Quick Wins1 month planning, 8+ months implementationConstruction

Can't Tell Which Projects Are Profitable

A boutique construction company had found their niche and experienced explosive growth - going from 5 employees to managing 20+ concurrent projects within 3 years. The founder, skilled in construction and client relationships, was drowning in manual data work: tracking project costs in spreadsheets, reconciling invoices manually, and spending 15+ hours weekly compiling reports instead of running the business.

StrategyRoadmapPhased Implementation

The Challenge

The company was facing several critical challenges:

Key Issues:

Founder working nights and weekends compiling spreadsheets instead of managing projects or winning new business
15+ hours per week manually tracking project costs, reconciling invoices, updating financial reports
Zero visibility into real-time profitability: Didn't know if projects were profitable until months after completion
Can't scale hiring: No systems to onboard project managers or delegate financial oversight
Bidding in the dark: No historical cost data to accurately estimate new projects
Client communication delays: Manual invoice tracking meant slow billing and payment cycles
Team frustration: Office admin spending entire Fridays compiling weekly reports for leadership
Data scattered across QuickBooks, BuilderTrend, Google Sheets, email attachments, paper receipts
70% of "data work" was redundant: Same information entered 3-4 times in different places

Business Impact:

The founder's dilemma: Excellent at construction and client relationships, but no technical background. Knew they needed "better systems" but didn't know what that meant, where to start, or how much to invest. Couldn't afford to hire a full-time data person, but couldn't keep operating manually. "I'm spending more time in Excel than on job sites. This isn't what I built this company to do."

The Solution

Delivered comprehensive data assessment and strategic roadmap showing the path from current chaos to automated operations. Phase 1 established data foundations and cleanup processes. Client then expanded engagement to Phase 2: built automated dashboards connecting QuickBooks, project management software, and customer data - eliminating manual reporting. Phase 3 added advanced analytics for job costing and profitability tracking.

Our Approach:

Phase 1 - Assessment & Roadmap (Month 1): Documented all manual processes, assessed existing systems, created 3-phase roadmap with clear outcomes and investment levels, educated founder on data-driven decisions
Phase 2 - Data Consolidation & Automation (Months 3-5): Built unified data pipeline (QuickBooks, BuilderTrend, customer data), created real-time dashboards (sales, finance, project manager), automated weekly reports, improved data collection (mobile time tracking, photo documentation)
Phase 3 - Advanced Analytics (Months 6-8+): Historical job costing analysis (50+ completed projects), predictive bidding tool (within 8% accuracy), customer insights (lifetime value, referral sources), operational efficiency metrics
Strategic Roadmap: Foundation (data cleanup) → Automation (dashboards, reporting) → Advanced Analytics (job costing, forecasting, customer insights)

The Results

Founder's manual data work reduced from 15 hours/week to under 2 hours. Sales and finance teams have real-time dashboards instead of waiting for weekly spreadsheet updates. Can now bid jobs with accurate historical cost data.

Founder's Time

15hrs → 2hrs/week

Manual data work eliminated

Administrative Overhead

1.5 → 1 admin

Same workload with fewer people

Report Generation

4hrs → automated

Weekly reports auto-generated in minutes

Billing Cycle

14 → 5 days

Improved cash flow

Team Scale

5 → 12 employees

Without proportional admin overhead

Revenue Growth

40% YoY

While maintaining profitability

Additional Results:

Bidding accuracy: Variance reduced from 25% to 8% using historical cost data
Project selection: Now deliberately targets most profitable project types
Material waste reduction: $8K saved in first quarter by identifying patterns
Faster invoicing: Reduced outstanding receivables by 30%
ROI on engagement: Founder's time savings = $40K/year; total value = $100K+/year
Cultural transformation: From "gut feel" to data-informed strategy
Long-term partnership: One-month assessment became 8+ month ongoing relationship

Technical Details

Architecture:

Lightweight modern data stack optimized for small business budget and complexity

Technology Stack:

Data Warehouse: Google BigQuery (~$10/month)
BI Tool: Looker Studio (free tier)
ETL: QuickBooks Online API → Cloud Function → BigQuery
BuilderTrend API → Cloud Function → BigQuery
Google Sheets → BigQuery Data Transfer Service
Automation: Cloud Functions for scheduled data pulls (~$5/month)
Alerts: Cloud Scheduler + SendGrid, Slack webhooks (~$1/month)
Total monthly cost: ~$20

Technical Highlights:

Phase 1 - Foundation: Consolidated 30+ Google Sheets, standardized project naming, established file organization, created data dictionary
Phase 2 - Dashboards: Sales dashboard (pipeline, conversion rates), Finance dashboard (cash position, profitability), Project manager dashboard (real-time costs, budget alerts)
Phase 3 - Predictive Bidding: ML model using historical data predicts costs within 8% accuracy, includes confidence intervals and contingency buffers
Customer lifetime value: Repeat customers worth 2.3x first-time clients, architect referrals = highest-value projects
Automated alerts: Budget threshold (>80%), invoice aging (>30 days), project timeline (<7 days to completion)
Data collection improvements: Mobile time tracking, photo documentation, material waste tracking
Maintenance: Weekly data quality check (15 min), monthly dashboard review, quarterly roadmap updates

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