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Demand Forecasting

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Demand Forecasting

Empower your demand planning process with enhanced Translytics AI/ML based forecasting Engine

The model offers a fully functional demand forecasting algorithm with 11 advanced techniques, including automated history cleansing, AI-based forecasting, algorithm selection, ensembling, and feature selection
Challenges
Addressing the Challenges of satisfying customers, Market Fluctuations, New Product Introductions, and Demand Prediction Uncertainties.
Benefits
Enhanced production planning, streamlined supply chain operations, successful new product launches, risk mitigation, optimized pricing strategies, improved Cash to Cash Cycle, lesser stockout situations, and improved profit margins .

Processing Steps

Following a systematic approach tailored to Your Business Nature, our Advanced System analyzes Multiple Techniques to Identify the Optimal Method for Achieving the Best Forecasting Accuracy, Outperforming Current Standard Levels
  • Step 01
  • Step 02
  • Step 03
  • Step 04

Step 01

Loading the historical demand data, performing EDA to identify trends; and cleaning data by handling missing values/inconsistencies

Step 02

After removal of outliers, data is split into Train and Test data, and calculation of trend component for identifying underlying growth and demand

Step 03

Train ML model using training data and use it to make predictions for each SKU in test dataset using optimal evaluation metrics

Step 04

Compare predicted demand with actual demand to access performance and use refined model to generate demand forecasts for future time periods

Results

The model can be applied to Sales data to make predictions and estimate future demand in order to monitor the forecast accuracy regularly and refine the model as needed