The Challenge
Professional services firms and agencies face a critical visibility gap that silently destroys profitability:
- Delayed profitability insights - Teams work for weeks or months before discovering a project is bleeding money, when it’s too late to salvage margins
- Labor cost opacity - Actual hours worked exceed estimated hours, but no one notices until invoicing time when the damage is done
- Resource allocation mistakes - Senior (expensive) resources get assigned to tasks that junior team members could handle, destroying profit margins
- Scope creep blindness - Additional requests and “quick favors” accumulate untracked, turning profitable projects into money losers
- Poor future pricing - Without accurate historical labor data, firms under-bid similar projects repeatedly, perpetuating the profitability problem
A 2023 industry study found that 40% of agency projects finish over budget, and firms typically don’t realize this until final reconciliation—when the only option is absorbing the loss or damaging client relationships by requesting additional payment.
The Autohive Solution
Autohive transforms Harvest from a simple time tracker into a real-time profitability command center that prevents losses before they happen.
Continuous Profitability Monitoring
The integration automatically calculates project profitability by comparing actual hours logged (at team members’ billable rates) against project budgets and contracted amounts. You see profit margins update in real-time as work happens.
Labor Cost Analysis by Task and Role
Break down exactly where time is being spent—which tasks, which team members, which project phases. Identify immediately when expensive resources are doing low-value work or when specific deliverables are consuming disproportionate hours.
Automated Budget Alerts
Set threshold-based alerts like “Notify me when project reaches 75% of budgeted hours” or “Alert when senior developer time exceeds 20 hours on this project.” Catch problems while there’s still time to adjust scope or staffing.
Historical Project Intelligence
Build a comprehensive database of actual labor costs by project type, deliverable, and client. When scoping similar future projects, you have real data showing that “website redesign for mid-market SaaS typically requires 120 hours, not 80.”
Benefits
- Prevent project losses - Identify unprofitable trajectories early enough to renegotiate scope, adjust staffing, or have honest client conversations
- Improve resource allocation - Data-driven insights show which team members should work on which tasks to maximize both quality and profitability
- Accurate future pricing - Historical labor cost data enables confident, profitable project estimates instead of hopeful guesses
- Increase average project margin by 10-15% - Better visibility and control directly improve profitability across your portfolio
- Make strategic decisions faster - Know immediately which project types, clients, or service lines are most profitable
How It Works
Connect Harvest to your analysis system - Link Harvest time tracking data with your project budgets, client contracts, and team billing rates
Configure profitability tracking - Set up automated calculations that compare actual labor costs against budgeted amounts and contracted fees
Set alert thresholds - Define when you want notifications (75% budget consumed, 10 hours over estimate, senior resource allocation exceeded)
Receive real-time insights - Dashboards update continuously showing current profitability status, labor cost breakdowns, and trend projections
Take corrective action - Use the data to adjust staffing, renegotiate scope, or accelerate delivery before losses compound
Build pricing intelligence - Historical project data becomes your competitive advantage for accurate, profitable future estimates
Getting Started
- Sign up at app.autohive.com
- Connect your Harvest integration from the marketplace
- Import your project budgets and team billing rates
- Configure profitability tracking and alert rules
- Start monitoring real-time project profitability and make data-driven resource decisions
