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Pandora Intelligence
Pandora Intelligence is a data analysis platform that uses AI to help organizations detect patterns, assess risks, and make informed decisions. It turns complex, fragmented data into clear insights, supporting users in high-stakes environments like security, finance, and the cargo industry.
Turning Complexity into Clarity
A View That Guides Decisions
0.1 Overview
I designed a consolidated view that transforms complex, scattered data into a single, actionable interface. By streamlining workflows, improving information clarity, and validating designs through stakeholder input and scenario-based testing, the solution enables users to make faster, more confident decisions while reducing errors. This project demonstrates my ability to solve complex UX problems, iterate efficiently, and deliver impactful, user-centered design solutions.
0.2 The challange
The core challenge was twofold: simplify complex, scattered data into a single, clear view and design effectively without direct access to end users. This required finding creative ways to validate decisions, through stakeholder input, simulations, and scenario-based tests, while maintaining speed and accuracy in a high-pressure environment.
Problem
Information Overload: Based on stakeholder insights, scenario based tests, and workflow review, it was clear that users had to navigate multiple sections to extract critical information, slowing decision-making.
No Direct User Access: Without the ability to conduct formal user research or testing, design decisions risked being based on assumptions rather than actual analyst workflows.
Fast-Paced Environment: As the sole designer in a dynamic context, I needed ways to validate design decisions quickly while managing a heavy workload.
Solution
Consolidated Summary View: Designed a single interface that brought critical data together, eliminating the need to switch between sections and allowing users to act on information faster.
Weekly Design Critiques: Facilitated recurring sessions with stakeholders and domain experts to leverage their knowledge, validate assumptions, and collect information that reflected real workflows.
Scenario-Based Validation: Conducted usability tests with external participants, simulating users tasks. These sessions revealed gaps in navigation, data clarity, and usability, enabling targeted refinements.
Persona Development: Created user personas to guide design decisions and ensure the interface met real user needs across different contexts.
0.3 UX Strategy
The core challenge was twofold: simplify complex, scattered data into a single, clear view and design effectively without direct access to end users. This required finding creative ways to validate decisions, through stakeholder input, simulations, and scenario-based tests, while maintaining speed and accuracy in a high-pressure environment.
70% Familiarity
Guided by Jakob’s Law—users expect your interface to work like the ones they already know—the summary view uses well-established layout patterns and interaction models. Borrowing from familiar design conventions lowers the learning curve, reduces cognitive load, and lets analysts focus on analysis instead of figuring out the interface.
30% Distinction
The “magic” is in the micro-decisions: typography that supports quick scanning, balanced spacing that prevents visual clutter, and a content hierarchy that makes critical risk information impossible to miss. These small choices turn raw data into a clear, decision-ready view.
The power of familiarity
With limited design resources and no room for deep-dive user research, we anchored our UX strategy in Jakob’s Law: users spend most of their time on other sites, so they expect ours to feel familiar.
I drew inspiration from familiar design patterns that the target group encounter daily in established platforms like DHL and FedEx tracking interfaces for the navigation structure and status indicators, enterprise supply chain dashboards like those used in MetricStream for the risk assessment layouts
This approach aims to minimise onboarding time and streamline future development by leveraging patterns users already know by heart.
0.4 Closing
The final call
Ultimately, the team proceeded with……
Winning Moments
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Lessons Learned
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