Pharma Master Data Management
Developing the right pharma master data management solution for your business
Providing expert pharma master data management resource
As people move roles over time, the management of essential master data within a business can slip, with the quality of the data held deteriorating and the company no longer trusting the numbers they are running the business from.
Master data management is crucial because it provides a centralised and consistent view of the key data elements that an organisation uses to conduct business. Good master data management helps to ensure the accuracy, completeness, and consistency of this data, which in turn supports effective decision making, improves operational efficiency, enhances data quality, and reduces risk.
CSL supports pharma clients by putting in place a pharma master data management strategy. The key to success is ensuring an ongoing process is in place. By supporting you to establish a clear understanding of master data, CSL can help you to better align your processes, systems, and people to achieve your business goals.
Tackling the data quality circle
CSL provides expert resource to our pharma clients to help them move round the data quality circle, making sure they are achieving their pharma master data management strategy.
The data repair stage will typically be made up of the following processes:
- Deduplication
- Mapping unmapped items
- Repairing mis-matched items
- Categorising data – adding data dictionaries and keeping them up to date
- Removing or flagging erroneous data
- Removing or flagging outliers
- Resolving issues in the data supply chain
It is important to continue communicating with the user base to inform them of progress being made and collect feedback on their satisfaction, as new issues may have arisen. As data is used in new and different ways, quality objectives may need to change to reflect these.
CSL is able to fast-track the process of pharma master data management for pharma companies. By the end of the process, major gaps in the data are closed, with the business regaining its confidence in the data.