Dashboard
Finance leadership dashboard
P&L, cash, balance-sheet drivers, and forecast.
- Connected to GL/ERP, FP&A planning, AP/AR, payroll, and operational systems
- Thresholds and owners
- Drill to operational detail
Industry analytics
Finance packs fail when GL balances, FP&A forecasts, and AR/AP subledgers disagree on company/period grain and FX. We build Power BI close packs with marked date tables, documented FX rules, and Import refresh that finishes before the flash meeting, with SOX-aware access controls on certified close datasets.
Typical friction when CRM, ERP, and operational tools are reported separately.
What changes when those systems feed a governed Power BI model.
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Commercial considerations
Finance organizations already manage the business in GL/ERP, FP&A planning, AP/AR, payroll, and operational systems. The reporting problem is usually not “we need another chart”—it is that CRM, ERP, and operational extracts disagree on timing, filters, and owners before every meeting.
Close and forecast still depend on ledger extracts pasted into workbooks—so variance commentary starts late. Power BI for Finance Teams only works when those systems of record feed one governed semantic model with documented KPI definitions.
Power BI Analytics scopes the first release around the finance decisions that currently wait on manual packs—then connects the right source systems, validates totals, and lands the report in a real operating cadence.
Built for leaders who need dependable numbers in real operating conversations—not another unused dashboard.
We establish a baseline before delivery so ROI is discussed in operating terms, not slideware.
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Measure hours currently spent assembling finance reporting packs, reconciling totals, and answering “which number is correct?”
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Track how many days earlier leaders can see exceptions, variances, or forecast risk after the release.
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Count disputed metrics, failed refreshes, and unmanaged workbooks replaced by governed models.
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Confirm the intended audience actually uses the report in the meeting or process it was designed for.
Close and forecast still depend on ledger extracts pasted into workbooks—so variance commentary starts late. Power BI consulting connects these systems of record into one governed reporting model.
P&L, balance sheet, actuals
budget, forecast
payables, receivables, cash timing
people cost
volume drivers behind the P&L
Earnings before interest, tax, depreciation, and amortisation.
Cash from operations with AP/AR drivers.
Actual vs approved plan from GL + FP&A.
Collection speed for trade receivables.
Recommended dashboards
Power BI for Finance Teams patterns we tailor to your systems, owners, and review cadence. Click any preview to expand.
Dashboard
P&L, cash, balance-sheet drivers, and forecast.
Dashboard
Close status, variances, and commentary workflow.
Reporting only creates value when it lands in a real review rhythm.
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Buyer questions answered
Connect the systems you already use and leave with a clear place to report—before another orphan dashboard appears.
Build 1–2 live dashboard pages that pull from multiple sources—not a screenshot of Excel pasted into Power BI.
Retire the Monday email of pasted workbooks: scheduled refresh and one pack finance can open without stitching tabs.
Data Warehouse Design starts by killing contradictory extracts—then publishes measures that data leaders, IT managers, and executives can defend from multiple operational systems and historical data.
Loss ratio and claims cycle time from policy + claims systems: connect policy admin, claims, distribution CRM, finance, and actuarial systems so leaders manage underwriting performance, claims outcomes, and distribution insight.
NOI, occupancy, and collections from PMS + leasing + GL: connect property management, leasing CRM, accounting, and maintenance systems so leaders manage asset performance, leasing, portfolio risk, and cash flow.
Utilization, WIP, and delivery margin from PSA + CRM—one staff-week grain: connect PSA, CRM, timekeeping, accounting ERP, and resource planning so leaders manage utilization, delivery margin, pipeline, and client health.
Talk through priorities, data sources, and a practical first Power BI release.