June 19, 2018
June 19, 2018
Contributor: Susan Moore
Follow these 5 steps to effectively design a compelling data quality improvement business case.
Poor data quality destroys business value. Recent Gartner research has found that organizations believe poor data quality to be responsible for an average of $15 million per year in losses.
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This is likely to worsen as information environments become increasingly complex — a challenge faced by organizations of all sizes. Those with multiple business units and operations in several geographic regions, and with many customers, employees, suppliers and products will inevitably face more severe data quality issues.
Speaking ahead of the October Gartner Data & Analytics Summit 2018 in Frankfurt, Ted Friedman, vice president and distinguished analyst at Gartner, says, "As organizations accelerate their digital business efforts, poor data quality is a major contributor to a crisis in information trust and business value, negatively impacting financial performance."
Many organizations are struggling to successfully propose a program for sustainable data quality improvement. Effective business engagement and funding may be limited for several reasons:
"Data and analytics leaders need to understand the business priorities and challenges of their organization. Only then will they be in the right position to create compelling business cases that connect data quality improvement with key business priorities," explains Friedman.
He shares five steps to create a business case for data quality improvement.
If a business case is to be taken seriously, you must present it in the language of the business and speak to the critical and specific business priorities of key stakeholders. Understanding the business goals of your organization will not only enable you to identify senior-level support for your business case, but also help to identify and engage the right level of senior business sponsorship.
Ironically, one of the primary reasons for unsuccessful business cases for data quality improvement is because they focus on data quality. To be successful, business cases must address the key components necessary to achieve the business goals, such as financial performance, operational performance, legal and regulatory compliance, and customer experience. Linking data quality to these metrics is critical.
Once the scope of the business case has been agreed on, initial data profiling can begin. Carry out data profiling early and often. Establish a benchmark at the initial level of data quality, prior to its improvement, to help you objectively demonstrate the causal impact on business value and justify ongoing funding.
Business leaders sometimes struggle to understand that data quality improvement is not a "one and done" activity. It's very important to make it clear that unless a sustainable environment for data quality improvement is established, it will rapidly revert to its original poor state. The target state for data quality must be described in terms of how it can positively and sustainably improve critical business metrics such as financial results.
A "go" or "no-go" decision for business case proposals often comes down to the financials, and this is no different for data quality improvement. A good business case must identify the anticipated benefits of the initiative, which must be tangible, quantifiable and desirable to the stakeholders.
This article has been updated from the original, published on January 9, 2017 to reflect new events, conditions or research.
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Recommended resources for Gartner clients*:
How to Create a Business Case for Data Quality Improvement by Saul Judah and Ted Friedman.
*Note that some documents may not be available to all Gartner clients.