It is hard for me to believe that this marks the beginning of the 10th year of the Plain English about Information Quality column. As January is a month of reflection, renewal and resolutions, I reflect and celebrate the growth of information quality (IQ) as a discipline, then revisit our purpose and the journey ahead.
In the early and mid 1990s, my clients had data quality (DQ) functions whose role was to be a "data dump" where people sent defective information to be corrected. This was a very immature and reactive function, as were the early manufacturing quality functions. There was no real measurement and no real process improvement - just "scrap and rework" the defects as they were found. Now, organizations are addressing formal measurement of IQ, and the leading-edge companies find and improve defective processes to prevent defective information.
In the early days, the focus of an IQ team was the data. Now, more IQ teams focus on the information consumers and their information quality requirements and expectations.
Early IQ functions focused mostly on data content quality, and only in databases and files as opposed to process quality.
Now, more organizations are moving from data quality to information quality. They are paying attention to data definition and information model quality as the information product specifications, as well as to information presentation quality. Poor quality definition and business rule specification cause information producers to create errors and omissions. Poor quality or biased presentation of information can mislead knowledge workers and cause them to take a wrong action or make a wrong decision.
In the early days, organizations sought IQ software to solve their IQ problems.
Now, more organizations recognize that software is part of the solution, with sound IQ processes, principles and culture change required for a proactive, sustainable IQ environment.
My earliest clients usually saw DQ as an information systems initiative. "We are the keepers of the data; therefore, we shall solve the IQ problems for the business." We know now it is impossible for information systems to solve IQ problems in a vacuum.
Increasingly, the business leads IQ initiatives, or there is a strong partnership between IS and the business in IQ, with the business providing the governance.
The earliest DQ functions focused almost solely on data cleansing (corrective maintenance), which is simply information scrap and rework. There was minimal awareness of process improvement in the earliest DQ functions. The mind-set today among leading-edge organizations is focused on information process improvement or preventative maintenance, with data correction as a one-time event for a given data set.
The IQ software tools used 10 years ago addressed only data assessment or cleansing. Now, nearly all IQ software providers that have data correction capabilities also have defect prevention capabilities that can be invoked in real time by applications that create the data.
Ten years ago, there was no formal association available for IQ practitioners. Now, we have a professional association for the discipline of IQ management, the International Association for Information and Data Quality (IAIDQ). The IAIDQ is open to all, from IQ professionals and management to academia, to IQ software developers to knowledge workers and business managers who care about their information products.
We can be proud of the gains we have made, but there is much more to do.
Collectively, organizations in the U.S. alone waste from $1.3 to $1.7 trillion every year in direct costs of processes failure, recovery and information scrap and rework caused by poor quality information definition, database design, content and presentation.
There are now several laws on the books that address IQ. In the U.S., the Information Quality Act, or OMB Section 515, requires federal agencies that provide "influential information" to the public must have processes in place that assure the "quality, objectivity, utility and integrity" of the information. Sarbanes-Oxley requires the CEO and CFO to sign their organization's financial statements, attesting to their accuracy, under penalty of severe fines (up to $20 million) and imprisonment. The HIPAA (Health Insurance Portability and Accountability Act) gives individuals the right to verify and correct errors, omissions or misleading information in their healthcare records.
For all the legislation, the truth is that proactive IQ management is simply good business. When you improve processes to prevent IQ problems, you eliminate the waste of process failure and information scrap and rework, and that increases profits. It also eliminates or minimizes poor quality information that alienates customers, causing them to go elsewhere, taking their customer lifetime value.
Leading-edge IQ organizations are already achieving significant business benefits. Wherever your organization is in its journey, resolve to help it become successful by enhancing or starting a proactive IQ management function. Join the IAIDQ, and get involved in the premiere professional organization for information quality and information management professionals. Visit www.iaidq.org.
You have nothing to lose, and everything to gain.
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