The Data Quality Maturity Model (Infographic)
You may know that improvements in data quality lead to reduced costs, increased sales, increased performance, better customer engagement, and better business decisions.
Let’s examine how, by looking at some business scenarios:
- Sales executives trying to contact prospects using wrong phone numbers and e-mail addresses, resulting in lost business and revenue
- Customer service staff has similar incorrect customer information regarding purchases, returns, and service calls, and thus provides less-than-stellar service
- Physicians treating a patient without a full history of treatments, which increases their likelihood of misdiagnoses
- Shop floor managers cannot identify underlying causes of product defects with incomplete claims data, resulting in slowdowns in production and lost business
So what does this have to do with a data maturity model? And how can that help you?
What a data quality maturity model (DQMM) does is help an organization gauge its behavior relative to the overall condition of its data. It measures all efforts – from the very tactical to the extremely strategic. You can see what I mean in the new DQMM infographic (click to enlarge):