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Kaarya

A digital solution designed for multi-generational households struggling to manage energy expenses. At its best, KAARYA will reduce the burden on your wallet and the planet.

Duration
Six Weeks

Role
UX Research, Ideation, User Journey,  User Testing, UI Design

Tools
Figma, Miro

Project Brief: We teamed up with GenGame to work on the brief, “ How might we design a mobile app that utilises smart meter data to help multi-generational families work together to reduce their domestic energy consumption and engage positively with climate action.”

Project Outcome: The final solution is a mobile app that pairs the family's daily schedule to the smart meter data using live tracking of appliance usage. It helps reduce tension related to energy usage among family members.

Project Type
Group Project with GenGame

Team
Krishna, Shaardhool MS, Benson Fernandes, Kristine

Empathise

What problem are we solving?

GenGame helps people manage their energy better, to save money and reduce their carbon footprint

• Households contribute to 27% of total carbon emissions in the UK

• 4.7% increase in UK greenhouse gas emissions between 2020-21

Gengame wants us to takle the use of smart meter data in multi-generational families in the UK.

Empathise

What do we know about these families?

 Multi-generational families settled in the UK.

A household run by many members at once and is very unorganised.

Families that prioritise value for money and look for solutions which have immediate effect and are long-lasting.

Families that don’t really have a sense of energy consumption & waste.

Empathise: COM-B Model

How do we get to know them better?

Using the COM-B model we could break down the recognised opportunities for the family + draw out the issues of individual members, considering the different expectations of the multiple generations + try and create a link among these individual pain points to understand how this affects the other members.

Unpacking Assumptions

1

Drawing on personal experience:
This helped us approach this problem with a different perspective and empathise with our target user better.

2

Video Personas:
To better understand families living in the UK, we then watched a curated list of video personas provided on LEEDR project.

3

Empathy map:
We created an empathy map to contextualise our users needs and identify pain points.

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Empathise: Proto-Persona

Who are the target user?

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Understanding the primary persona - Lily.

Part-time working mother of three children

WHO?

Decision maker for a multi-generational family

CONTEXT

Keep a check and take control of energy consumption within the house

WANTS?

She wants to provide a good standard of living for her children

BECAUSE

There are a lot of communication gaps in the family.

BUT?

Vision Statement

We want to design a mobile app for a multi-generational household that lacks control on energy consumed. The app will reduce domestic energy consumption, give its users more confidence when planning energy expenses and improve synergy among family members.

Conceptualise

Defining the UX Design Principles.

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Autonomy
Give our users more control over how much energy is being consumed at home.

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Empowering
Ensure that our product always places the user front and center and allows them to be the main decision maker

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Harmony
Encourage and facilitate coordination among all key members of the family

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Sustainability
Reduce domestic energy consumption and help our users engage positively with climate change

Conceptualise: Brainstorming ideas

How did we address user needs?

Initial Idea

1. Visualizes smart meter data in a more comprehensive manner.
2. Displayed information users can access easily from the IHD provided by their energy supplier

Drawback: Didn’t address any user or business need

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Iterated Idea

1. An activity tracker which required users to schedule their daily activities which consumed energy.
2
. The app would make recommendations to save energy and would track and display energy wasted

Drawback: Addressed a few business goals, but required a lot of input from the user to function effectively.

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Finalising the feature set.

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Activity Tracking

Monitoring all appliances in the house to better understand their usage.

Smart data

Live presentation of peak and off-peak hours from the smart meter data to keep track of best times to perform energy consuming tasks.

Scheduling tasks

AI will automatically provide the best times to perform energy comsuming tasks to save cost.

Ideation: Body-storming

Testing the solution

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Ideation: Journey Mapping

How do we deal with the current drawbacks?

We used a journey map to map out emotions during various moments of interaction with the app and further decide how we need to regulate them for keeping users motivated and make the app effective.

Design: Final prototype

What are the core features of Kaarya?

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1

TRACK

Live tracking of peak and off peak hours helps to plan activities consciously.

2

PLAN

Recommendations of time to perform activities from your to-do list helps you reduce energy consumption and cost wastage.

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3

COLLABORATE

Communication with family about task completion by tracking members helps improve synergy.

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4

TRACK

Keeping track of appliance usage helps you discover opportunities for cost savings.

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5

REWARDS

Get discounts and coupons for making sustainable choices.

Design: User Story

When does Kaarya come in play?

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Reflection

What is the role of Smart Meter data?

1

Push notifications based on proximity & location
Tracking the location of all the registered family members and ensuring that only members present at home receive notifications.

2

Studying peak and off-peak energy supply
Collecting data on timings of peak and off-peak energy supply to make energy forecasts.
 

3

Using external data like weather data to give recommendations
Eg. If weather channels predict clear skies for the day, this data can be used to nudge the users to dry their clothes out in the sun. Prompt users to make more sustainable choices.

Visualise: Risk Analysis

What are the risks related to the design and technology?

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How can we overcome these risks?

1

Monitor AI activity and intervene where necessary.

2

Conduct more user tests to generate and improve functions.

3

Collect user feedback where possible.

How ca we improve the solution in the future?

Conduct our own primary research to understand current contexts better.

Re-evaluate our proto personas and user needs statements.

Increase our target user base and identify a more diverse set of issues

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