The Data Quality Maturity Model (Infographic)

Beth Adams's picture
 By | februari 08, 2018
in Omni-Gen, data maturity, Data Quality, data quality challenge, Data Cleansing, Data Governance, Data Integrity, Data Quality
februari 08, 2018

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:

  1. Sales executives trying to contact prospects using wrong phone numbers and e-mail addresses, resulting in lost business and revenue
  2. Customer service staff has similar incorrect customer information regarding purchases, returns, and service calls, and thus provides less-than-stellar service
  3. Physicians treating a patient without a full history of treatments, which increases their likelihood of misdiagnoses
  4. 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?

Tweet This: How can your org improve the state of its #data? Check out the #dataquality maturity model in this @infobldrs blog post from @badamsnj to find out!

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):

Can you see where you lie? Using this model in order to check where you are gives you a good indication of where you need to start ramping up.

Luckily, my company has a solution for wherever you want to start your new initiative. If you don’t know where you are in the process, try our Data Quality Challenge. It will give you lots of insight into where you are on the DQMM.

Try it today and see the benefits pile up.