Background: What Internal Signals Revealed

Lebaran 2022 brought a sharp spike in orders on the BBD platform. Internal team findings highlighted several bottlenecks:

• Overwhelmed operators struggled to keep pace with order assignment.

• Manual direct assignments led to high driver rejection rates.

• The current interface lacked intuitive hierarchy and slowed down decision-making.

The insight? Design inefficiencies were contributing to operational failure — especially under pressure.

Role Scope: Research & Design Facilitator

My contributions included:

• Coordinating cross-team alignment on research goals

• Leading contextual inquiries with operators

• Synthesizing survey and task-flow insights

• Recommending actionable interface design updates

Process Overview

1. Mixed-Method Research
   Quantitative: Analyzed BBD system logs and order timeout data.

   

   
   Qualitative: Conducted contextual inquiry with 5 operators and surveyed 267 drivers in Jabodetabek.

   

   
   

2. Pain Point Mapping

   

   To uncover real workflow challenges, I conducted a contextual inquiry (field observation) with operators during live dispatch sessions. This helped me understand their actual journey, decision points, and the frictions they faced in the moment. Based on these observations, I have mapped out the following user journey (HD version of the journey can be accessed through this link).

   

   
   Then, I translated it into an Operator Direct Assignment Workflow. However, during our contextual inquiry in the Lebaran 2022 period, we uncovered a critical bottleneck: only four dispatchers were responsible for managing the entire surge of incoming orders.

   

   
   From the observed workflows, we identified two categories of snipper pain points:

   Non-Product Issues (experienced by all snippers):

   • Slow internet connection

   • Lagging or unresponsive devices

   
   Product-Related Issues:

   • High rejection rates and delayed acceptance from drivers, making direct assignment take up to 20 minutes

   • Poor informational hierarchy and layout in the UI, causing navigation friction
     
     
     

3. Ideation & Redesign Proposals

   Design improvements were proposed based on operator pain points and repetitive task patterns. With two interface versions available (existing and revamped), specific solutions were outlined for each to address usability and efficiency gaps.

   

   
   

📘 Lessons Learned

Designing for time-critical systems like dispatching demands more than just a clean UI — it requires precision in layout and frictionless execution. During this case, a few key insights emerged:

1. Real-world usage beats assumptions. Field observation revealed operational bottlenecks that raw data alone couldn’t surface, such as the fact that only four snippers were handling a massive order load during peak times.

2. Driver rejection patterns are predictable. Many drivers reject assignments because they’re already busy with Gojek, loyal customers, or short-distance jobs. These behavioral insights helped inform clearer system logic and messaging.

3. Small UX tweaks go far. Reordering critical table columns, reducing scroll effort, or preventing pop-up interruptions had a disproportionately large impact on task speed and user comfort.
   
   

🎯 Opportunities for Iteration

The following enhancements were proposed as part of future improvements:

1. Operator-aware flagging to show if another dispatcher is already handling an order — reducing double effort.

2. Sticky UI layout to keep key actions (like Direct Assign) within constant reach.

3. Integrate fleet availability into Jobwatch — enabling snippers to prioritize based on real-time driver location.