Data Quality Baseline

Have you Prepared your Data Quality Baseline?

Has your organization planned a data quality initiative for 2014? If so, have you prepared your 2013 data quality baseline? Data quality initiatives are great if they produce measurable results. How do you measure the results of a data quality initiative? By preparing a data quality baseline before beginning your initiative.

Once you have your data quality baseline, you will be able to demonstrate the value that your data quality initiative delivered. Baselining is a familiar approach to athletic competitors. In October 2012, H. James Wilson, a senior researcher at Babson Executive Education blogged in the Harvard Business Review (HBR) blog network about how Ironman athletic competitors use baselining to measure and improve their performance. With the right subscription you can read the post here. As one post responder remarked,

You can’t know where you’re going if you don’t know where you stand.

That is really the essence of creating a baseline.

As this year winds down, my colleague Cal Braunstein of The Robert Frances Group and I will be interviewing IBM Infogov Community members who participated in our 2013 “Poor Data Quality – Negative Business Outcomes” online survey. In conjunction with our online survey, we will find out about the challenges our survey respondents experienced with data quality and information confidence in 2013 and earlier, as we conduct these interviews. In essence, we will be asking interviewees to provide a mini-data quality baseline, and Cal and I will prepare an aggregated version.

In the post that follows, I’ve posed many of the questions we will be asking our interviewees. You might find it useful to introspect and interview your colleagues. In conjunction with taking our online survey, you will have a jump on your own mini- 2013 data quality baseline.

How does your organization measure up?

Take a few minutes to think about data quality and information confidence issues in your data quality baselineorganization. Thinking of your organization as a whole, how would you rate your firm – the best, average, or among the worst in your industry at data quality? Take note of why you have answered as you did. Now, what about your line of business? Is it better than, equal to, or worse than your whole organization? Again, take note  of why you came to your conclusion.

Your organization and the IBM Data Governance Maturity Model

data quality baselineData governance may be one of the areas your data quality initiative will address in 2014. IBM InfoGov has a data governance maturity model. The model considers aspects of maturity that range from organizational structures and data governance awareness to data architecture and data quality management. These are only a few areas that the model considers.

Without taking a deep dive into the model, what does your gut tell you about your organization’s data governance maturity? Take note of your feeling and the reasons behind it. Now, rate your organization and, if applicable, your line of business on a scale of 1-5 (5 is the most mature, and most difficult to attain.) Is your organization at the Initial stage(1)? Is your governance program defined(2)? Are your defined processes repeatable (3)? Is your governance program managed (4)? Or, has your program become optimized (5)?

Perhaps your 2014 data quality initiative will include evolving to a higher level of data governance maturity. If your organization has not assessed its present data governance strengths and weaknesses, now would be a good time to have a look.

What about your business and IT leadership?

Someone with power must to provide leadership to make data quality improvements. If an organization is to create change, an influential individual needs to take control and make it happen. Without a leader with the vision to drive data quality forward, nothing will happen. Think about your organization’s business and IT leadership. What does your data quality leadership baseline reveal?

Here are some questions we will be asking our interview subjects. Why not answer them yourself, and ask your peers for their opinions?

Business Leaders and Data Quality

Is your organization’s business leadership (non-IT) convinced that data quality is critical? Ifdata quality baseline so, why, and if not, why not? What are their views on your organization’s progress on improving data quality? Are these views ever articulated to you and your peers? Do you think a senior manager in your organization can discuss the principles of data governance and the reasons your organization takes data quality seriously?

IT Leaders and Data Quality

What about your organization’s IT leadership? Are they convinced that data quality is critical? Do you know your IT leadership’s view of your organization’s progress on improving data quality? Does your organization still believe that “IT owns our data?” If so, what does IT have to say about that belief?

Incentives for Achieving Data Quality

One well-known motivator for good behavior in business is a strong incentive program. Are there compensation incentives/disincentives for good/bad behavior with respect to data quality? If there is a defined data quality incentive plan in place with measurable goals? Do you and your peers understand it? What about your manager? Has anyone been rewarded lately for doing the right “data quality” thing? No data quality incentive program? That deserves a note in your baseline. 

Cultural Change

A true shift in behavior often requires an organizational “cultural shift.” In my experience, culture changes when new approaches are tried, and get good results. In your organization, Is the business, IT, or both working to produce a cultural shift in the organization with respect to data quality? If so, can you list the three most important cultural changes that occurred in the past year? Aspects of a cultural shift towards data quality, or its lack thereof deserves mention in your baseline.

Unstructured Data Quality

Many of us think of data as structured reference data or transactional data. However, we all know about the enormous growth of unstructured data. How does your organization define unstructured data, and what level of confidence do you have in its constituent parts? Use the familiar 1-5 scale, where 5 is “complete confidence” and 1 is quite the opposite. The many facets of unstructured data, their governance, and your level of satisfaction with them belong in your baseline too.

Data Criticality Segmentation

Does your organization segment its data by criticality (e.g. most important to have high quality vs. least data quality baselineimportant)? Read my Information Confidence Integrity Level post to learn more about the concept.  Is your organization investing in monitoring and improving data quality based on data criticality? Des a set of criticality rating principles exist? Who decides which data is most critical, and which is less so? The processes, technology, and results associated with rating data criticality, measuring its quality, and improving it belong in your data quality baseline.


 The Bottom Line

I have asked you to think about your present data quality issues and approaches, and record your observations in a data quality baseline. If you develop a baseline and would like to discuss it in confidence, I would like to speak with you. Please do contact me for a confidential interview.

Not ready for an interview? That’s OK. The real importance of your data quality baseline exercise is to ensure you are aware of the gap between your organization’s present state of data quality, and the state you would like to have at the end of 2014. Remember,

You can’t know where you’re going if you don’t know where you stand.






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