As the lead program manager for an interoperable mobility network, I faced a critical challenge: drivers weren’t accepting rides. This posed a serious threat to the network’s goal of empowering taxi and rickshaw drivers across India. Despite having a well-designed ride-hailing application centered around drivers’ needs, the weekly dashboard revealed a significant issue – high rates of auto-cancellations, indicating a reluctance to accept ride requests.
Investigating the Issue:
Understanding that the problem ran deeper, the program team delved into data analysis. In a market dominated by a duopoly of ride-hailing apps imposing high commissions, our network aimed to offer drivers a better future through technology and interoperability. The team identified auto-cancellations as a bottleneck, leading to a low number of completed rides each week.
Identifying Potential Causes:
The team hypothesized two potential causes: a driver community-related issue or a technical glitch. To validate these assumptions, on-ground research and proactive feedback collection were initiated. Community-related issues were explored, considering factors like dissatisfaction with earnings, pickup distances, and alignment with the app’s long-term vision. Simultaneously, technical aspects, including user experience (UX) and process-related issues, were investigated.
Throughout our problem-solving journey, I maintained a dynamic decision tree, updating it with each newfound insight. This visual representation became a compass, guiding us through the complexities of our mission. A rough representation of this decision tree is shared below:
Strategic Solutions:
Prioritizing the technology track for quick fixes, the team addressed UX and process issues swiftly. However, recognizing the need for a long-term solution, efforts were directed toward understanding and resolving the lack of driver support. In-person meetings, pitch sessions, and weekly online interactions were established to rekindle the initial excitement among drivers and address their concerns promptly.
Results and Progress:
Implementing these measures resulted in a gradual decline in auto-cancellations and a subsequent increase in ride acceptance. The program’s commitment to understanding and supporting the driver community paved the way for improved collaboration, leading to a significant rise in completed rides through the application.
Conclusion:
Unraveling the mystery behind drivers’ hesitation to accept rides required a holistic approach. By addressing both community-related and technical issues, the mobility network successfully transformed challenges into opportunities, fostering a stronger bond with drivers and ensuring the network’s continued success.