Despite decades of technological advancements, businesses still grapple with fundamental data quality issues: Is our data accurate, complete, and consistent? This ongoing challenge highlights why high-quality data is crucial for a data-driven enterprise. Without it, companies face inefficiencies, missed opportunities, and potential financial losses—issues no organization can afford.
According to Gartner’s Data Quality Market Survey, poor data quality costs companies an average of $15 million annually. The survey also found that inadequate data practices hinder digital initiatives, damage competitive positions, and erode customer trust. As data is reused in models and analytics, the financial impact of poor data quality can grow exponentially.
Companies should turn to their chief information officers (CIOs) to address these challenges. The role of the CIO has evolved significantly. No longer just responsible for maintaining IT infrastructure, today’s CIOs are integral to strategic planning and project implementation, particularly with the rise of AI. According to Deloitte, 63% of CIOs now report directly to the CEO, and compensation for CIOs has increased by an average of 7.5% in large enterprises and 9% in mid-sized enterprises from mid-2023 to mid-2024, reflecting their elevated status.
Despite this increased recognition, CIOs must master the fundamentals of data quality and prioritize data governance to leverage their influence effectively. Data governance, which often falls under the purview of the Chief Data Analytics Officer (CDAO), requires collaboration between multiple stakeholders, including the CIO. Successful governance involves integrating both business and technical perspectives.
Looking ahead, CIOs will face three critical issues shaping their roles over the next three to five years:
