Provides clear visualizations and interactive graphs for demand predictions.
- ✔️ Includes features like historical data analysis, outlier detection, model competition algorithms, and KPI forecast systems.
USE CASES
- Generate accurate demand forecasts for a wide range of products and services by leveraging historical sales data and optimizing classical machine learning algorithms, allowing companies to anticipate future demand trends with high precision and effectively plan production schedules and inventory levels for enhanced operational efficiency and cost savings.
- Automatically select the most suitable forecasting model based on uploaded data sets, such as ETS, ARIMA, Prophet, Random Forest, and SVM, eliminating the need for manual model selection and providing users with optimal predictions for each product, streamlining decision-making processes and ensuring reliable forecasting outcomes.
- Utilize advanced features like outlier detection, imputation, model competition algorithms, and KPI forecast systems to enhance demand forecasting accuracy, identify potential anomalies in sales patterns, and establish key performance indicators for evaluating forecast reliability and supporting data-driven strategies for business growth.
