We are living in a fast changing world with all the emerging technology and customers’ demographics emerging in front of us. To make decisions, we should not solely rely on our past experience or mere assumptions. We should therefore use the logic and power of data to guide and form our decisions from scratch. But we also are swimming in the sea of data with a lot of ‘white noise’ and need to be more aware of all biases that cloud our judgment.
On the other hand, Design Thinking is about putting people first. Design Thinking is about being divergent and convergent healthily during the problem framing and solving process. We are diving into uncertainty, undefined complex problems, and a need to be broad and imaginative in our problem framing.
How might we be more considerate on the use of data and turn it into a source of inspiration for innovation? How might we combine soft and hard research, the logical and intuitive and human experience together?
How might we integrate data into Design Thinking to further bring out extra validation and confidence in our design steps?
The understanding of “what” and “why”
We are exposed to data a lot. We use data in our market feasibility study or customer segmentation. We gather data from research projects, witnessing and listening in customers’ interviewings, focus groups or analyze collected data to understand their behaviors, barriers and attitudes of the targeted customers. Which segment is unexplored? What products are purchased more? Where is the missing pie? How to grow market share? so on and so forth. Data tells great length what we should know about the customers’ demographics or the market – what is happening so far.
We use Design Thinking or the use of ethnographic and participatory research to get deeply into what we can further make sense out of what we already learn about our customers. We dive deeper into layers of the human’s “ice-berge of thoughts” to get into the ‘why’ and ‘stories”’ behind the “what”. Why do they choose A over B? What is it that they are crying out for help right now from us? What is the core need that is unmet right now? Understanding the “why” behind the ‘what, those reasons behind helps us better gain deeper knowledge, insights and most importantly to have more informed and validated problem framing to seek directions for future problem solving.
Take an example from one of the projects we were involved in. A company identifies 10% employees of its organizations as ‘high performers’. They know everything about them. Their age, their levels, their lengths of services. They ran surveys and gained further knowledge on their key challenges and goals at work. But they don’t know what exactly drives their performance? What are their daily habits? What are the key factors that best thrive or detract them from growing? And the answers to these questions are to observe them, witness them and capture in their most natural being their daily actions. These observations draw a more meaningful portrait beyond the “what”.
Combining the understanding of ‘what’ and ‘why’ is a rounded and solid way to better bring out innovative solutions.
Data is not the end of the story, but the beginning.
This is a great extension to our “Design Thinking process”. Every single data is a prompt and a probe to possibilities. If you are familiar with the Design Thinking process, you probably are familiar with ‘framing a problem with creative questions’. “How might we….”, according to Harvard Business Review, is the innovators’ most secret sauce to success. At Doodle, we always love asking these questions. It is broad enough not to gear divergent thinking yet narrow enough to help us stay within a certain focused area of problem. During the Design Thinking process, this is where we bring in all the synthesized findings, insights, understandings of ethnographic research (understanding your customers personas or archetypes) into defining a problem. A problem that speaks for the customers we want to solve for. How might data help?
Interpreting “as is’ ‘ data as a whole team to bring out stories is a great step to spark further creativity. What if we can sketch data and turn it into creative stories, creative questions to frame our understanding? Finding the knots and nuggets in among data to open healthy discussion, debate, or ideation brings an extra powerful percentage of ideas.
Design Thinking may be a fast paced and broad process. Sometimes, we are asked “where are we heading to?”. Most of the time, our best answer is to “trust the process’. While 10 out 10 projects take us to the outcomes we want to achieve, it also takes some ‘gut’ or a bit of ‘faith’.
Data is a collective echo of the past experience while we are leaning towards the future. What if we can use our past understanding to validate our ‘gut’. Bringing in data to validate, prioritize our insights, our choices to further reinforce the conclusion brings even more confidence to take our next steps.
Making choices and decisions with data-driven validation
We deal with choices and decisions everyday. Sometimes with uncertainty. Through the D.V.F. (Desirable. Viable. Feasible) framework, we ask ourselves critical questions. “Do our customers want it?”. Should we do it?”. “Can we do it?”. This D.V.F innovation framework is used heavily in our design to weigh out different perspectives from multiple stakeholders. We always hold customers’ hands tightly to guide our creativity but we also don’t forget that ideas need to make business sense and it needs to be executable. This process, in fact, should be a ‘slow thinking’ process and shouldn’t be rushed. We need to slow down and think deliberately and use logic, the calculation of probabilities, evaluating alternatives and options, avoiding statistical pitfalls, and removing bias.
How not to rush and gain clarity for decisions and more confirmation on our choices?
Take, for example, “prioritization” step, in the Design Thinking fashion way, we are asked to make choices. Some require a slow and dedicated process such as the impact/difficulty method, offering a great way to force rank ideas into “impact” and “difficulty”. We would answer questions such as “How many people actually enjoy this idea” and “how often?” “How many people it may reach”, expanding to execution territory involving Technology, Time and Money and so on and so forth. But those explorative understandings are only formed as ‘hypotheses’. We think and feel it may be true. It is formed by our direct interaction and experience with the people. And we somehow still ‘walk in the dark’ with it until we bring in further confirmatory research to shed further light and to validate our assumptions. Or take prototyping for example. We may have different concepts and we want to know which one is better. We could run live prototyping or participatory research to withnest and improve our ideas. However through validation with data, we will be able to confirm if our hypothesis is true or false. Will our ideas lead to actions? A hypothesis is only stronger if it is tested further. A/B testing, for example, is helpful to make choices. By implementing and being creative with different variables we will be able to get a crystal glance into what is actually preferred out there in the realistic world and look into results, statistics, performance and combine with the soft research to make the well informed and logical decision.
In short, we can be creative, innovative and collaborative with data. This doesn’t make us less of a Design Thinker . By marrying soft and hard research, logical and intuitive, fast and slow thinking together, the human experiences with the data and logic, we can become a more business savvy designer.
Written by Nhu Vo, Co-Founder, Doodle Design