• You want to accurately forecast customer demand for different classes of customers.
• You want to avoid overstock situations, which tie up capital unnecessarily.
• You want to avoid shortages, which can disrupt production schedules.
• You want to take seasonal and regional effects into account.
• You want to support uninterrupted operations and customer satisfaction.
• You need to balance stock availability with minimal holding costs and service levels.
• You need efficient stock replenishment processes with accurate safety stocks and reorder points to suppress lead time fluctuations.
• You need flexibility to adjust stock levels and loading quickly in response to changes in customer demand.
• You need real-time insights and analytics for continuous improvement.

• Precise driver analysis

  You understand the complex relations between stock levels, service levels, and purchasing conditions.

  We take the complex relations between customer groups, regions, seasonal effects and marketing into account.

• Precise recommendations

  You get precise results for the customer demand on a daily basis.

  You understand the root causes for high stock values and how to avoid them.

• Risk analysis

  You get precise values for safety stocks, safety times, reorder points and other steering parameters to avoid risks due to in- or outbound fluctuations.

• Quick wins

  You get reliable results for optimizations that can be realized quickly, including a precise estimate for savings.

With Xeniath, Analytics Translator offers Analytics as a Service within an integrated service and software approach. The cornerstone are detailed stock and material movements data including purchasing and sales out of your ERP system. Using modern AI techniques and advanced robust statistics, we deliver reliable results within short time.

• You can start right away. No software installation.
• You don’t have to wait anymore for virtually endless IT projects.
• You get reliable results. No dependency on data cleansing, aggregation etc. due to the use of robust techniques.
• Simple to use for you. No need for special data science skills on your side