Hours of manual work, done in seconds
Reporting Automation for Tanzanian Businesses
The report someone rebuilds by hand every week becomes a system that builds and sends it on schedule.
01 — The problem
Signs you need this
- 01.1
Reports are late when one person is away
- 01.2
The same figure differs from file to file
- 01.3
Month-end means late nights rebuilding the same workbook
02 — Deliverables
What you get
- 02.1
Scheduled and on-demand generation
On a timetable, or the moment someone asks.
- 02.2
Excel and PowerPoint exports
Formatted, in the files you already circulate.
- 02.3
Automatic delivery
Each recipient gets the version for their role.
- 02.4
Consistent every time
The same logic every run, so numbers can be reproduced.
03 — Sample
See it in a sample
Charts from our sample dashboards, with the decision each one supports.
Sample data — we never publish client dashboards
Sample lender’s reporting system · September 2026 · schedule for a sample Monday · TZS
SAMPLE DATA
- Reports delivered automatically
- 1,284
- In September
- Median generation time
- 38 s
- Last 14 runs
- Staff hours returned
- 212 h
- Estimate, against manual work
- Failed runs
- 2
- DoneBoth re-run the same morning
Fig. 03.1
Monday schedule
Five jobs run from 05:30 to 18:30.
05:30 Daily PAR report → 14 branch managers
05:58 Board pack (Mondays) → 9 recipients
12:00 Cash position
18:30 Daily close
07:00 Collections exceptions → agent drafts follow-ups
07:02 Follow-up note drafted → Head of Credit
- The PAR report reaches 14 managers at 05:30, before branches open.Decision: Managers start the day with yesterday’s numbers.
Source: DataHub sample data · TZS · Sep 2026
View as table
| Time (EAT) | Lane | Job |
|---|---|---|
| 05:30 | Reports | Daily PAR report → 14 branch managers |
| 05:58 | Reports | Board pack (Mondays) → 9 recipients |
| 07:00 | Alerts | Collections exceptions → agent drafts follow-ups |
| 07:02 | Agent | Follow-up note drafted → Head of Credit |
| 12:00 | Reports | Cash position |
| 18:30 | Reports | Daily close |
Fig. 03.2
Generation time, last 14 runs
Most runs took 35–41 seconds.
Run 14 · 36 s
- One run took 61 seconds against a median of 38.Decision: A slow run shows before it becomes a late report.
Source: DataHub sample data · TZS · Sep 2026
View as table
| Run | Seconds |
|---|---|
| 1 | 36 |
| 2 | 41 |
| 3 | 38 |
| 4 | 35 |
| 5 | 39 |
| 6 | 37 |
| 7 | 61 △ Slow run |
| 8 | 38 |
| 9 | 36 |
| 10 | 40 |
| 11 | 37 |
| 12 | 39 |
| 13 | 38 |
| 14 | 36 |
Every name and number here is invented.
Source: DataHub sample data · TZS · Sep 2026
04 — Questions
Questions about Automation
Q 04.1Can you automate reports we already build in Excel?
Yes. We rebuild your workbook’s logic as a system and keep the format people know.
Q 04.2Will our team lose control of the report?
No. It removes the typing, not the judgement: your team still sets targets, thresholds and recipients.
Q 04.3What happens when we need a new report?
Once the pipeline exists, a new report is a small job, not a new project.
05 — More services
