Data Accuracy 101: Why it Matters and How to Achieve it


It is no question that businesses are finding themselves in an ocean of data, struggling to navigate towards the shores of insight, analytics, and intelligence. What’s concerning is that even though millions are being invested in data management solutions, a study involving 75 executives by Harvard Business Review reveals that only 3% found their data to be within the acceptable range of 97 or more correct records out of 100. This alarming statistic highlights the importance of maintaining data accuracy, not just collecting more data.

We would like to thank Data ladder for some of the information in this article.

Why Data Accuracy Matters

Accurate data serves as the foundation for several crucial business operations and decisions. Be it planning an expansion into a new market, launching a novel service, assessing market position, understanding competitors, customising customer experiences, or enabling efficient company processes – all these rely heavily on the accuracy and reliability of data.

Accurate data improves decision-making, aids in efficient operations, enhances risk management, ensures regulatory compliance, and supports improved customer service. Moreover, in a landscape marred by data breaches and privacy concerns, accurate data can foster trust and transparency, providing organisations with a distinct competitive advantage.

The Hurdles to Achieving Data Accuracy

Several roadblocks hinder businesses from maintaining precise records. 

Three significant obstacles include:

-A poor data culture

-Tendency to hoard data rather than using it effectively

-An outdated approach reliant on traditional methods and technologies.

Organisations frequently focus more on gathering new data rather than optimising and making use of the existing data. Employees often lack awareness of concepts like data quality or data accuracy, leading to lapses in maintaining data integrity. 

Businesses also persistently use outdated technologies that are ill-equipped to handle the complexities of modern data, making it impossible for them to achieve the desired data accuracy.

Calculating the ROI on Data Accuracy

Calculating the return on investment for data accuracy can seem elusive at first, but the impact of poor data quality is evident. Businesses lose millions annually due to issues arising from outdated, incomplete, mismatched, and inaccessible data.

Consider the example of a logistics company that needs to match a million records obtained from three sources. Using traditional ETL tools, the company ends up with a significant percentage of false positives and negatives, leading to valuable funds being  lost in sales and manual data correction. 

Steps Towards Data Accuracy

To improve data accuracy, organisations should consider the following steps:

Conduct a data quality audit

Identify the top issues affecting your data quality. Common problems usually include duplicates, incomplete information, and data stored in various silos, many of which are obsolete or forgotten.

Measure the estimated impact and cost of fixing the data

Determine how many of your leads are usable and how much time your teams are spending on data verification. This will help you understand the revenue you’re losing and the cost of manually correcting the data.

Opt for an automated solution

You might need a data match solution to help remove duplicates and consolidate multiple data sets into a single, golden record.

Hire a data analyst and provide them with the right tools

Your data analyst should focus more on strategising rather than spending most of their time on data janitorial work. Equip them with the right resources to aid in data accuracy.

Focus on specific data sets

Performing a blanket operation on your entire database would be not only impractical but also inefficient. Prioritise the data that is immediately crucial for your operations.

Accurate data is the lifeblood of today’s businesses, and its importance cannot be understated. Companies need to move past the hurdles and understand that maintaining data accuracy is not just an option, but a business imperative. Doing so can significantly improve the bottom line, paving the way for informed decision-making, efficient operations, and enhanced customer satisfaction.


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