Aakash’s story

Frost & Sullivan: Building an ROI Tracker Across 40-Plus Mobility Agencies

Structured an ROI and KPI framework from unstructured data across a fragmented mobility services dataset.

Aakash .

Growth Opportunity Analytics (Mobility) Intern at Frost & Sullivan

FFrost & Sullivan
GGirlUp Ruhi
KKartavya - The Social Service Forum of SSCBS
JJindal Stainless
TThe IMPACT Project
2+ years of experience

From their time as

F

Growth Opportunity Analytics (Mobility) Intern

Frost & Sullivan β€’ 2025 - 2025

Overview

Aakash joined Frost & Sullivan's mobility analytics team as an intern and was handed a large, unstructured dataset covering more than 40 transportation agencies across service types including two-wheelers, four-wheelers, paratransit, and shared mobility. The brief was open-ended: calculate ROI and utilization for these services, and deliver analysis and recommendations. The method was left to the team.

The Story

Aakash joined Frost & Sullivan's mobility analytics team as an intern and was handed a large, unstructured dataset covering more than 40 transportation agencies across service types including two-wheelers, four-wheelers, paratransit, and shared mobility. The brief was open-ended: calculate ROI and utilization for these services, and deliver analysis and recommendations. The method was left to the team.

Rather than diving straight into the data, Aakash took the initiative to organize the internal team of four interns, running coordination meetings and dividing the work based on each person's availability and skill set. He owned the structure of the approach before anyone touched the numbers.

His personal output was the ROI tracker and KPI framework, which included utilization rate, fixed cost per passenger, variable cost per passenger, and profit per trip. One insight that shaped the analysis was that headline ROI figures were misleading without accounting for utilization rate: a service that looked profitable in isolation could be underperforming when measured against actual usage at a given time and location.

The team built Power BI dashboards to visualize the findings and presented the recommendations and dashboards to their immediate manager, who then took them to senior management for client review.