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Before/after montage showing the transition from a raw list of energy assets to a decision interface with map, available capacity and simulation.

From a raw list to a decision

In 2019, we were working on a tool that helped energy suppliers manage batteries, solar panels and other distributed assets across the grid. Energy traders struggled to quickly know how much energy was available, where it was located and how long it could be used — I designed an interface to make those answers visible and test a power demand.

Challenge

Help traders quickly know how much energy can be used, where it is, and how long it remains available.

My role

OwnedContributed
DiscoveryProduct scopingUX architectureData visualizationPrototypingUser testingDelivery

Year

2019

Timeline

9 months

Tools

Figma, Notion, Zeplin

Understanding the problem

Before: an asset list useful for browsing, but insufficient for making quick decisions.

Methodology

Business expert interviews
Energy portfolio mapping
Business scenarios
Data readability tests

Time needed to find

18mn

Available

power

14mn

Available prod or

storage units

22mn

Risk to

local comfort

Key answers required too much manual search.

Business insight

Data existed but answers didn't

Traders could see assets, but not directly the energy actually usable

Trading scenarios

Answers obtained without interaction

1/10

Without filtering, calculating or cross-referencing outside the tool.

Answers requiring manual analysis

7/10

Comparison, forecasting or estimation outside the tool.

The list displayed data, but not answers.

How can we help a trader quickly know how much energy can be used, where, and for how long?

01

Friction

For energy traders

They had to quickly answer a simple question: how much energy can we use now or soon?

Fast decision

Variable availability

Trust required

02

Friction

For energy providers

Thousands of distributed assets had to become a readable and usable reserve.

Distributed assets

Hard to aggregate potential

Local comfort to preserve

Exploration and Solution

01

Create a filtered list view

Add filters, statuses and key columns to find available assets faster.

Mini-wireframe of a filtered list of energy assets.

Quick to ship

Familiar usage

Answer still to reassemble

Decision still slow

Explored
02

Create a geographic view

Display assets on a map to understand where available energy is located.

Mini-wireframe of a geographic view of energy assets.

Clear localisation

More readable portfolio

Observation view only

No simulation

Explored
03

Create a decision view

Combine map, capacity, forecast, local risk and simulation in a single interface.

Mini-wireframe of a combined view with map, forecast, local risk and simulation.

Immediate answer

Testable action

More complex

Thresholds to explain

Selected

Check out the 4 key decisions I made

Readability

Answer, don't list

The list displayed assets, but the interface had to directly answer the decision questions.

Comparison between a raw asset list and an after view directly showing power, availability, risk and simulation result.

Comparison between a raw asset list and an after view directly showing power, availability, risk and simulation result.

Avoided cost

  • Line-by-line searching
  • Answer to reassemble manually

Accepted cost

  • Prioritising the answers
  • Hiding secondary details

Location

Locate before analysing

The map made the distribution of capacity visible before going into details.

Map showing a selected zone of energy assets with available capacity highlighted.

Map showing a selected zone of energy assets with available capacity highlighted.

Avoided cost

  • Invisible capacity by zone
  • Slow geographic comparison

Accepted cost

  • Map to make readable
  • Filters to prioritise

Time

Forecast before acting

The decision had to distinguish currently available capacity from expected capacity during the target window.

Chart comparing currently available capacity and forecast capacity during the target period.

Chart comparing currently available capacity and forecast capacity during the target period.

Avoided cost

  • Too instantaneous a decision
  • Poorly anticipated availability

Accepted cost

  • Displaying uncertainty
  • Explaining the forecast

Action

Simulate before committing

Before using assets, the trader needed to test the demand and verify its feasibility.

Simulation block showing requested power, target period, result, coverage and confidence.

Simulation block showing requested power, target period, result, coverage and confidence.

Avoided cost

  • Too risky a commitment
  • Underestimated local impact

Accepted cost

  • Constraints to model
  • Limits to display

The impacts

The interface transformed slow searching through a raw list into fast reading of decision-ready answers.

  • Traders found usable energy faster

    less line-by-line searching in the asset list

  • Available zones and units became more readable

    production, storage and availability visible in a single view

  • Decisions required fewer manual cross-checks

    more answers obtained directly from the interface

Time to get an answer

Before / After

18mn
4mn
Availablepower
14mn
3mn
Available prod orstorage units
22mn
6mn
Risk tolocal comfort

The same questions became faster to answer.

Before

Answers obtained without interaction1/10
Answers requiring manual analysis7/10
Answers obtained without interaction6/10
Answers requiring manual analysis2/10

After

The new interface reduced manual cross-checking.

Retrospective

Show more data

DON'T

Turn data into actionable answers

INSTEAD

See visualisation as an end

DON'T

Use it as an entry point for a decision

INSTEAD

Hide uncertainty to simplify

DON'T

Make it visible to decide with confidence

INSTEAD
From a raw list to a decision - Quentin Gillon — Quentin Gillon