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Revamping Upholstered Furniture Company's S&OP with IoT
Technology Category
- Functional Applications - Inventory Management Systems
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Transportation
Applicable Functions
- Procurement
- Warehouse & Inventory Management
Use Cases
- Demand Planning & Forecasting
- Inventory Management
Services
- System Integration
The Challenge
The company, a major player in the upholstered furniture industry with a sales volume of $1.7bn, primarily in North America, was grappling with the challenge of integrating its S&OP activities. These activities included forecasting, capacity planning, inventory and replenishment planning, and procurement functions. The company was using multiple tools, primarily Excel, for creating their forecast, leading to inaccurate demand forecasts and a lack of demand visibility and collaboration. Furthermore, the company's style level forecasting was hampered by complex processes and lack of data visibility due to the use of legacy systems. This limited them to top-down forecasting. Another challenge was the inclusion of the Distribution Centers' (DCs) capacity to ensure optimized inventory levels for Build-to-Stock.
About The Customer
The customer is a leading manufacturer, marketer, importer, exporter, distributor, and seller of upholstered furniture products and accessories. The company has a significant presence in international markets, with the majority of its $1.7bn sales coming from North America. The company was seeking to implement new processes and software to ensure complete integration between its S&OP activities, including forecasting, capacity planning, inventory and replenishment planning, and procurement functions. The company's goal was to improve forecast accuracy, reduce working capital with optimally managed inventory, and enable data-driven agile decision-making.
The Solution
The company partnered with o9 to improve forecast accuracy, reduce working capital with optimally managed inventory, and enable data-driven agile decision-making. With o9, all demand forecasts were executed in a unique system that provided collaborative options, enabling the establishment of accurate demand forecasts. The company could now predict product demand in the market and use bottom-up forecasting. The DC Capacity was modeled into the platform, allowing the company's teams to include the capacity as a constraint in the demand forecast and replenishment calculations. Key functionalities implemented included Demand Planning, Supply Planning, S&OP, Supplier Collaboration, Available-to-Promise, and Financial Planning (AOP) process area. This helped replace many manual and disparate spreadsheets. The systems replaced were Excel & Demand Solutions (Logility product), and the ERP was JDA.
Operational Impact
Quantitative Benefit
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