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Revolutionizing Supply Chain Management with IoT: A Case Study
Technology Category
- Application Infrastructure & Middleware - Data Visualization
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Transportation
Applicable Functions
- Logistics & Transportation
Use Cases
- Demand Planning & Forecasting
- Supply Chain Visibility
The Challenge
The company, a global leader in engineered joining technologies, was facing significant challenges in its supply chain management. With over 10,000 customers in approximately 100 countries, the company was grappling with frequent capacity constraints and core planning problems. The lack of forecast visibility was a major issue, with the forecast inaccuracy being high and lagging a few months behind as a standard. This led to a strong need for demand signal improvement to ensure correct capacity adjustments. Additionally, the company was experiencing material and capacity constraints due to a lack of visibility into the capacity load for the 3-5 month horizon. The company was also unable to conduct real-time scenario planning and could not evaluate the financial impact of scenarios. Furthermore, they lacked the ability to evaluate the supply chain supportability of the different scenarios.
About The Customer
The customer is a global market leader in the three engineered joining technologies product categories: clamp, connect, and fluid. With a vast customer base of over 10,000 customers spread across approximately 100 countries, the company has a significant global presence. The company's operations are complex and extensive, requiring robust and efficient supply chain management. However, the company was facing challenges in managing its supply chain due to forecast inaccuracies, capacity constraints, and the inability to perform scenario planning. These challenges were impacting the company's ability to meet customer demands effectively and efficiently.
The Solution
The company adopted o9's platform to address these challenges. The platform enabled the company to leverage a well-established consensus-driven forecasting process, with an increased capability of tracking forecast deviations, thereby increasing forecast accuracy and timeliness. The platform also provided full visibility for the supply chain on a single integrated cloud-native platform, increasing reaction time and ensuring an integrated, more feasible, and executable plan. The company could now conduct scenario planning and evaluate the full P&L impact, including real-time supply chain supportability, thanks to o9’s differentiated platform supported by the Enterprise Knowledge Graph. The o9 Enterprise Knowledge Graph was used to build market, supply, and demand knowledge models, to run all key planning processes for all product lines and customers, across all time horizons in a single integrated platform. o9 leverages its open architecture to incorporate different forecasting techniques to manage different market demand patterns.
Operational Impact
Quantitative Benefit
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