Case Studies Big Data has big payoffs for this APTA-award winning transit agency

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	Big Data has big payoffs for this APTA-award winning transit agency

Big Data has big payoffs for this APTA-award winning transit agency

Technology Category	Analytics & Modeling - Big Data Analytics Functional Applications - Remote Monitoring & Control Systems Networks & Connectivity - Cellular
Applicable Industries	Cities & Municipalities Transportation
Applicable Functions	Business Operation Logistics & Transportation
Use Cases	Fleet Management Predictive Maintenance Real-Time Location System (RTLS) Remote Asset Management
Services	Software Design & Engineering Services System Integration
Challenge	Blacksburg Transit (BT) faced the challenge of improving customer experience, planning, and service efficiency. With a dynamic ridership primarily composed of university-affiliated individuals aged 18 to 24, BT needed to adapt to frequently changing locations and schedules. Traditional transit databases were insufficient for providing the granular data required to make informed decisions. Additionally, BT aimed to enhance customer service by addressing complaints effectively and providing accurate predicted bus arrival times, which varied daily due to changing class schedules and mini rush hours. Read More
About Customer	Blacksburg Transit (BT) is a public transportation provider serving the town of Blacksburg, including Virginia Tech. BT offers a variety of services, including fixed routes, paratransit, commuter services, deviated fixed routes, demand response, and a service for seniors. With a fleet of 69 vehicles and 200 employees, BT caters primarily to university-affiliated individuals aged 18 to 24. The agency collects 11,000 data points per day to analyze and improve its services. BT has been a long-time partner of TripSpark, utilizing their fixed route software and mobile data terminals to enhance operational efficiency and customer satisfaction. Read More
Solution	BT adopted TripSpark’s fixed route software, Streets, and mobile data terminals (MDTs) to gain complete access to their data and develop custom reports. This allowed BT to collect and analyze 11,000 data points daily, providing insights into fare types, schedule adherence, passenger loads, and trends. The data enabled BT to make short-term adjustments, such as changing headways and consolidating stops, and informed long-term strategic decisions about new routes and service levels. Additionally, BT invested in a passenger information system, including a texting service and real-time bus map, to provide accurate predicted bus arrival times and improve customer service. The system allowed BT to make schedule changes without reprinting and offered riders the convenience of receiving route and time information via text. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Big Data Analytics

Functional Applications - Remote Monitoring & Control Systems

Networks & Connectivity - Cellular

Applicable Industries

Cities & Municipalities

Transportation

Applicable Functions

Business Operation

Logistics & Transportation

Use Cases

Fleet Management

Predictive Maintenance

Real-Time Location System (RTLS)

Remote Asset Management

Services

Software Design & Engineering Services

System Integration

Challenge

Blacksburg Transit (BT) faced the challenge of improving customer experience, planning, and service efficiency. With a dynamic ridership primarily composed of university-affiliated individuals aged 18 to 24, BT needed to adapt to frequently changing locations and schedules. Traditional transit databases were insufficient for providing the granular data required to make informed decisions. Additionally, BT aimed to enhance customer service by addressing complaints effectively and providing accurate predicted bus arrival times, which varied daily due to changing class schedules and mini rush hours.

About Customer

Blacksburg Transit (BT) is a public transportation provider serving the town of Blacksburg, including Virginia Tech. BT offers a variety of services, including fixed routes, paratransit, commuter services, deviated fixed routes, demand response, and a service for seniors. With a fleet of 69 vehicles and 200 employees, BT caters primarily to university-affiliated individuals aged 18 to 24. The agency collects 11,000 data points per day to analyze and improve its services. BT has been a long-time partner of TripSpark, utilizing their fixed route software and mobile data terminals to enhance operational efficiency and customer satisfaction.

Solution

BT adopted TripSpark’s fixed route software, Streets, and mobile data terminals (MDTs) to gain complete access to their data and develop custom reports. This allowed BT to collect and analyze 11,000 data points daily, providing insights into fare types, schedule adherence, passenger loads, and trends. The data enabled BT to make short-term adjustments, such as changing headways and consolidating stops, and informed long-term strategic decisions about new routes and service levels. Additionally, BT invested in a passenger information system, including a texting service and real-time bus map, to provide accurate predicted bus arrival times and improve customer service. The system allowed BT to make schedule changes without reprinting and offered riders the convenience of receiving route and time information via text.

Impact #1	BT improved its ability to analyze and adjust service levels based on granular data, leading to better schedule adherence and strategic planning.
Impact #2	The implementation of a passenger information system, including a texting service and real-time bus map, enhanced customer service by providing accurate predicted bus arrival times and reducing the need for voice calls.
Impact #3	BT was able to address customer complaints more effectively by using data to investigate and understand the root causes of issues, such as pass-bys and early departures.

Impact #1

BT improved its ability to analyze and adjust service levels based on granular data, leading to better schedule adherence and strategic planning.

Impact #2

The implementation of a passenger information system, including a texting service and real-time bus map, enhanced customer service by providing accurate predicted bus arrival times and reducing the need for voice calls.

Impact #3

BT was able to address customer complaints more effectively by using data to investigate and understand the root causes of issues, such as pass-bys and early departures.

Benefit #1	Increased ridership by 22% between 2016 to 2018.
Benefit #2	Increased revenue service hours by 22% between 2016 to 2018.
Benefit #3	Achieved an on-time performance rate of 90%.

Benefit #1

Increased ridership by 22% between 2016 to 2018.

Benefit #2

Increased revenue service hours by 22% between 2016 to 2018.

Benefit #3

Achieved an on-time performance rate of 90%.

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Overview

Big Data has big payoffs for this APTA-award winning transit agency

Operational Impact

Quantitative Benefit