How do you approach data quality issues within your ITSM framework?

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CIO in Consumer Goods, 11 - 50 employees
First of all you must assume that ITSM is not perfect. Not even the data.
On the other way you will need efficient and well qualified resources. 
Data is always tough to correct but is doable
Director in Manufacturing, 1,001 - 5,000 employees
We always approach data quality issues from a clean the stream feeding the pond before cleaning the pond. If you are receiving bad data and try to clean the repository first you will never catch up

In terms of cleaning the stream… find the biggest polluters first. A common cause we found was poor data definitions and poor communication of those definitions. Then automate as much quality checks against those definitions as you possibly can.
Global Director - Information Technology in Services (non-Government), 201 - 500 employees
The most common data quality issues and possible approach to address these:

1. Duplicate data - due to siloed processes and not having single source of information. It can be addressed using de-duplication tools and improving the business processes.

2. Inconsistent formatting (for dates and other fields like phone numbers etc.) and incomplete information (due to in-appropriate data validation) - data governance and automated solution to enter correct and complete data.

3. Management of data stored in different languages - use international data sets.

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CTO in Software, 201 - 500 employees
Without a doubt - Technical Debt! It's a ball and chain that creates an ever increasing drag on any organization, stifles innovation, and prevents transformation.
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