Inventory Management

A supply chain management organization's primary approch is to establish and maintain processes with the purpose of inventory optimization. A constantly growing complexity of supply networks requires IT-assisted solutions to determine optimal stocks – neither too high nor too low.

Objectives

A sustainable inventory management greatly impacts a company's economic success. Thus, inventories directly affect a company’s working capital and – due to needed storage capacities – logistical expenses as well. Sufficient stocks ensure complete deliveries of customer orders and contribute to proper production without down times due to material shortage. In many industry sectors, large stocks may lead to high disposal costs because of a limited utilization period. Procurement and distribution markets are driven by exchange rate fluctuations and, additionally, progressive resource scarcity and optimized discounting contribute to increasing complexity.

Potential Benefits

ORSOFT has more than 20 years of experience in the field of development and roll-out for Advanced Planning Solutions in various industry sectors. In order to achieve significant improvements, the solution requires key figure systems and suitable efficient and user-orientated planning functions. The Inventory Management is a functional component of ORSOFT Manufacturing Workbench, designed as an Add-On solution for ERP systems that can be integrated with the company’s IT very swiftly via a phased process instead of a big bang.

  • Integration of logistic model in software
  • Gaining transparency within the logistical situation
  • Analyze supply chain and fixed capital
  • Identification and evaluation of improvements
  • Implementation of most potential solutions
  • Establishing management systems

Software

ORSOFT Manufacturing Workbench is a well-proven standard solution that makes logistical data permanently available within a computer's RAM, even in complex multi-plant-scenarios. The solution provides transparency and automatically analyzes data at runtime without running batch processes. Specifically designed algorithms and evaluation methods contribute to identifying potentials in terms of stock reduction.