In today’s digital age, data quality is of paramount importance for business to make informed decisions, deliver personalized experiences to customers, and drive growth. However, maintaining data quality can be challenging, and it is often difficult to measure the return on investment (ROI) of data quality initiatives. This blog explores the significance of data observability, how it can mitigate the risks of bad data, and ways to measure its ROI. By understanding the impact of bad data and implementing effective strategies, organizations can maximize the benefits of their data quality initiatives.
Bad data can have damaging consequences, leading to incorrect decisions, financial losses, legal implications, and reduced team productivity. Poor data quality often results in strategic decisions such as misguided investments that harm a company’s performance. The cost of data quality issues varies across organizations, with the average cost estimated at 13 million dollars annually according to a 2021 Gartner report.
For example, in 2022, Unity Software reported a loss of $110 million in revenue and $4.2 billion in its market cap. “Consequences of ingesting bad data from a large customer”, the company stated. Similarly, bad data caused Equifax, a publicly-traded credit reporting agency, to send lenders inaccurate credit scores on millions of customers.
Data quality issues can result in various problems, including loss of trust in data, reduced team productivity and morale, non-compliance with regulations, and diminished quality of decision-making. Siloed data within departments or business units makes it challenging to gain a holistic view of the organization’s data landscape. This can lead to ineffective decision-making, hinder data culture, and jeopardize compliance with regulations like GDPR and HIPAA. Moreover, data teams can become frustrated by spending excessive time troubleshooting data issues, negatively impacting their job satisfaction and potentially leading to employee churn.
Data observability is a solution to proactively monitor and maintain the health of data throughout its lifecycle. By implementing logging, tracing and monitoring techniques, organizations gain visibility into data streams, quickly identify and troubleshoot data quality issues, and prevent disruptions to analytics dashboards. Data literacy, involving sourcing, interpreting, and communicating data, is essential for decision-makers to translate data into business value effectively. Cultivating a data-driven culture and investing in the right tools are crucial steps towards achieving data quality through data observability.
Measuring the ROI of data observability helps business leaders understand the value and benefits associated with investing in this practice. Several quantifiable metrics can serve as a starting point for evaluating the cost of bad data, including the rate of occurrence or number of incidents per year, time to detection, and time to resolution. These metrics provide insights into the frequency and efficiency of identifying and resolving data quality issues:
Additionally, non-quantifiable metrics such as effective decision-making, preservation of data trust, regulations compliance, and satisfaction of the data team, contribute to the overall value of data observability:
By addressing these aspects, data observability not only provides quantitative benefits but also safeguards against data issues, promotes trust, ensures compliance, and supports a productive and satisfied data team.
Data quality issues significantly impact businesses, leading to wasted resources and missed opportunities. Investing in data observability is essential to prevent and mitigate the risks associated with bad data. By leveraging quantifiable metrics and considering non-quantifiable factors, organizations can measure the ROI of data observability and demonstrate its value to decision-makers. Ensuring data trust, promoting effective domain decision-making, complying with regulations, and fostering a satisfied data team are all critical aspects of maximizing the benefits of data quality initiatives. Embracing data observability is a strategic investment that safeguards the accuracy, reliability, and utilization of data in today’s data-driven world.
