One-Third of Respondents Rate Their Data Quality as Poor at Best and 63 Percent Don't Know How Much Money Poor Data Quality Is Costing Their Businesses
Pitney Bowes Business Insight, the leading global provider of data quality and location intelligence solutions, and Silver Creek Systems, the pioneer and leader in automated data mastering, today announced the findings of a co-sponsored report on "The State of Data Quality Today."
The report's findings, which were based on a survey conducted by The Information Difference, a UK analyst firm focused on master data management (MDM), indicate that while the issue of business data quality has been prevalent for decades, companies still find it a major challenge to maintain accurate data and quantify the true business cost of poor data quality.
The survey respondents were mainly from North America and Europe with annual revenues greater than $1 billion USD and represented a wide spectrum of industries.
The findings of this report indicate that while more businesses are acknowledging the value of having good quality data as a corporate asset, they are still challenged by the complexity of measuring and improving data quality through enterprise-wide initiatives supported by upper management.
One-third of respondents rate their data quality as poor at best and only four percent rate it as excellent. Meanwhile, 63 percent of respondents said their organization has made no attempt to calculate the cost to the business of errors in data arising from poor data quality.
Other key findings from the study include:
Two-thirds of respondents acknowledged that they have issues with non-standard data, data that is incorrect or data with missing attributes that require correction, yet only 37 percent currently have some form of data quality initiative in place. Surprisingly, 17 percent have no plans at all to start a data quality initiative, while the remainder plan to introduce data quality over the next one to three year period.
Thirty-five percent of respondents have some combination of manual and automated processes for cleaning up their data, while only nine percent claim to have some form of a fully automated system.
Traditionally, data quality has been heavily focused on "name and address" quality improvements. Yet, 71 percent reported that maintaining good quality product data is particularly challenging and 81 percent of respondents believe that data quality is not all about "name and address."
The top two barriers to progress with data quality initiatives are cited as "Management does not see this as an imperative" and "It's very difficult to present a business case." However, 42 percent do not know what the quality of their data is since they do not measure it.
"Many companies continue to 'work around' poor data quality, although the cost of doing so can be devastating to productivity, operational expenses and customer relationships," said Navin Sharma, director of product management for Global Data Quality (GDQ) for Pitney Bowes Business Insight. "In fact, poor data quality prevents these companies from ever realizing the full ROI on far more extensive enterprise initiatives such as CRM, ERP or BI. Our goal in sponsoring this survey was to raise awareness that solving a once seemingly difficult problem is now quite manageable. Companies simply can't afford to be at a standstill regarding their data quality initiatives if they want to grow and succeed in today's economy."
"This survey shows that there is much greater awareness of the need for reliable data, and especially the reliance of any MDM program on good data quality," said Martin Boyd, vice president of marketing for Silver Creek Systems. "In fact, many companies are now starting their data quality initiative well in advance of a full MDM program as they find they can drive significant short-term benefits while doing necessary preparation for future infrastructure improvements, such as MDM."
