Analyze data to evaluate workplace programs

Analyze data to evaluate workplace programs — real work, not an imagined feature: named inside 7 evidenced career tasks. Below are four ready AI prompts for it, one per height of help: do it, make it easier to accept, decide when you are stuck, and change the pattern for good.

7career tasks name it
4prompt heights

The four heights

The same task, four distances: today's deadline, the next reviewer, the stuck moment, the pattern.

Execute — do the immediate task

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I need a summary analysis of workplace program data for Monday’s safety review. Pull together…
I need a summary analysis of workplace program data for Monday’s safety review. Pull together observations on incident frequency, near-miss rates, training completion, and corrective action closure over the past quarter. Present one clear sentence on whether the program is improving and one recommendation for the safety manager.

Improve — make it easier to accept

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Before I present to the safety committee, make the analysis easy to approve: surface the three…
Before I present to the safety committee, make the analysis easy to approve: surface the three metrics that changed most, flag any statistical anomalies, make the corrective-action backlog findable, and call out any data gaps that would make a skeptical manager push back.

Decide — diagnose the stuck moment

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Quarterly injury counts dropped 30% but recorded near-misses rose sharply in June. Training…

Our injury rate dropped but near-misses spiked last month

Quarterly injury counts dropped 30% but recorded near-misses rose sharply in June. Training completion is steady and one supervisor reports underreporting historically. I can’t tell if reporting improved or risk actually increased. What is the likely diagnosis and the single best next action to recommend to the safety manager?

Become — change the pattern

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Across multiple reviews we keep showing up with a growing corrective-action backlog: items are…

We keep missing closure on corrective actions

Across multiple reviews we keep showing up with a growing corrective-action backlog: items are opened but not closed within agreed timelines, undermining credibility with leadership. Recommend one habit change for owners, one tracking metric that makes overdue visible, and one governance step to enforce timely closure.

Where the evidence lives

Who was seen doing this, and what people really ask.

Software tasks in the LLOS Work Atlas come from evidence, never a feature list: careers attested to do the work, real job descriptions, and the questions people actually ask (with their view counts). Facets — feature, workflow, troubleshoot, administer, deploy, scale — are open metadata: the work decides, not a taxonomy.
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The rest of the map

Same library, five ways in.