AI did not end the data literacy crisis. It changed it. As machines move from providing information to interpreting it and recommending what to do, the scarce skill is becoming judgment: knowing what to trust, what to question, and what decisions are still ours to make.
Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Feeling sure doesn't mean you're right. Learn five simple ways to question what feels true, spot what might be influencing you, and make better decisions about what to believe.
Organizations often pride themselves on being "data-driven." Yet many struggle to translate their vast data collections into meaningful business impact. The key to unlocking this value lies in understanding the fundamental difference between data and analytics—a distinction that shapes how organizations derive value from their information assets.
Think of data as the raw material in a manufacturing process. Just as a furniture maker needs wood, organizations need data. But having a warehouse full of wood doesn't automatically create beautiful furniture—similarly, having databases full of information doesn't automatically generate business insights.
Data represents the basic facts and figures about our business operations. When a customer makes a purchase, we capture data: the time of sale, items bought, price paid, and payment method. When an employee completes a task, we record data: completion time, resources used, and quality metrics. When a machine operates, it generates data: temperature readings, performance metrics, and maintenance records.
However, this data in its raw form tells us very little. A list of transaction timestamps and amounts can't tell us whether our business is healthy. A collection of temperature readings can't tell us if a machine needs maintenance. This limitation brings us to the transformative power of analytics.
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Evidence does not make decisions. People interpret it, weigh it, challenge it, and make judgments. A courtroom reveals what leaders can learn about evidence, expertise, confidence, and data-informed decision-making.
Feeling sure doesn't mean you're right. Learn five simple ways to question what feels true, spot what might be influencing you, and make better decisions about what to believe.
We teach data literacy as a ladder: data at the bottom, wisdom at the top, climb step by step. But the rungs are not where the work happens. The judgment lives in the gaps between them, and that is exactly where AI now carries us straight past.
Every organization keeps one scoreboard for mistakes and none for missed opportunities. So people optimize the one they can see, and the largest losses never appear as losses at all. They appear as things no one tried.
