Development of a demand planning system

Customer Information

Our client is one of the largest steel producers in Russia and globally. This holding company's production capacity is approximately 18 million tons of steel per year. The company has a vertically integrated structure that covers all stages of production, from iron ore mining to final steel processing. With 17 production facilities in seven countries, the metallurgical holding company supplies its products to Russian and international markets, including Europe, Asia, and the Americas. Demand planning is one of the company's key management processes.

Project Tasks

The main goal of the project is to create an effective demand planning system as the basis for the entire planning chain, as well as import substitution for the Western SAP APO system.

The new KS-based system must also address additional challenges.

Increase the planning horizon to 18-24 months to improve strategic management and account for the impact of seasonal factors and maintenance work on demand and margins.
Process automation and integration of all participants The new system should unite participants in the planning process into a single environment, allowing for detailed demand analysis and improved forecast accuracy.
Increasing margins through more flexible and accurate demand and price planning will significantly improve demand volume management and alignment of plans with the company's strategic initiatives.
Creating user-friendly tools for working with data Automation, flexible settings, and the ability to model demand scenarios should increase efficiency and reduce reliance on manual labor.

System Functionality

The system automates the following company processes.

Demand Planning

  • Updating Reference Books

  • Generating and Cleaning Historical Data

  • Statistical Forecast Modeling

  • Setting Up and Applying Disaggregation and Clearing Minimum Volumes Methods

  • Demand forecasting by responsible persons

  • Coordination of forecast scenarios

Price planning

  • Updating formula pricing components

  • Updating and assigning pricing formulas

  • Calculating prices using formulas

Automatic disaggregation (based on the Customer's own methodology).

System Features and Benefits

The solution is a comprehensive product that includes:

  • User applications (viewing and adjusting data, setting parameters and running calculations, monitoring results, and supporting the reconciliation process).

  • Dedicated, manageable calculation modules (such as statistical forecasting or disaggregation).

  • An integration database designed to store data transferred to or received from related systems.

  • Built-in integration module that enables interaction with related class systems: ERP, MDG, PDM, and SNP.


Working with Big Data:

  • The solution is designed to meet the requirements for calculating speed on large volumes of data. Demand is described by a large number of analytics, the arbitrary combination of which enables volume planning.

  • Calculations are performed in the background and do not block users.

  • The application supports multi-user calculation mode. Multiple planners can simultaneously run statistical forecast generation, for example, at different levels of demand aggregation using different statistical forecasting methods.

Implementation Benefits

  • Formation of a statistical demand forecast
  • Managing forecast versions and scenarios, forming a consensus forecast
  • Flexible configuration of forecast balancing rules
  • Supporting the forecast approval and coordination process

We would like to highlight the unique atmosphere of mutual respect and trust that developed during the implementation of the demand and pricing planning project. As the vendor’s specialists, we worked in close cooperation with the functional customer, the holding’s IT specialists, and methodologists. A shared understanding of the common goals, mutual support, and openness allowed us to quickly and effectively overcome all challenges we encountered.

Inna Panchenko Director of Modelling Knowledge Space
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