A framework for data-driven decision-making for F. Hoffmann-La Roche Ltd - with examples from Quality Assurance (QA) in the pharmaceutical sector

Abstract

Currently, the supply chain QA organization within Roche produces a lot of data in its daily business. It is many types of data, such as information about temperature deviation, planned as well as unplanned events, contract status, and many more. This data is either stored in different systems or in local files. However, the data obtained is currently not being used to develop knowledge and make decisions in the most effective way possible. This is due to the fact that there are currently no frameworks available for employees that provide a guideline of how to employ DDDM.