Grain Logistics
Mobile App

A leading Australian agricultural company needed a prototype to improve Truck Turnaround Time during the harvest season. With a small window for harvest, avoiding bottlenecks for trucks delivering grain to their sites was critical.

To address this, a site visit, stakeholder workshops, SME consultations, and driver insights were gathered to understand key pain points. The resulting prototype was designed to streamline processes and enhance efficiency.

To comply with my non-disclosure agreement, I have omitted and obfuscated confidential information in this case study.

Role

Senior UX Designer

Team

Myself
+
1 x Principal Designer

1 x Lead UX / UI Designer

1 x Designer

Tools Used

Figma

Miro

Duration

Discovery Phase (6 weeks)

Project Timeline and Approach

Week 1:
Discovery Kickoff

  • Kick-off

  • Site Visit

  • Context Mapping

  • Desktop Research

Week 2: Exploration

  • Desktop Research

  • Process Mapping

Week 3: Insights & Strategy

  • Pain Point Prioritisation

Week 4: Ideation

  • Solution Ideation

  • Solution Prioritisation

Week 5: Design

  • Wireframing & Prototypes

  • Internal review and refinement

  • Feedback

Week 6: Planning

  • Solution Backlog

  • Strategic Roadmap

Week 7: Wrap-Up

  • Engagement Showcase

01. Overview

The grain harvest season in Australia operates within a short and critical window, making efficiency in logistics essential. Delays in Truck Turnaround Time (TTT) during this period can lead to significant losses, affecting farmers, transport operators, and storage providers alike.

Inefficiencies in Truck Turnaround Time (TTT) caused delays, congestion, and financial losses for growers and transport operators. I worked as a Senior UX designer in a cross-functional team to research, design, and prototype a digital solution that would:

  • Reduce truck turnaround times

  • Provide real-time site visibility

  • Digitise manual paperwork

This proof of concept validated the need for a mobile-first platform to streamline grain deliveries and improve operational efficiency.

02. My Role

I led the end-to-end UX design process, including:

  • Conducting on-site and desktop research

  • Workshop facilitation

  • Creating current-state process maps

  • Wireframing and UI

03. Understanding the Problem

Each harvest season, thousands of trucks arrive at sites to unload grain, but inefficiencies caused significant delays.

Key Challenges

  • Long TTT Delays – Weighbridge and tip off bottlenecks and manual processes slowed operations.

  • Lack of Real-Time Visibility – Farmers had no insight into site congestion before arrival.

  • Manual Paperwork – Crop declarations and check-ins required physical forms.

Our research confirmed the need for a digital, data-driven solution to improve efficiency.

04. Research & Insights

The team conducted a site visit to Barellan NSW, I led the desktop research of existing resources, context workshops, and competitive analysis to define the solution.

Findings

On-Site Delays

Trucks can spend up to 3 hours on-site due to bottlenecks.

Lack of Live Status Updates

Without real-time updates, growers and drivers arrived uninformed.

Process Maps

  • Process maps were created to visualise grain delivery and pickup workflows, identifying inefficiencies and opportunities for improvement (red sticky notes). By mapping key steps, task owners, and bottlenecks, these insights informed solution development to enhance efficiency during the critical harvest window.

Inefficient Manual Processes

Manual workflows created unnecessary delays in operations.

Competitive Benchmarking

  • We studied a comparable logistics platform from another provider, which improved efficiency through digital scheduling and queue tracking.

“If I knew which site had shorter queues, I could plan my deliveries better and
complete more deliveries for the day.”

Driver

Painpoint Prioritisation

  • To ensure the most critical issues were addressed, pain points were prioritised based on frequency and impact. This approach helped focus efforts on solving the most pressing inefficiencies that affected farmers, truck drivers, and site operators.

  • Pain points from the “Address First” and “Address Next” quadrants and grouped in the following:

    • No live data of how busy a site is

    • Difficulty of communicating real-time standardised updates

    • Inefficiency from manual data entry

5. Designing the Solution

I facilitated a brainwriting workshop, an ideation exercise where SMEs take turns refining each other’s ideas to address the prioritised pain points from the high frequency / high impact quadrant.

Solution Prioritisation

To determine the best starting point for the solution, high-value ideas were identified based on their potential to alleviate pain points, reduce organisational risk, and ensure feasibility from both a technical and operational standpoint.

SMEs assessed the value of each solution, while a technical expert provided insights into feasibility, ensuring a balanced and strategic approach to implementation.

We designed a mobile-first platform with three core features:

  • Real-time site visibility

  • Digital job creation & automation

  • Alerts & notifications

Focused Features

Real-Time Site Visibility

  • Live queue updates for better scheduling

  • Alternative site recommendations based on congestion

Digital Job Creation & Automation

  • Paperless crop declarations and check-ins

  • Pre-filled truck and grower profiles for faster processing

Alerts & Notifications

  • Real-time alerts for site closures, weather changes, and delays

6. Prototyping & Testing

Wireframes were tested with SMEs and mid-fidelity screens were iterated based on feedback.

Key Refinements

  • Simplified queue tracking for clarity

  • Reduced manual inputs in job creation

  • More intuitive navigation based on user feedback

  • Timely notifications to avoid overwhelming the user

1. Tom starts delivery

Grower Tom sees the stacked job card and presses “Start delivery” to pre-submit the load details and estimated arrival time (ETA) to GrainCorp.

→ This replaces manual handoffs, reducing paperwork and admin delays.

Final UI examples

  1. Active Monitoring with a map view of current location

  2. Notification preferences for the users to choose relevant alerts

  3. Next load planning to plan for subsequent loads and check status

1. Tom starts delivery

Grower Tom sees the stacked job card and presses “Start delivery” to pre-submit the load details and estimated arrival time (ETA) to GrainCorp.

→ This replaces manual handoffs, reducing paperwork and admin delays.

07. Next Steps & Future Impact

Future Impact & Next Steps

  1. Measure Impact & User Testing – Conduct further testing to validate assumptions and refine the solution based on real-world feedback.

  2. Pilot Deployment at Selected Sites – Implement the proof of concept at chosen locations to analyze real-time efficiency gains.

  3. Expand Functionality – Enhance offline capabilities and introduce AI-driven queue prediction for better scheduling and automation. for low-connectivity areas

08. Final Thoughts

This proof of concept demonstrated how UX-driven solutions can streamline logistics, reduce delays, and improve efficiency for farmers, truck drivers, and site operators.