After conducting research, we need to bring structure to what has been found and learned. We sort, cluster, and organize the data gathered and begin to find important patterns. We analyze contextual data and view patterns that point to untapped market opportunities or niches. Finding insights and patterns that repeatedly emerge from multiple analyses of data is beneficial. ~ Vijay Kumar, 101 Design Methods
“It’s what happens after the research that’s important” is something I found myself saying three times to three different people in three different contexts over the past couple of days. Anyone can go out and interview users and beneficiaries. What’s important is what happens during the Analysis phase.
To ponder this in detail, I wanted to go back to first principles, and drill down into the post research stage where we are expected to frame our insights.
Vijay’s slide pops out 5 key outcomes from this phase, and these are critical for solution development in the subsequent phase. These 5 outcomes from analysis of the data collected during the research phase are:
- Looking for patterns
- Exploring systems
- Identifying opportunities
- Developing guiding principles
- Constructing overviews
It is this stage that distinguishes the quality of the outcome. Now, in the case of our work in the informal economy operating environment, we have built up an overview of the landscape over the past several years, primarily through immersion and thick data collection using design ethnography methods.
Starting from the purchasing patterns and buyer behaviour of low income consumers, back in early 2008, all the way through to the development of guiding principles such as flexibility, we have explored and mapped the ecosystem from numerous vantage points.
Today, our synthesis of user research does not happen in isolation from the body of work – intellectual property – that has been developed over time, through experiential and practical knowledge.
This, then, is what underlay my conviction when I spoke about the importance of the quality of interpretation of the data, and the transmutation of these interpretations into implemented insights in the form of new product features, service design elements, or nuances of the payment plan in the business model.
Increasingly, the Frame Insights phase of our work has led to the evolution of our understanding of the commercial landscape in rural and informal markets where incomes tend to be irregular and volatile, and infrastructure is inadequate or missing. It is this that I’ve been attempting to capture under the category of Biashara Economics.
It’s not Africa specific. The patterns hold, give or take ~30% margin for historical/cultural/social differences, across continents. That is because these patterns are the natural response to the common characteristics of seasonality, volatility, uncertainty, and unpredictability. And this is why one can see the success of the prepaid business model around the world.
It strikes me here that this in fact validates the methodology and approach to exploration and discovery in unknown contexts, something I had framed as the starting point for the very first such project almost a decade ago. Over time, I discovered how much the methods, as delineated by Vijay in Chicago, had to be adapted for the context but that is a topic for another time.