Did Business and IT Executives see the causes of poor data quality the same way?
Our survey investigating the causes of poor data quality leading to negative business outcomes has been in flight for four weeks now. You can read about our first survey insights here, and the survey launch here. I’m running this survey in conjunction with the IBM InfoGov Community, the Robert Frances Group, and Chaordix. At the time of this writing, we have 141 completed surveys and another 48 in progress. The analyses presented in this post are based on that survey response set. It should be interesting to see how business (non-IT respondents) and IT executives perceived the causes of poor data quality, both in aggregate, and by functional business area.
Who is an Executive?
We requested that survey respondents indicate their title, and used the following breakdown, as shown in the graphic following.
Figure 1 – Respondent’s Titles
For the purposes of these analyses, respondents identified as “Executive Management C-Level or VP” and “Director” are Executives. The same title structure was applied to both IT and Business respondents.
On the business side, I’m scoring 19 respondents, comprising 39.6% of the total, as executives. On the IT side, I’m scoring 29 respondents, or 20.6% of the total respondents as executives.
Executives and Company Size
To ensure that I’m comparing apples to apples, I looked at the respondents reported company size. Insights into causes of poor data quality would probably differ between the CIO of a 50 person company, and one from a 5,000 person company. More business executive respondents come from larger companies than their IT counterparts, but there is reasonable symmetry for comparison.
Most individuals scored as Business Executives (~ 79%) came from organizations with more than 1000 employees, as shown following.
Figure 2 – Business Executives by Company Size
As for IT Executives responding, 50% came from organizations with more than 1000 employees.
Figure 3 – IT Executives by Company Size
Causes of Poor Data Quality across All Functional Areas
Near the end of the survey, and regardless of which functional areas respondents reported finding data quality problems, they were asked to identify the top three causes of poor data quality. Business and IT Executives agreed that the number one cause of poor data quality is Inaccurate Data. Business Executives scored Ambiguously Defined data as the next greatest cause of poor data quality, followed by Unreliable data. IT Executives split the second greatest cause of poor data quality between Disorganized data and Unreliable data, with Ambiguously Defined data as a fourth cause. So, whether our respondents are on the business side of the house or the IT side, data that is
- Inaccurate,
- Ambiguously Defined,
- Disorganized, and
- Unreliable
Is costing their organizations time and money.
Graphical survey results of this information is shown in Figure 4, following.
Figure 4 – Business (left) and IT Executive Scoring on Top Three Causes of Poor Data Quality
The takeaway here is that Business Executives are aware of poor data quality, and believe it has much the same causes as their IT Executive colleagues. If both groups see the same problems cause poor data quality, why hasn’t business or IT stepped up to the plate and insisted these problems be fixed?
Customer-related Costs of Poor Data Quality
Our survey offers respondents the opportunity to monetize problems due to poor data quality. I think it is interesting to compare the perceptions of Business and IT Executive about costs or lost revenue opportunities when customer-related data is of poor quality, regardless of the cause. See Figure 5, following. Click the graphics to see full size images.
Figure 5 – Comparison of Business and IT Executive Perceptions of Cost of Poor Customer Data
Across these three customer data cost or loss areas, Business Executives see consistently higher costs or missed profits than IT Executives.
The Bottom Line
I think we have uncovered an interesting pattern here, in which Business Executives see the cost of poor data quality as being higher than IT Executives see it. While there are too few data points to make a statistically relevant statement, that is how the trend appears to me. I would encourage many more InfoGov members to respond to our survey, to solidify these findings.
I’ve given you a glimpse of Executive level response in the Customer section of our survey. There are many more categories of respondent and many more functional areas for analysis. I urge the reader to stay tuned. If you have not joined the InfoGov community and taken the survey, please visit the site, and spend some time letting us know about your poor data quality experiences.
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