AccAnalysisAccAnalysis
Revenue Cycle & Financial Operations

Twenty-five recurring tasks, taken off a team that should be analysing

An analytics team was spending its week on repetitive preprocessing, report generation and distribution. We automated twenty-five-plus workflows so the team's capacity went back to analysis.

At a glance
Status
Delivered
Region
United States
Engagement model
Shared specialists

Status: Delivered. Described from our own delivery records. Client identity, brand and commercial terms are withheld. Figures, where given, cover the period stated and nothing beyond it.

The organisation

Context

A data and analytics function inside a revenue-cycle operation. Most of its recurring work was not analysis: it was preparing data, refreshing and generating reports, and distributing them to the right destinations.

Each individual task took around half an hour. There were a great many of them.

The brief

The problem

  • Recurring tasks consumed a significant share of the team's week, every week.
  • Because the work was manual, it competed with analysis for the same hours — and analysis lost, since the recurring work had deadlines.
  • Consistency depended on whoever ran the task that day.
  • Distribution to email, document stores and file transfer destinations was a separate manual step at the end of every task.
The work

What we built

Twenty-five-plus automated workflows

Covering preprocessing, report refresh, generation and distribution — each replacing a task that had been performed by hand on a schedule.

Pipeline automation and stored procedures

For the data preparation steps and the database-side work, so the logic lives where it belongs rather than in a person's routine.

Automated report refresh, rendering and distribution

To email, document storage and file transfer destinations on the correct cadence.

Method

How we delivered it

  1. 1

    Inventory the recurring work

    Every task, its frequency, its duration and its destination. Ranked by total hours, not by how annoying each one felt.

  2. 2

    Automate in order of that ranking

    So the largest returns land first.

  3. 3

    Run each automation alongside the manual task

    For a cycle before retiring the manual version.

  4. 4

    Instrument

    Every automated run reports success or failure to a named owner.

  5. 5

    Hand over

    With documentation, so the team can extend the pattern themselves.

Sequence

How it was phased

PhaseDurationWhat happens
1Inventory & ranking
1–2 wks

Every recurring task, timed and ranked

2First automation wave
3–4 wks

Highest-volume tasks, run in parallel

3Subsequent waves
6–10 wks

Remaining workflows, batched by pattern

4Monitoring
1–2 wks

Run reporting, failure alerting, ownership

5Hand-over
1 wk

Documentation and pattern transfer to the team

Indicative phasing for work of this shape. Actual duration varies with data quality, access and decision speed.

Hand-over

What the client keeps

  • All automation definitions and pipeline code in their own repository
  • Stored procedures documented
  • Run-monitoring configuration
  • The task inventory that drove the sequencing
Stack
Power Automate (cloud and desktop)Python ETLSQL stored proceduresPower BI paginated reportsSharePointSFTP
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