1. Technician Staffing Levels for Modern Public Transit Fleets TCRP Project E-10 Summary

2. TCRP E-10 Project Scope  Analysis of NTD Data, and surveys of 68  Survey of existing data and outreach to transit agencies to identify main factors driving technician staffing levels  Develop Interactive Staffing Tool to evaluate local needs and model fleet or maintenance practice changes  Develop Guidebook explaining application of findings and how to use Staffing Tool

3. Analysis of NTD Data  Reviewed NTD submissions from 321 agencies  Correlations identified in several areas: – Between agency size and staffing ratios – Between spare ratio and staffing ratios – Duty cycle and miles based staffing ratios – Data was widely distributed; many outliers might be mistakes in the submission of data or misunderstanding of NTD definitions – Could not really compare “apples to apples”

4. Detailed Staffing Questionnaires  68 Participating Agencies – Diversity of Size – Diversity of Geography  Most agencies found it very difficult to provide confident data for the breadth of information sought  A main goal – identifying the right fleet with the right staff – e.g. adjusting for outsourced fleets or maintenance staff maintaining non-transit vehicles

5. Geographic Distribution of Participants RegionRound 1Round 2Total California10212 Northwest325 Midwest3811 Southeast189 Southwest112 Mid-Atlantic527 New England224 Canada21618

6. Size Distribution of Participants Agency SizeRound 1:Round 2:Total: >1000 Buses426 500-999 Buses347 250-499 Buses6612 100-249 Buses71017 50-99 Buses51217 <50 Buses279

7. Existing Staffing Levels Maintenance Technician Hours per 10k Vehicle Miles # of AgenciesAgency SizeAverage Standard Deviation 6>1000 Vehicles Maintained15944 7500-999 Vehicles Maintained11454 12250-499 Vehicle Maintained9729 17100-249 Vehicles Maintained10833 1750-99 Vehicles Maintained8439 9<50 Vehicles Maintained6329

8. Summary of Correlations  Strong correlation between variable and staffing level: – Fleet Size (for core maintenance as well as overall) – Fleet Composition (articulated buses / cut-aways) – Level of Outsourcing

9. Summary of Correlations – Fleet Size

10. Summary of Correlations – Outsourcing Effect

11. Summary of Correlations – Core Maintenance

12. Summary of Correlations – Fleet Size

13. Summary of Correlations – Bus Type

14. Summary of Absent Correlations  Small or no correlation between variable and staffing level – Spare ratio (small correlation, but not as big as NTD data) – Duty Cycle (Fleet mph) (small correlation, not as big as NTD data) – Fleet age (very small) – % of time on scheduled maintenance – % of fleet using alternative fuels Most correlations identified were not as strong as found in NTD Data, but data set much more reliable

15. Limitations of Data  Breakdown of hours by type of maintenance seems unreliable  Definition of “Scheduled” and “Unscheduled” maintenance varied  Definitions of “Productive time” varied – some based on contract, others actual timesheets

16. Interactive Staffing Tool The Bus Maintenance Staffing Calculator has three related purposes:  Compare actual current maintenance staffing levels with agencies in your peer group  Planning tool to determine necessary staffing levels for your particular maintenance operation based on existing factors  To model possible changes to maintenance policy to determine the impact it will have on your maintenance staffing levels.

17. Interactive Staffing Tool - Fleet Composition

18. Interactive Staffing Tool – Existing Staff

20. Interactive Staffing Tool – PMI

21. Interactive Staffing Tool – Other Core Maintenance

22. Interactive Staffing Tool – Unscheduled Maintenance and Repairs

23. Interactive Staffing Tool – Heavy Repair and Overhaul

24. Staffing Sufficiency Dashboard

25. Staffing Comparison Dashboard (1 of 2)

26. Staffing Comparison Dashboard (2 of 2)