Spotlight: DDOT Detroit Department of Transportation
Customer Company Size
Large Corporate
Region
- America
Country
- United States
Product
- Ecolane DRT Brokerage software
- Touch screen MDT software on Android tablets
- SMS Text Messaging
- Self-Service Web Bookings
- Google Transit Integration
Tech Stack
- Android tablets
- SMS Text Messaging
- Google Transit Integration
Implementation Scale
- Enterprise-wide Deployment
Impact Metrics
- Customer Satisfaction
- Productivity Improvements
- Cost Savings
Technology Category
- Functional Applications - Fleet Management Systems (FMS)
- Analytics & Modeling - Predictive Analytics
- Functional Applications - Remote Monitoring & Control Systems
Applicable Industries
- Transportation
Applicable Functions
- Logistics & Transportation
- Business Operation
Use Cases
- Fleet Management
- Predictive Maintenance
- Remote Asset Management
Services
- System Integration
- Training
About The Customer
Detroit Department of Transportation (DDOT) services the greater metro Detroit area and even extends their service ¾ mile further than the furthest fixed route bus stop in the area. DDOT contracts with Transdev’s IntelliRide division to provide ADA demand response operations with curb-to-curb paratransit service. With this brokerage system, Transdev handles all scheduling, dispatching and reservations for DDOT, and all drivers are subcontracted. DDOT uses a fleet of approximately 49 vehicles and completes an average of 1,000-1,200 trips on weekdays across seven transportation providers. On weekends, DDOT expects 300-400 trips on Saturdays and 250-300 trips on Sundays, adding up to approximately 26,000 trips on a monthly basis. With 30 employees operating the paratransit department coupled with the large volume of demand response rides they provide, DDOT is categorized as a larger transit agency.
The Challenge
Larger transit agencies face unique challenges compared to smaller transit agencies. Large transit systems face more complex scheduling, dispatching, and billing processes because of the sheer size of their fleets, their day of service operations, and the fact that they are often dealing with multiple providers. Large transit agencies have a longer span of operational requirements, more days of service, and usually, multiple depot locations for vehicles. DDOT is no exception, and was facing challenges that were hindering operations and efficiency. Examples of specific issues they were dealing with include: • Poor or disjointed communication issues between management and drivers due to paper manifests and reliance on antiquated technology • Coordination between DDOT, the previous broker, and subcontractors were cumbersome due to the largely manual process of scheduling and moving trips • Limited visibility into driver data, scheduling, and execution • Manual scheduling that resulted in drivers always running behind schedule Additionally, DDOT was not seeing any real benefits with their legacy scheduling software, and in fact, it was contributing to the overall operational challenges that they were facing. DDOT’s frustration with the previous legacy software stemmed from several issues including: • Staff was required to collect all pick-up calls for the next day by 4:30pm and pool all of the trips into a report to send to each provider manually, which created disjointed delivery of customer trips • Zero visibility into how the trips were being booked • Because of the way that the trips were scheduled, they could have three provider vehicles all driving down the road at the same time to pick up one customer Ultimately, DDOT’s goal was to be more efficient, increase their rides per hour, and improve customer service. So, how did they get there?
The Solution
DDOT realized that they did not have the technical capacity and expertise to fix the problem. They put out a 5-year contract RFP and evaluated Ecolane as a potential new solution to help address their challenges and turn everything around. Ecolane was one of two options considered. When comparing Ecolane with their legacy software, they noticed several major differences: Ecolane • Fully automated scheduling that reduced the number of staff needed to make schedules • Increased flexibility to make adjustments to manifests • Training was robust and thorough, with the Transdev partnership • Software was more efficient • Able to use Detroit-based providers Previous Legacy Software • 15 people were needed to schedule trips • No flexibility to change the trip manifest • Manual schedule creation with 20-year-old software There was no question in DDOT’s mind as to what software would take their program to the next level, and they ended up choosing to transition away from their legacy software and implement Ecolane software instead. They implemented the Ecolane DRT Brokerage software solution with the following capabilities: • Touch screen MDT software on Android tablets (100% MDTs in all vehicles in operation daily) • SMS Text Messaging • Self-Service Web Bookings • Google Transit Integration • Sub-Contractor Portal for added visibility • Advanced reporting system with ad-hoc reporting tool
Operational Impact
Quantitative Benefit
Case Study missing?
Start adding your own!
Register with your work email and create a new case study profile for your business.
Related Case Studies.
Case Study
Airport SCADA Systems Improve Service Levels
Modern airports are one of the busiest environments on Earth and rely on process automation equipment to ensure service operators achieve their KPIs. Increasingly airport SCADA systems are being used to control all aspects of the operation and associated facilities. This is because unplanned system downtime can cost dearly, both in terms of reduced revenues and the associated loss of customer satisfaction due to inevitable travel inconvenience and disruption.
Case Study
IoT-based Fleet Intelligence Innovation
Speed to market is precious for DRVR, a rapidly growing start-up company. With a business model dependent on reliable mobile data, managers were spending their lives trying to negotiate data roaming deals with mobile network operators in different countries. And, even then, service quality was a constant concern.
Case Study
Digitize Railway with Deutsche Bahn
To reduce maintenance costs and delay-causing failures for Deutsche Bahn. They need manual measurements by a position measurement system based on custom-made MEMS sensor clusters, which allow autonomous and continuous monitoring with wireless data transmission and long battery. They were looking for data pre-processing solution in the sensor and machine learning algorithms in the cloud so as to detect critical wear.
Case Study
Cold Chain Transportation and Refrigerated Fleet Management System
1) Create a digital connected transportation solution to retrofit cold chain trailers with real-time tracking and controls. 2) Prevent multi-million dollar losses due to theft or spoilage. 3) Deliver a digital chain-of-custody solution for door to door load monitoring and security. 4) Provide a trusted multi-fleet solution in a single application with granular data and access controls.
Case Study
Vehicle Fleet Analytics
Organizations frequently implement a maintenance strategy for their fleets of vehicles using a combination of time and usage based maintenance schedules. While effective as a whole, time and usage based schedules do not take into account driving patterns, environmental factors, and sensors currently deployed within the vehicle measuring crank voltage, ignition voltage, and acceleration, all of which have a significant influence on the overall health of the vehicle.In a typical fleet, a large percentage of road calls are related to electrical failure, with battery failure being a common cause. Battery failures result in unmet service agreement levels and costly re-adjustment of scheduled to provide replacement vehicles. To reduce the impact of unplanned maintenance, the transportation logistics company was interested in a trial of C3 Vehicle Fleet Analytics.
Case Study
3M Gains Real-Time Insight with Cloud Solution
The company has a long track record of innovative technology solutions. For example, 3M helps its customers optimize parking operations by automating fee collection and other processes. To improve support for this rapidly expanding segment, 3M needed to automate its own data collection and reporting. The company had recently purchased the assets of parking, tolling, and automatic license plate reader businesses, and required better insight into these acquisitions. Chad Reed, Global Business Manager for 3M Parking Systems, says, “With thousands of installations across the world, we couldn’t keep track of our software and hardware deployments, which made it difficult to understand our market penetration.” 3M wanted a tracking application that sales staff could use to get real-time information about the type and location of 3M products in parking lots and garages. So that it could be used on-site with potential customers, the solution would have to provide access to data anytime, anywhere, and from an array of mobile devices. Jason Fox, Mobile Application Architect at 3M, upped the ante by volunteering to deliver the new app in one weekend. For Fox and his team, these requirements meant turning to the cloud instead of an on-premises datacenter. “My first thought was to go directly to the cloud because we needed to provide access not only to our salespeople, but to resellers who didn’t have access to our internal network,” says Fox. “The cloud just seemed like a logical choice.”
