2025_EML Capstone Projects

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new process, assigned responsibilities, and how it aligns with all the stakeholders’ objectives. Starting

July 1st, the selected individuals will partake in the hands-on sessions outlined in Table 9. Additional

support and feedback mechanisms will be in place to address any challenges and as the project

progresses, we will measure success through our KPIs (Table 10).

Data Collection and Analysis

To understand inefficiencies in the Suspension Service Transfer Process, data was gathered from

a range of sources. Primary data came from interviews with Trek technicians, service managers, and

inventory staff, along with a structured survey sent to Trek stores using the suspension service. This

feedback captured issues related to service delays, process gaps, and inventory challenges. Additional

input from managers across multiple locations further clarified service bottlenecks. Secondary data was

extracted from the Dealer Online Tracking System (DOTS), including metrics on work order volume,

turnaround times, technician workload, inventory levels, part deliveries, and backorder rates. Historical

service demand and customer feedback were also analyzed to identify recurring disruption patterns.

A mix of qualitative and quantitative methods supported the analysis. Process mining was used

to visualize workflow inefficiencies. Pareto analysis identified the most common root causes of service

delays, while ABC analysis prioritized inventory items linked to downtime. Supplier performance was

evaluated through lead time tracking and control charts, and time series forecasting helped anticipate

demand shifts and improve inventory planning.

Collaboration with Trek’s Stirling, New Jersey and Kearny Mesa, California service centers

revealed regional trends. In New Jersey, demand surged in spring and summer due to seasonal cycling

patterns, while San Diego experienced stable, year-round demand. These differences shaped a broader

understanding of system-wide inefficiencies.