UX Case Study

Recykal

Collection Agent App

Building a Scalable Platform to Empower Recyclers and Sellers

UX Case Study

Recykal

Collection Agent App

Building a Scalable Platform to Empower Recyclers and Sellers

Overview

Overview

The Collection Agent App was designed to solve operational challenges faced by recycling agents working under the Deposit Refund Scheme (DRS). The goal was to create a reliable and easy-to-use tool that improved agent productivity, ensured transparency, and supported the environmental goals of the programme.

Role

UX and UI Designer (sole contributor)

Role

UX and UI Designer (sole contributor)

Role

UX and UI Designer (sole contributor)

Duration

April 2024 – August 2024

Duration

April 2024 – August 2024

Duration

April 2024 – August 2024

Team

UX Manager, Product Manager, Developers

Team

UX Manager, Product Manager, Developers

Team

UX Manager, Product Manager, Developers

Tools

Figma, Notion, Google Meet

Tools

Figma, Notion, Google Meet

Tools

Figma, Notion, Google Meet

Context

Context

Context

What is the Deposit Refund Scheme ?

The Deposit Refund Scheme (DRS) encourages recycling by attaching a refundable deposit to beverage containers. When consumers return used bottles through Reverse Vending Machines (RVMs) or Soundboxes, they receive their deposit back. This initiative reduces waste and promotes responsible disposal.

What is the Deposit Refund Scheme ?

The Deposit Refund Scheme (DRS) encourages recycling by attaching a refundable deposit to beverage containers. When consumers return used bottles through Reverse Vending Machines (RVMs) or Soundboxes, they receive their deposit back. This initiative reduces waste and promotes responsible disposal.

What is the Deposit Refund Scheme ?

The Deposit Refund Scheme (DRS) encourages recycling by attaching a refundable deposit to beverage containers. When consumers return used bottles through Reverse Vending Machines (RVMs) or Soundboxes, they receive their deposit back. This initiative reduces waste and promotes responsible disposal.

First Pilot Location:

Kedarnath Temple trek, Uttarakhand

First Pilot Location:

Kedarnath Temple trek, Uttarakhand

First Pilot Location:

Kedarnath Temple trek, Uttarakhand

Partners:

Uttarakhand Government and Recykal

Partners:

Uttarakhand Government and Recykal

Partners:

Uttarakhand Government and Recykal

Visual Representation of DRS Process

Who are the Collection Agents ?

Collection agents manage the recycling process on the ground. They monitor RVMs and Soundboxes, collect and sort recyclable material, and coordinate transport to recycling depots. They often operate in remote and low-connectivity areas, making efficient coordination crucial.

Who are the Collection Agents ?

Collection agents manage the recycling process on the ground. They monitor RVMs and Soundboxes, collect and sort recyclable material, and coordinate transport to recycling depots. They often operate in remote and low-connectivity areas, making efficient coordination crucial.

Who are the Collection Agents ?

Collection agents manage the recycling process on the ground. They monitor RVMs and Soundboxes, collect and sort recyclable material, and coordinate transport to recycling depots. They often operate in remote and low-connectivity areas, making efficient coordination crucial.

Problem Statement

Problem Statement

Problem Statement

What challenges did the agents face

Agents struggled with inefficiencies that slowed operations and created confusion in earnings and logistics. The goal was to design a digital platform that streamlined daily workflows, reduced downtime, and built trust through transparency.

What challenges did the agents face

Agents struggled with inefficiencies that slowed operations and created confusion in earnings and logistics. The goal was to design a digital platform that streamlined daily workflows, reduced downtime, and built trust through transparency.

What challenges did the agents face

Agents struggled with inefficiencies that slowed operations and created confusion in earnings and logistics. The goal was to design a digital platform that streamlined daily workflows, reduced downtime, and built trust through transparency.

Device Failures

Frequent device failures with no manual backup process

Device Failures

Frequent device failures with no manual backup process

Device Failures

Frequent device failures with no manual backup process

Earnings Tracking

Manual earnings tracking prone to error and mistrust

Earnings Tracking

Manual earnings tracking prone to error and mistrust

Earnings Tracking

Manual earnings tracking prone to error and mistrust

Poor Coordination

Poor coordination in recyclable pickups

Poor Coordination

Poor coordination in recyclable pickups

Poor Coordination

Poor coordination in recyclable pickups

Limited Visibility

Limited visibility into device status and operational metrics

Limited Visibility

Limited visibility into device status and operational metrics

Limited Visibility

Limited visibility into device status and operational metrics

Research and Discovery

Research and Discovery

Research and Discovery

How we understood the problem

To identify the real challenges, multiple field-based research methods were conducted to map workflow patterns and gather direct feedback from agents.

How we understood the problem

To identify the real challenges, multiple field-based research methods were conducted to map workflow patterns and gather direct feedback from agents.

How we understood the problem

To identify the real challenges, multiple field-based research methods were conducted to map workflow patterns and gather direct feedback from agents.

Shadowing the Processg

Observed agents during active collection to map workflow patterns

Shadowing the Processg

Observed agents during active collection to map workflow patterns

Shadowing the Processg

Observed agents during active collection to map workflow patterns

Conversations with Agents

Discussed pain points and gathered feedback directly from agents

Conversations with Agents

Discussed pain points and gathered feedback directly from agents

Conversations with Agents

Discussed pain points and gathered feedback directly from agents

Operational Issues Log

Reviewed system logs to identify repeated failures

Operational Issues Log

Reviewed system logs to identify repeated failures

Operational Issues Log

Reviewed system logs to identify repeated failures

Key Insights Discovered

Downtime Impact

Agents lost significant productive work time during device failures, with no alternative method to continue serving consumers or processing returns.

Downtime Impact

Agents lost significant productive work time during device failures, with no alternative method to continue serving consumers or processing returns.

Downtime Impact

Agents lost significant productive work time during device failures, with no alternative method to continue serving consumers or processing returns.

Downtime Impact

Agents lost significant productive work time during device failures, with no alternative method to continue serving consumers or processing returns.

Communication Burden

Coordination required multiple phone calls per pickup, consuming time and leading to miscommunication about locations, timing, and quantities.

Communication Burden

Coordination required multiple phone calls per pickup, consuming time and leading to miscommunication about locations, timing, and quantities.

Communication Burden

Coordination required multiple phone calls per pickup, consuming time and leading to miscommunication about locations, timing, and quantities.

Communication Burden

Coordination required multiple phone calls per pickup, consuming time and leading to miscommunication about locations, timing, and quantities.

Trust Deficit

Lack of real-time tracking reduced trust in the system, with agents uncertain whether their work was being accurately recorded and compensated.

Trust Deficit

Lack of real-time tracking reduced trust in the system, with agents uncertain whether their work was being accurately recorded and compensated.

Trust Deficit

Lack of real-time tracking reduced trust in the system, with agents uncertain whether their work was being accurately recorded and compensated.

Trust Deficit

Lack of real-time tracking reduced trust in the system, with agents uncertain whether their work was being accurately recorded and compensated.

Manual Recording

Earnings and refunds were tracked manually in personal notebooks, creating disputes and making it impossible to verify historical transactions.

Manual Recording

Earnings and refunds were tracked manually in personal notebooks, creating disputes and making it impossible to verify historical transactions.

Manual Recording

Earnings and refunds were tracked manually in personal notebooks, creating disputes and making it impossible to verify historical transactions.

Manual Recording

Earnings and refunds were tracked manually in personal notebooks, creating disputes and making it impossible to verify historical transactions.

Images from the Pilot Project (Credit : Recykal Team)

Design Goals

Design Goals

Design Goals

Design Goals

The Collection Agent App was designed to solve operational challenges faced by recycling agents working under the Deposit Refund Scheme (DRS). The goal was to create a reliable and easy-to-use tool that improved agent productivity, ensured transparency, and supported the environmental goals of the programme.

1. Real-Time Device Monitoring

Provide visibility into device status and errors to minimize downtime.

1. Real-Time Device Monitoring

Provide visibility into device status and errors to minimize downtime.

1. Real-Time Device Monitoring

Provide visibility into device status and errors to minimize downtime.

1. Real-Time Device Monitoring

Provide visibility into device status and errors to minimize downtime.

2. Manual Return Processing

Enable operations to continue even during device or network outages.

2. Manual Return Processing

Enable operations to continue even during device or network outages.

2. Manual Return Processing

Enable operations to continue even during device or network outages.

2. Manual Return Processing

Enable operations to continue even during device or network outages.

3. Transparent Earnings Tracking

Give agents confidence with clear and accurate earnings data.

3. Transparent Earnings Tracking

Give agents confidence with clear and accurate earnings data.

3. Transparent Earnings Tracking

Give agents confidence with clear and accurate earnings data.

3. Transparent Earnings Tracking

Give agents confidence with clear and accurate earnings data.

4. Simplified Pickup Scheduling

Reduce coordination effort and improve timing through a structured scheduling system.

4. Simplified Pickup Scheduling

Reduce coordination effort and improve timing through a structured scheduling system.

4. Simplified Pickup Scheduling

Reduce coordination effort and improve timing through a structured scheduling system.

4. Simplified Pickup Scheduling

Reduce coordination effort and improve timing through a structured scheduling system.

Success Criteria

Solutions must work reliably in low-connectivity environments, require minimal training to adopt, and demonstrably reduce time spent on administrative tasks whilst increasing transparency and trust.

Success Criteria

Solutions must work reliably in low-connectivity environments, require minimal training to adopt, and demonstrably reduce time spent on administrative tasks whilst increasing transparency and trust.

Success Criteria

Solutions must work reliably in low-connectivity environments, require minimal training to adopt, and demonstrably reduce time spent on administrative tasks whilst increasing transparency and trust.

Success Criteria

Solutions must work reliably in low-connectivity environments, require minimal training to adopt, and demonstrably reduce time spent on administrative tasks whilst increasing transparency and trust.

Design Execution

Design Execution

Design Execution

Design Execution

Wireframes

We began with low-fidelity sketches to simplify agent workflows and define key task sequences. The focus throughout this phase was on speed, clarity, and minimal navigation layers.

Wireframes

We began with low-fidelity sketches to simplify agent workflows and define key task sequences. The focus throughout this phase was on speed, clarity, and minimal navigation layers.

Wireframes

We began with low-fidelity sketches to simplify agent workflows and define key task sequences. The focus throughout this phase was on speed, clarity, and minimal navigation layers.

Wireframes

We began with low-fidelity sketches to simplify agent workflows and define key task sequences. The focus throughout this phase was on speed, clarity, and minimal navigation layers.

Final Designs

Final Designs

Final Designs

Final Designs

Design System

Testing & Validation

Testing & Validation

Testing & Validation

Testing & Validation

Testing Method

To validate the MVP, we conducted a two-week field test with 15 collection agents during the Kedarnath pilot. The goal was to evaluate real-world usability, efficiency, and agent satisfaction. Our approach combined qualitative insights with measurable outcomes:

Testing Method

To validate the MVP, we conducted a two-week field test with 15 collection agents during the Kedarnath pilot. The goal was to evaluate real-world usability, efficiency, and agent satisfaction. Our approach combined qualitative insights with measurable outcomes:

Testing Method

To validate the MVP, we conducted a two-week field test with 15 collection agents during the Kedarnath pilot. The goal was to evaluate real-world usability, efficiency, and agent satisfaction. Our approach combined qualitative insights with measurable outcomes:

Testing Method

To validate the MVP, we conducted a two-week field test with 15 collection agents during the Kedarnath pilot. The goal was to evaluate real-world usability, efficiency, and agent satisfaction. Our approach combined qualitative insights with measurable outcomes:

In-person Shadowing and Communication

We closely observed agents as they used the app in their daily routines, engaging in direct conversations to understand their needs, struggles, and feedback in real-time.

In-person Shadowing and Communication

We closely observed agents as they used the app in their daily routines, engaging in direct conversations to understand their needs, struggles, and feedback in real-time.

In-person Shadowing and Communication

We closely observed agents as they used the app in their daily routines, engaging in direct conversations to understand their needs, struggles, and feedback in real-time.

In-person Shadowing and Communication

We closely observed agents as they used the app in their daily routines, engaging in direct conversations to understand their needs, struggles, and feedback in real-time.

Quantitative Metrics Collection

We tracked key performance indicators such as time saved, task completion rates, and overall satisfaction score to evaluate the app’s impact on efficiency and usability.

Quantitative Metrics Collection

We tracked key performance indicators such as time saved, task completion rates, and overall satisfaction score to evaluate the app’s impact on efficiency and usability.

Quantitative Metrics Collection

We tracked key performance indicators such as time saved, task completion rates, and overall satisfaction score to evaluate the app’s impact on efficiency and usability.

Quantitative Metrics Collection

We tracked key performance indicators such as time saved, task completion rates, and overall satisfaction score to evaluate the app’s impact on efficiency and usability.

Key Results

The testing revealed significant improvements across all measured dimensions, with agents reporting high satisfaction and demonstrable efficiency gains.

Key Results

The testing revealed significant improvements across all measured dimensions, with agents reporting high satisfaction and demonstrable efficiency gains.

Key Results

The testing revealed significant improvements across all measured dimensions, with agents reporting high satisfaction and demonstrable efficiency gains.

Key Results

The testing revealed significant improvements across all measured dimensions, with agents reporting high satisfaction and demonstrable efficiency gains.

Increased Task Confidence

Agents appreciated the clarity provided by real-time device monitoring and error notifications.

Increased Task Confidence

Agents appreciated the clarity provided by real-time device monitoring and error notifications.

Increased Task Confidence

Agents appreciated the clarity provided by real-time device monitoring and error notifications.

Increased Task Confidence

Agents appreciated the clarity provided by real-time device monitoring and error notifications.

Faster Troubleshooting

Agents were able to resolve issues faster, even when devices malfunctioned.

Faster Troubleshooting

Agents were able to resolve issues faster, even when devices malfunctioned.

Faster Troubleshooting

Agents were able to resolve issues faster, even when devices malfunctioned.

Faster Troubleshooting

Agents were able to resolve issues faster, even when devices malfunctioned.

Higher User Satisfaction

Agents found the app intuitive and appreciated having everything they needed in one place.

Higher User Satisfaction

Agents found the app intuitive and appreciated having everything they needed in one place.

Higher User Satisfaction

Agents found the app intuitive and appreciated having everything they needed in one place.

Higher User Satisfaction

Agents found the app intuitive and appreciated having everything they needed in one place.

Enhanced Trust in Earnings Transparency

The earnings tracker reassured agents that their payments were accurate and up-to-date.

Enhanced Trust in Earnings Transparency

The earnings tracker reassured agents that their payments were accurate and up-to-date.

Enhanced Trust in Earnings Transparency

The earnings tracker reassured agents that their payments were accurate and up-to-date.

Enhanced Trust in Earnings Transparency

The earnings tracker reassured agents that their payments were accurate and up-to-date.

Constructive Feedback

1. Navigation Challenges

Some agents felt navigating between features took extra steps.

1. Navigation Challenges

Some agents felt navigating between features took extra steps.

1. Navigation Challenges

Some agents felt navigating between features took extra steps.

1. Navigation Challenges

Some agents felt navigating between features took extra steps.

2. Visibility of Key Metrics

Agents suggested making total earnings and bottle collections more prominent.

2. Visibility of Key Metrics

Agents suggested making total earnings and bottle collections more prominent.

2. Visibility of Key Metrics

Agents suggested making total earnings and bottle collections more prominent.

2. Visibility of Key Metrics

Agents suggested making total earnings and bottle collections more prominent.

3. App Responsiveness

A few agents reported slight delays in screen loading during peak usage.

3. App Responsiveness

A few agents reported slight delays in screen loading during peak usage.

3. App Responsiveness

A few agents reported slight delays in screen loading during peak usage.

3. App Responsiveness

A few agents reported slight delays in screen loading during peak usage.

4. Offline Mode Needs

Agents requested offline functionality for low-connectivity areas.

4. Offline Mode Needs

Agents requested offline functionality for low-connectivity areas.

4. Offline Mode Needs

Agents requested offline functionality for low-connectivity areas.

4. Offline Mode Needs

Agents requested offline functionality for low-connectivity areas.

Images from the user testing (Credit : Recykal Team)

Images from the user testing (Credit : Recykal Team)

Iteration and Improvements

Iteration and Improvements

Iteration and Improvements

Iteration and Improvements

Home Screen

Profile Screen

Conclusion

Conclusion

Conclusion

Conclusion

Key Learnings

1. Observe Before Designing

Real field observation revealed needs that documentation missed, providing invaluable context for design decisions.

1. Observe Before Designing

Real field observation revealed needs that documentation missed, providing invaluable context for design decisions.

1. Observe Before Designing

Real field observation revealed needs that documentation missed, providing invaluable context for design decisions.

1. Observe Before Designing

Real field observation revealed needs that documentation missed, providing invaluable context for design decisions.

2. Iterate With Intent

Regular feedback cycles shaped usable and meaningful features that truly addressed agent needs.

2. Iterate With Intent

Regular feedback cycles shaped usable and meaningful features that truly addressed agent needs.

2. Iterate With Intent

Regular feedback cycles shaped usable and meaningful features that truly addressed agent needs.

2. Iterate With Intent

Regular feedback cycles shaped usable and meaningful features that truly addressed agent needs.

3. Design for Reliability

Consistency matters more than visual complexity in low-resource contexts and challenging environments.

3. Design for Reliability

Consistency matters more than visual complexity in low-resource contexts and challenging environments.

3. Design for Reliability

Consistency matters more than visual complexity in low-resource contexts and challenging environments.

3. Design for Reliability

Consistency matters more than visual complexity in low-resource contexts and challenging environments.

4. Collaborate Early

Working closely with engineering and product teams ensured scalability and technical feasibility.

4. Collaborate Early

Working closely with engineering and product teams ensured scalability and technical feasibility.

4. Collaborate Early

Working closely with engineering and product teams ensured scalability and technical feasibility.

4. Collaborate Early

Working closely with engineering and product teams ensured scalability and technical feasibility.

Final Thought

The Collection Agent App unified disconnected recycling processes into one reliable digital workflow. It helped agents work confidently, reduced downtime, and strengthened transparency across the DRS ecosystem.

Final Thought

The Collection Agent App unified disconnected recycling processes into one reliable digital workflow. It helped agents work confidently, reduced downtime, and strengthened transparency across the DRS ecosystem.

Final Thought

The Collection Agent App unified disconnected recycling processes into one reliable digital workflow. It helped agents work confidently, reduced downtime, and strengthened transparency across the DRS ecosystem.

Final Thought

The Collection Agent App unified disconnected recycling processes into one reliable digital workflow. It helped agents work confidently, reduced downtime, and strengthened transparency across the DRS ecosystem.

Note :

Complete design flows, intermediate explorations, and several key screens are not shown publicly due to confidentiality. A detailed walkthrough of the user journey and final interactions can be shared privately during portfolio discussions.

Note :

Complete design flows, intermediate explorations, and several key screens are not shown publicly due to confidentiality. A detailed walkthrough of the user journey and final interactions can be shared privately during portfolio discussions.

Note :

Complete design flows, intermediate explorations, and several key screens are not shown publicly due to confidentiality. A detailed walkthrough of the user journey and final interactions can be shared privately during portfolio discussions.

Note :

Complete design flows, intermediate explorations, and several key screens are not shown publicly due to confidentiality. A detailed walkthrough of the user journey and final interactions can be shared privately during portfolio discussions.