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IoT Implementation in Tire Manufacturing: Enhancing Forecast Accuracy and Inventory Management
Technology Category
- Functional Applications - Inventory Management Systems
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Mining
Applicable Functions
- Sales & Marketing
- Warehouse & Inventory Management
Use Cases
- Demand Planning & Forecasting
- Inventory Management
The Challenge
One of the world's largest tire and rubber companies, delivering a wide range of tires to customers globally, was facing significant challenges in its operations. The company was struggling with inaccurate forecasting, which was predominantly based on lagging indicators. This lack of precision in forecasting led to a lack of visibility into supply risk and capacity prioritization. Additionally, the company was unable to effectively use drivers of demand to predict future trends. This resulted in frequent excesses and shortages in inventory, leading to potential inventory liabilities and the need for additional price promotions to clear inventory. The company's current Sales and Operations Planning (S&OP) process was inefficient and lacked visibility into supply risk and capacity prioritization based on financials.
About The Customer
The customer is one of the world's largest tire and rubber companies, delivering a wide range of tires to customers globally. Their product range includes tires for passenger cars, trucks, buses, aircraft, construction and mining vehicles, motorcycles, and more. The company was facing significant challenges in forecasting and inventory management, leading to frequent excesses and shortages in inventory and a lack of visibility into supply risk and capacity prioritization. The company's existing systems, Excel and Aspen, were not able to effectively address these challenges.
The Solution
The company partnered with o9, a leading provider of AI-powered planning solutions, to address these challenges. o9's platform enabled the company to understand the drivers of demand, such as dealer/retailer sell-out and channel inventory information, pricing/promotion impacts, and zip code level analytics. This information was used to detect gaps faster and respond to changing market conditions more effectively. The platform also helped the company optimize and reduce inventory levels by incorporating these drivers of demand into its forecasting capabilities. These insights were then used by the sales force to make assortment recommendations to dealers. Additionally, o9's platform provided the company with full visibility on a single integrated cloud-native platform, enabling it to drive S&OP more efficiently. The company also implemented the Enterprise Knowledge Graph, which integrated sales and demand planning, S&OP, and what-if scenario planning. The company replaced its existing systems, Excel and Aspen, with o9's platform.
Operational Impact
Quantitative Benefit
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