The Key to Good Decisions

The Key to Good Decisions

Summary

Bill Yeargin argues that the difference between good and poor decisions often comes down to the quality and treatment of data. Using historical and business examples — Neville Chamberlain’s Munich decision, the US intelligence on Iraq’s WMDs, the Challenger disaster, the 2008 financial crisis and New Coke — he shows how bad, filtered or misunderstood data leads to catastrophic outcomes.

Yeargin then sets out practical steps leaders can use to make decisions more data-driven: build a data culture, invest in reliable systems and dashboards, train people to interpret data, ensure data is considered in decisions (including one-off choices), and be candid about how much emotion shapes choices. He also highlights companies that have turned data into a competitive edge (Target, Amazon, Starbucks) while reminding readers data complements — not replaces — judgement and intuition.

Key Points

• Poor or misleading data has driven major historical and business failures (e.g. Chamberlain, Bush/Iraq, Challenger, 2008 crisis).
• Decisions can be harmed not only by bad data but by filtering — the right information failing to reach decision-makers.
• Organisations need a clear data-driven culture modelled by leaders for data to matter in practice.
• Create reliable systems (dashboards, agreed metrics, cross-department sharing) so everyone measures the same way.
• Invest in people: train users and hire internal data experts to build and interpret reports.
• Make sure data is consulted for one-off decisions as well as recurring ones; don’t assume only routine choices need metrics.
• Recognise emotional and behavioural drivers: a large share of decisions are emotional, so deliberately check emotions against the data.
• When used well, data creates huge value (examples: Target predictive analytics, Amazon dynamic pricing, Starbucks site selection).

Content Summary

The article opens with examples where bad data or filtered information produced poor outcomes: Chamberlain’s appeasement (misjudged Luftwaffe strength), US intelligence on WMDs in Iraq, and the Challenger O-ring warnings that didn’t reach the right people. Yeargin broadens the critique to corporate missteps such as the 2008 sub-prime data failures and consumer misreads like New Coke.

He then offers a concise playbook for leaders: create and model a data-driven culture; build dependable data systems and agree on metrics; develop in-house expertise and train staff; insist data is examined when decisions are made; generate specific data for unique decisions; and actively assess how emotion influences choices. The piece closes by emphasising that data is a force-multiplier for judgement, not a substitute.

Author style

Punchy. Yeargin uses sharp historical and corporate examples to underline his point and finishes with a straightforward, actionable checklist. If you lead people, capital or strategy, the argument is presented briskly and purposefully — read the detail if you want to avoid obvious, avoidable mistakes.

Why should I read this?

Short and practical — this one tells you how leaders keep from cocking things up when the stakes are high. It’s full of real-world examples and a no-nonsense checklist you can start using right away to make your organisation less likely to be blindsided by bad data.

Source

Source: https://ceoworld.biz/2025/11/16/the-key-to-good-decisions/