Driver Safety Analytics Dashboard

Driver safety analytics dashboard

Designing a rapid decision-support system to assess driver suitability and risk

This project was completed as part of a rapid tender process for Engen. The goal was to design a clear, credible system that could help assess driver suitability and safety risk, supporting early decision-making rather than full product development.

Problem

Engen needed a way to quickly and consistently assess whether driver candidates would be suitable to operate within their safety standards.
Existing information was fragmented across documents and spreadsheets, making it difficult to form a clear view of risk, compliance, and readiness.

This challenge was further constrained by the tender context:

Tight timelines
Limited access to end users
The need to demonstrate feasibility and clarity quickly

Objective

Design a clarity-first dashboard concept that enables managers to:

Assess driver suitability at a glance
Interpret safety and competency indicators consistently
Make informed decisions without manually interpreting raw data

The goal was to support confident decision-making, not long-term optimisation.

Role

UX/UI designer (end-to-end) in collaboration with a data analyst.

Responsabilities

Structuring complex safety and competency data
Defining information hierarchy and user flows
Designing a clear, scannable dashboard interface
Translating tender requirements into a usable system concept

Timeline

5 days

Tools

Figma

UX Strategy

Every design decision was evaluated against one question:
Can a manager confidently make a decision using this interface?

Given the safety-critical and time-constrained context,
the UX strategy focused on:

Reducing cognitive load while presenting complex data
Making risk immediately visible without overwhelming
users
Supporting both quick scanning and deeper investigation
Designing for trust, consistency, and accountability

Understanding Key
Safety Needs

Early exploration focused on understanding what decision-makers needed when assessing drivers, rather than exposing raw data.

Key considerations included:

Overall safety compliance
Competency coverage across required criteria
Indicators of potential risk or concern

The intent was to surface meaningful signals, not overwhelm
users with numbers.

Decision-Led User Flow

The user flow was designed to support both rapid checks and deeper review, depending on the situation.

The Initial views prioritise high-level awareness and risk signals,
whilst subsequent steps allow managers to drill into detailed driver information when needed

Decision points were intentionally limited to reduce friction and support fast, confident judgment in operational environments.

Final Design
Solution (below)

The final dashboard concept prioritises clarity, consistency, and scannability.

While the underlying scoring and risk logic was defined by the data team, the interface was designed to help managers interpret and act on these insights quickly and confidently.

The dashboard enables managers to:

Identify high-risk drivers through clear visual indicators
Compare safety and competency status across candidates
Drill down into detailed reports when further assessment
is required
Maintain oversight without switching between tools

Usability Validation

Given the tender context, lightweight validation was
conducted with internal stakeholders.

The goal of testing was to validate decision support, not
the accuracy of underlying data models.

Feedback confirmed that: