The cost of waiting for perfect data.

0:00 - Intro / Oracle Study

A 2023 Oracle study across 14,000 employees and business leaders found 72% say data volume, and their lack of trust in it, stops them from making a decision.

3:17 - Cost of Waiting for Perfect Data
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McKinsey puts the cost of slow and stalled decisions at 530,000+ lost working days and roughly $250 million in wasted labour a year for an average Fortune 500 company, with indecisive teams taking up to 40% longer to deliver.

6:30 - Data Trust & Quality
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Distrust usually comes down to not knowing a number's lineage: who touched it, how old it is, and whether it was ever cleaned up. Data needs the same housekeeping as anything else, or it quietly loses credibility.

9:08 - Unstructured Data & New Sources
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80% of the world's data is unstructured, documents, emails, PDFs, video, audio, and in industrial environments it outweighs even sensor data. The opportunity isn't collecting more, it's finally using what's already there.

13:18 - Real-Time vs Historical Data
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Which matters more depends on the decision. Predictive, AI-driven insights need the freshest data available, but historical data still drives things like accurate bid pricing and margin protection.

18:20 - Risk Frameworks
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Financial risk gets measured constantly, but the psychological cost of indecision rarely does. Undigitized paper records, well logs, land records, decades of archived data, carry their own risk since they can't be recreated if lost.

19:09 - Analysis Paralysis & Good Enough for Now
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A framework for setting tolerance thresholds that match data quality to the risk of the decision, so teams stop chasing certainty they don't actually need.

21:15 - Closing Thoughts & Charter
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Better data matters, but waiting for perfect data becomes a very expensive habit. Charter helps industrial companies identify the decisions that matter most and prioritize practical data integration over a full overhaul.