Flawless product reliability, prompt support and exceptional customer satisfaction. These are the cornerstones of the company’s success. As a business that strives to satisfy every type of logistic need, Unicar-Yale offers its customers a comprehensive range of consultancy, sales and after-sales solutions.
Following the successful implementation of Slim4, Unicar-yale has increased the level of service. Furthermore, the business has improved the fulfilment rate across its spare parts operation while simultaneously rationalising inventory levels throughout the assortment.
In an environment where speed and availability are essential, Unicar-Yale acquires new customers as well as retains current customers through building lasting relationships. For this reason, Unicar-Yale decided to implement Slimstock’s Slim4 solution to optimise its approach to demand forecasting & replenishment.
After an initial phase of process analysis, Slimstock moved on to configure the interfaces between the ERP and Slim4. During the project, Unicar-Yale’s only had to invest a limited number of working days to prepare the required historic sales, stock and product data files. Within just three months, the solution was up and running. Thanks to the comprehensive training programme, all users were ready to take advantage of Slim4 immediately.
The focus of the project was to improve forecast accuracy through the analysis of demand of both the forklift components (frames, uprights, batteries, etc.). Furthermore, the business needed to optimise inventory levels of spare parts across its 4 regional warehouses.
In addition to achieving these goals, the inventory purchasing process was automated reducing the workload of the planning team. As a result, they could dedicate more time to validate purchase orders with Yale factories and third-party suppliers.
Given the complexity that comes with managing a spare parts assortment of over 5000 SKUs and more than 12,000 purchase orders and sales orders every year, it is vital to have the right tools in place.
In addition to increasing forecast accuracy to 95% and reducing the workload of the ordering process by 50%, the main benefits of the project include; a drastic reduction in urgent replenishment orders, increased level of customer service and improved sales turnover. Furthermore, by utilising Slim4’s intelligent algorithms, Unicar-Yale optimised safety stock to reduce the inventory value by 20%.