Innovation is tedious without the lens of cognition
Innovate or die. Regain market share. Differentiate our solutions so people notice. Disrupt the market. These are the tired phrases of orgs who must compete with one another.
A refreshing way to attract the attention of a market is to simply understand deeply what people are facing as they try to address their intent. This understanding shows you where to aim your creativity. It also results in solutions that are more aware of the wider systems, and more likely to bring value to people.
How It Has Worked
Innovation and differentiation are dear to organizations that compete with each other. Here are examples of how Data Science that Listens helps an org get the edge.
Personal Identity Change
Objective:
How do we help young people build self-confidence in their identity? (coming from an expertise of gaming and fashion)
Outcome:
We suggested creating for TS1 and TS3 because they were the unique ones. (?) But the founder at the meeting said, “This isn’t how we do it here. So I’d rather go with my gut.” This was after a year of the researchers trying to get budget for the study.
Creative Home Chefs
Objective:
Are there avenues where we can innovate for home cooks?
Outcome:
The internal team used the thinking styles to come up with a new idea as part of an internal contest. This idea was very well received. That's all we know about it.
Taking Care of Clothing
Objective:
We want to truly innovate in our appliances, not just mess with features. How can we take "doing laundry" in a new direction?
Outcome:
People knew how they wanted an item of clothing treated, but had trouble translating that to the controls on the machine. The controls only describe what the machine can do (steam, cold/hot), but the people were thinking, ‘I don't want my sweater to get pilled up,’ and ‘My running clothes never seem to smell fresh enough after washing.’ We must change the language of the controls on the machine to speak to the same purposes people have in mind. There was an additional opportunity for us in one of the thinking styles, The Separationist. Their concern about bacteria is foremost. We can create a line of appliances that caters specifically to germ control.
Programmer Karma
Objective:
The director of developer relations wanted more developers to reach for Sybase data tools as a first choice.
Outcome:
To understand developers deeply, we framed a study about resolving issues using a new SDK. We compared the experience to developer experiences for Apple and Android SDKs. The resulting thinking styles catalyzed a variety of tailored ideas for the director. The mental model skyline helped the team re-design the online experience according to the view of developers, resulting in a successful initial year attracting developers to the program.
Quick Lunch
Objective:
A rapid-serve restaurant chain wanted inspiration for ideas to improve in-store menus and drive-through mobile connectivity features. To create a foundation for inspiration, Indi reframed this from people's intent: what am I gonna grab for lunch?
Outcome:
The data gathered from re-framing in this manner was represented in a room-wrapping mental model skyline. Seeing the cognition around lunch, and the gaps between the restaurant chain's capabilities, inspired the design team with many ideas. Some were not even related to menus or phones. The team also gained common language, better collaboration, and the capacity for future exploration outside the solution space.
