Bad Data Costs US Businesses Trillions – How Data Quality Audits Can Help
In this special feature, Timur Yarnall, CEO of Neutronian, believes that the costs of bad data are many: inaccurate information, wasted investments, lost productivity, ineffective marketing campaigns. Bad data hits businesses with a double whammy, affecting both the bottom line by squeezing margins and revenue by lowering sales. A data quality audit will in turn lead to reduced costs, less wasted effort and, most importantly, better business results. Neutronian is a SaaS platform for comprehensive, independent verification of data quality and compliance.
Businesses today depend on data more than ever. But the smartest business plan, the most brilliant advertising campaign, the most exacting sales projections are worthless if they are based on bad data. When a business makes decisions based on inaccurate, incomplete, or inconsistent data, it doesn’t matter how accurate their business strategy is. You cannot build a great house on a bad foundation.
Suppose a company is in the midst of a major upgrade to its IT system: sophisticated new infrastructure, the latest data analytics applications, all with the goal of becoming a data powerhouse. The sad truth is that it doesn’t matter how much the company spends on whizbang technology. The quality of the system depends on the data it analyzes.
According to IBM, bad data costs American businesses about $3.1 trillion a year. The costs of erroneous data are numerous: inaccurate information, unnecessary investments, lost productivity, ineffective marketing campaigns. Bad data hits businesses with a double whammy, affecting both the bottom line by squeezing margins and revenue 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 hinder a digital transformation by blocking migration from one platform to another. The irony, of course, is that giving a business a digital makeover is often driven by a desire to become more data-driven.
Bad data can also take a toll on a company’s marketing resources. According to a recent survey, almost a third of the average marketing team’s time is wasted on bad data. This slowdown in productivity means that about twenty cents of every dollar a company spends on marketing campaigns is essentially wasted.
Compliance can also fall victim to bad data. High-quality, well-maintained data is essential to staying on the safe side of data privacy regulations, which typically require special processes and policies for collecting and storing personal information. Constantly working with bad data will not only mean spending time and money to resolve issues internally, but will also expose companies to significant fines for non-compliance.
Companies using bad data can also lose customers. In a recent survey, nearly 20% of businesses said they had lost a customer due to inaccurate or incomplete data. Alienating customers is rarely a good thing, but it hurts a little more when it results from something that could have been avoided.
How to Use Data Quality Audits to Cut Costs
The first step to mitigating the negative effects of poor quality data is to perform a data quality audit. Data audits help companies confirm the accuracy and quality of their data, while ensuring that processes are in place to ensure compliance with any relevant regulations. An audit will also help companies gain easier access to their data and break down silos and bottlenecks.
Data quality starts at the point of entry. An audit can help ensure that a business is getting high-quality data from the start. During the audit, companies can rule out data collection issues that can lead to inconsistencies. The audit will also reveal the sources of bad data – whether particular vendors or internal processing errors – and help companies avoid them in the future.
In terms of compliance, a data audit can determine if the data has the proper consent and if the right data governance procedures are in place. The audit process will also keep your business compliant by ensuring transparency regarding the source of the data, how secure it is, and how you intend to use it. A properly executed audit will also assess the legal risks associated with potential security breaches.
Data quality audits can be performed internally or through an independent third-party agency specializing in data quality and compliance verification. Internal teams are often already strapped for time, so relying on an outside party can help reduce internal load. Additionally, by hiring an organization that specializes in these reviews, you can benefit from their data quality expertise and industry knowledge.
Once the audit is complete, it is important to use what it reveals to establish performance criteria. These benchmarks can then serve as the basis for regular performance reviews and, in turn, help put future business performance into context. This information will help you, for example, when selecting or evaluating data providers, or when designing new processes for obtaining first-party data.
Performing an audit can seem daunting at first, not to mention time and money consuming. But the effort and money a company now spends improving its critical data will, ultimately, produce better quality data. This will in turn lead to lower costs, less wasted effort and, most importantly, better business results.
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