The Data Analyst
a.k.a. Reporting Analyst · BI Analyst · Performance Analyst
Turns operational data into actionable visibility.

Who they are
Where the data analyst runs the day from the desk.
Turns operational data into actionable visibility.
Software relationship: daily
Goals · what “good” looks like
- ▸Clear operational visibility teams actually use
- ▸Earlier problem detection through alerts
- ▸Better data-driven decision-making
Who shows up · how they think
Demographics & mindset.
Demographics
Typical MBTI types
the temperaments we keep meeting in this seat
A day with the data analyst
Wake to bed.
11 waypoints. 2 peak-stress hours.
Wake
Coffee, dog out, laptop open at the kitchen table. Opens the alerts inbox — first-time-fix dropped 4 points week-over-week on the residential HVAC team, and the dispatch-to-billing reconciliation flagged 23 jobs out of sync overnight.
Commute
Train into the office with headphones on. Sketches the FTF investigation in a notebook — by tech, by job type, by day-of-week — before he touches a query. Pen catches the question faster than the keyboard.
Anomaly dig
At his desk. Pulls the FTF drop into the warehouse query tool — two new techs onboarded three weeks ago, both running 60-something percent on heat-pump diagnostics. Not a system problem. Not a data problem. A training signal. Writes it up in three bullets before the 10 a.m.
Scorecard with the GM
Thirty minutes with the GM and the Service Manager. Walks the FTF drop, the two-tech root cause, and the recommendation — pair them with a senior on heat-pump calls for two weeks. Holds back the seven other dashboards he could show; the room only needs the one decision.
Reconciliation cleanup
Back to the 23 out-of-sync jobs. Traces them to a dispatch software update Friday that broke a webhook payload field. Files a ticket with the Systems Administrator with the failing payload attached, then writes a temporary nightly script to backfill until the fix lands. Notes the upstream cause in the data-quality log instead of just patching the symptom.
Lunch
Salad bar across the street with a coworker from finance. Twenty minutes, no laptop. Talks about her kid starting kindergarten.
Dashboard build
Membership churn dashboard the Sales Manager asked for last week. Three charts, not nine — renewal rate, churn by tenure cohort, churn by service history. Deletes two metrics that were locally interesting but didn't drive a decision. Ships it to a staging link for review.
Forecast review
Pairs with the Operations Manager on the Q3 capacity forecast. Walks the call-volume model, the assumptions on the new Installer crew, and the two scenarios — base and aggressive. Logs the assumption changes in the model notes so next quarter's review can see what moved.
Data quality routine
Runs the weekly hygiene check. Three job records with negative duration (clock punch errors), eleven with missing zip codes from a CSR shortcut. Pings the CSR with the eleven and the screen path that caused it — the fix is upstream, not in his query.
Close-out
Sends the GM the FTF brief in writing so the recommendation lands in the Tuesday huddle. Confirms the membership dashboard review with Sales for tomorrow morning. Reconciliation script queued, data-quality items routed.
One last look
Couch, laptop on his knees for ten minutes. Checks the overnight reconciliation ran clean, closes it. Reads twenty pages of a novel before bed.
What they own · where they slip
The job, frankly.
Core duties
what’s on their plate every week
Where they trip
watch for these, they’re common
What makes them a champion
Connect operational data from dispatch, field, billing, and customer systems into one analysis.
Career map · the ladder in and out
Where they came from, where they’re headed.
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