Case Study
The client is a leading global high performance electrical products company with business operations across the globe. The company offers a comprehensive range of enclosures, electrical connections and fastening and thermal management solutions across industry-leading brands that are recognized globally for quality, reliability, and innovation.
The client’s entire demand planning process was un-structured and driven using Microsoft Excel. Implementing SAP IBP Demand Planning gave the client the opportunity to revisit and improve the to-be business process. It also helped bring demand planning into the mainstream SAP IBP toolset that can be used by global business users.
The client partnered with Infosys to focus on their thermal division and help set up and streamline their forecasting process.
Key Challenges
- Absence of a formal demand planning and S&OP process. Processes were ad hoc and based on Microsoft Excel
- Absence of a statistical toolset to generate forecast calculations based on inherent patterns in the data
- Challenges due to a vast product portfolio with significant churn and changes in buying patterns based on several independent variables
- Operational issues due to ad hoc processes for forecasting and introduction of new products
- Difficulty in aggregation and dis-aggregation of data using Microsoft Excel
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Talk To ExpertsThe Solution
Infosys followed the waterfall approach to implement SAP IBP Demand Planning for the thermal business of the client. This involved continuous engagement with the business teams using demonstrations and Microsoft Excel mock-ups. The aim was to manage user expectations and ensure coverage of all business requirements.
In scenarios where the product was not able to adequately meet a business requirement, adjustments to the business processes were recommended to minimize customizations.
Infosys used a big bang approach with a defined scope, which was preceded by a mock cutover ensuring data completeness and automation of tasks.
The SAP IBP based solution had the following key features:
- System of record for SAP IBP demand, which does forecasting using statistical methods and weather-related variables using ML models
- Demand sensing
- NPI process and product segmentation
- Direct outbound integration with SAP ECC for planned independent requirements (PIR) generation
- A solution with configuration and batch set-ups driving an industry leading forecast cadence
- Ability to aggregate, disaggregate, view, and manage data across different dimensions
- Visual setups for demand management for better data-driven decisions using analytics and dashboards
Implementation of a robust SAP IBP driven forecasting solution to provide a formal platform for managing demand
Best-fit statistical forecasting models including history cleansing and outlier correction
Time series property-based planning
Statistical forecasting using regression of weather variables using machine learning (ML) models
KPI measurement using analytics and dashboards
NPI process management and product segmentation
Defining monthly cadence set-up or working day calendar for demand planning process
Benefits
Improved planner productivity with exception-based data management, reporting, and segmentation
Better forecast accuracy due to modeling of different independent variables thereby minimizing inventory for comparable customer service
Platform design that drives a consensus demand in the organization in a transparent manner, visible to supply chain executives
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