Archive for February, 2011

Year 2011 has been somewhat different for data management field in terms of manifestos and predictions about what the future holds. At least in the field of data management (DQ/DG etc…) there have been predictions about what features will not hold. In her blog “Jills anti-predictions of 2011”, Jill Dyche identifies what will not happen in 2011 as far as data management /data governance/MDM is concerned within organizations, Dylan Jones in his blog What is or (anti) Data Quality Manifesto? suggest creating anti-manifesto as a viral (anonymous) marketing to force the awareness around perception of the data with management ranks.  This trend has been purely based on many of our collective experience when it comes to management’s lack of commitment and sponsorship (over the years)  to support, plan and execute holistic data governance strategies for supporting high quality data throughout organization for decision-making and operations.

More I think about it, more I feel that (in many instances) ignorance about the state of the data (or data quality) is by design rather than being out of ignorance or lack of understanding. Businesses often hires smart people (most of the cases) in the executive management roles because of their capabilities and the smarts they bring to the table. Many of these executives probably have MBAs and have gone through course work which highlights importance of using accurate data in decision-making. Many of these executives have worked (probably) in some capacities with data throughout their careers and have learned the importance of fact based rather than gut feel based decision-making.

Unwillingness to commit to data management strategies might be stemming from factors which have to do with how success of the executives is evaluated and rewarded.

1.       Pressure to perform on quarterly basis (managing expenses). Many public companies provide their financial results on quarterly basis; every executives focus is to maximize sales profitability in these 90 days. Every attempt is made to curb any unwarranted (in executive’s minds) expenses.

2.       Short term contracts CEO’s (and other executives) have with the board are not conducive for finding long-term solutions. Executives have to prove their worth and short period of time. (In the paper titled “CEO EMPLOYMENT CONTRACT HORIZON AND MYOPIC BEHAVIOR” by Moqui Xu, author concludes that CEO’s with short term contract invest less than their peers. CEO’s with short term contract tend to sacrifice long-term investments for short term value maximization)

3.       Attitude “If I can get “my” numbers and (correct?) data without investing more, Why spend money and efforts on it?”. Little do they know about the manual efforts involved in getting this accurate data, day in and day out to them.

So how can we make a case for investments in Data Management initiatives?

It’s human nature to work hard to avoid pain and/or negative outcome. As human beings, we will do more to avoid pain and negative outcome than to ensure positive results. Executive management will pay more attention to your proposals and business cases for data management when they are faced with situations which are somewhat negative in nature to the performance of overall business. Situations like a restatement of financial results, fines by governing bodies, de-certification or refusal by auditors to sign on compliance, introduction of new legislation around compliance and regulations(it’s no coincidence that many of highly regulated industries like insurance, health care are farther ahead when it comes to data quality/data governance initiatives implementation and adoption) are some of the examples of major negative events (I call them compelling events)within organizational operations which can be effectively used to get executives to listen to the business case for data management. Be ready with your business case, proposal all the time. And when the time is right, present this business case to executive management for their approval and sponsorship. Highlight how initiatives you are proposing will either help avoid these negative situations or help lessen the impact of those negative situations and as a bonus help with the strategic goals of the organization.

For example, recently in their blog, Utopia, Inc. highlighted how inaccurate statement of revenues to their executive rekindled the focus on the data quality/governance initiative within their organization. This is not to say that they were not committed to the data governance or data management initiatives, in fact, they had some of that already in place. This incident provided executive sponsorship and visibility to the data issues and hence commitment from executives for data governance/management initiatives.

I’m not saying that this is the only way to get executive management sponsorship to data management initiatives. There are instances, and there are organizations which will proactively adopt the data management initiatives. Many CEOs will understand strategic inflection points (Only the paranoid survive: Andy Grove) in their industry and would realize importance of effective data management in navigating through changing business conditions. This almost always results in proactively investing and adopting data management business cases.

In ideal world, if businesses adopt best practices for data management ground up, it will help businesses in leveraging data as an asset. Effective data management would help organizations potentially avoid getting into unfavorable situation in first place. Sometimes, though to make a business case one has to choose appropriate timing even though it seems counter intuitive to do so. Sometimes it has to be that way…..


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This is a eighth blog entry in a blog series highlighting the criticality and the importance of executive sponsorship for data governance initiatives. So far I have explored step-by-step approach of how one can go about developing the case for data governance by connecting initiatives under data governance umbrella with business strategy and outcomes.

In last post we explored how assessing data quality, reliability and timeliness will help towards establishing a baseline around data issues within the organization.

As the data governance teams are exploring data, policies and procedures around handling data, it is important to catalog key findings in a way such that key stakeholders can clearly understand the impact and the issues on hand. Clearly documenting data quality issues, policy issues and any other systemic issues associated with the specific business process (which has the highest influence on strategy outcomes) is very important for ultimately gaining executive sponsorship for initiatives which strive to fix those issues.

Attached is a sample example which demonstrates how findings could be summarized. If you’re using repositories or tools to capture some of this metadata I would highly recommend that you take the effort to summarize those findings in easy to understand fashion. This will help in articulating how data management issues are impacting overall business and in specific some of the key goals which organization is trying to manage.

Key here is clarity, simplicity and relevance. Providing some of the data/metrics around how current are the data management issues will help establishes credibility of your findings (in many instances these metrics may not be readily available, work with your counterparts from the business side and capture these metrics as a part of your discovery process). Always remember that your findings are only as good as the understanding of those findings and its impact by stakeholders in your organization. That is why it is important to make sure that you are presenting the findings in a simple yet impactful form.

You are three fourth of the way in getting executive buy-in, you have done your homework; identified the data management related issues; and presented your findings and the impact of those findings on key performance indicators. You are yet to have a formal agreement/shake hand with stakeholders around common understanding about the impact and possible course of action. In next blog posts, I will discuss how to go about reaching this agreement, and what additional information it might take to get to that point.

In the meantime, feel free to share your presentations/ideas or thoughts on how you explained your findings to key stakeholders in support of ongoing data governance investments.

Previous Relevant Posts:

Litmus Test for Data Governance Initiatives: What do you need to do to garner executive sponsorship?

Data Governance Litmus Test: Know thy KPIs

Data Governance Litmus Test: Know goals behind KPIs

Data Governance Litmus Test: How and who is putting together metrics/KPIs for executives?

Data Governance Litmus Test: Do You Have Access to the Artifacts Used by Executives?

Data Governance Litmus Test: Systems, Processes and Data Behind the KPIs and Goals

Data Governance Litmus Test: Quality, Reliability and Timeliness of the Data

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