How would you present mixed results to a board when some metrics improved and some didn't?
Model answer
Model answerMixed results are an honesty test. I'd never lead with the good news and bury the bad — boards see through it and it destroys trust. I'd open with the signal: 'Here's what the data says about business health and what we don't yet know.' I'd frame each metric in context: against our own forecast, against industry benchmark, against our business theory. I'd close with a recommendation, not a metric list.
Framework · Dashboard Design
- HHonesty first
Open with the signal, not the spin. Boards value candor over polished narratives - CContext, not just numbers
Against forecast, against benchmark, against your own theory — raw numbers are meaningless - UUnknown is valuable
What don't you know yet? Naming uncertainty builds credibility - RRecommendation required
Close with a point of view — what does this mean for strategy?
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