Understanding
The analysis and synthesis of research data is the process by which we move from observations to understanding. As discussed elsewhere, there are a number of methods we employ to make this leap. The key consideration here is that we move beyond what we observe - from our adoption and usage data, satisfaction surveys, interview notes, photographs, videos, or journal studies -, or even themes of observations, to a deeper understanding based on empathic insights.
I've witnessed the difficulties people can have making this leap, and yet these leaps are crucial to the design process. A design based on what we recorded, rather than insights, will lack clarity and is more prone to solving superficial problems rather than deeper, more significant problems. Quite simply: if we don't push towards understanding, we are unlikely to reach towards the designs we really need.
The patterns that we look for in our data - the connections we seek and forge between observations - are intended to deliver on that understanding. We look for what people do - the activities that fill their daily lives; the habits, rituals, jobs, and leisure. These are the more obvious of what we observe.
But we also seek to understand why people do what they do. What are the drivers, influences and shapers of these activities? We look for their hopes and dreams, their cares and fears.
This is why observational, contextual and anthropological research techniques are so useful to the designer. They allow us to see much more than would otherwise be possible using other techniques. And with this additional visibility we are supposed to see more deeply - not just more.
When we understand people in this way, we gain an appreciation for the things that are of significance and hold meaning for them. At that point we can begin solving the problems, or creating the opportunities for the actvities, that hold that meaning.
People
People are generally not well placed to tell us what motivates them. So much of these influences are unconscious, tacit, cultural. Through observation and interviewing we are better able to identify these influences.
But there is a danger we see in the analysis of research data by designers - especially when carried out in isolation from the business stakholders on the project. That danger manifests as a superficiality of insight; a failure to move beyond observational themes and fall short of real understanding.
What is required is something akin to the "5 Whys" - the technique for determining root causes popularised by Toyota and lean manufacturing - to ask progressively deeper questions about the underlying causes for our observations and themes.
This is one of the main points in the design process when the team is called upon to mentally exert themselves. Whilst the work of research and analysis up to this point is strenuous, it falls to nil if the team fails to push beyon observations and themes. This effort is necessary if the design activities are to break new ground.
Mundane observations provide barren soil for the creation of design ideas. The failure to develop good ideas is probably due to a failure to make the important step from observation to insight.
So what does that step look like? And how do you know if you've successfully made it?
Observations
As we go through our research data the first step is typically to group duplicate or very similar observations together. Repetition is important and a good point to note. And it's easy to recognise. As a first pass through our data - it's a smart one.
For example, we might note a series of very similar points of confusion showing up amongst our participants. Collectively, this is still an observation.
As we move through our data, we might note other instances where confusion arises. Together, these represent a theme.
Insights
If we stop at themes we will have stopped well short of the potential. At this stage in our analysis we need to look at our themes and obserations and look for an underlying cause. To explain what we have seen, we need to bring our own experience to bear as well.
This step requires effort. We need to keep digging until we hit fresh and fertile soil. That 'soil' contains real insight about our audience; insight that explains the behaviour we've been observing. Our own past experience auds us in this endeavour - this person and subjective perspective is entirely appropriate. This is why we include a diversity of backgrounds and experiences in the project team, and look upon that diversity as a source of strength - not as a weakness.
In many respects, an insight is an hypothesis about the world. In many cases it is outside our sphere of activity to test whether our insights are accurate. This is why a sketch-based ideation and critique activity is important to the design process. But that is a topic for another article.
When faced with thousands of data points (as one project team here at Meld currently faces) it is easy to be daunted by the task of moving from observation to theme and then to insight. Especially daunting when taking into account that several different groupings of the data may be warranted.
This is exactly when it becomes critically important to move past what you've observed, towards a point of insight. At that point, not only have you done justice to the research and the stories you have heard, but you've also delivered on the intention of design research: understanding.
And that means you're ready to move on to the next stage of designing.