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Poor data hampers business agility
The 2023 Data Integrity Trends and Insights Report from Precisely ( and the Centre for Business Analytics at Drexel University’s LeBow College of Business (LeBow) reveals top concern for enterprises seeking to drive agility through trusted data is the impact that the negative ripple effect of poor data quality is having on strategic initiatives across the business.

In 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), 70% of organizations cite poor data quality and low levels of trust in their data as the biggest challenge when making confident decisions.
The findings reveal a concerning disconnect, with 77% of the professionals naming data-driven decision-making as their top goal for data programmes in 2023, followed by 73% who say the desire is to improve operational efficiency, and 62% cite reduction in costs with a further 59% saying their top data goal is in generating revenue.  Over half (57%) of all respondents say that to improve regulatory compliance will rely on trusted data.
Further illustrating the systemic impact of poor data quality across organizations, 60% of respondents say poor data quality is hampering their organization’s ability to deliver a successful data integration program across the whole enterprise, with a further 41% citing that the most common barrier to achieving this is the use of location data to inform decision-making.  

“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,” says Kevin Ruane, Chief Marketing Officer, 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.”
“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 rated trust in their data as “high” or “very high,” adds Murugan Anandarajan, PhD, Professor of Decision Sciences & MIS and Academic Director, Centre for Business Analytics, LeBow.

The research also found that over 70% 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.
Macro-economic impacts are also shaping the way that organizations approach data strategies.   Around 40% of those surveyed say decreases in staffing and resources plus budget reductions mean businesses are turning to technology to increase flexibility and drive down costs.  Over half (57%) of the data leaders surveyed confirmed that they are moving workloads to the cloud, with 42% of respondents saying that this is part of their organization’s digital transformation.

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 as Ruane explains these come with the own challenges, “These technologies raise the stakes on the need for data integrity – data that is accurate, consistent and contextual to the business purpose.  If you're feeding bad data into these automated scenarios, you’re going to get worse outcomes.”

A full copy of The 2023 Data Integrity Trends and Insights Report can be found at

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