Normal workflow
Sources connect, KPI logic runs, dashboards refresh, exceptions highlight, and review is scheduled.
Use case
Management Reporting Automation
Reports are built after the decision window has moved.
Workflow model
Normal workflow first. AI assistance only when the path breaks.
Where the workflow breaks
A KPI definition, source mismatch, or data freshness issue makes the view unreliable.
What AI prepares
Explain the variance, identify the source issue, and draft the review note.
What humans approve
KPI definition changes and management release decisions need approval.
What becomes a reusable rule
Repeated report questions become KPI definitions, data checks, and review rules.
Why status quo fails
Manual coordination cannot create reliable control.
Reports are assembled after the decision window has moved.
KPI definitions vary across teams.
Source data needs manual cleanup.
No one owns report freshness.
Workflow Layer
The workflow becomes a controlled sequence.
Collect data from source systems, clean it, calculate KPIs, and refresh management views.
Sources connected
Data validated
KPIs calculated
Dashboard refreshed
Exceptions highlighted
Review scheduled
Core features
What the system needs to do.
Data pipeline
KPI definitions
Validation rules
Refresh schedule
Exception dashboard
Connected tools
Tools that can participate in the flow.
Accounting systemBusiness suiteSpreadsheetBI dashboardCustom dashboard
Expected outcome
Better decision speed and visibility.
Implementation
Define management questions
Implementation
Map source systems
Implementation
Create KPI logic
Implementation
Build and validate dashboard refresh
Next action
Build Management Reporting
Tell us where this workflow currently breaks. We will map the AI assistance, approval gates, and first build path.