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Optimize Demand Forecasting with Machine Learning: 5-Wk Implementation

Columbus Global

Prijzen € 18.649

Optimize your demand forecasting in Microsoft Dynamics 365 Finance and Operations with machine learning for increased accuracy

Increase the accuracy of your demand forecasting in Microsoft Dynamics 365 Finance and Operations with Microsoft Azure services and enable higher efficiency and transparency in supply chain operations and planning.

Demand forecasting plays an important role in supply chain decision-making. It is an essential component of any supply chain strategy because it can help businesses make informed decisions about production and inventory levels, pricing, and other aspects of their operations.

Applying machine learning (ML) in demand forecasting can increase the accuracy of your demand predictions and help reduce traditional challenges in planning such as long delivery lead times, high transport costs, high inventory, and waste levels.

By utilizing Microsoft technologies, this solution enables a more accurate and reliable demand forecast for higher efficiency and transparency in supply chain operations and planning.

Ready-made solution to apply ML in demand forecasting

The ML-based demand forecasting solution developed by Columbus uses Microsoft Azure services and can be integrated with and managed within Microsoft Dynamics 365 Finance and Operations.

Benefits

  • Improved demand forecasting accuracy
  • Reduced inventory and safety stock
  • Predictive analysis that can help you save operational costs
  • Less manual time spent on generating forecasts and planning process
  • Meet or increase customer service expectations
  • Ease of use for the users
  • Managed within Microsoft Dynamics 365 Finance and Operations

    • Who is the solution for?

  • Businesses looking for a way to achieve more accurate demand forecasts
  • Companies implementing or already using Microsoft Dynamics 365 Finance and Operations
  • Companies using XLS-based forecasting or any non-scalable forecasting solution
  • Companies looking for a ready-made solution to apply ML in demand forecasting

    • Features and functions

  • Select how much historical data to use
  • Select the start date for the forecast
  • Select and view the forecast period (day, week, and month)
  • Select and view the forecast for specific categories or items
  • Modify and authorize adjusted demand forecasts by adding manual updates
  • View historical demand and forecast lines
  • Remove outliers from historical data to improve forecast accuracy

    • Our approach

    We can offer support in implementing the solution, as well as initially developing the proof of concept. The estimated price is for implementation services.

    Implementation (5 weeks):

  • Onboarding
  • Understanding your needs
  • Data understanding
  • Showcasing initial insights
  • Development
  • Testing
  • Deployment

    • The final pricing and timeframe will be based on custom terms, and the customer is responsible for procuring required Microsoft Azure services.

    Een overzicht

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