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Case Study

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Chazki Afiliados App

Redesigning operational infrastructure for last-mile delivery

Hero image featuring the app on a phone device

Project Overview

Company

Chazki

Industry

Logistics Last-mile delivery Operations

Period

2020

My role

Lead UX Designer

Key actions

Decision layer definition Logistics flow simplification Integrated tools architecture Offline-first execution strategy

01. Context

Last-mile operating system

Chazki operates a last-mile logistics network across multiple Latin American cities, powered by independent delivery drivers known as Afiliados. The Chazki Afiliados app is the system these drivers use to execute routes, register deliveries, and synchronize status in real time with the network.

Operational Scale

The platform supports thousands of daily deliveries. Its performance directly impacts OPEX (Operating Expense), cost per delivery, and SLA compliance with enterprise-tier clients.

02. Problem

The problem wasn't the interface

It was the business's operating system. Research showed drivers weren't following the designed flow; they were manually optimizing their work outside the app based on their own economic incentives.

+30

Steps to complete a single route

+30

Steps to complete a single route

35%

Average non-productive time

35%

Average non-productive time

+30%

Non-optimized kilometers driven

+30%

Non-optimized kilometers driven

High

Dependency on external apps

High

Dependency on external apps

+30

Steps to complete a single route

35%

Average non-productive time

+30%

Non-optimized kilometers driven

High

Dependency on external apps

Driver: "The app doesn't optimize my work. I have to optimize the app."

Problem reframing

The system was not designed to maximize delivery value per effort.

Problem reframing

The system was not designed to maximize delivery value per effort.

Problem reframing

The system was not designed to maximize delivery value per effort.

Problem reframing

The system was not designed to maximize delivery value per effort.

North Star Metric

% Routes completed without ops intervention

Maximized Earnings per Effort Unit

North Star Metric

% Routes completed without ops intervention

Maximized Earnings per Effort Unit

North Star Metric

% Routes completed without ops intervention

Maximized Earnings per Effort Unit

North Star Metric

% Routes completed without ops intervention

Maximized Earnings per Effort Unit

03. Constraints & Complexity

Designing within real-world friction

The project operated under simultaneous technical, connectivity, and organizational constraints, each shaping the scope of every design decision.

Technical Constraints

  • Pre-existing routing engine, no modification allowed.

  • Dispatch systems with fixed APIs and rigid constraints.

  • Third-party logistics APIs with dependency constraints.

Technical Constraints

  • Pre-existing routing engine, no modification allowed.

  • Dispatch systems with fixed APIs and rigid constraints.

  • Third-party logistics APIs with dependency constraints.

Technical Constraints

  • Pre-existing routing engine, no modification allowed.

  • Dispatch systems with fixed APIs and rigid constraints.

  • Third-party logistics APIs with dependency constraints.

Technical Constraints

  • Pre-existing routing engine, no modification allowed.

  • Dispatch systems with fixed APIs and rigid constraints.

  • Third-party logistics APIs with dependency constraints.

Connectivity Constraints

  • Unstable signal across key operational delivery zones.

  • Imprecise GPS behavior in dense urban environments.

  • Low-end Android devices with limited performance.

Connectivity Constraints

  • Unstable signal across key operational delivery zones.

  • Imprecise GPS behavior in dense urban environments.

  • Low-end Android devices with limited performance.

Connectivity Constraints

  • Unstable signal across key operational delivery zones.

  • Imprecise GPS behavior in dense urban environments.

  • Low-end Android devices with limited performance.

Connectivity Constraints

  • Unstable signal across key operational delivery zones.

  • Imprecise GPS behavior in dense urban environments.

  • Low-end Android devices with limited performance.

Organizational Constraints

  • Conflicting vision between control and autonomy.

  • Operations team prioritized manual oversight actions.

  • Shift needed: "control mindset" to "aligned incentives".

Organizational Constraints

  • Conflicting vision between control and autonomy.

  • Operations team prioritized manual oversight actions.

  • Shift needed: "control mindset" to "aligned incentives".

Organizational Constraints

  • Conflicting vision between control and autonomy.

  • Operations team prioritized manual oversight actions.

  • Shift needed: "control mindset" to "aligned incentives".

Organizational Constraints

  • Conflicting vision between control and autonomy.

  • Operations team prioritized manual oversight actions.

  • Shift needed: "control mindset" to "aligned incentives".

04. Strategy & Key decisions

Drivers don't follow flows

The strategy was anchored in a behavioral model: drivers follow incentives. Designing for that reality was the central strategic pivot.

01

Introduce a Decision Layer

Added real-time visibility of earnings, distance, and ETA, enabling informed decisions within the system while eliminating external calculations and guesswork.

Economic Visibility

North Star

01

Introduce a Decision Layer

Added real-time visibility of earnings, distance, and ETA, enabling informed decisions within the system while eliminating external calculations and guesswork.

Economic Visibility

North Star

01

Introduce a Decision Layer

Added real-time visibility of earnings, distance, and ETA, enabling informed decisions within the system while eliminating external calculations and guesswork.

Economic Visibility

North Star

01

Introduce a Decision Layer

Added real-time visibility of earnings, distance, and ETA, enabling informed decisions within the system while eliminating external calculations and guesswork.

Economic Visibility

North Star

02

Reduce Execution Friction

Simplified the operational flow from 30+ to ~12 steps by removing redundant validations, manual steps, and external tool dependencies across execution.

Flow Optimization

−60% steps

02

Reduce Execution Friction

Simplified the operational flow from 30+ to ~12 steps by removing redundant validations, manual steps, and external tool dependencies across execution.

Flow Optimization

−60% steps

02

Reduce Execution Friction

Simplified the operational flow from 30+ to ~12 steps by removing redundant validations, manual steps, and external tool dependencies across execution.

Flow Optimization

−60% steps

02

Reduce Execution Friction

Simplified the operational flow from 30+ to ~12 steps by removing redundant validations, manual steps, and external tool dependencies across execution.

Flow Optimization

−60% steps

03

Integrate Critical Tools

The system stopped delegating core functions. Native navigation and native messaging were integrated, eliminating operational fragmentation across multiple apps.

Native Navigation

Native Messaging

03

Integrate Critical Tools

The system stopped delegating core functions. Native navigation and native messaging were integrated, eliminating operational fragmentation across multiple apps.

Native Navigation

Native Messaging

03

Integrate Critical Tools

The system stopped delegating core functions. Native navigation and native messaging were integrated, eliminating operational fragmentation across multiple apps.

Native Navigation

Native Messaging

03

Integrate Critical Tools

The system stopped delegating core functions. Native navigation and native messaging were integrated, eliminating operational fragmentation across multiple apps.

Native Navigation

Native Messaging

04

Automate Repetitive Actions

Notifications, confirmations, and delivery status updates were automated to reduce cognitive load and minimize operational errors across execution flow consistently.

Event-driven Logic

Cognitive Load ↓

04

Automate Repetitive Actions

Notifications, confirmations, and delivery status updates were automated to reduce cognitive load and minimize operational errors across execution flow consistently.

Event-driven Logic

Cognitive Load ↓

04

Automate Repetitive Actions

Notifications, confirmations, and delivery status updates were automated to reduce cognitive load and minimize operational errors across execution flow consistently.

Event-driven Logic

Cognitive Load ↓

04

Automate Repetitive Actions

Notifications, confirmations, and delivery status updates were automated to reduce cognitive load and minimize operational errors across execution flow consistently.

Event-driven Logic

Cognitive Load ↓

05. System Architecture

From fragmented to decision platform

The architecture was redesigned across four coherent layers that eliminated operational fragmentation and placed decision optimization at the core of the product.

06. Cross-Functional Influence

Strategic alignment across three fronts

As Lead Designer, I translated the behavioral model into business language to align Product, Operations, and Engineering around a single strategic objective.

Stakeholder Alignment Map

Product

Metrics Redefinition

Operational efficiency, delivery autonomy, and feature adoption redefined how product success was measured across the system.

Product

Metrics Redefinition

Operational efficiency, delivery autonomy, and feature adoption redefined how product success was measured across the system.

Product

Metrics Redefinition

Operational efficiency, delivery autonomy, and feature adoption redefined how product success was measured across the system.

Product

Metrics Redefinition

Operational efficiency, delivery autonomy, and feature adoption redefined how product success was measured across the system.

Operations

From Control to Data

Manual oversight was replaced by data-driven monitoring, enabling full traceability and scalable operational decision-making.

Operations

From Control to Data

Manual oversight was replaced by data-driven monitoring, enabling full traceability and scalable operational decision-making.

Operations

From Control to Data

Manual oversight was replaced by data-driven monitoring, enabling full traceability and scalable operational decision-making.

Operations

From Control to Data

Manual oversight was replaced by data-driven monitoring, enabling full traceability and scalable operational decision-making.

Engineering

Feasibility-first design

Offline-first logic, tool integration, and system state simplification ensured scalable execution under operational constraints.

Engineering

Feasibility-first design

Offline-first logic, tool integration, and system state simplification ensured scalable execution under operational constraints.

Engineering

Feasibility-first design

Offline-first logic, tool integration, and system state simplification ensured scalable execution under operational constraints.

Engineering

Feasibility-first design

Offline-first logic, tool integration, and system state simplification ensured scalable execution under operational constraints.

07. Implementation & Adoption

Iterative, evidence-based deployment

The rollout was structured across three progressive phases with field validation before each scale-up.

Phase 01

Internal Testing

  • Validation of optimized flows.

  • Field shadowing with real drivers.

  • Identification of unanticipated friction points.

Qualitative validation of the core hypothesis.

Phase 01

Internal Testing

  • Validation of optimized flows.

  • Field shadowing with real drivers.

  • Identification of unanticipated friction points.

Qualitative validation of the core hypothesis.

Phase 02

Iteration

  • Automation logic adjustments.

  • Fixes based on real network errors.

  • Refinement from direct field feedback.

System stabilized and validated for scale-up.

Phase 02

Iteration

  • Automation logic adjustments.

  • Fixes based on real network errors.

  • Refinement from direct field feedback.

System stabilized and validated for scale-up.

Phase 03

Gradual Rollout

  • Reduced ops support dependency.

  • Increased adoption of key features.

  • Improved operational consistency cross-city.

Measurable impact across business unit P&L.

Phase 03

Gradual Rollout

  • Reduced ops support dependency.

  • Increased adoption of key features.

  • Improved operational consistency cross-city.

Measurable impact across business unit P&L.

Adoption Timeline - multi-squad rollout dashboard
Adoption Timeline - multi-squad rollout dashboard
Adoption Timeline - multi-squad rollout dashboard
Adoption Timeline - multi-squad rollout dashboard

08. Business Impact

Direct impact on the P&L

The redesign delivered measurable improvements in efficiency, scalability, and operational autonomy across the business unit.

-0%

-0%

Route execution time

-0%

-0%

Route execution time

-0%

-0%

Route execution time

-0%

-0%

Manual interactions

-0%

-0%

Manual interactions

-0%

-0%

Manual interactions

+0pp

+0pp

Autonomous routes

+0pp

+0pp

Autonomous routes

+0pp

+0pp

Autonomous routes

+0pp

+0pp

Feature adoption

+0pp

+0pp

Feature adoption

+0pp

+0pp

Feature adoption

Business Impact Dashboard
Business Impact Dashboard
Business Impact Dashboard
09. Key Learnings

What this project taught me

01

Drivers optimize for economics:

The system must align incentives with the business, not impose flows. Designing without understanding the user's economic model produces invisible friction.

02

Fragmentation kills efficiency:

Integrating critical tools delivered more value than improving aesthetics. The biggest UX gain came from reducing context-switching, not from redesigning screens.

03

Decisions > Flows:

Optimizing the user's decision drives greater impact than optimizing the flow. The Decision Layer changed behavior more than any UI change could have.

04

Design defines the system:

The project evolved from UX improvements into the design of scalable operational infrastructure, shaping how delivery execution works at a system level across the network.

Evolution: Quipu Design System

To sustain this new operational model, a standardized design and development foundation was required, leading to the creation of the Quipu Design System as its direct outcome.

Evolution: Quipu Design System

To sustain this new operational model, a standardized design and development foundation was required, leading to the creation of the Quipu Design System as its direct outcome.

Evolution: Quipu Design System

To sustain this new operational model, a standardized design and development foundation was required, leading to the creation of the Quipu Design System as its direct outcome.

Evolution: Quipu Design System

To sustain this new operational model, a standardized design and development foundation was required, leading to the creation of the Quipu Design System as its direct outcome.

Have a product worth scaling?

I help teams turn complex ideas into products users adopt, trust, and rely on

Have a product worth scaling?

I help teams turn complex ideas into products users adopt, trust, and rely on

Have a product worth scaling?

I help teams turn complex ideas into products users adopt, trust, and rely on

Have a product worth scaling?

I help teams turn complex ideas into products users adopt, trust, and rely on

Have a product worth scaling?

I help teams turn complex ideas into products users adopt, trust, and rely on

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