If you haven’t had a chance to listen to our podcast Episode 1, Beware of the True but Useless (with Martha Cotton), definitely do so. It’s a 15 minute listen and it’s well worth your time. Martha shares wisdom on her years of research design and how to sidestep some common misconceptions of research in business.
We can all (at least on a logical level) agree that data plays a role in design thinking. However, the idea of incorporating research into a design process is one that, often times, feels rigid and somewhat oppositional to the creative process. At first glance, the investment in research upfront is wasting precious time that should be spent on going to market.
Yet, when we take a step a back and look at the larger picture, we begin to understand that business objectives, research, and design are inextricably linked and all very necessary for success:
→ Products and services exist for the purpose of moving the needle on business objectives.
→ Design of that product or service is in service to the end-user. It’s designed so people use it. The right people. Your customer.
→ Research is in service to the business objectives. It exists to identify which business objectives are the priority and clear the path for reaching them.
Martha insists that you can’t have empathy for your customer without deep qualitative work. And she’s right. Understanding your customer requires conversation and investigation. And you can’t design for a group of humans that you don’t have empathy for. It’s hard to solve a problem you aren’t aware of or you don’t understand.
So how does an organization rethink the integration of data into their design thinking process?
Start with Objectives
Anytime we look to incorporate data into a process it’s important to outline a data strategy. This is the same for big data analytics, AI development, and design thinking. A data strategy defines objectives, end-goals, from both a business and end-user perspective. This strategy allows us to move forward in the construction and application of data. Without a data strategy in place, it’s easy for data to migrate or miss the target altogether.
For design thinking, it’s important to define the design objectives — which are led by the business objectives. It’s the “what are we building, who is it for, what does it do, and why do we want people to use it” type questions that provide a general understanding of the end goal.
When we understand what the design objectives are, we can craft the research to directly speak to those objectives.
This approach goes a long way in keeping the research directed and purposeful.
Once you’ve outlined your design objectives, you should be able to clearly see the constraints, if you didn’t already. Sometimes constraints are considered through a negative connotation as if they are restrictions on the possibilities. However, in the research process, constraints are wonderful creative tools that help shape what is possible.
Constraints allow us to set up natural boundaries for the research methodology. When presented with tight timelines and small budgets, creative solutions can be applied resulting in direct research focused on the solving problems at hand.
Focus on Actionable
Data is only as good as it is actionable. Martha expounds on this idea in the podcast with her rule of thumb, “beware of the true but useless.” As researchers, we find humans interesting. We find true data points fascinating. It’s what makes us good at our jobs. But, as Martha notes, truth doesn’t equal useful. And interesting doesn’t direct business or design strategy.
Defining objectives and applying constraints are helpful in creating actionable research — however, it is up to the researcher to ensure that the points we are communicating to our teams are indeed actionable.
Part of incorporating data into the design thinking process means unpacking some of those long-held assumptions. The dated perception that research is extraneous, weighed down by lengthy timelines, expensive invoices, and unactionable reports are all assumptions that prevent research from being used effectively. Companies that learn to effectively leverage data in their creative process to understand their consumer and better outline their business objectives find that data serves to create opportunities that weren’t there before.
It’s Worth Doing Right podcast is a collection of conversations exploring the intersection of data in the creative process. You can listen to more of It’s Worth Doing Right Podcast, here.
Mad props from IWDR:
A huge thank you to Martha Cotton for joining us on this conversation on data in design thinking and our very first podcast episode! Martha brought a wealth of experience to the conversation, as the Group Director of Design Research at Fjord, the interactive agency at Accenture. Martha has twenty years consulting experience, working as an applied ethnographer across multiple industries. Martha is on the faculty of Northwestern University MMM program–the Kellogg School of Management’s marquee Design Thinking degree–where she developed and now teaches the Design Research curriculum. A frequent writer and speaker on the intersection of anthropology and business, Martha’s article “The Shelf Life of Data” was recently published in “The Handbook of Anthropology in Business” (LeftCoast Press, 2014. Denny, Sunderland editors).