Crediton Dairy - Deploying Maextro on SAP S/4 HANA - Bluestonex

Crediton Dairy - Deploying Maextro on SAP S/4 HANA

Benjamin Evans - IT Manager

” A perfect solution to manage master data processes and associated artwork documents. By adopting Maextro, we have been able to track master data requests more efficiently thereby reducing the risk of delays with product to market."

Who Are Crediton Dairy?

Crediton Dairy is a UK leading dairy business situated in the heart of Devon. With turnover of over £74m, it caters for nearly 13 thousands retail stores across UK supplying fresh, UHT and flavoured milk. Delivering products on time and reacting to ever changing customer demands in shortest possible timescales is at the heart of driving Crediton Dairy's future business growth initiatives.

Overview

As part of their recent SAP system upgrade to SAP S/4 HANA, Crediton Dairy have deployed Bluestonex's Maextro solution to manage material master data requests and associated packaging components for finished products. The solution was deployed and configured by Bluestonex Consulting in order to manage Crediton Dairy's high volume of product throughput within their centralised SAP platform. Crediton Dairy opted for the Maextro solution due to its scalability, flexibility and close integration with external document management systems' for unstructured data management.

Benefits

By re-aligning and fully integrating Crediton Dairy's finished goods business processes with SAP, Maextro provided the foundations for a lean data management platform that Crediton Dairy could utilise to drive future business growth initiatives and more importantly, improve product cycle turnaround time for customers. The Maextro solution also manages the ongoing end-to-end processes associated with Crediton's SAP master data maintenance, driven by inherent workflow and within a pre-defined data governance framework.

Results

Since deploying the Maextro solution, Crediton Dairy have administered more than 500 finished goods change requests, with an average reduction of 25% in data processing time and a 40% reduction in data error incidence rate.