Sponsors carry a change with a few vivid, true stories of failure under the old way and success under the new, and put the actual rates on the table beside them.
Borderline: whether this move is justified depends on the situation, and only the person in it can judge.
An example
Forty pages of business case for replacing an electric and gas company's outage management system had moved nobody in two steering meetings. For the third, the chief operating officer opened with two stories, both checked with the crews involved: a storm night when the old system sent a crew to the wrong substation for forty minutes, and a pilot crew that restored a hospital feeder in record time with the new tablets. The next slide gave the rates. The old system had dispatched correctly on 99.6 percent of calls over five years, its failures clustered in storms, and the pilot had two failures of its own in its first month. The case for replacement rested on the storm cluster. The steering group approved it, and the crews told both stories at the rollout sessions.
Why it works
Vivid, checkable stories make the new system's benefits feel concrete and the old system's risks feel real, so the change looks better and staying put looks worse. Defending the status quo against a remembered failure is also costlier than defending it against a spreadsheet. Putting the rates beside the stories keeps the case honest and makes it sturdier, since a data team or long-tenured staff with their own memories will check. It depends on real raw material, repeated venues for telling it, and stories that match what employees know firsthand.
The thinking behind it
Amos Tversky Judgment under Uncertainty: Heuristics and Biases (1974), by Tversky and Kahneman, describes availability: people judge how frequent something is by how easily instances come to mind. A vivid, true story about a crew sent to the wrong substation is easy to recall, and it makes failures feel common whatever the rate. The story moved people a forty-page model did not, and putting the rate on the next slide keeps the judgment of frequency honest.
Cass R. Sunstein Availability Cascades and Risk Regulation (1999) describes a self-reinforcing process in which a belief gains plausibility the more it is repeated in public, fed in part by people who promote it deliberately. Repeating the same two stories in every forum starts such a cascade. Keeping the rates attached to each telling is what stops the stories from turning into the belief that failures are the norm.
When it fits
Cases that are sound in the numbers but have failed to move people suit it, especially where decision-makers are tired of models. You need true stories you can verify with the people in them, the rates to set beside them, and forums where the stories will be repeated.
How to use it well
Choose stories that are true, recent, and representative of the pattern you are arguing about, and check each one with the people involved.
- Pair every story with the rate it illustrates: how often, compared with what, over what period.
- Include a story that cuts against you if one exists, such as a pilot failure.
- Let the people in the stories tell them where possible.
- Keep the repetition honest. The same story told everywhere should still carry its numbers.
If the rates do not support the story, change the case or drop the story.
What it costs and where it backfires
Stories work until someone with a longer memory tells a different one, and a sponsor caught overselling loses the room for good. Counter-anecdotes turn the debate into a contest that the side with the larger communications budget tends to win, which can make your case look like propaganda. The move holds up only while the rates stay beside the stories. Letting a rare failure stand in for the norm, or leaving out figures someone has asked for, conceals material facts from the people deciding.
When it is used on you
Put the denominator in the room: ask how often the failure happens, how peers compare, and how the new system did in its pilot. Ask whether the cited incidents share a root cause that a targeted fix would address, and avoid trading counter-anecdotes.