Evidence vs. Gut Feeling: Designing for Social Change. A #blabchat Round Up

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“If you find your logic is talking you out of a good idea, question the logic first, then question the idea. This is entertainment; logic is less important than the impact of the story.”

- Luc Mayrand, Themed Entertainment Designer for Disney


This month we hosted our eighth Bromford Lab Twitter Chat. We thought that to mix things up a little, we would throw out an open invite via Twitter and our internal Yammer platform for contributors to send us the questions they would love to ask the #blabchat community. On reflection, because we didn’t provide a topic, it made it difficult for us to include all of the questions in the form that they were suggested. However, in true design style, we did a little synthesis, discovered an emergent topic and structured four (OK, five) questions around it which were inspired by the questions people had suggested. Everyone was included, so we hope you were able to spot a hint of your original question in the edit.

In this month’s #blabchat we discussed striking a balance between going with our gut feelings and making design decisions based on evidence. We wanted to explore the part that gut feeling and evidence play in the design process; are there tensions between the two and if so can they be overcome? We wanted to know whether people thought it was ever OK to work off your instincts or whether hard data is the only way to go?

It prompted me to think. Two weeks ago, like many parents with children starting primary school this September, my wife and I found ourselves reminiscing with our childminder; discussing where the four years had gone, and how much our boys had enjoyed their time with her. We knew they would. We knew from the moment we first walked through her door. We just had an instinct. Her Ofsted rating and certificates were a nice comfort blanket, but our gut feeling was what really made our decision easy. I have a hunch, another gut feeling if you like, that this type of experience will be familiar to many. We recognise and accept that our instincts have something to offer us in our personal lives so we listen to them, but I’m less sure how often that acceptance translates into our corporate lives?

So, I was looking forward to this #blabchat and as ever, we had some great discussion. Here’s the round-up . . .

On the whole, when data was discussed there was recognition that it comes in different forms, from hard statistics to soft observation. Data can provide both conscious inspiration and unconscious intuition, meaning that intuition isn’t always uninformed, but is often not fully understood. As Salma Afzal suggests, gut feelings are like a sixth sense, but as they aren’t backed up by any tangible data, it’s hard to prove and even harder to argue if something goes wrong. It’s often organisational culture and approach to failure and risk which determines whether people will be willing to take that leap of faith or not.

The overwhelming feeling however, was that we shouldn't think of evidence vs. intuition as an either or but rather as a complementary partnership. As our CEO Philippa Jones highlighted, data is often great at allowing us to understand the current situation or take a retrospective on the past, but it’s our intuition, perhaps informed by that same data, that allows us to take a speculative view of the future.

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Michelle Butler describes gut feelings as our ‘human compass’. If our organisational culture is right we will be encouraged to listen to our intuition, gathering ‘just enough’ evidence to get the project started. Without the right culture, there is a risk that projects will get caught up in an endless cycle of discussion which often results in work never getting started at all. As our Bromford colleague Steph Foster suggests, gut feeling is often the catalyst which gives you the courage to try.

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If you have the innovation frameworks in place which allow you to manage risk and use failure as a tool for learning, starting from a position of intuition is actually an efficient way to run a project. It’s a scientific model based on starting with a hypothesis and gathering evidence (using both quantitative and qualitative data) to prove or disprove it; which goes a long way in highlighting that design is actually a rigorous discipline for solving all kinds of tricky problems.

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Dyfrig Williams captured the spirit of the discussion when he suggested that this question was perhaps less about data and more about behaviours and an unwillingness to take risks. People like the notion of a safety blanket and often use lack of data or evidence as an excuse not to do something; in such instances, data certainly can be an innovation killer. But is data really the enemy of design? Perhaps if you believe that all data is dry, un-personal, voluminous and time-consuming. But as participants were keen to point out, data comes in a variety of forms from quantitative financial data to qualitative ethnographic observation, so clearly, data is an integral part of design and innovation. As Michelle Butler suggests, sometimes the best data is the stuff you get from just doing things at low scale and low risk. Perhaps linked with culture, it’s less about data killing innovation and more the bureaucracy which can often surround it within the corporate environment.

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The trick is identifying the best method to gather the data you need, in the volume you need, with the robustness you need. As Steph Foster explained, if you are asking the right questions the data should support what you are doing, rather than get in the way.

Data is necessary to help establish baselines and can influence and help shape research and exploration. Data is also useful at helping to spot future trends, which is great when it comes to stretching thinking during ideation sessions. Machine Learning techniques are becoming ubiquitous and newfound ability to crunch data on a large scale in the background means that we should be able to access powerful insights which are useful at every stage of the design process. As Matthew Gardiner suggests, the right data is vital in order to truly understand the problem. Layer by layer, data builds on the original gut feeling to provide the vital evidence required for evaluation.

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Searching for evidence may slow down the design process, but as Dyfrig Williams commented, this is often because evidencing activity isn’t approached properly. Evidence is necessary in order to get to the root of the problem we are trying to solve. Failing to take evidence seriously and relying on gut feeling alone risks committing time and resources to answering the wrong question.

Once again, organisational culture was brought into question with The Improvement Agency suggesting that if design processes in an organisation stall while more evidence is sought, there may be a problem with its culture. Afterall sourcing evidence through prototypes, tests and pilots is central to the design process. Michelle Matthews reminded us that trying something out is where you get your best evidence because if you don't try ideas out they just remain an idea.

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It’s clear that there is a balance which needs to be struck. Salma Afzal observes that how well you manage time and resources depends on how well you achieve a balance between meeting user needs and reaching a saturation point where no further new evidence materialises.

Iterative approaches facilitate evidence gathering as a matter of course and so long as an approach to incremental improvement is in place, as Matthew Gardiner explained, you’ll get all the evidence you need from customers when the service or product is live or being tested.

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The subjective nature of intuition means it’s often more personal than quantitative data sets, which also means its easier to argue against, and arguments often come down to a matter of opinion rather than a set of hard facts. But participants felt that this wasn't always a bad thing when it comes to design and innovation. In organisations where prototypes and tests are favoured over silver bullet ideas which go straight to pilot, two or three different low resource prototypes or tests often run concurrently. This means that it’s possible to start with two or three hunches and use evaluation to do the talking. As whats the pont outlined, trying out all of the ideas and running tests in parallel gets great data and learning.

Clearly, understanding the dynamics of project teams is important and being open to critique and challenge is essential, but Paul Taylor hits the nail on the head with his commentary - “Whether you go gut feel or evidencing the action you need to agree on is knowing when to pull the plug. The most well-conceived study or the best design isn't always going to work. Evidence-based or gut-based you'll still have a fair share of failures. Flexibility is key. If we are going to innovate let’s try new things, collect the evidence as we go and have the courage to be reactive”

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As always, thank you to everyone who joined the conversation on Thursday evening and ultimately contributed to this post! Perhaps the most important thoughts to leave you with are these . . .

“It’s common to think of data and instincts as being opposing forces in design decisions. In reality, there’s a blurry line between the two. After all, instincts are built by observing the world around us, and those observations are just another stream of data. Statistics help us summarize and understand the hard data we collect, and instincts do the same for all the messy real-world experiences we observe. And that’s why the best products — the ones that people want to use, love to use — are built with a bit of both.”

- Braden Kowitz for Wired

To paraphrase Paul Taylor, Matthew Gardiner and Richard Haynes; the conventional belief is if we gather more data we can make better decisions, but this may not always be true when it comes to innovation. If you are crunching numbers, you are probably gathering data from past behaviours. This doesn't necessarily inform future behaviours. The best way to find out whether an idea is good is by spending time with it, getting more informed with each iteration. After all evidence from doing is so much better than “evidence” of opinion.

Which seems to bring us right back to where we started - Gut feeling is a good place to start but a bad place to end.

Looking forward to seeing you all again in October 2018 for the next instalment!