Utilization and pipeline in one warehouse
for consulting firms, answered in Slack, not a spreadsheet
Time tracking lives in one tool. Billing in another. Pipeline in a CRM. Nobody can say which practice area is actually profitable without a week of manual joining. We build the warehouse that joins them, and an analyst who answers in minutes.
Where the profitability question gets stuck
Every consulting firm asks the same question sooner or later: which practice area, which engagement type, which partner’s book actually makes money. It sounds simple. In practice it needs manually joining time tracking, billing and pipeline data that live in three separate systems, each chosen for a different job. By the time someone finishes that join for a quarterly review, the data is already a quarter old.
Utilization blindness at the individual level is just as costly. A firm can look fully booked by total revenue while several senior consultants are quietly underutilized. They spend hours on proposal writing and internal work that never gets flagged, until a review finds the gap months later.
Pipeline visibility is often disconnected from actual profitability too. A practice area with a strong close rate is not automatically the most profitable one, if its typical engagement runs at lower margin. Without a dashboard joining pipeline data to realized profitability, a firm can keep pouring business development effort into the wrong practice area.
What the warehouse joins
A warehouse joins your time-tracking tool, billing system and CRM, so utilization, profitability and pipeline all answer from the same consistent data. The utilization dashboard breaks out billable versus non-billable time by practice area and by consultant, surfacing underutilization before it shows up as a quarter-end surprise.
Engagement profitability joins actual hours logged and billed against revenue, by practice area and engagement type. You see which segment of the business actually produces margin, not just top-line revenue. Pipeline dashboards track close rate and average deal size by practice area, joined against the same profitability data. Business development effort then goes toward what is actually worth winning.
An AI analyst answers business questions directly in Slack or Telegram with real SQL against the warehouse. A partner asks “what was our utilization on the operations practice last quarter” and gets an answer in minutes, instead of waiting for someone to manually reconstruct it.
What stays with your partners
Engagement delivery, client relationships and business development strategy stay entirely with your partners and consultants. We build the warehouse and the dashboards that make the numbers visible. We do not decide where to invest business development effort. We just make that decision informed.
What it costs
| Package | Price | Timeline |
|---|---|---|
| Agency runs it | from $2,500 | 3 to 6 weeks |
| Full control, handover-ready | from $3,500 | 4 to 7 weeks |
Where this fits next
Pair this with the AI agent for management consulting firms, so qualified leads flow straight into a pipeline you can actually report on. Or Google Ads for management consulting firms, to see which campaign actually produces signed, profitable engagements. See the full package breakdown on the analytics service page, or get a written plan with a fixed price for your firm.
FAQ
How much does an analytics warehouse for a consulting firm cost?
A tracking audit starts from $800 if you want to see the gaps first. A full warehouse with utilization, profitability and pipeline dashboards starts from $2,500. The AI analyst is included from that tier.
How long until we have working dashboards?
3 to 6 weeks for the warehouse and the core dashboards, depending on how many time-tracking, billing and CRM fields need to be joined.
Which tools do you connect?
Harvest, Toggl or a similar time-tracking tool. Your billing or invoicing system. And HubSpot, Pipedrive or a CRM for pipeline data.
Can it show which practice area is actually most profitable?
Yes, that is the core of the dashboard. Engagement profitability joins against actual hours logged and billed, by practice area and engagement type. Not a top-line revenue number that hides where the margin actually comes from.
Can the AI analyst get our numbers wrong?
It runs read-only SQL against a prepared data mart, one query at a time, with forced limits, and shows the query it ran. We built and audited this exact guard before trusting it on live data, closing several gaps in one internal review.