AI 驱动的销售助理彻底改变了 CAKE 的客户参与度

The hospital supply chain team is responsible for ensuring that the right medical supplies are readily available to clinicians when and where needed, and to do so in the most efficient manner possible. However, many of the systems and processes in use at the cancer center for supply chain management were not best suited to support these goals. Barcoding technology, a commonly used method for inventory management of medical supplies, is labor intensive, time consuming, does not provide real-time visibility into inventory levels and can be prone to error. Consequently, the lack of accurate and real-time visibility into inventory levels across multiple supply rooms in multiple hospital facilities creates additional inefficiency in the system causing over-ordering, hoarding, and wasted supplies. Other sources of waste and cost were also identified as candidates for improvement. Existing systems and processes did not provide adequate security for high-cost inventory within the hospital, which was another driver of cost. A lack of visibility into expiration dates for supplies resulted in supplies being wasted due to past expiry dates. Storage of supplies was also a key consideration given the location of the cancer center’s facilities in a dense urban setting, where space is always at a premium. In order to address the challenges outlined above, the hospital sought a solution that would provide real-time inventory information with high levels of accuracy, reduce the level of manual effort required and enable data driven decision making to ensure that the right supplies were readily available to clinicians in the right location at the right time.

SML Intelligent Inventory's customers, some retail and supply chain businesses wanted a cost-efficient way to improve their inventory management so that they can increase their revenue.

Top ABB customers asked for advanced services and faster parts replacement to keep their plants up and running, where production downtime can cost up to $2 million per minute.

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Ace tracked which products retailers ordered, when they were ordered and shipped. However, the company could not track or forecast actual sales. Data used for reporting was up to a one-week old, owing to performance and data cleansing issues. Requirement to integrate wholesale and inventory data with POS data to help drive key business decisions, improve category management, lower inventory costs and optimize pricing. Reliance on custom coding to integrate POS data was excessively resource intensive and led to major performance constraints.

The client was running a legacy material flow tracking system and wanted to replace the system with a more effective one as the system was increasingly expensive to maintain and support and also was not extendable. The client's IT landscape was filled with modern applications and it was difficult to interface the material flow tracking system with modern applications.