Highlights of the Case Study:
|Client||A UK-based auto component manufacturer with a global presence partnered with Quantzig to streamline its inventory operations.|
|Business Challenge||The client wanted to extract real-time supply-demand data & plan and rationalize inventory operations to reduce inventory costs.|
|Impact||Quantzig used its automotive data analytics system, combined with machine learning and AI, to help the client optimize its supply chain and manage inventory efficiently.|
Game-Changing Solutions for Automotive Manufacturers
The automotive sector has witnessed a radical consolidation after a forced transition to BS6 norms. Against the backdrop of pent-up demand and the steep hike in vehicle usage in the post-pandemic world, the automobile sector is showing vital signs of revival. However, escalating costs due to excess inventory, stock-outs, data overlap, and data silos continue to impede growth.
Spare parts rationalization brings enormous opportunities for auto component manufacturers that plan to expand their operations without investing in new facilities. Inventory rationalization would mean optimizing spare part usage and cutting down on inventory and warehouse costs. Quantzig’s cutting-edge automotive data analytics solutions enable inventory managers to estimate and plan spare parts orders, anticipate demand, and thus streamline procurement and availability by ensuring end-to-end transparency in the supply chain.
The Challenges of the Manufacturing Client
Our client, a UK-based auto component manufacturer with a global presence, sought to streamline its inventory operations. The client was struggling with the following issues while trying to identify the SKUs that were in high demand:
- Unavailability of spare parts
- Highly optimistic forecasts, which led to excess inventory
- Skewered supply chain and logistics
- Lack of integrated manufacturing due to data silos
- Overstock or stock-outs due to unpredictable demand for spare parts
The client wanted to extract real-time supply-demand data and plan its inventory operations beforehand to rationalize its spare parts stock and bring down the inventory cost. The client relied on Quantzig’s data intelligence and automotive data analytics solutions to bring such superior capabilities onboard. The availability of these capabilities would enable the client to collect accurate demand forecast data from the OEMs (original equipment manufacturers) in the UK, including their forecasted annual sales in all the segments. In addition, our client would get visibility and real-time data about the number and the model of spare parts stocked at its facilities.
Manufacturing Operations Analytics Solutions for the Automotive Sector
Quantzig’s advanced automotive data analytics system combined with AI-driven intelligence identified high-demand spare parts. The solution assigned every spare a unique code with a description to avoid discrepancies caused by duplication. By integrating these factors with the delivery turnaround and manufacturing cycles, we created a database with which we can accurately forecast and predict the requirement and nature of the spare part. We identified the SKUs in high demand and recommended stockpiling these products to cater to the high demand.
Impact Analysis of Quantzig’s Automotive Data Analytics System
Our automotive data analytics system, combined with machine learning and AI, helped our client optimize its supply chain and manage inventory efficiently, which led them to save significant inventory space. Our solution was more effective and efficient than traditional paper-based processes. Navigating the complexities of manufacturing and operations was nearly impossible using conventional and outdated solutions.
Our automotive inventory management system helped our client achieve the following benefits:
- Created a database that provides a holistic view of spare parts from all the manufacturing facilities across the globe
- 15% enhancement in forecast accuracy
- 4% reduction in inventory cost
- Enabled a 9% increase in profit margin annually
- 15% enhancement in forecast accuracy 15% 15%
- 4% reduction in inventory cost 4% 4%
- 9% increase in profit margin annually 9% 9%
Key Outcomes of Automotive Inventory Management Solutions:
Quantzig’s manufacturing operations analytics solutions enable manufacturers to ensure efficiency and prevent stockpiling and wastage. These solutions offer much more than simply providing data. They analyze the data to provide actionable insights. In addition, our analytical solutions help streamline workflows and anticipate disruptions in real-time, which ensure prompt and appropriate actions for the management of situations.
A Broad Perspective On the Role of Operations Analytics Solutions in the Manufacturing Sector:
The manufacturing industry has become more digital and interconnected than ever before. Data analytics, AI, the Internet of Things (IoT), and big data are the leading technologies that help these industries to evolve and manage massive data volumes. Various industry segments have started embracing these technologies because of their widespread reach and extensive benefits. For instance, the automotive sector uses data analytics to extract real-time information on spare parts availability and storage. When combined with other revolutionary technologies, automotive data analytics solutions accurately identify future demands and proactively respond to them. In essence, disruptive technologies such as AI and analytics raise productivity and provide widespread benefits to players in the manufacturing industry.
- The client was able to prevent the stockpiling of inventory and expand within the existing facility.
- Our solutions helped reduce lead-time and down-time by using predictive analytics solutions.
- Industrial automation solutions implemented by Quantzig helped streamline and optimize spare part demand forecasting and order management.
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