Most organizations don't consistently measure the quality of the data produced by their teams. When they begin, they're often alarmed by the results.

That's the eye-opening topline from this 2017 study published in the Harvard Business Review. Its authors conducted a simple survey of business managers, asking them to identify unambiguous data errors in a standardized set of recent work products put out by their respective organizations, then determine the number of error-free records within their sets. The total number of error-free records in a standardized set of 100 records was their data quality score.

The results of the study were shocking, "even horrifying," as the authors put it. Just 3% of data quality scores were rated "acceptable," defined as scoring 97 or better on a scale of 100. The other 97% of record sets were too error-riddled to pass muster, with about 40% scoring below 50 on the data quality scale.

Statistically, it's quite likely that your organization's records would fail the HBR's data quality test. As more organizations gain awareness of the importance of data quality, the implications for your business are clear.

What's the fix? In a word, good data management, or a holistic approach to improving data quality, visibility, security, and fidelity, all done with the end goal of ensuring business continuity, improving reliability, and raising the bar for consistency.

It can be done. Here's why - and how - to make it a priority for your team.

Data Observability Solutions Drive Insights That You Might Otherwise Miss

Effective data operations begin with comprehensive data observability.

What's that? Data observability "can predict and automatically fix issues before they impact performance or create unplanned outages, cost overruns, or bad output based on low-quality data," according to Acceldata, which offers an end-to-end data observability platform.

A comprehensive data observability solution helps streamline data management and reduces the technical challenges (and workloads) inherent in ensuring data quality and fidelity. It's the building block of a coherent approach to data management.

Moreover, having a data observability solution has numerous benefits, such as the following: 

• Improved data quality: It can help identify and correct data quality issues, like duplicate records, incorrect data types, and missing values.  

• Increased data reliability: It can help ensure the data is consistent and reliable by tracking changes and determining potential issues.  

• Reduced downtime: It can help minimize data downtime by identifying and addressing issues before they impact business operations with significant data loss.  

• Enhanced data usability: It can help make data more usable by acquiring insights about data quality, usage, and lineage.  

A data observability solution can be a valuable investment if you're looking for a perfect way to boost data quality, reliability, security, and usability.  

A More Careful Approach to Data Management Can Have Knock-On Effects for Corporate Culture

Proponents of strong data management practices most often talk about its direct practical and technical benefits. While laudable, these benefits pale in comparison to the indirect systemic shifts that a concerted data management focus can produce within an organization.

Culture shift is the biggest prize here. A culture of care around data, even meticulousness, can spill over into other critical aspects of the business: accounting, customer relationship management, incident reporting, even product development. Raise the bar here, raise it everywhere.

Standardized Naming and Metadata Conventions Make Data Searchable Across Geographies and Timespans

Zooming back in, let's consider a key practical benefit of data management: standardized naming and metadata conventions that make data searchable across the organization, regardless of where the data is stored or who's doing the searching. In particular, attaching the same metadata attributes to every data set produced within the organization - author name, field descriptions, content summaries, purpose summaries, time- and geo-stamps - can dramatically improve search efficiency and reduce the risk of misinterpretation.

Strong, Redundant Data Storage Practices (And a Recovery Plan) Minimize Risk of Loss and Version Mismatching

Inherent in a holistic approach to data management is a holistic approach to data storage and recovery.

Redundancy is the name of the game here. Modern organizations can't afford any downtime or data loss, both of which are rightly considered competitive threats at minimum and existential threats in the worst-case scenario.

Working back from this principle, every business that cares about data management needs to invest in redundant infrastructure that covers the organization's entire data footprint and serves all existing and future endpoints. Key elements of this infrastructure include "high speed [and] high bandwidth connections, main data center, a resource duplication remote site, and uninterrupted power supply," according to ComputerWorld.

This infrastructure means nothing if it doesn't work as intended, of course. Businesses need to develop plans that cover every aspect of post-incident recovery. They also need to test their data backup and recovery processes regularly through the technical equivalent of live-fire exercises.

But aside from the ones mentioned above, installing a dedicated server can also be another strong data storage practice your business can implement. It's a hosting service that can provide businesses exclusive use of an entire server. This means they have complete control over the server's resources, such as the CPU, RAM, bandwidth, and storage.  

When your business has a dedicated server, you can guarantee the highest level of security and increased performance. This is because no other applications and websites share the resources when using a dedicated server. As a result, your business can minimize the risk of loss and version mismatching. 

To make this happen, it's best to invest in dedicated servers as soon as possible.  

Standardized Data Documentation Keeps Everyone on the Same Page and Enables Rapid Deduplication

Effective data documentation goes beyond metadata and naming conventions. Organizations that care about data quality need to have detailed documentation schema at the software, project, and file levels. These schema enable deduplication of identical file sets (freeing up storage resources), empower version control and fidelity, and enable collaboration across teams and divisions that may have their own uses for applicable data sets.

Minimum Necessary Permissions Strike the Right Balance Between Useful Access and Security Risk

Organizations that care about data quality and fidelity also need to abide by the principle of least privilege, or minimum necessary permissions.

According to the principle of least privilege, employees and contractors need only those access permissions which are absolutely necessary for them to perform their job duties. This is a critical firewall against malignant "insider threats," which are among the most difficult digital threats to detect and prevent. Like some other key data management practices, it also has indirect benefits beyond data quality, including for the accountability and performance measurement metrics that managers rely on to make personnel decisions.

How's Your Data Management Going?

Let's revisit that HBR data management study for a moment. Its shocking finding - that just 3% of the data quality scores in the study were rated as "acceptable" - strongly suggests that your data management practices could be going better. That is, unless you're among the lucky few whose data quality consistently ranks in that 3%.

If it's clear that you have work to do to improve your data management practices and up your overall data quality, it's time to buckle down. Fortunately, you've just completed reading a road map for doing just that. If you can translate the advice above into actionable steps to improve data management within your organization, you'll find yourself rising above the pack in short order.

And that's likely to produce real benefit for your organization. If you're able to act.