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Advanced Analytics

See the SlipBefore It Hits

One service across three layers — Power BI reporting, machine learning, and MLOps. Production ML systems that forecast schedule slips, predict cost overruns, and surface safety leading indicators, all running on your real project data. And it isn't just predictive: we also deliver governed Power BI reporting and dashboards on a single source of truth, so leadership sees the same trusted numbers every morning.

What We Deliver

Governed Power BI reporting & dashboards
Slip risk scored at the activity level
Cost overrun forecasts by WBS / cost code
Leading safety indicators from field data
Real-time productivity and utilization scoring
Full MLOps lifecycle — not just models
Explainable predictions — every score justified
35–60%
Forecast accuracy improvement vs. spreadsheet baselines
Weeks
Earlier slip detection vs. monthly cost reports
<50ms
Real-time model scoring latency
100%
Production-ready with monitoring

Seven Analytics Practice Areas

From governed Power BI reporting to schedule risk to crew productivity — reporting and production ML across the metrics that move your project margin.

Power BI Reporting & Dashboards

Governed, refresh-on-schedule reporting your leadership actually trusts — built on a single source of truth. Safety, labor, cost, and progress dashboards that replace the spreadsheet sprawl, with row-level security and a clean semantic model underneath.

Executive & operational dashboards
Governed semantic model & single source of truth
Row-level security and access control
Automated scheduled refresh
Self-service report distribution

Schedule Risk & Slip Prediction

Models that read your P6 schedule, productivity data, and historical project performance — and flag which activities are most likely to slip, by how much, and why. Risk-weighted CPM analysis your scheduler can't do alone.

Activity-level slip probability scoring
Critical-path risk monitoring
Resource bottleneck prediction
Weather and external-factor adjustment
Look-ahead reliability scoring

Cost Overrun Forecasting

Predict cost overruns by WBS, cost code, or subcontractor — weeks before they hit your monthly cost report. Built on your actual cost-loaded schedules, change orders, and commitment data.

WBS-level cost forecast vs. budget
Change-order trend modeling
Sub commitment burn-rate analysis
Productivity-driven cost projection
Cash flow forecast at portfolio level

Safety Leading Indicators

Move from lagging metrics (TRIR, LTIR) to leading ones. ML on inspection data, near-miss reports, toolbox talks, and behavioral observations — surfacing risk patterns before incidents happen.

Near-miss clustering and trend detection
Crew / area / activity risk scoring
Toolbox topic recommendation from trends
Behavioral observation pattern analysis
Incident root-cause classification

Real-Time Field Analytics

Decisions that need to happen on shift can't wait for tomorrow's report. Streaming pipelines that process daily reports, equipment telemetry, and field sensor data — surfacing productivity and safety signals live.

Streaming daily-report ingestion
Equipment utilization & idle detection
Crew productivity scoring in near real-time
Live superintendent alerts
Geofence and area-access monitoring

MLOps & Model Monitoring

A model that was accurate at project kickoff won't stay that way once site conditions change. We build MLOps infrastructure that monitors drift, retrains on schedule, and alerts before quality degrades.

MLflow experiment tracking
Automated retraining pipelines
Model drift detection & alerting
Feature store for project metrics
A/B testing for model versions

Crew, Equipment & Sub Analytics

Which crews are actually most productive? Which equipment is bleeding hours? Which subs hit their schedule and which don't? Behavioral analytics on the people and assets that drive your margin.

Crew productivity benchmarking
Equipment idle and utilization analysis
Sub schedule-reliability scoring
Self-perform vs. sub trade comparison
Resource allocation optimization

Power BI Gallery

Real construction reports we've built — safety, workforce, and labor analytics leadership checks every day.

Safety & Incident Analytics Power BI report

Safety & Incident Analytics

Body-part heatmaps, leading indicators, and root-cause breakdowns by activity, procedure, and object — with an AI summary tab that explains the trend in plain English.

Power BIAI SummaryEHS
Craft Labor & Locations Power BI report

Craft Labor & Locations

Where your workforce is, by craft and class — apprentice ratios, travelers vs. locals, and project staffing on a live national map.

Power BIGeospatialWorkforce
Labor & Attrition Power BI dashboards

Labor & Attrition Dashboards

Craft mix, open requisitions, absence and attrition trends by trade — the operational pulse leadership checks every morning.

Power BIForecastingOps

Our ML Development Lifecycle

Rigorous. Reproducible. Production-ready. We don't hand you a notebook — we hand you a system.

01

Problem Framing

Define the construction question precisely. What's the decision the prediction will change? Whose hands will it land in — the scheduler, the PM, the superintendent? Most ML projects fail here. We don't skip it.

02

Data Preparation

Feature engineering on your real project data — P6, cost reports, daily logs, safety records. We handle the messy real-world cases: missing data, coding inconsistencies, project-to-project variation.

03

Model Development

Experiment-driven approach with full tracking. We test multiple algorithms, tune hyperparameters, and validate against your historical projects — with explainability built in from day one.

04

Production Deployment

Model serving in your environment — embedded in Power BI, surfaced through a P6 plugin, or available via API. Monitoring, logging, and alerting from day one.

How It Plays By Sector

Project intelligence looks different on a petrochemical EPC versus a public-works infrastructure job. Here's how we tailor by sector.

Heavy Industrial / EPC

Schedule slip risk by area
Commissioning critical-path analysis
Equipment / crane utilization
Subcontractor performance scoring

Infrastructure & Civil

Weather-adjusted productivity
Earthwork progress forecasting
Material delivery risk modeling
Public-works prevailing wage analytics

Large Commercial GCs

Trade sequencing risk
Punch-list closure forecasting
Cost-overrun probability scoring
Submittal-cycle bottleneck analysis

Owners & Developers

Portfolio schedule rollups
Contractor performance benchmarking
Project P&L variance forecasting
Capital allocation optimization

Analytics & ML Technology Stack

Production-grade tools — not academic experiments.

Power BIPythonRscikit-learnXGBoostLightGBMTensorFlowPyTorchMLflowDatabricks MLAzure MLApache SparkKafkaDelta LakedbtSQLGreat ExpectationsEvidently AIGrafanaFastAPI

What Would Better Predictions Change on Your Next Project?

Start with a free analytics assessment. We'll identify where governed reporting and predictive models can have the highest business impact on your specific operations and project mix.

Need Power Apps & workflow automation? See Microsoft Power Platform

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Project Intelligence — Frequently Asked Questions

The answers below are the same text Google sees in our FAQ schema.

For projects with at least 30-60 days of actuals captured against the budget, yes. The models combine schedule slippage signals, productivity vs. plan, change-order velocity, and material cost variance to forecast where the project lands at completion — typically within 5-10% on builds we have enough history to train on.