A data-driven analysis of declining profitability trends from your Power BI environment, with breakdowns and actionable findings.
This report analyzes declining profitability trends using data from Autotask PSA.
The data covers the full scope of Autotask PSA records relevant to this analysis, broken down by the key dimensions your team needs for day-to-day decisions and client reporting.
Who should use this: MSP owners, finance leads, and operations managers tracking profitability
How often: Monthly for financial reviews, quarterly for strategic planning, on-demand for pricing decisions
A data-driven analysis of declining profitability trends from your Power BI environment, with breakdowns and actionable findings.
-- Combined summary metrics from Power BI datasetRevenue breakdown by company from billing data
| Company | Revenue |
|---|---|
| Montgomery-Peck | €214,468 |
| Hahn Group | €253,148 |
| Wu-Jackson | €321,669 |
| Torres-Jones | €255,698 |
| Thompson, Contreras and Rios | €320,831 |
| Patterson, Riley and Lawson | €416,449 |
| Richards, Bell and Christensen | €328,164 |
| Burke, Armstrong and Morgan | €469,660 |
| Price-Gomez | €286,926 |
| Little Group | €1,431,177 |
| Wall PLC | €476,622 |
| Craig-Huynh | €2,324,616 |
| Martin Group | €637,091 |
| Lopez-Reyes | €589,694 |
| Lewis LLC | €2,212,914 |
EVALUATE TOPN(15, SUMMARIZECOLUMNS('BI_Autotask_Companies'[company_name], "Revenue", SUM('BI_Autotask_Billing_Items'[total_amount])), [Revenue], DESC)Monthly revenue trend over the observed period
| Month | Revenue |
|---|---|
| 2025-04 | $1,584,573 |
| 2025-03 | $1,355,867 |
| 2025-09 | $1,338,729 |
| 2025-07 | $1,333,798 |
| 2025-05 | $1,309,025 |
| 2025-08 | $1,293,341 |
| 2025-10 | $1,292,670 |
| 2025-06 | $1,258,445 |
| 2025-02 | $1,254,705 |
| 2025-11 | $1,186,353 |
| 2025-12 | $1,148,866 |
| 2026-01 | $842,410 |
EVALUATE VAR _data = ADDCOLUMNS(VALUES('BI_Autotask_Billing_Items'[item_date]), "YM", FORMAT('BI_Autotask_Billing_Items'[item_date], "YYYY-MM"), "Revenue", CALCULATE(SUM('BI_Autotask_Billing_Items'[extended_price]))) RETURN TOPN(12, GROUPBY(_data, [YM], "MonthlyRevenue", SUMX(CURRENTGROUP(), [Revenue])), [YM], DESC)Distribution of contracts across types
| Type | Count |
|---|---|
| Recurring Service | 1,207 |
| Time & Materials | 504 |
| Block Hours | 173 |
| Fixed Price | 5 |
EVALUATE SUMMARIZECOLUMNS('BI_Autotask_Contracts'[contract_type_name], "Count", COUNTROWS('BI_Autotask_Contracts'))What the data is telling us
The data above paints a picture of declining profitability trends across your MSP operations. Look for patterns, outliers, and trends that warrant attention. Each section includes the DAX query used, so you can drill deeper into any metric that catches your eye.
Set up a weekly or monthly review of declining profitability trends metrics. Trends matter more than snapshots. Use the DAX queries in this report as your starting point.
This report uses demo data. Connect Proxuma Power BI to your own Autotask PSA to generate this analysis from your real numbers.
This report pulls data from PSA through the Proxuma Power BI integration, using DAX queries against the live data model.
The underlying Power BI dataset refreshes daily. Reports can be regenerated at any time for the latest figures.
Yes. Proxuma reports are fully customizable. You can modify the DAX queries, add new sections, or adjust the analysis to match your specific MSP needs.
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