LESSON - Demanding Enterprisewide Data Quality
By Len Dubois, VP, Marketing and Sales Support, Harte-Hanks Trillium Software
Organizations strive to differentiate their products from their competition while offering unique approaches for addressing customer needs. Yet for all companies—large or small, growing or downsizing—there is the same direct correlation between relevant, timely, high-quality data and the company’s ability to succeed in business.
In fact, data assets often become the differentiator for those organizations that compete successfully and increase shareholder value. There is no clearer example of this than in the global financial services market. As we have witnessed over the past year, poor data quality can severely impact an organization, damage a market sector, and deteriorate the public’s faith and trust in the economy.
The types and volumes of data amassed in today’s business systems are varied, numerous, ever-changing, and more complex than ever before. Even sophisticated companies are having difficulty keeping pace with data quality. The use of data and its corresponding informational value changes based on many factors, including the type and number of applications for which it is acquired, accuracy and completeness, and an organization’s ability to share the data across the enterprise.
At the end of the day, though, it is the responsibility of key business stakeholders to ensure the data within multiple, disparate repositories is “fit” for the business purposes for which it was intended. More and more we see business analysts stand side-by-side and collaborate with their IT partners, recommending or implementing changes to the data to ensure alignment with business processes, and always keeping in mind that these changes made to the data at one stage of its lifecycle may impact other processes downstream.
As a result, the marketplace expects a more comprehensive approach to addressing an organization’s data quality needs. An enterprise-wide approach to data quality is more closely aligned with the most strategic and operationally oriented initiatives, such as master data management, data governance, and risk management and compliance. It is these types of engagements that enable organizations to move beyond the legacy approach of solving data quality challenges to an approach that instills trust and confidence in the quality of data throughout the organization. This approach also readily derives the most business buy-in for continually improving information quality.
The evolving role of data stewards and business users has given rise to the requirement for data quality vendors to demonstrate how poor data quality manifests across organizations’ strategic operational applications, in addition to the more traditional role of providing the ever-elusive “single view.” Industry leaders must provide a distributed enterprise approach to data quality—one that delivers not only best-in-class technology but also a collaborative environment that enables business analysts to understand the impact of poor data quality through the use of ratings, rankings, and scores tied to key performance indicators (KPIs).
In addition, data governance practices have also emphasized the need and desire to demonstrate the impact of data quality to executive management levels. Data quality providers, whose offerings are tied to data in movement or low-volume departmental views, are simply not equipped to deliver information with the speed, accuracy, and ability to mitigate the risks associated with today’s complex business environment.
The need for high-quality information is only going to continue expanding across the enterprise. Today, organizations require a foundation and platform that allows them to deliver consistent, actionable, and trustworthy information, both for individual data quality projects as well as operational information needs that span the enterprise. To do so, they will need a strategic data quality solution partner that can deliver the people, process, and technology to overcome whatever enterprise data quality challenges an organization may face.
For a free white paper on this topic, click here and choose the title “The Challenges of Worldwide Data Quality.”