Research Uncovers Data Quality as Top Concern for Enterprises Seeking to Drive Business Agility through Trusted Data

New data integrity study from Precisely and Drexel University reveals negative ripple effect of poor data quality across strategic initiatives making it a priority for data leaders in 2023.

BURLINGTON, Mass.–(BUSINESS WIRE)–Precisely, the global leader in data integrity, today released new findings from a global survey of over 450 data and analytics professionals conducted in collaboration with the Center for Business Analytics at Drexel University’s LeBow College of Business (LeBow). The 2023 Data Integrity Trends and Insights Report uncovered poor data quality as a pervasive theme for organizations across the industry, with 70% of those with low levels of trust in their data pointing to data quality as the biggest challenge to making confident decisions.

The findings reveal a concerning disconnect, with 77% of the professionals surveyed naming data-driven decision-making as their top goal for data programs in 2023. This was closely followed by the desire to improve operational efficiency (73%), reduce costs (62%), generate revenue (59%), and improve regulatory compliance (57%) — all of which rely on trusted data to be successful.

“Data leaders are being called upon more than ever to enable data-driven decision-making, which is fundamental to driving every one of the top business priorities identified by the research,” said Kevin Ruane, Chief Marketing Officer at Precisely. “The survey provides a benchmark for organizations in their journey to data integrity — highlighting both pockets of progress and areas for continuous improvement and investment.”

Quality Issues Dominate the Data Discussion

The study further illustrated the systemic impacts of poor data quality across organizations, named the number one impediment to successful data integration programs (60%) as well as the most common barrier to effective use of location data (41%) to inform decision-making.

“With data quality cited as both the leading challenge and the leading priority in 2023, it’s not surprising that less than half of respondents (46%) rated trust in their data as “high” or “very high,” said Murugan Anandarajan, PhD, Professor of Decision Sciences & MIS and Academic Director, Center for Business Analytics at LeBow.

More than half (53%) of those surveyed named data quality as the top priority for ensuring the integrity of their data. Furthermore, 71% of respondents reported that their organizations spend 25% or more of their work time preparing data for reporting and decision-making — a costly negative consequence of poor data quality.

Need for Business Agility Drives New Data Priorities

Macro-economic impacts are also shaping the way that organizations approach data strategies. Decreases in staffing and resources (40%) plus budget reductions (37%) mean businesses are turning to technology to increase flexibility and drive down costs. Over half of the data leaders surveyed confirmed that they are moving workloads to the cloud (57%), with many also reporting that their organization is currently going through digital transformation (42%).

Additionally, workflow automation (43%), artificial intelligence (AI) and machine learning (41%), and DataOps (31%) are all complementary technologies being deployed to enable organizations to automate data management and processes. This also helps to address widespread data integrity issues even when people and skills are scarce — but come with their own challenges.

“These technologies raise the stakes on the need for data integrity — data that is accurate, consistent and contextual to the business purpose,” added Ruane. “If you’re feeding bad data into these automated scenarios, you’re going to get worse outcomes.”

Watch the State of the Industry Panel from this year’s Precisely Trust ‘23 event to hear more from Precisely CEO Josh Rogers, Kevin Ruane, and the LeBow team on what the research findings mean for organizations and access the full 2023 Data Integrity Trends and Insights Report for a deeper dive into the data.

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