Weekly Service Bay Utilization Report

Track and analyze service bay performance metrics focusing on utilization rates, efficiency, and revenue generation across all service bays. This report helps optimize scheduling, staffing, and resource allocation while identifying opportunities to improve operational efficiency and customer satisfaction.

Report Objective

Monitor service bay utilization and efficiency metrics to optimize resource allocation, maximize revenue potential, and ensure high-quality service delivery. Track key performance indicators including bay utilization rates, service completion times, and revenue per bay to support data-driven operational decisions.

Service Bay Utilization Overview

Line chart showing daily utilization rates across service bays

Questions to Consider:

2025-02-012025-03-012025-04-01date70%72%74%76%78%80%bay_utilization_ratebay_utilization_rateHow are service bay utilization rates trending?Daily utilization rates showing weekly patterns and trends
  • What is the week-over-week trend in utilization rates?

  • Are there specific days showing consistently lower utilization?

  • How close are we to target utilization rates?

  • What is the average variance between scheduled and actual hours?

  • Are there patterns in scheduling accuracy?

  • How can we improve scheduling efficiency?

2025-02-012025-03-012025-04-01date0.02.04.06.08.010.0scheduled_hoursscheduled_hoursHow do scheduled vs. actual hours compare?Analysis of scheduling accuracy and time management

Service Efficiency Metrics

Bar chart comparing planned vs. actual service duration by service type

Questions to Consider:

Oil ChangeBrake ServiceTire Serviceservice_type0%1000%2000%3000%sum(efficiency_score)sum(efficiency_score)How efficient are different service types?Comparison of planned vs. actual duration by service type
  • Which service types show the highest efficiency?

  • Where are the largest gaps between planned and actual duration?

  • What factors contribute to service time variations?

  • How accurate are our service time estimates?

  • Which services show the most variability?

  • What is the impact on scheduling and customer satisfaction?

5.010.015.020.025.0sum(planned_duration)2.04.06.08.0sum(actual_duration)What is the distribution of service durations?Analysis of actual service times across different service types

Revenue Performance

Bar chart showing revenue per bay and service type distribution

Questions to Consider:

Bay 1Bay 2Bay 3bay_number$0$1,000$2,000$3,000$4,000$5,000sum(revenue_per_hour)sum(revenue_per_hour)How does revenue performance vary by bay?Analysis of revenue generation across service bays
  • Which bays are generating the highest revenue per hour?

  • How does service mix affect revenue performance?

  • What opportunities exist to optimize revenue generation?