Maple AI Consultants

AI consulting case studies by Joel & Nanz Inc.

Equipment Rental • 450 Units

Case Study 26: Equipment Rental Company

Marketing-optimized case study for Canadian SMBs.

$156,000
Annual Savings
385%
ROI
3.7 months
Payback
Equipment Rental • 450 Units
Industry Focus

Executive Summary

Availability Prediction: ML forecasts equipment demand by type, season, and local construction activity. Optimizes purchasing and fleet distribution across locations.

Challenge

Solution

  • Availability Prediction: ML forecasts equipment demand by type, season, and local construction activity. Optimizes purchasing and fleet distribution across locations.
  • Maintenance Scheduling: IoT sensors track equipment hours and usage patterns. AI predicts maintenance needs and automatically schedules service before breakdowns occur.
  • Dynamic Pricing: Automated pricing adjusts rental rates based on demand, availability, rental duration, and competitor rates.

Technical Stack

Key Metrics

61%
Equipment utilization increased from 61% to 78%
72%
Unplanned downtime reduced 72%
$1,240
Revenue per unit increased $1,240 annually
28%
Maintenance costs reduced 28%
2
Eliminated 2 FTE yard coordinator roles ($71k savings)

Implementation Timeline

14 weeks including IoT installation and system integration

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