This commentary relates to the article Design Justice: Why it matters and how you can apply the principles to your work
So often, social research either has much to teach those of us who inhabit the world of research and analytics for commercial purposes or it holds up a mirror to us in terms of best practice. In this article, Maya Hasan and Sanam Amin do both. In their very first paragraph they remind us of the brutal reality experienced by so many in a world of pandemics, economic injustice and discrimination. That reality is as relevant to the why, who and how of how we commercial researchers conduct ourselves as it is to our social research cousins.
All of which begs the question: how does and can Design Justice apply to the world of commercial research and analytics? Probably the easiest way in which to approach this subject is to examine it in terms of just three key elements of what we do – sampling, design and outcomes.
Sampling
It has long been a truism that communities that are marginalized in life are also, for the most part, marginalized in research and data analytics as well. While it is true that the original principles of sampling – especially that of everyone having an equal chance of being selected to participate – were much less likely to allow for marginalization, those principles have been observed pretty much in name only for many a decade. From the advent of quota sampling to the use of convenience samples, we have blithely chosen to ignore that there have been many who were systematically excluded from our work. Sometimes this has been a product of laziness or shortage of budget and time, but often it has been a deliberate choice. A good example of this is research among Spanish-dominant Hispanics in the U.S.A. For a short time, as corporations woke up to the fact that Hispanics would form 30% of the population within a decade or two, a lot of emphasis was placed on researching and understanding this population. But as those same corporations then also decided that they were really only interested in “assimilated”, younger Hispanic buyers, so that emphasis slipped away, and they were rolled into the study of Millennials and Gen-X.
As Hasan and Amin point out, research has long-term consequences. In this instance, the commercial decision to de-emphasize non-assimilated populations in research meant that those same populations became even more isolated and marginalized. Even in something as potentially inconsequential as packaging research, a decision to restrict a sample to an online panel and cut off recruitment at 65 or older can mean packaging designs that are difficult, if not impossible, for the elderly to open, thus depriving them of goods that they may want or need.
Design
When designing a programme of research, are we considering the consequences of what we design? All too often, what we cobble together is a study the original design of which is 100 years old – I am talking of the quantitative survey. Something that resembles an interrogation more than a conversation. As Hasan and Amin say, research does not need only to be ‘extractive’, it can be inclusive and collaborative. This refers to Principle 6 of Design Justice – that participants are experts in their own experiences. I believe commercial researchers – especially those in UX and CX – are beginning to do a far better job of this than in the past, but we still have a long way to go. We also would do well to remember Principle 5 – that research designers should act as facilitators. After all, we facilitate the consumer being brought into the decision-making process within the organization. Shouldn’t we do that with the consumer’s well-being in mind?
Since the founding of ESOMAR in 1948, a fundamental principle has been that the process of research should in no way harm its participants – the equivalent of the medical Hippocratic Oath of ‘do no harm’. Should we not extend that to say that the outcome of research should also do no harm?
Sometimes, the way in which we design research also has the effect of excluding or marginalizing those who may in fact be key audiences. Anyone who has tried sending non-mobile prioritized online surveys to males aged 18-35 knows what I mean! When the subject matter is of little real-life consequence, perhaps that may not matter as much, but when it deals with healthcare, parenting or any other number of topics of importance it again has consequences.
Outcomes
Some commercial researchers like to believe that they are the objective purveyors of truth to the organizations that they serve. I doubt that was ever really the case, but Hasan and Amin brutally lay it out for us: “There is no such thing as objective research”. Add in data analytics, AI and machine learning and that truth is multiplied many times. The why, who and how of research have real world outcomes on our participants, whether they be first or third parties in our work. Hasan and Amin aver that who is designing the research is as important as why it is being designed and how it is being carried out. This is as true in commercial research as it is in social inquiry. We all carry within us biases, often implicit and maybe unknown, that can have major consequences in terms of outcomes. Take, for example, the case of an algorithm designed to assign credit limits on credit cards – an algorithm based on previous research, practices and inherent learning. When that algorithm assigns differential limits to women as opposed to men, Blacks as opposed to Whites, those are consequences that go far beyond the trivial.
This applies in even more basic ways. For example, should we apply our research skills to aiding tobacco companies to sell their products in developing countries? Or to helping oil companies combat negative associations with global warming? Or to polling for political candidates spreading falsehoods and conspiracy theories? In all of these cases, Principles 1 and 8 come into play – is our mission social and equitable and are we building to a society that is sustainable?
These are all moral questions that apply not only to social research but what we, as commercial researchers, do every day. The time is now to confront these questions and to decide for ourselves as individuals and corporate entities what our answers will be.
