o9 Solutions, Inc. > Case Studies > Automating Forecasting and Capacity Checks for a Global Automotive Supplier

Automating Forecasting and Capacity Checks for a Global Automotive Supplier

Technology Category

Analytics & Modeling - Machine Learning
Platform as a Service (PaaS) - Application Development Platforms

Applicable Industries

Automotive
Transportation

Applicable Functions

Discrete Manufacturing
Sales & Marketing

Use Cases

Additive Manufacturing
Demand Planning & Forecasting

About The Customer

The customer is a leading global supplier to the automotive and industrial sectors. It is one of the world’s largest family companies and has a global network of manufacturing, R&D, and sales facilities. The company was facing challenges in managing the quality and accuracy of OEM forecasts, leveraging external market data for demand planning, and conducting manual capacity checks. The company was heavily reliant on Excel and SAP APO for these processes, which were inefficient and lacked the necessary intelligence for effective decision-making.

The Challenge

The customer, a leading global supplier to the automotive and industrial sectors, was facing significant challenges in managing the quality and accuracy of OEM forecasts. The company was unable to leverage external market drivers to predict demand and was heavily reliant on Excel. This resulted in high variability in the quality and accuracy of forecasts. Additionally, there was a lack of demand alignment across OEM forecasts, which were stored in multiple Excel sheets. The company also had access to external market data from providers such as IHS, but was unsuccessful in leveraging this data to improve demand planning. Furthermore, capacity checks were done manually in Excel, which resulted in the lack of a layer of intelligence on top of the execution system (SAP APO).

The Solution

The company adopted the o9 platform to automate the consolidation of OEM forecasts, on one single platform, including trend analytics, enriched with bottom-up sales forecasts. The platform also enabled intelligent triangulation of OEM forecasts sent to multiple plants for the identification of mismatches. The company was able to incorporate data from external data providers (e.g. IHS) in the planning processes to streamline the calculation of take-rate forecasts for all produced parts. The o9 platform also allowed the company to run capacity checks and the full S&OP process directly on the platform. The o9 platform was used to run demand forecasts, high level S&OP, capacity checks, trend analytics and automate OEM forecasts, while leveraging o9’s machine learning forecasting models. The systems replaced by the o9 platform were SAP APO and Excel.

Operational Impact

The implementation of the o9 platform brought about significant operational improvements for the company. The automation of OEM forecasts and the incorporation of external data into planning processes streamlined operations and improved the accuracy of forecasts. The ability to run capacity checks and the full S&OP process directly on the o9 platform eliminated the need for manual checks in Excel, adding a layer of intelligence to the execution system. The platform's intuitive UI/UX boosted user adoption, further enhancing operational efficiency. The company was able to leapfrog to best-in-class planning and decision-making, thanks to the deep industry knowledge of the o9 team and the future-proof planning platform.

Quantitative Benefit

Forecast accuracy improved by more than 10 percentage points.
Improvement in planner productivity, in line with previous experiences (15–25%).
Higher automation of tasks, estimated at 30% of initial baseline.