A workforce dashboard that refreshes every hour

Your team updates a 21-tab workbook by hand every day. You want this month against last month, and nobody has time to build it.

Philippine manpower agencyWorkchestra client
Hourlyrefresh, fully unattended
21workbook tabs read every run
0changes to the client's workflow
In their shoes · Management at a manpower agency

Before and after.

A manpower agency tracked deployed staff, attendance, hires and attrition for a dozen client sites in a large Excel workbook updated by hand. Management wanted week-on-week and month-on-month comparisons, but changing how the team worked was not an option.

  • A 21-tab workbook updated by hand
  • 8 recruiter sheets with no combined view
  • No week-on-week or month-on-month comparisons
How it works

What we built, step by step.

Step 1

Read the workbook as it is

Every hour, the live workbook is read as is. Odd headers, half-filled rows and shifting tab names are handled.

Step 2

Work out the numbers

Headcount against target, attendance, hires against attrition and month-on-month changes, with full daily history for any date range.

Step 3

One recruitment funnel

Eight recruiter sheets merge into one funnel, with each recruiter shown by number at the client's request.

Step 4

Monday report in the inbox

Every Monday, management gets a short emailed report. Code works out every number, and AI only writes the summary.

Hourlyrefresh, fully unattended
21workbook tabs read every run
0changes to the client's workflow
The full story

From busywork to running on its own.

The problem

A manpower agency tracked deployed staff, attendance, hires and attrition for a dozen client sites in a large Excel workbook updated by hand. Management wanted week-on-week and month-on-month comparisons, but changing how the team worked was not an option.

What we built

We built an hourly job that reads all 21 tabs exactly as they are, cleans the messy rows, and works out headcount, attendance, hires, attrition and month-on-month changes. Eight recruiter sheets feed one recruitment funnel, and every Monday management gets an emailed report where code does the math and AI only writes the short summary.

What changed

Management can compare any period, refreshed every hour, while the operations team keeps the same workbook. Showing attrition as a monthly rate revealed that much of the new hiring was replacing people who left, which moved the focus to retention.

Built withn8nSheetJSDockerCaddyOpenAI

Built for a Workchestra client. Names and numbers in the screens are samples; the results are real.

Want this for your team?

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Case studies

Keep exploring the work.

18 case studies from real teams. Each one started with a team doing the same task by hand, every day.

Case study 01Workchestra client

More than 1,200 candidates are routed and traceable from first contact to orientation, with nothing retyped by hand.

Philippine manpower agencyRecruiters and the agency's management1,200+candidates routed and tracked
Case study 03

Response time dropped from hours to under 60 seconds, with no manual data entry.

Regional online marketplaceAccount managers and their sales lead< 60 sfrom ad form to CRM record
Case study 04

Every thread, meeting and client session now has one source of truth.

US executive coaching firmA CEO and his executive assistant3ranked time slots per request
Case study 05

802 at-risk accounts, 35% of the 2,267 in scope, got a timely personal message in a single run.

Regional online marketplaceAccount managers with hundreds of accounts802at-risk accounts messaged in one run
Case study 06

Research that took 20-30 minutes now finishes in under 2 minutes.

Regional online marketplaceAccount managers preparing for first calls< 2 minto research one company
Case study 07

Decisions take seconds because each card carries its own context, so anyone on the team can act.

US executive coaching firmThe CEO's team reviewing AI workHourlyAI runs reviewed in one place
Case study 08

3.04 TB and 36,118 files moved, preserving about seven years of client history in the firm's own storage.

US executive coaching firmA firm with years of session recordings3.04 TBmigrated end to end
Case study 09

Every lead gets an instant reply, at 2 PM or 2 AM.

Regional online marketplaceSales reps and account managers5qualifying questions asked automatically
Case study 10

Nobody pulls report data by hand anymore, and the team saves 8-10 hours a week.

Regional online marketplaceA marketing team running ads in two markets0manual data pulls
Case study 11

The mastersheet updates itself, so nobody runs VLOOKUPs.

Regional online marketplaceThe ops person who owns the mastersheet3data sources joined automatically
Case study 12

Coaches get overviews the same day and can turn one into a client email draft with a single button, now rolled out to every coach.

US executive coaching firmCoaches following up after client sessions8kinds of AI mistakes checked
Case study 13

A spoken note becomes a review-ready draft in under 30 seconds.

Internal teamAn executive who thinks faster than they type< 30 sfrom voice note to email draft
Case study 14

Both markets start the day with an enriched, cleaned lead list, and existing clients never reach sales.

Regional online marketplaceSalespeople who should be selling300leads discovered per run
Case study 15

Every submission is classified within seconds, before the sales team opens the file.

Regional online marketplaceSales reps calling new sign-ups< 2 sto verify each submission
Case study 16

A 2-day, 4-person process became one click.

Regional online marketplaceA sales manager approving monthly results1 clickto approve, down from 4 people and 2 days
Case study 17

Every request gets an answer within seconds and lands on the calendar, so nothing falls through the cracks.

Internal teamThe one builder everyone messages0requests left unacknowledged
Case study 18

The content team gets polished Google Docs drafts in both languages on schedule.

Regional online marketplaceA content team serving two markets2languages written at the same time