Data Quality Framework

A Process-Driven Approach to Data Quality

Data Quality is often down-prioritized in many companies. However, the good quality of data is fundamental for having right overview of the enterprise situation and proper management of business processes.

What drives the wish or need for data quality

The benefits of good data quality vs the risk of poor data quality. Business can make the right data driven decisions, if the data they use is correct. Without sufficient data quality, data is practically useless and sometimes even dangerous.

Poor data quality is a pain point throughout the whole value chain, causing...

• … Additional costs due to rework
• … Delays in production, due to unauthorized changes or simple mistakes in data
• … Customer dissatisfaction due to wrong prices and volumes
• … Customer tickered fines due to data misalignment
• … missing product launch and in some cases
• … damage to brand and image.
• …wrong business decisions
• … and you can add further lost opportunities and risks….

Data Quality as a process

To maintain high quality of the data, we can guide you in setting up a right loop process in master data management.

Our methodology allows to identify weak points in MD and set up relevant rules or adjust processes to protect the quality. Additionally, we support in creation of right measurement that will be helpful in monitoring whether the implemented solutions are bringing expected improvements.

MDM Maturity Model

Determination of current state and To-Be states

Adaptive Group Experts will help you find out what is the maturity level of your MDM organization and together we will be able to determine your end goal and how to get there – build your MASTER DATA STRATEGY.