Metro Transit Strategic Initiatives Department Update

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Metro Transit Strategic Initiatives Department Update Supporting a culture of data-driven decision making Metropolitan Council Transportation Committee September 25, 2017

Metro Transit Strategic Initiatives Link use of data to specific business needs and challenges Understand what is happening and why -> Allow faster, more effective response to changing conditions Use predictions and forecasts to inform decisions -> Allocate resources (service, staff, etc.) to achieve goals Provide advanced support for data collection, data management, data analytics, and data visualization Build partnerships inside and outside Transit 2

Metro Transit Strategic Initiatives Department Director John Levin Manager Business Systems Glenn Gilbert Manager System Performance Rachel Dungca Manager Analytics & Research Joel Huting Data Scientist Matt Broughton Intern Jen Kochaver Data Scientists Eric Lind Kim Eng Ky Intern Becca Freese Project Manager (Vacant)

Example 1: Shelter placement How do we allocate limited resources for shelters and shelter features (heat and light)? Important for customer satisfaction High priority equity goal Partnership with Engineering & Facilities, Community Engagement, Better Bus Stops project 4

Data Collection and Analysis Assist with Better Bus Stops Survey Survey questions that facilitate analysis Support survey distribution to ensure adequate samples across demographics Apply advanced analysis techniques Help translate results into guidance, policy Develop equity-focused measure for shelters Link performance measures to policy goals Integrate data sets: facilities, ridership, demographics 5

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Example 2: Service Reliability How can we provide highly reliable service for customers? How do we measure reliability? How do we focus efforts to improve? Partnership with Operations, Service Development 13

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Diving Deeper Factors that affect on-time performance Ridership and Go-To card use Traffic, signal delay, obstructions Weather, events, construction Variation in operator experience, performance Tools to identify OTP issue Where, when, who, why Lead to improvements to: service control, schedules, training, coordination with public works 15

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Change in I-35W South PM Peak Speeds 21

Example 3: Service Planning Core question: How do we design a transit network to best meet customer needs? Understanding travel demand and how riders use the system is essential for planning Partnership with Service Development, Metropolitan Transportation Services 22

Growing Data Sources Better understanding of travel demand, how transportation network is used, demographics of the travelers Travel Behavior Inventory Transit On-Board Survey Cell phone location data, auto and multimodal trips How to visualize data to inform decisions How to plan service changes and forecast results 23

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Other areas of work Increase Mobility and Access to Opportunity Origin/destination & travel demand data collection Route and facility planning tools Maximize Operational Efficiency, Safety and Financial Integrity Analysis and forecast of ridership changes Workforce optimization and efficiency Bus and rail accident analysis Fare policy analysis Fare evasion measurement Building utility forecast and exception detection 27

Other areas of work, continued Improve the Customer Experience Customer satisfaction survey design and analysis Service quality analysis (speed, reliability, loading) Accuracy and improvement of customer information Support Sustainable, Prosperous, and Equitable Communities Equity of service design, facilities and fares Equity in policing practices and outcomes Develop a Healthy, Resilient and Effective Workforce Employee satisfaction and engagement survey and analysis Operator retention analysis 28

Metro Transit Strategic Initiatives Department John Levin, Director john.levin@metrotransit.org 612-349-7789