AI-generated analysis via Proxuma Power BI MCP server. Identifies clients with high time investment but low revenue generation, ranked by effective hourly rate.
AI-generated analysis via Proxuma Power BI MCP server. Identifies clients with high time investment but low revenue generation, ranked by effective hourly rate.
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
AI-generated analysis via Proxuma Power BI MCP server. Identifies clients with high time investment but low revenue generation, ranked by effective hourly rate.
EVALUATE ROW("TotalRevenue", SUM('BI_Autotask_Charges'[billable_amount]), "TotalHours", [Tickets - Hours Worked], "EffectiveRate", DIVIDE(SUM('BI_Autotask_Charges'[billable_amount]), [Tickets - Hours Worked]), "BillableHours", SUM('BI_Autotask_Time_Entries'[Billable Hours]), "NonBillableHours", SUM('BI_Autotask_Time_Entries'[Non billable Hours]))Clients with 50+ hours logged and effective rate below $100/hr — sorted by hours worked
| Client | Hours Worked | Revenue | Effective Rate | Portfolio Benchmark | Revenue Gap | Status |
|---|---|---|---|---|---|---|
| Smith and Sons | 101.5h | $1,286 | $12.67/hr | $418/hr | -$41,141 | Critical |
| Smith Ltd | 97.1h | $2,677 | $27.56/hr | $418/hr | -$37,911 | Critical |
| Shaw-Ryan | 86.4h | $2,803 | $32.46/hr | $418/hr | -$33,312 | Critical |
| Palmer, White and Decker | 96.5h | $7,822 | $81.08/hr | $418/hr | -$32,515 | Review |
EVALUATE
TOPN(20,
FILTER(
ADDCOLUMNS(
SUMMARIZE('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_name]),
"Hours", [Company - Hours Worked],
"Revenue", [Revenue - Total],
"EffRate", [Analytics - Client Effective Rate],
"Profit", [Profit - total]
),
[Hours] > 50 && [Revenue] > 0 && [Revenue] < 8000
),
[Hours], DESC
)Clients with effective rates below $60/hr — regardless of hours volume
EVALUATE
TOPN(15,
FILTER(
ADDCOLUMNS(
SUMMARIZE('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_name]),
"Hours", [Company - Hours Worked],
"Revenue", [Revenue - Total],
"EffRate", [Analytics - Client Effective Rate],
"Profit", [Profit - total]
),
[Hours] > 0 && [EffRate] > 0 && [EffRate] < 60
),
[Hours], DESC
)Your highest-volume clients by hours worked, all operating above the portfolio effective rate
| Client | Hours Worked | Revenue | Effective Rate | Profit | Rate Health |
|---|---|---|---|---|---|
| Craig-Huynh | 4,370h | $2.32M | $531.90/hr | $1.31M | Excellent |
| Little Group | 3,791h | $1.43M | $377.48/hr | $828K | Good |
| Lewis LLC | 2,801h | $2.21M | $790.02/hr | $1.32M | Excellent |
| Martin Group | 2,217h | $637K | $287.37/hr | $389K | Good |
| Wall PLC | 1,697h | $477K | $280.88/hr | $262K | Good |
| Burke, Armstrong and Morgan | 1,312h | $470K | $357.90/hr | $245K | Good |
EVALUATE
TOPN(15,
FILTER(
ADDCOLUMNS(
SUMMARIZE('BI_Autotask_Companies',
'BI_Autotask_Companies'[company_name]),
"Hours", [Company - Hours Worked],
"Revenue", [Revenue - Total],
"EffRate", [Analytics - Client Effective Rate],
"Profit", [Profit - total]
),
[Hours] > 0 && [Revenue] > 0
),
[Hours], DESC
)The portfolio effective rate sits at $418/hr across 50,752 hours and $17.6M in revenue. That number represents what your team's time is worth when properly priced. Three clients are operating at rates between 3% and 8% of that benchmark.
Smith and Sons is the most extreme case: 101.5 hours logged against $1,286 in revenue. That works out to $12.67/hr — 97% below the portfolio average. At the benchmark rate, those same hours should have generated $42,427. Smith Ltd and Shaw-Ryan follow the same pattern: 97h and 86h logged at $27 and $32 per hour respectively.
The contrast with your highest-volume clients tells the full story. Lewis LLC generates $790/hr across 2,801 hours. Craig-Huynh runs at $532/hr across 4,370 hours. These accounts work because the pricing reflects the value delivered. The low-rate accounts have the opposite problem: the team is delivering work, logging hours, and billing almost nothing for it.
The most common causes are legacy flat-fee contracts set years ago, unlimited-support arrangements that were never updated, or T&M accounts where billing is inconsistently captured. Power BI surfaces the symptom; the fix happens in the contract conversation.
4 priorities based on the findings above
101.5 hours at $12.67/hr is not a pricing problem — it is a contract structure problem. Pull the contract, check whether work is being logged correctly, and determine whether this is a flat-fee arrangement that caps billing regardless of hours. If so, this account needs a new contract structure before the next renewal.
At $27 and $32/hr respectively, both accounts are absorbing significant engineer time at rates that do not cover costs. Prepare a utilization report for each client showing hours worked over the last 12 months versus contracted rate. Use this data to justify a price increase at the next QBR.
At $81/hr and 96.5 hours logged, this account sits in the “review zone” — below the critical threshold but still generating a loss. With 96 hours logged and only $7,822 in revenue, the account is running at a loss of $637 when factoring in costs. It is not an emergency, but the next renewal is the time to bring rates in line.
At $790/hr across 2,801 hours, Lewis LLC is your most efficiently priced high-volume account. Document what their contract looks like: the service scope, the rate structure, and the billing mechanism. This is the model for new contracts and renewals going forward.
The effective rate is total revenue divided by total hours worked for a given client. It tells you how much revenue each hour of your team's time actually generates. A high effective rate means you are billing well for your time. A low rate means your team is working more hours than the client pays for.
The most common causes are outdated flat-fee contracts that cap monthly billing regardless of actual hours, unlimited support plans without scope limits, T&M accounts where not all hours are being captured in the PSA, or reactive clients who generate a lot of ad-hoc work that falls outside billable scope.
Yes. Connect Proxuma Power BI to your Autotask PSA account, add an AI tool via MCP, and ask the same question. The AI writes the DAX queries, runs them against your real data, and produces this analysis in under fifteen minutes. All client names, hours, and rates will reflect your actual portfolio.
Monthly is a good cadence for operational monitoring. Quarterly is the right time to bring findings to contract or QBR conversations. The data refreshes in real time via Power BI, so you always see the current picture.
Connect Proxuma Power BI to your PSA, RMM, and M365 environment, use an MCP-compatible AI to ask questions, and generate custom reports - in minutes, not days.
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