Seamless Experience for Tech Agents
Owigo solution offers a comprehensive suite of software tools aimed at improving the workflow efficiency of a drone delivery personnel.
Owigo
Logistics
2022
The Problem
Owigo originated due to the challenges faced by drone delivery operations including route optimization, real-time tracking, and delivery coordination. As the use of drones for delivery purposes continues to gain traction, businesses are seeking ways to optimize the workflow efficiency of their drone delivery personnel.
Research
To kickstart, I conducted a primary research where I understood the context of the problem, conducted initial stakeholders interviews, the drone delivery industries, and audited existing solutions. All of these data were synthetized into an affinity map that helped with build a persona, user flows, and design ideas.
Frustrations with the lack of visibility into their performance metrics, which made it challenging to gauge efficiency and effectiveness.
Manual parcel management by drone delivery personnel leads to inefficiencies, extra work, and potential errors/delays. Automated tools are needed!
Difficulty in achieving real-time tracking and communication during drone deliveries.
Ideation
To kickstart, I choose the Crazy 8’s technique as the foundation for the solutions recognizing its efficacy in rapidly generating a diverse range of ideas that will uncover a wide variety of solutions to optimize drone delivery workflows. My overarching objective was to generate diverse and innovative set of solutions that would not only bring cohesion to the process but also enhance the user experience and expedite the development of new features.
Outcome
Given the tight schedule and deadline, I swiftly transitioned from conceptualization to creating high-fidelity screens, continuously refining designs based on valuable ideas from the Crazy 8 Technique. Fortunately, the data gathered from our research significantly expedited this process. I maintained a close and collaborative relationship with the stakeholders and product manager, from the proof of concept phase to meticulous QA testing and, ultimately, its beta phase.
Features
The platform displays daily, weekly and monthly earnings prominently, highlights earned bonuses and incentives to showcase the rewards of high performance, and provides real-time updates on completed, pending, and upcoming deliveries. Instant notifications for changes in delivery status such as package pickup confirmation, arrival at the delivery location, or any unexpected delays. Notifications regarding sudden changes in weather conditions like rain, strong wind, or low visibility, allowing for proactive safety measures.
Key Features
The system prioritizes assigning deliveries to drones with sufficient payload capacity to handle the package's weight and size, while also considering the availability of drones in specific areas to ensure efficient allocation and avoid unnecessary repositioning.
Key Features
Estimated arrival times adjust automatically based on factors like weather conditions, providing a timeframe within which the delivery is expected to arrive, thus enhancing customer convenience and planning. Instant notifications for changes in delivery status such as package pickup confirmation, arrival at the delivery location, or any unexpected delays.
Evaluation
Owigo’s allocation model is designed with a “parcel” approach, streamlining the process of assigning drones by key factors such as weight, dimensions, and other critical parameters. This system ensures that personnel can efficiently allocate the most suitable drone for each delivery task.
This project marked the culmination of my HCI studies. It was an invaluable experience to apply my HCI knowledge to a real-world challenge - Drone Delivery Optimization.
Theoretical solutions often face unforeseen challenges in real-world applications. Immersing myself in the actual environment helped identified roadblocks. This insights allowed me to develop solutions that is both effective and realistic.
While evaluating the designs throughout the project, I always pushed to get a varied sample for testing. This helped in making sure that the solution wasn’t targeting just experienced tech personnel but also new/intern tech personnel, which could improve delivery optimization for Owigo Brand.
With more time, I would have loved to conduct in-depth ride along usability studies with various drone tech personnel of differing experience levels and tested the prototype in the field/real world scenario. This would have helped identify some of the feasibility factors such as handling in different weather conditions, ease of use in varied terrains, and the impact of environmental factors on drone performance.
