Evolution Of Data Quality Solutions = Opportunity For Business

June 4th, 2012 by Stan Duda

Nearly every organization, including midsize businesses, is challenged with issues related to data quality, inconsistent terminology of business information and the availability of trusted information.
Organizations of all sizes are recognizing the importance of data quality and the cost of mistrusted data.  Numerous studies have been conducted to determine the cost of bad data, all confirming the importance of a solid data governance strategy that ensures business managers have access to trusted information.
A study by Indianapolis-based LeadJen found that companies who don’t invest in cleansed data prior to an outbound lead generation campaign waste approximately $20,000 per inside sales rep annually.
An IBM study revealed that 64% of CIOs are unsure that management is using the right information to run their business and 47% of users don’t have confidence in their information.  Information Quality expert, Larry P. English, estimates that poor information quality costs organizations 20%-35% of operating revenue wasted in recovery from process failure and information scrap and rework.
Studies like these confirm what we already know – bad information exists and is costly.  The relevant questions, however, are; how bad is your data, how costly is this bad data to your organization, and how can you effectively address the problem?  Also, what opportunities is my organization missing as a result of information that can’t be trusted?
Answering these questions may be easier than you think, and fortunately significant improvements in technology, functionality, and pricing have made any data quality problems much easier to solve.  Leading Information Management vendors, including IBM, Informatica, and Talend, have recently introduced new advancements in their data quality portfolios that are more affordable and feature easy-to-use, browser-based functionality.  Leveraging best-of-breed technology to build an automated, reliable approach to data quality is now a realistic alternative to manual attempts that are temporary, inconsistent, resource-dependent, and, in the long-run, costly.
If your organization’s information can’t be fully trusted, or if you don’t know the extent of your organization’s data quality problems, something to strongly consider is a Data Quality Assessment, or DQA.  A DQA performed by an experienced, reputable firm will provide your organization with a complete understanding of the quality, content, and structure of your data.  More importantly, a solid DQA will provide a custom Data Quality Roadmap with specific recommendations for you and your team.
Accurate, consistent, and trusted information is critical to the success of your organization.  Manual approaches to fixing data quality issues are temporary and unreliable.  Applying reliable, automated data quality technology and processes to your data quality strategy are more effective and affordable than ever before.  Can you afford not to take advantage of these advancements?
Previous Post
Next Post