Data quality is essential for any organization that relies on data to make decisions. Most companies realize they need to monitor and maintain their data quality, but not all employees understand the benefits of data quality and how high-quality data can enhance business use cases and opportunities. Discover 10 ways data quality can positively impact your business in this article.
Jump to:
What is data quality?
Data quality is a measurement of business data that looks at measures such as consistency, reliability, completeness, and accuracy. The highest levels of data quality are achieved when data is accessible and relevant to what business users are working on.
To use a simple baking analogy, high data quality is achieved with the right ingredients (data cleaning), measured correctly (data preparation) and combined in the right way (data transformation) into a delicious end product (actionable insights).
The benefits of data quality are numerous and have a major impact. With good data, companies can make better decisions, improve operational efficiency, optimize marketing campaigns and increase customer satisfaction. It is essential for companies that want to develop a competitive advantage.
TO SEE: Hiring Kit: Database Engineer (Tech Republic Premium)
When data is accurate, complete, and consistent, organizations can make informed decisions that lead to positive outcomes. Poor data quality, on the other hand, can lead to wrong conclusions, wasted time and resources, and missed opportunities.
Top 10 benefits of data quality
Increased trust in data
Trust is critical in an organization, but difficult to achieve, especially since the people who use data to make decisions are rarely involved in collecting and preparing it for consumption.
Take the example of a CEO who has to make tough decisions based on data provided by his technical teams. If the CEO has received incorrect data in the past that led to poor business decisions, they may have doubts about future data, hesitate to rely on it and try to validate it.
When an organization has a robust data quality strategy and processes that everyone trusts, it gives the CEO and other decision-makers the confidence they need to rely on the data for decisions.
Better decision making
Data quality has a direct impact on an organization’s bottom line as it affects the accuracy of decisions. When data is complete, accurate and timely, organizations can make good decisions that lead to positive results.
Poor data quality, on the other hand, can lead to wrong conclusions and poor decisions that can hurt profits.
For example, if a bank or financial services company makes decisions based on incomplete or inaccurate data, they risk making poor credit decisions, which can lead to defaults and losses. An insurance company that relies on flawed data to price its products may overcharge or undercharge customers, which can hurt the company’s reputation and competitive advantage in the industry.
Increased scalability
As organizations grow, their data needs change and evolve. Good data quality is essential to ensure that an organization’s data is scaled for new business use cases and opportunities.
Poor data quality can hinder an organization’s ability to scale effectively and efficiently. For example, an e-commerce company that uses data to personalize the customer experience for each visitor to its website will need a robust and scalable data infrastructure to support this personalized experience at scale. If the company’s data quality is poor, it will be difficult to scale personalized experiences for a large number of visitors without major mistakes or inefficiencies of staff.
Improved consistency
High data quality is essential for ensuring consistency in an organization’s processes and procedures. In many businesses, different people may need to see the same sales numbers, but may look to completely different data sources for those numbers. Incongruity between systems and reporting can harm decision-making and interdepartmental initiatives. A consistent data quality strategy ensures that data is harmonious across the organization.
Willingness to deal with changes in the business environment
Organizations with good data quality are often better prepared for changes in the business environment and can adapt to changes faster and more efficiently. Poor data quality can hinder an organization’s ability to change and adapt to new technologies, processes and operational needs, leading to stagnation and decline.
Lower costs
Higher data quality can also help reduce costs within an organization. When the data is accurate and complete, organizations spend less time and money on things like reprinting product documents or rerunning reports after initial errors. In addition, high-quality data can help organizations avoid fines or penalties for non-compliance with regulations.
Time saving
Inaccurate data can lead to operational inefficiencies and a waste of time and resources, especially if certain members of your team spend all their work hours on quality testing data.
For example, a company that doesn’t maintain a complete dataset of its customers could send marketing materials to the wrong addresses or call customers by the wrong name. These types of mistakes not only annoy customers and damage a company’s reputation, but also waste time and resources that could have been used more effectively.
Increased productivity
The by-product of lower operating costs and time savings is increased productivity. When an organization is more efficient, its employees can be more productive and can focus on more strategic tasks rather than tactical data maintenance tasks.
Improved compliance
Organizations that maintain high standards of data quality are also more likely to comply with the laws and regulations applicable to their industry. This is because accurate and complete data makes it easier for organizations to meet their reporting requirements and avoid penalties for non-compliance.
TO SEE: Data management checklist for your organization (Tech Republic Premium)
With most privacy laws today, such as CCPA and GDPR, trusting that your data is of high quality is an important first step to preparing for and passing compliance audits.
More effective customer satisfaction measures
Finally, good data quality can lead to higher customer satisfaction. When an organization has accurate and complete customer data, it can deliver a better and more focused customer experience. This usually leads to more sales and customer loyalty.
Optimizing data quality for future business goals
Data quality should be a top priority for any company looking to stay ahead of the competition. With the right data, companies can make decisions that will help them thrive in today’s ever-changing marketplace.
