Context

Pallet-Track is a member and customer-focused palletised distribution network, committed to delivering high-quality service throughout the UK. Their core value of ‘Doing it right’ underscores their support for team members, shareholders, and customers. By prioritizing collaboration, the network nurtures relationships through working groups, business clubs, and regional meetings.

My Role

As the lead designer on this engagement, I started working with Pallet-Track in a small team dedicated to exploring the business and uncovering the problem spaces faced by their various users. The Discovery was done through a Scan, Focus, Act framework - really understanding the users and processes to then develop the future strategy, including a feature roadmap.

With a strategic, holisitic approach I helped the core team establish and pritoritise the feature backlog, which led to bringing on two additional designers to help with the Delivery phase. I managed their workload and progress throughout. This division of responsibilities allowed for a smooth workflow, ensuring that our design process was both efficient and effective. Through our coordinated efforts, we were able to deliver a high-quality product that met the needs and expectations of our stakeholders.

Product Vision

The project aimed to develop a scalable and interoperable Network Management System (NMS) to enhance real-time visibility and manageability of network pallets and billing.

Project Overview

• Duration: November 2023 - September 2024

• Team: UX Designers (3), Developers (5), Data Engineers (3)

• Tools: Figma/FigJam, Jira, Confluence, Miro

Key objectives

• Meeting month-end accuracy within 8 days.

• Reducing scan processing time.

• Enhancing risk mitigation and proactive communication.

• Efficiently scheduling master data updates.

• Ensuring parity for depot functionality.

• Implementing self-serve price scales and providing comprehensive one-day training on the NMS.

Problem Statement

As a client in the early stages of digital transformation with a vision for their solution, we identified key issues and uncovered underlying causes to drive effective change. 

• What? The current system lacks real-time visibility and efficient data management, leading to operational inefficiencies and errors.

• Why? Due to heavy reliance on manual data entry and outdated processes that hinder immediate updates and comprehensive tracking.

• Why? Because of the system's initial design with limited automation and lack of integration with advanced tools for streamlined workflows.

• Why? Originally focused on basic functionality, the system lacks scalability and adaptability to future needs.

• Why? Initially addressing immediate operational needs without anticipating rapid growth or the increasing complexities of network management.

• Why? Due to the evolution of the logistics and pallet tracking industry, with competitors offering more advanced, scalable solutions supporting real-time data visibility to reduce errors.

Research

• Conducting ethnographic research (observation, interviews).

• Interviewing depot operators, logistics managers, and end-users to understand daily challenges and workflows.

• Mapping existing workflows to identify bottlenecks and automation opportunities.

• Evaluating competing products and features to grasp industry standards and innovative solutions.

• Testing early prototypes with end-users for feedback on usability and accessibility.

Key findings

• Challenges with visibility, especially for night staff and depot operators regarding pallet locations and billing statuses.

• High error rates due to manual data entry affecting OTIF and payment accuracy.

• Complex and time-consuming workflows, particularly during peak hours.

• Need for self-service capabilities to manage pricing and updates independently.

• New staff requiring significant time to adapt to the existing system, highlighting the need for a more intuitive design.

• Insights from competitive product audits revealing trends in automation and self-service functionality, emphasizing the necessity for a scalable platform.

Design Process

Continuous Discovery 

• Mapping current process flows to identify inefficiencies and understand the system.

• Conducting frequent stakeholder interviews to align with the company’s vision for operational efficiency and strategic goals.

• Creating story maps to differentiate essential features (MVP) from enhancements (Post-MVP) for development priorities.

• Establishing Epics in Jira.

Ideation & Flows 

• Collaborating with stakeholders to map out flows and develop detailed user flows for accuracy and alignment.

• Capturing flows as stories/JTBD to ensure clarity for the development team.

Wireframing & Testing

• Creating initial wireframes with key interactions annotated for functionality clarification.

• Designing screens in lo-fidelity to focus on core content and interactions during testing.

  
  

Visual Design 

Our visual design phase aimed to create a consistent, intuitive, and scalable interface:

• Colour palette

  • Refining Pallet-Track's existing colors to meet WCAG AA standards, utilizing dark blue (#253D71) as the primary action color for trust and calmness in data-sensitive processes.

• Typography

  • Employing Pallet-Track's ‘Raleway’ for headings and ‘Inter’ for other sizes and weights to ensure legibility and hierarchy in the system.

• Icons

  • Utilizing Material UI's set of icons for quick comprehension and incorporating a comprehensive UI component library for a cohesive visual language.

• Responsive design

  • Developing adaptive layouts for various devices based on user feedback to ensure consistency and ease of use.