Client Background and Business Context
The customer is one of the fastest-growing home appliance brands in the U.S. The company has built innovative, quality products that are trusted in half of all U.S. homes. Their products include refrigerators, freezers, cooking products, dishwashers, washers, dryers, air conditioners, small appliances, water filtration systems, water heaters, and RV-ready products
The organization aimed to implement a modernized Demand Management and S&OP Cloud process for finished goods to meet the present and future needs. This initiative was designed to support a transformed supply chain practice built on optimized processes, organizational alignment, and measurable KPIs.
They required fully integrated demand and supply processes to achieve the right balance between supply and demand, supported by a structured planning framework on a unified Cloud-based platform that integrates seamlessly with their legacy Oracle E-Business Suite (EBS).
A key objective was to enable effective supply and demand review cycles while transitioning from their existing Demantra on-premise system to Oracle Cloud, maintaining their current business processes. It should also support recasting between customer and organization mapping.
Improving data quality management, forecasting accuracy, and cross-functional collaboration were critical priorities. Additionally, the organization sought to enhance forecasting performance for finished goods by achieving at least a 10% improvement in forecast accuracy as part of their migration to the new Oracle Demand Management Cloud platform.
Trinamix brought a proven approach to strengthening planning accuracy, helping the customer improve forecast performance, reduce bias, and automate critical forecasting steps with minimal downtime. By enabling seamless collaboration across sales and operations teams and empowering planners through hands-on enablement, Trinamix ensured faster scenario reviews and more confident, data-driven decision-making.
Client Industry
- Manufacturing
Oracle Modules Implemented
- Oracle Demand Management Cloud
- Oracle Sales & Operations Planning Cloud
Project Location
- North America
Key Solution Highlights
Implementation of the history recasting process between customer and organization mapping.
Extension of mass NPI process for many-to-one (Combination) scenarios to fulfill the business requirements.
Fully automated integration with multiple target systems with different consensus forecasts.
Ability to view S&OP plans & scenarios at various levels of aggregation of products, customer hierarchies, and manufacturing locations. Production plan calculation based on fixed line rate irrespective of unconstrained forecast to utilize the resources.
Business-specific logic applied to sourced and in-house manufactured finished goods.
Ability to view fields for S&OP and scenarios including unconstrained forecast, lead time constraints, purchase orders, planned purchase/production plan, internal transfer recommendations, safety stock, and beginning/ending inventory based on plans.
Visibility of the constrained forecast and production plan in demand plan to review parallel to live forecast and override at item level as and when needed
Implementation of LMFOP lag processes for weekly/monthly archives and copy data between DM and S&OP plan
Projection estimates of Built-in inventory value ($) by week.
Enabled planners to master and apply advanced configurations independently through in-depth training.
Key Benefits
Improvement in forecast accuracy by 18% (28% to 46%) & bias by 22% (-25% to 3%), based on historical data by mapping multiple analysis sets & segmentation for different forecasting profiles.
Incorporation of short-horizon causal factors to improve short-term planning.
Strengthened cross-functional collaboration between sales and operations teams, ensuring updates are synchronized across ASCP and IO.
Automation of constrained forecast calculation. Mass data extraction in a minimal timeframe.
Aggregation of plan configuration at customer dimension to reduce the plan size.
Sustained improvement in forecast accuracy using segmentation based on sales patterns.
