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hero-engineering

Hero Engineering

Hero Engineering

Hero Engineering

Helping utility managers visualize key power grid data so they can take informed, timely actions to manage energy effectively across Ontario.

Helping utility managers visualize key power grid data so they can take informed, timely actions to manage energy effectively across Ontario.

Helping utility managers visualize key power grid data so they can take informed, timely actions to manage energy effectively across Ontario.

Helping utility managers visualize key power grid data so they can take informed, timely actions to manage energy effectively across Ontario.

Context

Hero Energy & Engineering is a climate-focused firm developing smart-grid solutions to help energy utility managers integrate renewables and improve grid stability. Their mission is to combat climate change by advancing the adoption of distributed energy resources through proprietary, efficiency-driven technologies.

Challenge

Energy Utility Managers in Ontario struggled to monitor grid performance, access critical information, and navigate essential data due to decentralized systems and fragmented workflows. These inefficiencies created major roadblocks in balancing real-time energy demand and supply—posing a complex, high-impact problem that called for a thoughtful and innovative design solution.

My design process

So let's begin!

So let's begin!

What we heard from our users..

To assess user satisfaction and discover areas of opportunities, I conducted user interviews with Energy Utility managers and discovered some common themes across the board:

What the data showed..

I collaborated with the Data & Analytics team to gather, study and interpret all relevant quantitative insights:

Identifying & Prioritizing Data

I conducted 8 user interviews with Energy Utility Managers, and categorized their inputs in order of priority. 



This way I would be able to determine what needed to be represented on the dashboard.

I conducted 8 user interviews with Energy Utility Managers, and categorized their inputs in order of priority. This way I would be able to determine what needed to be represented on the dashboard.

I conducted 8 user interviews with Energy Utility Managers, and categorized their inputs in order of priority. This way I would be able to determine what needed to be represented on the dashboard.

I conducted 8 user interviews with Energy Utility Managers, and categorized their inputs in order of priority. This way I would be able to determine what needed to be represented on the dashboard.

User flows

Mapping out the Grad stability and energy demand vs. supply

Mapping out the Grid stability and energy demand vs. supply

Mapping out the Grid stability and energy demand vs. supply

Mapping out the Grid stability and energy demand vs. supply

BEFORE — Manual data gathering, delayed analysis, and fragmented workflows made it difficult for utility managers to respond quickly to grid instability.

AFTER — Opportunity for a smart dashboard automated data visibility and analysis, enabling real-time decision-making and seamless coordination with grid operators.

How might we…

How might we…

How might we…

Measuring success (KPIs)

Rapid wireframing

The idea was to design fast, fail fast and not worry about perfection. I came up with as many different solution ideas as possible and got feedback and validation proactively from internal stakeholders.


The idea was to design fast, fail fast and not worry about perfection. I came up with as many different solution ideas as possible and got feedback and validation proactively from internal stakeholders.

The idea was to design fast, fail fast and not worry about perfection. I came up with as many different solution ideas as possible and got feedback and validation proactively from internal stakeholders.

Concept testing

Next, I evolved my sketches into

lo-fidelity designs for quick concept testing.



I conducted A/B testing with 4 end-users to determine which solutions resonated better and understand the reasons behind user preferences.

Results

VERSION A

✅

Users were able to easily track renewable power output as a percentage/fraction of total power output. Helpful to track against goals/targets

✅

Users stated that all graphs/charts were easy to read. They could pull key info without issue.

❌

Users wanted to have units of measurements displayed on the y axis as the reading was unclear without it.

Users wanted to have units of measurements displayed on the y-axis as the reading was unclear without it.

Users wanted to have units of measurements displayed on the y-axis as the reading was unclear without it.

Users wanted to have units of measurements displayed on the
y-axis as the reading was unclear without it.

VERSION B

❌

Users wanted more options than just ‘monthly’ when it came to how info was displayed.



Users wanted more options than just 'monthly' when it came to how info was displayed.

✅

Users preferred a different arrangement of the charts/graphs, with energy consumption and demand v supply info on top.

Users preferred a different arrangement of the charts/graphs, with energy consumption and demand v. supply info on top.

✅

Users wanted a clean display on power demand/supply info, and appreciated a number on top of the charts/graphs. Helped to outline power reserve margins.

Dev feasibility checks

Collaborated with developers for feasibility checks, ensuring designs were technically viable and minimizing implementation delays.

Usability testing

First, I created a detailed usability testing script to test for comprehension, discoverability and interaction.



Then, I set-up an interactive hi-fidelity prototype on Trymata to gather feedback from real users and any catch last-minute issues before handoff.

Usability testing

First, I created a detailed usability testing script to test for comprehension, discoverability and interaction.



Then, I set-up an interactive hi-fidelity prototype on Trymata to gather feedback from real users and any catch last-minute issues before handoff.

Review & Analyze — Did we succeed?

Review & Analyze Did we succeed?

Review & Analyze —
Did we succeed?

Reflections & learnings

What went well

Cross-Team Collaboration:
Involving EUM’s AND Grid Operators early in the design process helped identify key usability gaps and ensured the dashboard met real-world needs.

Research & Data-driven solutions:
Leveraging quantitative data and user interviews, I created evidence-backed design solutions, building team trust and stakeholder confidence.

What could I have done better

Calling out new components to devs:
FE developers were confused by new components in Figma that weren't in Atlas, unaware they needed to be built before reuse.

How I fixed this:
Calling out new components to devs:

FE developers were confused by new components in Figma that weren't in Atlas, unaware they needed to be built before reuse.