Feasibility Study for Recognizing and Exploiting Savings Potentials

Who wants to buy a product without a little test driving beforehand? To show customers the benefits of SAF’s software solutions and how effectively they pay for themselves in advance, SAF has developed a tool specifically for this purpose: the SAF FeasibilityStudy.

Based on actual customer data this tool simulates the concrete cost savings that can potentially be saved once the SAF Engines are operational. At the same time, the analysis provides helpful insights into the quality of the customer’s current ordering processes. The result is a tailored “what if“ analysis that reveals:

Quality level of the current ordering process
Current data quality
Internal processes
Potential areas of optimization

Results of Potential Analyses

(average, in percent)

Super and hyper markets Inventory reduction Out of stocks reduction Automation level		23 80 98
Drug store chains Inventory reduction Out of stocks reduction Automation level		21 76 99
DIY Inventory reduction Out of stocks reduction Automation level		22 37 98
Food retailers Inventory reduction Out of stocks reduction Automation level		18 72 98

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The SAF Simulation, Analysis and Forecasting AG is specialized upon development and sales of standard software for automatic ordering and forecasting for retail, logistics and industry. The SAF philosophy is based upon the demand chain management approach which conceives the customer as the key driver of the value chain. The solutions of SAF make room for significant cost savings. Not only does SAF improve the accuracy of sales and inventory forecasts but also optimizes the logistical framework. This results in lower inventory levels, improved product availability and equally important, greater customer satisfaction. Finally, the SAF products help to develop key competitive advantages throughout the value-added chain.

The SAF software solutions include products for automatic ordering, forecasting systems, CPFR concepts, vendor managed inventory as well as analytic tools to optimize the logistical framework.

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