The consequences of poor data quality for a business

In Experian’s latest Global research report, 84% of businesses surveyed said there has been more demand for data insights in their organizations with COVID-19. To gain data insights, it is essential to leverage trusted data—information that is correct and verified—for better decision-making. Otherwise, the impact of poor data quality will put up roadblocks to achieving your goals. Fortunately, by keeping an eye out for these roadblocks, you can address them and embrace opportunities for growth.

What does it mean to have poor data quality?

Data may be defined differently across organizations and industries. One source defines bad data first, saying, “We define bad data as those acquired through erroneous or sufficiently low-quality collection methods, study designs, or sampling techniques, such that their use to address a particular scientific question is scientifically unjustifiable”¹.

Examples of poor data quality in business include outdated customer contact information, improperly formatted address data, and customer data with typos. The impact of poor data quality extends to all departments within a business. For example, if you have bad customer data such as duplicate records or inaccurate records, it can affect the finance team for billing purposes, the renewals team for identifying who their customers are, and operations for processing and reporting on accurate products that the business has sold into.

What causes poor data quality?

Unfortunately, no business is immune from poor data quality. In fact, without a consistent data strategy, it is virtually inevitable. By knowing what to look for, you can target the precursors for poor data quality before they become deeper issues.

1. Inconsistent data collection methods

   If your business has not spent ample time ensuring that the inputs coming into your CRM or invoicing system are uniform, then you risk inaccurate information through these non-uniformed inputs. Establishing standard processes across all data-entry points is a great place to start; this will ensure that the data coming in is trusted, consistently formatted, and accurate, saving time and resources for your employees.

2. Ineffective data management

   The lack of best practices and policies could negatively impact your data consumption and management. If there are various ways to define, view, and manage data across your business—with no standard in place—you could be creating a roadblock when it comes to sharing insights across departments and overall decision-making.

   When it comes time for processes like data migration and integration, these standards only become foggier, making data less reliable with inconsistent formatting and quality. Your team should have a clear understanding of what data management looks like and how to work with data to meet business standards and goals.

   Sixty-two percent of businesses believe that a lack of basic data literacy skills impacts the value they get from their investment and technology, according to our latest study. After you standardize your records, we highly recommend that your business is trained across all departments on how to read, write, and argue with data.

3. Outdated data

   Understanding how to use data does not matter if the data is no longer useful. Data should be refreshed and viewed on a regular cadence to aptly take actions or make pivots as a business as needed. If your business is only collecting data and not reviewing it, then emails and addresses are becoming outdated and useless, leading to missed communication with customers and flawed decision-making down the line.

Consequences of poor quality data

Collecting data is not just for your convenience. Data collection should have a direct impact on business decisions and facilitate customer interaction. As a result, data quality issues can have debilitating effects, like the following consequences.

Reduced efficiency

Poor data quality can negatively impact the timeliness of your data consumption and decision-making. In fact, poor data quality may cost the US economy as much as $3 trillion in GDP. The best way to leverage data in a timely manner is to utilize tools alongside your process to create efficiencies with your time and resources, which will allow the expansion of timely strategy and tactics throughout your fiscal year. Without them, you are wasting time and energy that could be spent making decisions that support business growth on managing data quality issues and correcting avoidable mistakes.

Missed opportunities

Data quality issues affect communication between your business and the customer. If you do not have accurate contact information for your customers, then you cannot reach them to facilitate conversions. Poor data quality also causes you to miss opportunities to gain customer trust. Improper data leads to inefficiency in customer service interactions, impersonal emails, and ultimately unsatisfied customers.

Reduced revenue

Poor data quality can lead directly to flawed analysis and lost revenue, which is not uncommon. For example, marketing campaigns or analysis based on faulty data means not reaching potential customers and missing out on conversions. If you are investing money in failed mailing campaigns, you are also directly losing revenue. Not to mention, ineffective data management processes can also lead to a failure to follow important regulatory requirements and result in direct fines.

How to improve your data quality

The benefits of good-quality data can be felt across all departments. Standardized data, processes, and tools give your people the confidence and trust in the data and insight they need to make the best timely decisions for the business. To improve your data quality, you need to invest in and maintain systems that support these procedures.

Follow consistent collection methods

The worst way to maintain high-quality data is to start off with poor-quality data. Therefore, you need systems in place at the point of collection to prevent faulty data from ever entering your database to begin with. Resources like real-time email verification ensure that customer data is valid and accurate as soon as you receive it, preventing you from having to correct mistakes down the line.

Use effective data quality tools

Many tools on the market can help establish efficient processes to ensure high-quality data is captured and managed. Data validation and data management solutions are two options to ensure that both sides of the coin, data collection and ongoing maintenance, are reflected within your business.

Whether you are looking for data migration, data cleansing and standardization, or enrichment with additional consumer attributes, Experian’s data management solutions could provide the tools you need to maintain high data quality and reach your goals.

Take charge of your data quality with Experian

The impact of poor data quality can be seen throughout multiple daily business operations, from unsatisfied customers to poor decision-making. In a data-driven world where returns matter, these are risks your business cannot afford to take.

Fortunately, with an entire suite of data quality management tools, Experian can help you determine which ones can support your individualized business needs. For more information on Experian’s data management solutions, contact a consultant today!