PROJECT 3
Unveiling Opportunities in Urban Mobility
SYSTEMS THINKING / SERVICE DESIGN
CLIENT: Rapido, Bangalore
ROLE: Project Lead
OBJECTIVE:
To provide Rapido with actionable insights and tools to navigate the evolving urban mobility landscape and enhance its operational efficiency by mapping contextual opportunities and optimizing its value propositions.
Challenges to be Addressed
Problem Statement 1: Navigating the Urban Mobility Landscape
Need:
The COVID-19 pandemic and global socio-political, economic, and technological shifts have dramatically altered urban mobility. Rapido needed a comprehensive understanding of its position within this complex ecosystem to identify strategic opportunities and ensure contextual relevance.
Key Questions:
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How is Rapido situated within today’s context of urban mobility?
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What contextual levers can be harnessed to improve Rapido’s current and future standing?
Problem Statement 2: Mapping and Optimizing Value Propositions
Need:
Rapido’s organic growth across 100+ cities in India had resulted in fragmented service delivery mechanisms and unclear product and process ownership. This lack of a unified blueprint hindered the organization’s ability to make strategic and operational decisions.
Key Questions:
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How can a comprehensive picture of Rapido’s value offerings and service delivery mechanisms be developed?
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What metrics can provide actionable insights to identify strengths, weaknesses, and opportunities?
Approach &
Methodology
PROBLEM STATEMENT 1
PROBLEM STATEMENT 1
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Define Parameters:
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Scope: Focused on urban mobility in India, with insights from global trends.
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Purpose: Decode external forces to identify actionable intervention points for Rapido.
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Focal Areas: Political, economic, socio-cultural, technological, legal, environmental, and behavioral dimensions.
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Aggregate Data:
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Conducted a meta-analysis of reports, news articles, government policies, and global urban mobility studies.
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Mapped external factors such as EV adoption rates, urbanization trends, regulatory policies, and labor market dynamics.
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Synthesize Data:
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Organized data points into clusters and connections on a digital whiteboard.
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Mapped relationships between factors such as public transport availability, infrastructure investments, and consumer preferences.
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Identify Dynamics:
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Used Causal Loop Diagrams (CLDs) to depict feedback loops and cause-and-effect relationships within the system.
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Analyzed expanding (e.g., EV adoption) and shrinking (e.g., reliance on gig labor) phenomena.
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Develop Scenarios:
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Simulated five potential future scenarios:
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Transit-Oriented Development (TOD): Urban planning policies that favor public transport hubs and reduce car dependency.
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Decline in Gig Labor Supply: Impact of shrinking availability of urban gig workers on operational scalability.
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Accelerated EV Transition: Rapid adoption of electric vehicles driven by government incentives and rising fuel costs.
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Increased Frequency of Extreme Weather: Impacts of climate change on urban commuting and infrastructure reliability.
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Surge in Urban Commuters: Post-pandemic urban growth leading to higher transport demand.
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Generate Insights:
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Pinpointed Rapido’s position within each scenario and identified actionable strategies.
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Highlighted opportunities for partnerships with EV charging infrastructure providers, public transport agencies, and urban planning bodies.
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Scenario 1
Scenario 2
Scenario 3
Scenario 4
Scenario 5
Scenario 1 Causal Loop Diagram
Scenario 2 Causal Loop Diagram
Scenario 3 Causal Loop Diagram
Scenario 4 Causal Loop Diagram
Scenario 5 Causal Loop Diagram
Approach &
Methodology
PROBLEM STATEMENT 2
PROBLEM STATEMENT 2
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Develop Research Framework:
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Scoped the project to focus on rider (customer) and captain (driver) experiences.
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Designed methodologies to collect data on service delivery mechanisms, including customer touchpoints, operational workflows, and technology interfaces.
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Primary and Secondary Data Collection:
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Conducted interviews with riders and captains to capture journey experiences and operational challenges.
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Mined existing data from internal tools like CleverTap and Metabase to understand current metrics.
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Create Service Blueprint:
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Mapped rider and captain journeys, highlighting touchpoints, enablers, and barriers.
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Wove journeys into a comprehensive blueprint, identifying gaps and redundancies in service delivery.
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Validate Service Blueprint:
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Held workshops with internal teams to refine the blueprint and ensure accuracy.
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Blueprint Analysis and Prioritization:
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Conducted a multi-dimensional analysis involving business, operational, and technical teams to extract insights.
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Prioritized insights based on impact and feasibility, assigning ownership for implementation.
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Develop Measurement Framework:
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Reviewed existing metrics and identified gaps.
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Designed a comprehensive Measurement Framework detailing new metrics, data collection methods, thresholds, and accountability mechanisms.
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Research Methodology for Problem Statement 2
Sectional Blueprints used for analysis [Blurred intentionally]
Part of Metrics Framework [Blurred intentionally]
Solutions &
Recommendations
PROBLEM STATEMENT 1
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Systems Map:
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Delivered a comprehensive visualization of the urban mobility ecosystem, highlighting key trends, opportunities, and threats.
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Scenario-Specific Strategies:
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For Transit-Oriented Development: Collaborate with public transit providers to integrate Rapido into multimodal transportation networks.
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For Decrease in Gig-worker Availability: Ensure proactive adoption of froposed legislative changes to protect worker rights.
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For Rapid EV Transition: Accelerate EV fleet adoption and partner with renewable energy suppliers to address infrastructure challenges.
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For Climate Change: Build adaptive operational strategies to ensure service continuity during extreme weather events.
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Accelerating Urban Population: Threat of demand outpacing supply in urban mobility solutions, leading to a death-spiral.
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Actionable Recommendations:
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Developed a roadmap for strategic initiatives aligned with urban mobility trends, including diversification into last-mile delivery services.
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PROBLEM STATEMENT 2
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Comprehensive Service Blueprint:
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Visualized the service delivery ecosystem, capturing all stages of rider and captain interactions.
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Identified 30+ pain points, including inefficiencies in ride allocation and app interface usability.
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Measurement Framework:
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Defined 20+ new metrics covering customer satisfaction, operational efficiency, and driver retention.
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Provided guidelines for data collection, ensuring clarity in responsibilities and measurement methods.
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Operational Insights:
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Proposed automation of manual processes to reduce errors and improve efficiency.
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Identified opportunities for app flow optimization to enhance user experience.
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Impact &
Outcomes
PROBLEM STATEMENT 1
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Empowered Rapido to proactively address challenges and opportunities in the urban mobility ecosystem.
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Strengthened Rapido’s strategic planning with a systems-thinking approach.
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Enabled leadership to prioritize investments in future-proof solutions such as EV integration and adaptive operations.
PROBLEM STATEMENT 2
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Streamlined service delivery processes, reducing operational inefficiencies.
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Enhanced decision-making with actionable metrics and a unified understanding of Rapido’s ecosystem.
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Improved rider and captain satisfaction by addressing key pain points.