So many people get this wrong.

I truly believe it’s the biggest problem facing the industry right now because even if you are lucky to get initial funding you still need to prove the value of DQ continuously for it to be sustainable.

For example, people simply forget that the bigger cost of DQ is personnel.

Imagine a company buys a DQ product for say £50K with a £5K per annum maintenance charge.

Sure they can write that off as a one-off with minimal recurring fees but what about your staff?

You will need a DQ manager or analyst to lead the drive, other supporting staff, training services, probably additional consulting and before you know it your personnel costs are up there with the DQ product costs but people cost you every single day.

Quite often companies will take staff from their existing projects or departments so the impact of DQ is actually very personal to the business section who lose these key resources so if they fail to make a monetary impact the senior sponsors will no doubt be reminded of it.

Another problem is that companies need to get out of the single project mentality and think about what initiatives they can tie DQ into for 6 months, 1 year, 2 year, 3 years+. A one-off business case can be a really tough sell, people buy washing machines because they will save the launderette costs for a lot longer than 6 months!

In terms of your Tom Redman comments, can’t agree more. I’ve reviewed Data Driven and interviewed Tom on Data Quality Pro recently and I found his ideas really refreshing, particularly the chapters regarding monetizing your data to external markets.

Companies sit on a mine of data “gold” but lack the skills to tap this resource, his book is a great tool for discovering these techniques and is written in an accessible style regardless of your DQ knowledge.

You can check out the review, interview and even win a copy in our prize draw for the book here: http://www.dataqualitypro.com/tom-redman-interview

Particularly agree with your point about continuing to measure value. In my experience one of the key success factors in data quality is the creation of a data council – a group of senior stakeholders with sufficient authority to approve data quality programmes and ensure they happen, and the power to stop them too. In fact the most successful organisations make it a rule of thumb to can at least one faltering data quality activity for each new initiative that they give the green light. This survival of the fittest approach ensures finite resources don’t get overloaded while at the same time delivering steady incremental improvement in DQ

Oh and thanks for drawing our attention to the new Redman book, I am ordering my copy today!

Sue

Allen Taylor