Why does your business need to maintain high-quality data?

Regardless of a company’s industry or specialty, it’s increasingly important for the organization to ensure ongoing access to high-quality data. Here’s a closer examination of why dependable information supports success.

Better data quality increases trust within an organization. When a company prioritizes data quality, there’s a higher likelihood its executives will feel confident about the information’s validity. Before the days of big data analysis tools, leaders typically relied on experience and instinct when making critical choices within an organization. Now, technology can help them notice insights they would otherwise miss.

A trust disconnect between data professionals and senior managers. People throughout all levels of an organization likely know how important it is to have high-quality business statistics. However, a 2019 study found a striking gap between how well a company’s data professionals and its senior IT managers believe the organization keeps information trustworthy and captures it efficiently. Even so, trust in the data was not as high as it should be in any case.

Only 31% of data professionals were highly confident in their company’s information. However, the figure was 46% among managers. About 52% of managers were highly optimistic that the company complied with data regulations, but only 39% of data specialists shared the same optimism. Another worrying finding was that a mere 29% of data workers said their information was always accurate and up to date.

These outcomes show why it’s vital for managers to get data professionals’ feedback about how their strategies are going. Did unexpected complications occur? Where do best efforts still fall short? Otherwise, they could have overly rosy assumptions about how much people at an organization can – and should – trust this information.

Reliable business data can reveal customer preferences. Company leaders frequently use data to answer some of the most daunting questions they face. For example, does it make sense to move into a new market? Which product characteristics are most likely to make customers buy something rather than passing it over in favor of something else?

High-quality data gives company representatives the information they need to act promptly based on what’s known about current or potential customers. For example, if a business’s database features thousands of duplicate or incomplete records, it’s not the best source for providing accurate statistics that could guide the organization’s next decisions.

Customers often don’t use their cars’ included features. Anyone who has researched or shopped for a new car likely learned that automobiles have an eye-popping assortment of high-tech features. Manufacturers may think promoting those aspects is ideal for showing potential buyers the vehicles offer excellent value for money. However, a recent survey showed that’s not necessarily the case.

The study showed more than one in three advanced automobile technologies had fewer than 50% of owners using them within the first 90 days of purchase. Some have no plans to use the feature. For example, 52% of those with vehicles with driver/passenger communication technology said they’d never used it, and 40% admitted they had no reason to start.

However, that’s not to say car owners don’t want any advanced features in their vehicles. Ground- and rear-view mirror cameras were two of the top three things car owners said they wanted in their next automobile. Even so, tech desires vary by a person’s location. While 62% of people in the U.S. said they definitely would get cars with ground-view cameras next time, only 24% of respondents in China felt the same.

These variations show how dependable business data can help decision-makers choose how to effectively market their products to the public, whether it’s cars or candles. Company representatives can’t always accurately predict which features will thrill customers the most. However, data can shed light on that critical question.

High-quality data can build customer interest and trust. People often want concrete evidence that a product is likely to work for them. That’s especially true for items related to health and wellness. Companies often publish internal research and invite potential customers to dive into the information themselves. However, the mere intention to conduct a study does not automatically make it reliable.

Competence and process are the two components that bring reliability to such projects. The people conducting experiments should have relevant educational backgrounds and experience, and they must follow and document processes that enable repeatability and get consistent results.

When companies follow all the necessary steps during their internal investigations, the likelihood goes up that they’ll have high-quality data from a trustworthy study. As a result, customers can review that information and use it to make informed buying decisions. Plus, companies with a history of publishing data that stands up to scrutiny improve their reputations among customers and the marketplace at large.

The internet gives bad data a broad reach. Even people with the best intentions to properly conduct a study sometimes make mistakes. Those blunders often become apparent once outside parties examine the research and call some of its data into question. After that, the study’s authors look at the areas of concern and, when necessary, issue a retraction.

Unfortunately, the speed with which people can share links, screenshots and news coverage online means research identified as having incorrect data can still spread far and wide before the authors recognize and admit their mistakes. That problem can also have widespread societal implications.

For example, Canadian researchers recently issued a retraction for a preprint about the prevalence of heart inflammation in people who receive mRNA COVID-19 vaccines. The authors said a data mistake led to a “vastly inflated” incidence rate of that side effect. They did the right thing by announcing that error. However, media pieces and social media chatter about the information in its original form may have increased vaccine hesitancy and stoked unnecessary fears.

Committing to maintaining high data-quality levels does not eliminate accidents like the one above. However, when companies set that priority, they’re less likely to accidentally publish or spread misinformation that could quickly get out of control.

Good data quality supports business resilience. The Industrial Internet of Things has created exciting opportunities for companies to gather and analyze data in real time, allowing more visibility of overall operations and potential problems. One study showed that using data for a predictive maintenance strategy could save up to 40% compared to purely reactive upkeep measures.

However, such outcomes are most likely to happen when people feel they can trust the data. Sometimes, environmental characteristics can highlight abnormalities that don’t indicate an actual problem. For example, mounting a machine’s sensor too close to a building’s heat source could cause elevated temperature readings even if the piece of equipment itself functions as it should.

Conversely, if company leaders believe the information they have is accurate and current, they could use that data to prevent costly issues like machine downtime or product defects.

Data is even more critical during the pandemic. Business leaders collected data long before the COVID-19 pandemic disrupted the world. However, an October 2020 study indicated that the associated health and economic crises made them even more reliant on it. About 91% of respondents cited data’s skyrocketing importance since the pandemic began. Additionally, 90% of those polled became more aware of its significance for decision-making since COVID-19’s onset.

Business leaders also recognized the role of data in their recoveries, with 94% viewing it as a strategic asset that would show them the way out of these challenging times. Humans can’t predict the future with certainty, but using information to guide decisions minimizes doubt.

Excellent data quality helps companies excel. Organizations use business data to learn about customers, monitor profits, decide when to hire more team members and much more. That information will bring the most value when people take the time to verify its quality. While high-quality data brings numerous benefits to a company, misleading information could hurt it.