Pronto Xi Analytics

Analytics projects stall when every reporting problem is treated as the same problem. Board reporting, sales performance review, replenishment planning and daily operational exceptions all have different cadence, audience and drill-down requirements. We help clients decide when Pronto Xi Analytics is enough, when Phocas is the better fit for self-service analysis, when Cognos is the right tool for governed enterprise reporting, and when a semantic model on Pronto PostgreSQL makes more sense for Power BI or Tableau.

• Executive packs and governed reports need stable definitions, version control and handover discipline
• Operational dashboards need timely refreshes, simple drill paths and clear ownership
• Self-service analysis only works when dimensions, hierarchies and KPI logic are agreed upfront

Most trust issues in reporting are not caused by the visual layer. They come from mismatched item masters, inconsistent customer groupings, unclear gross margin logic, missing dimensional fields, or business rules that live only in one analyst's spreadsheet. We surface those issues early, document the reporting logic, and design the model around definitions the business is prepared to own.

• Common remediation work includes customer hierarchy clean-up, product categorisation and GL mapping review
• We document calculation logic so finance, sales and operations can validate the same numbers from the same source
• We design exception reporting as well as dashboards, so teams can act on problems instead of only seeing them

A dashboard project is only useful if the internal team can keep it current. We build with handover in mind: refresh logic, security, naming standards, documentation and user training are part of the engagement, not afterthoughts. That makes it easier to extend the model later without rebuilding the reporting stack every time a new KPI or business unit is added.

• User training focuses on how to interpret metrics, not only where to click
• Documentation covers data sources, refresh timing, definitions and ownership
• Phased rollout is often safer than a single large BI release because teams can validate logic incrementally