IBM estimates the U.S. economy loses over how much per year due to bad data?

• A. Over $3.1 trillion
• B. Over $100 billion
• C. Over $10 trillion
• D. Under $1 trillion

Answer: (A)

The main idea here is recognizing how costly poor data quality can be for the whole economy. IBM’s analysis puts the annual cost of bad data in the United States at over three trillion dollars. That figure is huge because small data problems—like inaccuracies, missing information, duplicates, or inconsistencies across systems—multiply across countless transactions, analyses, and decisions, wasting time, duplicating work, and leading to faulty business choices. Seeing it as about three trillion helps you grasp why investing in good data practices—validation, cleansing, governance, and reliable data flows—can have a big payoff. Numbers far smaller or larger wouldn’t match the scale IBM identifies, so this trillions-level estimate best reflects the scope of the impact.