The Costs of Low Quality Data vs. the Benefits of High Quality Data

October 16, 2018
August 24, 2020

Studies throughout the past decade have shown that businesses understand that data is key to enabling business success. However, many senior executives aren’t confident in their data and don’t feel comfortable basing important decisions—or any decisions—on the data they get from departments across the enterprise. Whether it’s siloed information lacking in insightful connection points, massive quantities of data too daunting to process, or negative past experiences, key decision makers are making moves based on gut instinct rather than facts.

So how do you overcome this lack of trust in data? Data quality and data governance are the key differentiators between business leaders who make proactive decisions based on facts and business leaders who make reactive decisions based on anecdotal evidence.

What do we mean by data quality and governance? Data quality refers to how complete, accurate, credible and consistent your data is. Your data quality level is partially dictated by what kind of data your business needs vs. what kind of data you currently have. Data governance, on the other hand, ensures that your data stays at a high quality throughout its lifecycle.

In addition to executives having low trust in data, many studies show that the cost of poor quality data is in the multi-millions or more. How?

It’s common for a marketing campaign, for instance, to have a high error rate due to outdated lists, incorrect contact information, duplicate entries, etc. A 50% error rate can easily cut sales revenue by 50% and is entirely avoidable.

An overview of other costs of poor data quality:

Reputation damage: look into the Apple Maps debacle from years ago. In a nutshell, poor data quality made the app far inferior to alternatives, and some would argue it’s still recovering. Here’s another great example of bad data—Skyscanner recommends a 47-year layover to a customer when booking a flight.

Lost opportunity to use data as an asset: large amounts of data may be available to your organization, but if they are inaccurate or poorly organized they will be of little use.

Regulatory fines: when collecting data from customers and suppliers it’s important to document how that data is used and protected. Good data governance allows you to avoid potential fines and maintain good faith and good relationships with those customers and suppliers.

Wasted resources fixing problems caused by data errors: this can be as simple as a package or email delivered to the wrong address and has real financial implications. Quality errors can create overwork and fatigue from staying late to handle overseas issues with data.

Unreliable analytics negatively impacting operations, inventory, planning and projections, etc.

Compare with some of the benefits of good quality data:

No more double checking or editing data last minute. When your data quality is low, it never fails—you’re bound to find errors just before an important report/presentation is due. Imagine freedom from racing the reporting clock every month/week and having more time to find deeper value in your reporting.

Become a true partner to the business and add quantifiable value by offering leadership information that makes their jobs easier. High quality data enables more fact based decision making and lowers risk to the business.

Increased productivity because teams are freed from solving data error issues and can focus on more valuable work. One of the reasons poor data quality costs so much is because it often forces employees to work around it daily. Corrections are made on an ad hoc basis without addressing the root cause. Corrections are not communicated across the enterprise, leading to more errors, leading to a culture of workers who spend extra time double checking all the data they encounter.

Keep cash flowing throughout the business by avoiding regulatory fines.

Enable sales growth by getting the facts about your customers that you need to offer them highly targeted experiences.

The last thing you need is a one-size-fits-all data quality and governance solution that’s impossible to customize to your business. That’s why Onebridge spends time embedding our team within our customers’ teams and understanding their unique challenges. We create a customized plan designed to solve specific pain points in your program or simply take it to the next level of maturity. Have a no-pressure conversation with us about our data analytics consulting experience now to find out more.

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