bpa-financial-performance

name	bpa-financial-performance
description	Analyzes financial performance data from Dynamics 365 Business Performance Analytics. Covers income statement (P&L), revenue breakdown, gross margin, EBITDA, operating expenses, cost of goods sold, and profitability by dimension (legal entity, department, cost center). Use when asked: "show me the P&L", "what is our gross margin", "revenue by department", "how is profitability trending", "compare revenue this year vs last year", "show income statement", "what is our EBITDA", "operating expenses breakdown", "net income analysis", "financial performance by legal entity", "profit margin by product".
license	MIT
metadata	{"author":"Dynagile Consulting","version":"1.0","domain":"Finance / CFO","bpa-coverage":"Record-to-Report"}

BPA Financial Performance Analysis

What This Skill Does

Queries the Business Performance Analytics dataset to analyze income statement data including:

• Revenue recognition and breakdown (by period, dimension, entity)
• Gross profit and margin calculation
• Operating expense analysis (by category, department, cost center)
• EBITDA and net income computation
• Year-over-year and period-over-period comparisons
• Profitability trending across multiple fiscal periods

Prerequisites

• BPA connector active (uses get_bpa_dataset_schema and execute_dax_query tools)
• User must have BPA User role in the Power Platform environment
• Data refreshes twice daily; queries reflect data as of last refresh

Workflow

Step 1 — Discover the schema

Call get_bpa_dataset_schema to identify:

• Revenue and income statement tables/measures
• Available date dimensions (fiscal period, fiscal year, quarter)
• Legal entity and dimension filters available

Step 2 — Clarify scope with user (if not provided)

Ask for:

• Time period: fiscal year, quarter, or specific months (e.g., "FY2024", "Q4 2024", "Jan–Mar 2025")
• Granularity: summary total, monthly trend, or by dimension
• Dimensions: legal entity, department, cost center, or all consolidated
• Comparison: single period, YoY, or period-over-period

Step 3 — Execute DAX query

Build and run a DAX query using execute_dax_query. Follow these patterns:

P&L Summary (total revenue, gross profit, net income):

EVALUATE
SUMMARIZECOLUMNS(
    'Date'[FiscalYear],
    'Date'[FiscalPeriodName],
    "Total Revenue", [Total Revenue],
    "Cost of Goods Sold", [COGS],
    "Gross Profit", [Gross Profit],
    "Gross Margin %", DIVIDE([Gross Profit], [Total Revenue]),
    "Operating Expenses", [Total Operating Expenses],
    "EBITDA", [EBITDA],
    "Net Income", [Net Income]
)
ORDER BY 'Date'[FiscalYear], 'Date'[FiscalPeriodName]

Revenue breakdown by department:

EVALUATE
SUMMARIZECOLUMNS(
    'Department'[DepartmentName],
    FILTER('Date', 'Date'[FiscalYear] = 2024),
    "Revenue", [Total Revenue],
    "Revenue %", DIVIDE([Total Revenue], CALCULATE([Total Revenue], ALL('Department')))
)
ORDER BY [Revenue] DESC

Year-over-year comparison:

EVALUATE
SUMMARIZECOLUMNS(
    'Date'[FiscalPeriodName],
    "Revenue CY", CALCULATE([Total Revenue], 'Date'[FiscalYear] = 2024),
    "Revenue PY", CALCULATE([Total Revenue], 'Date'[FiscalYear] = 2023),
    "YoY Change %", DIVIDE(
        CALCULATE([Total Revenue], 'Date'[FiscalYear] = 2024) -
        CALCULATE([Total Revenue], 'Date'[FiscalYear] = 2023),
        CALCULATE([Total Revenue], 'Date'[FiscalYear] = 2023)
    )
)
ORDER BY 'Date'[FiscalPeriodName]

If exact measure names are unknown, call get_bpa_dataset_schema first and adapt the query to match actual schema names.

Step 4 — Present results

Format the output as a structured table. Add a brief narrative summary highlighting:

• Key trends (growth/decline, notable period)
• Top/bottom performers by dimension
• Margin trend direction

Output Format

Period	Revenue	COGS	Gross Profit	GM%	Op. Expenses	EBITDA	Net Income
Jan 2024	1,250,000	750,000	500,000	40.0%	320,000	215,000	180,000
...	...	...	...	...	...	...	...

Followed by a 3–5 sentence narrative:

"Revenue grew 12% YoY driven by [entity/dept]. Gross margin declined slightly from 42% to 40% due to [cost pressure]. EBITDA remains healthy at [X%]."

DAX Best Practices for BPA

• Always use SUMMARIZECOLUMNS for grouped queries (more performant than SUMMARIZE)
• Use DIVIDE([numerator], [denominator]) instead of / to avoid division-by-zero errors
• Limit result sets: add TOPN(100, ...) for large dimensions
• Use FILTER inside CALCULATE for period scoping rather than slicers
• Query timeout is 120 seconds — break complex multi-step analysis into separate calls
• Data return limit is ~10 MB per query — use aggregations, not row-level detail

Example Prompts That Trigger This Skill

• "Show me the P&L for Q3 2024"
• "What is our gross margin trend over the last 12 months?"
• "Compare revenue by legal entity for FY2024 vs FY2023"
• "Break down operating expenses by department for this fiscal year"
• "What is our EBITDA margin this quarter?"
• "Which cost center is driving the most expenses?"