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Design Thinking meets Science

Updated: Jun 21, 2020

When one first hears about the human-centered design (HCD) approach of Design Thinking, they generally perceive it to be a methodology that is skewed towards being qualitative, subjective and heavily intuition-based. So you may ask exactly how might we make the HCD methodology be more scientific?


Inspired by the Stanford Social Innovation Review’s article on “Behavioural Design” and theories behind Behavioural Economics, we would like to share how you can use Design Thinking to encourage desired outcomes when approaching a problem challenge by taking these few steps into consideration when using the HCD approach.


To provide some context, Behavioural Economics theories state that human behaviours are non-rational due to social, environmental, emotional and psychological factors that impact a user’s decision making process. If we look around us, we find many applications of Behavioural Economics in our daily lives - from product marketing, consumption decisions, government policies to the route that we choose to use to get to work everyday.


Laying this out in the chronological (yet still, iterative) order of the HCD approach,


1. Let’s first look at the framing of the problem statement. In the standard HCD approach, we try to frame a problem statement that is specific, targeted and yet broad enough to not limit the potential of ideas. In the behavioural design approach, we should also be including the types of desired user behaviours we are trying to encourage in our problem statement. An example could be: How might we re-design healthcare accessibility in developing countries such that parents will ensure that their child obtains all required vaccinations?


2. Next, to understand our user persona, under the HCD approach, an in-depth analysis will be conducted to gather insights about the user’s motivations in decisions that they make. The way questions are asked are focused on the “Why”, as we try to probe into the root of the reasons. In the behavioural design approach, we can consider also asking the “How” when interviewing users to understand their rationale behind the decisions they make. This will allow us to gain additional insights into the 3Cs - conditions, circumstances, constraints during a user’s journey or decision making process. This gives us a more enriched picture of the social or environmental conditions, physical or mental circumstances and other constraints that the user is in at that point in time of their journey. With a behavioural design approach, we want to aim for the user to always choose the desired outcome regardless of the 3Cs that they face. An example could be asking the user: How were you feeling when carrying out this banking transaction using the mobile app?


3. Having gathered the additional insights from the 3Cs, the next stage of ideation will also factor in these information when we are brainstorming for ideas. However, this does not mean that we need to limit the quantity of our ideas based on the 3Cs. We should still aim to diverge in our thinking, and then converging subsequently. However, gathering these insights upfront could save us some time when deciding to converge on specific ideas and also ensure that we have considered how to successfully implement potential solutions with our targeted users.


4. In the prototype and test stages, we could adopt a randomised controlled trial approach to test the prototypes of our ideas. We can experiment on how to run them in shorter time frames to quickly and accurately obtain results. We should think about the quantifiable metrics to use to objectively measure the impact of our ideas when testing them with our users. This will allow a more robust approach when comparing our results between the groups in our trials and obtain quantifiable data using our defined metrics. Think about metrics beyond directly measuring the end outcome displayed by the user, and also the journey that they have taken to arrive at the desired outcome. Example metrics could be: The time taken before making the desired outcome decision or the number of queries asked before arriving at the desired end outcome.


We hope that these tips have given you some ideas on how you can make your Design Thinking approach more quantifiable. Let us know if you have any other thoughts on this!


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