Metric definition
Agree what each measure means, who owns it and which records count.
Dashboards, Analytics and Reporting
Make the important operational signals visible.
Create dashboards and reporting workflows around trusted definitions, refresh ownership, exceptions and decisions.
When this fits
Recognize the operational signals.
Leadership receives reports too late
Different teams calculate the same metric differently
Exceptions are buried in tables
Reports require repeated cleanup
Expected direction
What should become clearer or easier.
Agreed metric definitions
A traceable source-to-dashboard model
Decision-focused views
Clear refresh and ownership rules
Workstreams
How this engagement is structured.
The exact sequence depends on scope, but each workstream has a clear operational purpose.
Data preparation
Clean, map and structure the source data for repeatable reporting.
Dashboard design
Create views for decisions, trends, exceptions and accountable next actions.
Reporting operations
Document refresh schedules, distribution, access and issue ownership.
Indicative outputs
Concrete artifacts, not vague consulting.
Metric dictionary
Source data map
Power BI or Looker Studio dashboard
Exception views
Scheduled reports
Refresh and access notes
Technology approach
Tools follow the operational requirement.
Power BI, Looker Studio, SQL, Excel, Google Sheets and approved connectors are selected according to data size, sharing needs and maintenance capability.
Discuss this serviceScope clarity
Important boundaries.
A dashboard cannot repair an undefined or unreliable source process
Licensing and connector costs are separate
Sensitive data needs access and retention controls
Questions
Before starting this engagement.
Yes. The source model, metric definitions, refresh process and user decisions are reviewed first.