AI-Enhanced Project Forecasting
& EAC Management
How an engineering firm reduced project forecasting time by 80% and cut budget overruns by 15-20% with real-time Dynamics 365 integration.
Project Overruns Are an Industry-Wide Problem
Engineering and construction projects routinely exceed their budgets. The root cause isn't bad engineering - it's bad forecasting infrastructure.
When project managers lack real-time visibility into actual costs vs. estimates, overruns develop silently. By the time a variance shows up in a monthly spreadsheet review, it's too late to course-correct.
Enterprise project management tools exist, but they're built for mega-projects. Mid-sized engineering firms running Dynamics 365 or Sage are often stuck with spreadsheets. That's where this story starts.
Meet the Client
A 350-person engineering and construction firm running Dynamics 365. They managed 40+ active projects simultaneously, each with labor, materials, subcontractors, and equipment costs tracked separately.
Every month, each project manager spent 8-12 hours pulling actual costs from Dynamics 365, typing them into an Excel forecast template, and manually calculating EAC (Estimate at Completion). The process was slow, error-prone, and disconnected from the ERP.
Budget overruns averaged 15-20% across the portfolio. Some overruns were caught early. Many weren't - they surfaced during quarterly reviews when margins had already eroded.
This wasn't a project management problem - it was a data visibility gap. All the cost data existed in Dynamics 365. But it lived in silos, and project managers were manually bridging the gap between ERP data and financial forecasts.
The Monthly Forecasting Cycle
With 40+ projects, the collective time spent on manual forecasting exceeded 400 hours per month across the organization. And the output - static spreadsheets - was rarely trusted by leadership.
How We Built the AI Solution
We built a custom EAC management platform integrated directly with Dynamics 365. Project managers now enter their forecasts for remaining work, while the system automatically pulls real-time actuals from the ERP.
The AI component analyzes historical patterns across the project portfolio - labor productivity rates, material cost inflation, subcontractor performance - and flags projects that are trending toward overruns before the overruns happen.
The operating model centered on one principle: project managers should forecast from live project cost context, not from screenshots and static month-end workbook snapshots.
Actual costs flowed from Dynamics 365 into the forecasting workflow through API, remaining-work estimates were recorded against the same project structure, and the AI layer evaluated labor, materials, subcontractors, and equipment trends to surface margin pressure early. That gave project managers one governed review path instead of separate exports, chart decks, and spreadsheet versions.
Real-Time Cost Tracking
Actuals sync from Dynamics 365 automatically - no manual exports, no copy-paste
AI Early Warning
Projects trending over budget are flagged with specific cost category attribution
Structured Variance Review
Forecast changes, cost category movement, and margin impact are reviewed in one controlled workflow instead of disconnected chart packs
Mobile Dashboards
Project managers get real-time updates from any device - on-site or in the office
Before vs. After
Results That Scale
(was 8-12 hrs)
per project/year
budget overruns
per project
With 40+ active projects, the total annual impact exceeded 4,400 hours saved and $440K+ in overrun prevention - before counting the value of faster executive decision-making and improved bid accuracy on future projects.
Are Your Project Forecasts Still in Spreadsheets?
If your PMs spend more than 2 hours per month on cost forecasts, your ERP data isn't working hard enough. We'll show you what can be automated.
Get a free workflow analysis →8-Week Rollout
Weeks 1-2: Connect
Dynamics 365 API integration, cost category mapping, and historical data import for AI baseline training.
Weeks 3-4: Build
Core EAC dashboard and calculation engine. Real-time budget vs. actuals tracking with variance attribution.
Weeks 5-6: Alert
AI early-warning system, cost trend analysis, mobile optimization, and PM commentary features.
Weeks 7-8: Launch
User training for all PMs, parallel testing vs. spreadsheet process, and full production go-live.
"We turned project forecasting from a monthly burden into a real-time, proactive process. Project managers now have confidence in their numbers, and leadership gets fewer surprises. The overrun alerts alone have paid for the entire system twice over."
Frequently Asked Questions
Stop Discovering Overruns
After They Happen
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