Explain a Home Energy Spike
Design an energy dashboard that helps a household investigate an unusual usage increase without pretending to identify an appliance with certainty.
The brief
Understand the problem
Background
Energy totals are hard to act on without weather, tariff, occupancy, and data-quality context. Device-level estimates can be useful, but they are often inferred and should not be presented as measured fact.
User context
Anika notices that her weekly electricity cost is 38 percent higher than usual. A heat wave, a new portable air conditioner, and two missing smart-meter intervals may all affect the comparison.
Product problem
A resident needs to understand what is known, compare relevant periods, and choose a practical next check without being pushed toward an unsupported diagnosis.
Objective
Create an overview, spike investigation, comparison, and action-plan flow for one household energy anomaly.
What to design
Define the experience
Required experience
- Recognize an unusual cost or usage period and its data completeness
- Compare the period with weather-adjusted and user-selected baselines
- Review measured events separately from estimated appliance categories
- Save an observation or alert for a specific follow-up
Screens and states
- Energy overview
- Spike investigation
- Period comparison
- Follow-up plan
Core user flow
Follow the critical path
- 01
Anika opens the weekly overview and sees the cost increase plus a missing-data notice
- 02
She compares usage with a similar-temperature week rather than the previous calendar week
- 03
The investigation shows sustained afternoon load and labels appliance categories as estimates
- 04
She records the date the portable air conditioner was added
- 05
She sets a high-usage alert and a reminder to compare again after seven days
Product rules
Requirements and constraints
Requirements
- Separate energy use, estimated cost, tariff effects, and data completeness
- Let people compare calendar, weather-adjusted, and custom periods
- Label measured device data, household annotations, and inferred categories distinctly
- Provide accessible chart summaries and a tabular alternative
- Turn observations into a specific alert or follow-up rather than generic efficiency advice
Constraints
- Smart-meter readings can arrive late or be revised
- Tariffs may vary by time, tier, and billing period
- The service cannot confirm that a particular appliance caused the spike without direct measurement
Reality check
States worth considering
Ready-to-use content
Mock data
Use this content to test hierarchy and realistic data states. You can expand it when the concept needs more depth.
Current week
- 94.6 kWh measured
- $31.80 estimated cost
- 38% above baseline
- 96% interval coverage
Context
- Average high: 34 C
- Portable AC added Tuesday
- Peak tariff: 4:00 PM to 9:00 PM
Finish line
What to deliver
- Four responsive screens explaining an energy spike, incomplete data, and a concrete follow-up
Optional direction
Visual resources
Use these as a starting constraint if you want one. They are not part of the required solution.