AMEC – The ultimate habit changer

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WHAT? 

Tell us what the concept is about. What are you designing? What are the key benefits?

“Changing context leads to changing mind (you don’t force behaviour change) “.

Relationship, personal finance, and our beliefs are all tied to our daily habits. So often we want to change our habits but so often we fail (just think of new year’s resolution that didn’t happen).

Even when our partners / friends want us to change habits for better, we often fail to do so, and sometimes it leads to bitter argument.

So AMEC allows the first exchange between people to deliver the care. And AMEC as a technology will take the responsibility of all the other repetitive tedious reminders, so if you are not happy, you are not happy about the reminders but not towards your partner. But if you do change for the better, you remember favourably towards your partner.

WHY? 

Tell us some of the key findings of your background research and what is the problem you are trying to address.

Don’t drink and drive campaign was long running failure. But when the relationship context is mentioned, people cared a lot more about their friends and family. With this changing context mindset, can we apply it to help relationship money arguments, personal finance bad habits?

WHO? 

Tell us something about your users and key stakeholders involved.

People participate in pairs

WHEN? 

Give us an idea of the future scenario where your project will be working. 

The idea relies solely on physical human interaction — thus it is ready asap.

But the accuracy of background monitoring requires a few data points. The early stage will probably encounter some inaccurate prediction (lack of datasets and user learning), and it will probably evolve to maturity in two years time.

WHERE? 

Tell us if you have thought of a specific location where to prototype.

London

HOW? 

Give us an idea of your strategy, your process, your prototyping plan and the next steps.

Step 2: apply data collection to trigger AMEC with real data.

Step 3: scale up to a larger trial set, to measure success of behaviour change with workable metrics.

Step 4: investigate the usefulness of data generated and what verify again how value of data can be realised.

Most steps will continue with lean experimentation to realise value quickly.