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Is There Magic in the Mashup of Data and Creativity?

Is There Magic in the Mashup of Data and Creativity?

Jakki Mohr

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Forming a team of data-savvy creative marketers and consumer-savvy data analysts can help drive radical innovation in your organization

I have always been curious about how people generate ideas for radical innovation. It’s why I have a wide variety of books on the topic on my shelf, from Melissa Schilling’s Quirky: The Remarkable Story of the Traits, Foibles, and Genius of Breakthrough Innovators Who Changed the World to Janine Benyus’ Biomimicry: Innovation Inspired by Nature. I’m intrigued by the role of data in the innovation process— leading to another set of books in my collection, including Peter Verhoef and co-authors’ Creating Value with Big Data Analytics and Frank Bien and Tomasz Tunguz’s Winning with Data. In fact, I teach a course on this very topic in our business analytics master’s program at the University of Montana.

Certainly, marketing has excelled in developing sophisticated techniques to measure customer reaction to new concepts, whether new products or advertising messages. And now we have access to Big Data, characterized by the plethora of types (e.g., sentiment analysis, click streams, credit card usage) and sheer volume, real-time generation and analysis.

McKinsey’s Brian Gregg, Jason Heller, Jesko Perrey and Jenny Tsai wrote about the relationship between data analytics and innovation in a 2018 post on the company’s website. The authors called it a myth that “‘ideas and numbers’ have always had an uneasy alliance in marketing. … Creativity is an instinctual process of building emotional bonds with consumers. Bring in too much quantitative analysis and the magic dies.” Even Marketoonist Tom Fishburne has captured the stereotype. In one cartoon, professionals—presumably marketers—quip to a painter, “Now let’s optimize the creative by adding puppies, emojis and an incentivized call-to-action.”

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In contrast, McKinsey’s data offers a different perspective: Combining human ingenuity and insights from data analytics creates a power combination that drives value across the marketing value chain. Creative functions are becoming more data-driven, while data-driven functions are growing more creative.

Here are a few takeaways that I have gleaned from studying the mashup of these two domains over the past three years.

Temper Data-Driven Insights with Human Judgment

The need for intuition and experience doesn’t go away when data enters the picture, as Peter Horst and Robert Duboff write in a November 2015 Harvard Business Review article­: “In a data-driven, automated world, the risk of unintended missteps grows significantly in the absence of an appropriate judgment screen.” This overreliance on data is a big part of the story that managing editor Sarah Steimer wrote about for Marketing News in January 2018: “How Airlines Get Customer Experience So Wrong with So Much Data.” Data analysis can make surprising connections and suggest non-intuitive marketing moves, but marketers must always ensure that these insights make logical, intuitive sense. This insight harkens back to an August 1990 article in Management Science by Robert Blattberg and Stephen Hoch: “A 50/50 combination of database modeling and managerial intuition always outperforms either in isolation.”

Build a Team That Values Both Data and Creativity

It is well-known that a team tasked with generating radical innovation benefits from a diversity of skills and talents. This diversity is especially true when relying on a data-driven innovation strategy; a team with a tapestry of skills and roles—including skilled data scientists—can generate divergent ideas.

Horst and Duboff offer one reason to assemble a diverse team: “Just as the most creative marketers aren’t the best data people, analytic professionals usually lack the skills, the experience and perhaps even the ‘internal wiring’ to excel at brand, image and creativity.”

Although I don’t necessarily agree with their declarative statements—indeed, the McKinsey authors suggest that the best (e.g., not all) data engineers have incredible imagination and curiosity that help generate new insights—the important takeaway is to build a team of people nimble enough to work with colleagues with different skills and mindsets, including both younger and older team members.

(Note to young people: Be sure to generate data literacy. Not only will your older colleagues expect you to have it, you will also add great value by asking questions that demonstrate this proficiency.)

Clearly Articulate the Problem to Be Solved

Derek Thompson’s great article in The Atlantic from November 2017—“Google X and the Science of Radical Creativity”—notes that “Moonshots don’t begin with brainstorming clever answers. They start with the hard work of finding the right questions.” This is echoed by Nelson Repenning, Don Kieffer and Todd Astor in the MIT Sloan Management Review in March 2017: “Clear problem statements can unlock the energy and innovation that lies within … your organization.” They also note the flipside: The lack of a clear problem formulation can prevent innovation and lead to wasted time and money.

The focus on identifying the right question is consistent with a marketer’s focus on understanding the customer’s pain points. Getting to the root cause of an issue is required for creative problem-solving, followed by enlightened experimentation to generate and evaluate ideas. Gary Pisano’s article in this year’s January/February Harvard Business Review, “The Hard Truth About Innovative Cultures,” acknowledges that, “Demanding data to confirm or kill a hypothesis too quickly can squash the intellectual play that is necessary for creativity.”

Can data play a role in driving radical innovation? Based on my experience and expert insights, the answer is a resounding “yes.” Certainly, other factors also play a role in the mashup of data and creativity—importantly, the role of organizational culture—but these three are central to unleashing the magic: balancing data-driven insights with judgment and intuition, developing seamless working relationships between data-savvy creative marketers and consumer-savvy data analysts and valuing the importance of asking the right questions.

Jakki J. Mohr, Ph.D., is the Regents Professor of Marketing, the Poe Family Distinguished Faculty Fellow, and Fellow at the Institute on Ecosystems at the University of Montana.

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