Kargo Case Study
In summer of 2018, I interviewed for a product management role at Kargo, a trucking startup based in Indonesia solving the pen-and-paper logistics problem. As the more technical portion of my interview, in 24 hours, I redesigned the app experience and produced a very idealistic, multi-phase rollout of how the billion dollar problem could be tackled and ended up receiving an offer! Although I ended up pursuing an opportunity that was more local, I revisited the work a couple of months later and touched it up.
The Indonesian pen-and-paper logistics problem is one with a very prickly underbelly. In a non-exhaustive list of problems and side-problems:
Communication is still conducted mainly over WhatsApp / SMS
There are an excessive amount of middlemen that broker logistics and trucking
Shipping is a expensive task for Shippers
Many drivers still use traditional paper maps / routes that they memorize, which may not be the most optimal
The way that Kargo wanted to solve the problem was through a reverse auction — an experience where Shippers, folks looking to move packages across Indonesia, would compete for the truck space of Transporters, the people moving said packages. Following marketplace laws, this would create demand for truck space and run on its own. But, through my case study, I uncovered that this would lead Transporters to travel with less-than-optimal truck capacity utilization — not accounting for space and routes, trips would end up being much more expensive than they needed to be. I decided to design an app experience for both Shippers and Transporters to remedy this.
The introduction of the Transporter app helps Transporters visualize their trip before they embark on it as well as guide them to it, reducing the unnecessary directions along the way caused by them taking the ways that they are used to. Additionally, this flow introduces the multi-phase rollout plan that I recommended to Kargo — instead of firstly facilitating on-demand transportation, trucks would be pushed out in Waves, a 24 hour period where trucks can be loaded to full extent through FOMO and pre-emptive booking, allowing Transporters fuller trucks and Shippers cheaper mileage. On-demand booking would come later and at higher upfront costs.
I theorized that through this incentive of FOMO (ie. a Shipper missing a Wave through time / space constraints), this would lead to more full Trucks. On top of this, what looks like a step backwards into Waves is what I hope to actually be a step forward into bringing about fuller Trucks as well as carves out space for Surges / on-demand shipping to exist more efficiently. With Kargo's current feature of allowing any Shipper to use on-demand shipping, this only encourages Trucks to be sub-optimally filled. Hence, by making on-demand a premium feature, not only do Transporters earn more revenue taking these sub-optimal trips, this also encourages the majority of Trucks (through a majority of users being non-paid) to become more optimally full.
In early 2019, with some of the free time that I had from the holidays, I revisited the Kargo case to practice my visual design skills. I produced a problem visualizer to help illustrate the problem:
Additionally, I also worked on bringing my Shipper screens to life: