The State of Global Data Integrity in 2021

The State of Global Data Integrity in 2021

Key finding: Leading global enterprises are seeing success with analytics and AI projects. But poor data integrity is hampering data-driven initiatives for many.

When the responsibility for critical decision-making rests at the feet of data and analytics professionals, it is essential that the information they are passing to company stakeholders is wholly reliable.

Our first ever Data Integrity Trends survey of 304 data, analytics and AI executives shows that enterprises today have a range of critical business priorities that require a foundation of trusted data.

First and foremost, 63% say business initiatives geared toward meeting customer experience demands are influencing their 2021 priorities. Meanwhile, 58% say their priorities include launching or scaling AI and advanced analytics initiatives and 49% say the same about meeting compliance and regulatory requirements.

“There’s a genuine sense of urgency as businesses in all industries and all regions engage in significant digital transformation initiatives.”


Amy O’Connor

Chief Data and Information Officer, Precisely

Data-Driven Investments are Delivering Mixed Results

Please rate your organization’s level of success to date with each of the following data and analytics strategy objectives

Source: Corinium Intelligence, 2021

“You need to add another dimension to your data and consider it in context – not only the who and the what, but the when, where, and why”


Amy O’Connor

Chief Data and Information Officer, Precisely

At the same time, 48% are factoring enabling remote working, facilitating hyper personalization and rationalizing company data following merger or acquisition activities into their 2021 plans.

“There’s a genuine sense of urgency as businesses in all industries and all regions engage in significant digital transformation initiatives,” says Amy O’Connor, Chief Data and Information Officer at data integrity specialist Precisely. “These programs must be built on a foundation of data integrity if they are to be successful.”

‘Data integrity’ is foundational to success in analytics and insight projects. Ensuring that data is recorded correctly and remains accurate when retrieved or used throughout its lifetime is essential for preserving data integrity. However, it’s important that data integrity is not merely another expression for data quality.

Precisely defines data integrity as ensuring a company’s data is accurate, consistent and provides the right context for confident decision-making.

Our research shows that most enterprises still have work to do if they are to meet this standard and establish a base of high-integrity data that company stakeholders genuinely trust to inform their business decisions.

Data Integrity is Enabling Analytics Success

Our research suggests that many enterprises believe they’ve successfully laid the foundations for data-driven decision-making and automation.

Of the executives we surveyed, 61% say they have put their core data management and governance frameworks in place at least ‘quite successfully’, with 33% saying they’ve done this ‘very successfully’.

Meanwhile, 55% say they’ve established and are maintaining a base of trusted data for analytics at least ‘quite successfully’. However, 42% report that their attempts to do this have yielded ‘mixed’ or ‘disappointing’ results. In the financial services sector, this figure jumps to 50%.

“We are slowly maturing as an industry,” says Guy Taylor, Director of Data Science and Analytics and Interim Director of Experimentation at online travel company “We are slowly getting our heads around the kind of capabilities that we need in order to do our jobs better.”

However, the proportion of respondents reporting disappointing or mixed results in these two objectives shows many enterprises still have work to do to ensure the integrity of the data they’re managing.

“From what I’ve seen in my previous roles, [data integrity is] an area that we can all improve on in APAC, with a few notable exceptions, who are typically startups and began with a data-first mindset,” says Gladwin Mendez, Data and Information Security Officer at investment company Fisher Funds.

Putting these ‘data foundations’ in place is essential to the success of initiatives geared toward driving value with a company’s data assets. This may be why 41% say their attempts to establish a value-driving analytics program have yielded ‘mixed’ or ‘disappointing’ results.

Similarly, 42% are struggling to automate or augment processes with AI, drive analytics adoption or integrate insights with business processes, reporting ‘mixed’ or ‘disappointing’ results in all these areas.

The public sector and education sectors are the least mature, when it comes to analytics adoption. A full 73% of respondents in these verticals say their attempts to integrate insights with business processes have yielded ‘mixed’ or ‘disappointing’ results.

“ From what I’ve seen in my previous roles, data integrity is an area that we can all improve on in APAC”


Gladwin Mendez

Data and Information Security Officer, Fisher Funds

Tech Companies Lead the Way on Insight Generation

How successfully have you established an analytics program that reveals valuable insights?

Source: Corinium Intelligence, 2021

Few Trust Data Over Their Own Intuitions

While many respondents claim to have established trusted data sources staff can use to uncover valuable insights, their comments about how stakeholders use those insights tell a different story.

Only about a third of respondents say their colleagues will trust data-driven insights that run contrary to their own intuitions. Meanwhile, 22% say staff generally don’t trust data-driven insights and 44% report that staff won’t trust insights from data that don’t confirm their ‘gut feels’.

These findings shed light on the true state of data integrity in the world today. When data-driven insights aren’t repeatable and consistent across business units or aren’t presented in the right context for accurate decision-making, staff may feel justified in mistrusting them.

“If people don’t trust the insights, they’re not going to act on them, especially when the insights conflict with their so-called gut reaction,” notes Dan Power, Managing Director of Data Governance, Global Markets for financial services company State Street. “Solving this challenge is partly about trying to work backwards from the statement of, ‘I don’t trust the results.’”

Most Enterprises are Rushing to Embrace Analytics

How successfully is your company integrating data-driven insights with existing business processes and driving analytics adoption?

Source: Corinium Intelligence, 2021

“If people don’t trust the insights, they’re not going to act on them, especially when the insights conflict with their so-called gut reaction”


Dan Power

MD of Data Governance, Global Markets, State Street

Power argues that poor trust in data can have its roots in questions about the quality of the source data, or mistrust of ‘black box’ algorithms that function in ways staff can’t understand.

“The potential impact of data is orders of magnitude greater than just serving decision-makers’ confirmation bias,” adds O’Connor. “The real value in data is about uncovering hidden connections and unlocking new insights that help a business truly transform and grow.”

Establishing trust in data within an enterprise starts with data integrity. Data that’s used for insight generation must be accurate, consistent and filled with context for business decision-making.

While most enterprises are reporting at least some success with the data integrity basics, our research suggests that they have a way to go if they want to arm staff with valuable, trusted insights at scale.

This is an excerpt from our recent report in partnership with Corinium Business Intelligence — Data Integrity Trends: Chief Data Officer Perspectives in 2021. You can download the full report here.