In this special guest feature, Timur Yarnall, CEO of Neutronian, believes the costs of faulty data are many: inaccurate insights, wasteful investments, lost productivity, ineffective marketing campaigns. Bad data hits businesses with a double whammy, affecting both the bottom line by narrowing margins and the top line by lowering sales. A data quality audit will in turn lead to reduced costs, less wasted effort, and — most important — better business results. Neutronian is a SaaS platform for comprehensive, independent verification of data quality and compliance.
Companies today are more reliant on data than ever. But the smartest business plan, the most brilliant ad campaign, the most discerning sales projections aren’t worth anything if they’re based on bad data. When a company makes decisions based on inaccurate, incomplete, or inconsistent data, it doesn’t matter how finely tuned its business strategy is. You can’t build a great house on a bad foundation.
Say a company is in the middle of a major computer-system upgrade: fancy new infrastructure, the latest data-analytics applications, all with the goal of becoming a data powerhouse. The sad truth is that It really doesn’t matter how much the company spends on whizbang technology. The system is only as good as the data it’s analyzing.
Bad data costs U.S. companies an estimated $3.1 trillion per year, according to IBM. The costs of faulty data are many: inaccurate insights, wasteful investments, lost productivity, ineffective marketing campaigns. Bad data hits businesses with a double whammy, affecting both the bottom line by narrowing margins and the top line by lowering sales.
How bad data hurts your business
It’s no exaggeration to say that bad data can ruin every step of your business process, wasting valuable time and resources. Poor data sets can put the brakes on a digital transformation by stalling migration from one platform to another. The irony, of course, is that giving a company a digital makeover is often motivated by the desire to become more data-driven.
Bad data can also be a significant drain on a company’s marketing resources. Nearly a third of the average marketing team’s time is estimated to be wasted on bad data, according to a recent survey. That drag on productivity means that about twenty cents of every dollar a company spends on marketing campaigns is essentially going down the drain.
Compliance can also be a casualty of bad data. High quality, well maintained data is essential in staying on the right side of data-privacy regulations, which typically require special processes and policies for collecting and storing personal information. Consistently operating with bad data will not only mean spending time and money to fix the problems internally, it will also subject companies to significant fines for noncompliance.
Companies using bad data can also lose business. In a recent survey, nearly 20 percent of businesses said that they had lost a customer due to inaccurate or incomplete data. Alienating customers is rarely a good thing, but it hurts just a bit more when it emerges from something that could have been prevented.
How to use data quality audits to reduce costs
The first step in mitigating the negative effects of poor data is to conduct a data-quality audit. Data audits help companies confirm the accuracy and quality of their data, while also making sure that there are processes in place to ensure compliance with any relevant regulations. An audit will also help businesses gain easier access to their data and eliminate silos and bottlenecks.
Data quality starts at the entry point. An audit can help ensure that a company is obtaining high-quality data from the beginning. During the audit, companies can root out data-collection issues that can lead to inconsistencies. The audit will also reveal the sources of bad data — whether it’s particular vendors or internal processing missteps — and help companies avoid them in the future.
Regarding compliance, a data audit can determine whether the data has the appropriate consent, and that the correct data-governance procedures are in place. The audit process will also keep your business compliant by ensuring that there is transparency regarding the data’s source, how secure it is, and how you intend to use it. A properly executed audit will also assess any legal risks from potential security breaches.
Data-quality audits can occur in-house or through an independent third-party agency that specializes in data quality and compliance verification. In-house teams are often already strapped for time, so leaning on an outside party can help reduce the internal burden. In addition, by leveraging an organization that specializes in these reviews, you’re able to benefit from its data quality expertise and industry knowledge.
Going forward
Once the audit is through, it’s important to use what the audit reveals to establish performance benchmarks. Those benchmarks can then be the basis for regular performance evaluations, and in turn help to place future business performance in context. This information will help, for instance, when selecting or evaluating data vendors, or when you’re devising new processes for obtaining first-party data.
Conducting an audit may seem intimidating at first, not to mention time-consuming and costly. But the effort and money that a company expends now on improving its all-important data will, down the line, yield higher-quality data. This will in turn lead to reduced costs, less wasted effort, and — most important — better business results.
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