By Bob Deakin
Part I in the Data Integrity Series
The Harvard Business School defines data integrity as “the accuracy, completeness, and quality of data as it’s maintained over time and across formats.” But, what if your data lacks integrity? What if it is not accurate, complete, or of high quality?
To Protect Data Is To Protect People
“When a business fails to look after customers’ data, the impact is not just a possible fine. What matters most is the public whose data they had a duty to protect.”
These are the words of U.K. (ICO) commissioner Elizabeth Denham in response to the $23.8 million fine Marriott International, Inc. received in 2020.
The ICO ruling said Marriott failed to put “appropriate technical or organizational measures in place to protect people’s data.” This is in accordance with the pan-EU General Data Protection Regulation (GDPR).
Exposing the Data of 500 Million Customers
In 2018, the New York Times reported the Marriott hack as the target of a coordinated effort by Chinese intelligence-gathering operators.
Earlier in the year, an attempt to access the guest reservation database for Marriott’s Starwood brands was flagged. As it turns out, however, the initial breach occurred in 2014, two years prior to Marriott’s purchase of Starwood. According to the story, it potentially exposed the data of as many as 500 million customers.
Data Integrity Is What It Sounds Like
The word integrity sounds out of place in tech terms, but Data Integrity is just that. It’s accuracy, completeness and quality are vital to building and maintaining trust among an organization’s customers, partners, and team.
Obviously, ensuring data accuracy, quality, and security is vital. Additionally, identifying data-related issues that could affect operations is essential to the prolonged success of an organization.
Joshua Joseph is the manager of data integrity for the xOps team for LMS and GEM in its role for a global travel and leisure organization. He is in constant contact with its client’s leadership with a running update on data integrity.
“In a span of about two weeks, we validate close to around one hundred thousand guests,” he said. “In years past, if you look at the statistics, the number of guests with data-related issues was close to eighteen or nineteen percent. GEM has brought it down to zero-point four-five percent (0.45). Those are the statistics from last week, and that’s a very good accomplishment.”
The Doors of Communication Are Always Open
Key to the success of Joseph’s team is communication. Without fail, if an issue arises, they immediately ensure the entire team is aware.
“I believe the expectation is to exceed customer and client expectations,” said LMS and GEM Senior Applications Support Analyst Carlos Sarmiento. “Specifically, the culture at LMS is that of accountability. There are no excuses. You own your individual results.”
When LMS was contracted as part of a global project several years ago, as many as 50 other vendors participated. Remarkably, there are now four.
“We are the only team that has actually gotten bigger,” Sarmiento attests. “That is a testament to the work that we do. Our communication skills, our responsibility, and our accountability.”
What Is the True Value of Data Integrity?
According to a McKinsey & Company survey, intensive users of customer analytics are 23 times more likely to outperform their competitors in new customer acquisitions and nine times more so in terms of customer loyalty.
Forbes Councils Member Tendu Yogurtcu breaks down the big picture of data integrity in Why Making Data Integrity Is A Business Imperative. Data is highly vulnerable to errors.
“Only 3% of companies’ data meet basic quality standards, and 47% of newly created data records have at least one critical error. It’s no wonder that 84% of CEOs are concerned about the integrity of the data on which they’re basing their decisions. Poor data quality is especially problematic at scale, magnifying initially benign data issues and creating poor business insights.”
Put Data Into Context
Tendu points to COVID-19 as an example where data is often skewed. The number of fatalities compared to the number of new cases was frequently cited to display how serious the spread of the virus was in certain areas.
“Adding context with additional demographics data and enriching data with underlying health conditions for a region or community all help build our understanding of the relationship among data sets. This helps with predicting the outcome, leading to better decisions.”
What If Your Data Lacks Integrity?
Assuring data integrity is imperative as it protects businesses, large and small, from making incorrect decisions. A recent survey published by DemandBase reported that “2,190 global IT and business decision-makers found that only 35% have high trust in their organization’s use of analytics.”
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