KPIs, scorecards and dashboards that build and keep themselves current.
Phyllis builds and extends your whole analytics operation — any KPI, breakdown, target or dashboard — grounded in your live instance and staged for your approval.
Assess how we measure the service desk today and where our KPIs and dashboards have gaps.@ for records · / for commands
acmedevProject Analytics, end to end. Analyze, plan, develop, maintain.
The same loop on every build — grounded, planned, built and kept healthy, with every change staged for your approval.
Grounded in your instance
Phyllis reads your live tables, flows, ACLs, and update sets — every answer cited to the record it came from.
CMA-grade documentation
A signed design document alongside every build — discovery findings, impact analysis, every claim cited.
Approval-gated delivery
Every change staged in a scoped update set with the design doc, Instance Scan, and ATF results attached — nothing ships without you.
Self-heal on your approval
Hundreds of Instance Scan checks after every dev task. Phyllis stages the fix; you sign off; the finding closes.
Ask it in your own words.
A few of the requests teams start with.
Show me which KPIs we already track for the service desk and where the data comes from.
Create a KPI for average incident resolution time, collected daily.
Track a count of open high-priority incidents so I can watch the backlog.
Let me slice the resolution-time KPI by assignment group and by priority.
Set a four-hour target for first response and warn me when we miss it.
Show the SLA-compliance trend over the last twelve months.
Build a percentage KPI for SLAs met versus total from the counts we already collect.
Give the team a scorecard showing each KPI against its target.
Stand up a service-desk dashboard with the resolution KPI, a priority breakdown and the SLA trend.
Make sure these KPIs actually collect on schedule.
Share the service-desk dashboard with the support team, view-only.
Inventory the reports and dashboards we have today before I design a new one.
Questions? We’re glad you asked.
What does Phyllis actually build for analytics?
The setup behind your numbers: the KPIs and metrics you want to track, the targets you measure them against, and the dashboards, scorecards and trend charts that make them easy to read.
The measured results themselves stay read-only. Phyllis configures the reporting engine that tracks your data; she doesn't hand-enter the figures.
Will a new KPI actually show data, or just sit there empty?
It shows data. A KPI that never gets populated is the number-one cause of "I built it but nothing appears", so Phyllis sets up each metric to collect on the right cadence and confirms real numbers land on the tile before calling it done.
Daily measures fill in daily, and trends build up over time so you get a live picture rather than a blank chart.
Can she set targets and thresholds, not just track the raw number?
Yes. Phyllis defines the goal for each KPI — whether higher or lower is better — so every metric reads against its target and a miss is obvious at a glance.
Trend charts show whether you're moving toward the goal or away from it, not just where you stand today.
Nothing is deployed without my approval, right?
Correct. Phyllis explores, proposes a plan, and only builds once you approve. Every change is staged for review and is reversible, and she never finalises or promotes anything on her own.
Any fixes she spots afterward are held for your sign-off before they run.
How do I trust her findings?
Every claim is cited to your own live instance — the metrics you already have, the data behind each one — rather than assumed from out-of-box defaults.
That matters on migrated instances, where reporting often drifts far from the shipped baseline. You see the evidence, not a guess.
