Management report generation
Finance teams spend five to ten days a month building management packs: pulling numbers from multiple systems, writing narrative commentary and chasing variance explanations.
AI pulls approved figures from the data warehouse, drafts narrative commentary in your house style, and flags variances for finance business partners to review.
- 01
Numbers come from your approved data warehouse, not ad-hoc queries, so lineage is auditable.
- 02
Narrative commentary is drafted against historical pack examples, maintaining your tone and structure.
- 03
Variances above a threshold are surfaced with supporting context and a suggested line of enquiry.
- 04
A finance partner reviews and approves before the pack is circulated.
- 05
The approved pack is versioned and stored so month-over-month comparisons are trustworthy.
freeing three to five FTE days per month for higher-value analysis.
Ranges drawn from production deployments and public enterprise benchmarks. For a specific rupee or dollar figure tailored to your volume, use the calculator below.
Prerequisites for a clean deployment.
- A data warehouse with clean, reconciled P&L data
- Six months of prior MI packs as examples
- Agreed variance thresholds and commentary style
- A finance business partner to own the review step
Put your own numbers on it.
“At 80 reports a month and a loaded monthly cost of ₹1,50,000 per person, management report generation would typically save ₹4.0 L to ₹5.4 L a year.”
Range uses this use case’s typical automation rate (60 to 80 percent) against the baseline time per task for reporting work, with your cost per person converted at 160 working hours a month.