A Day in the Life: The Design Thinker Executive
This blog post highlights a case study of one of The Berkeley Innovation Group’s clients. Identifying information about individuals and companies have been altered for confidentiality purposes.
“We are not capturing the data streams our service generates, and we have no internal data analysis capabilities,” thundered the CEO. Seated across the conference table is Mei-ling, the fifty-something vice president of the company’s most profitable division. He continued, “in the past, you have expressed interest in data, so I want you to lead the data and analytics subcommittee in our next long-term planning effort.” She swallowed hard to mask the shot of anxiety she felt.
Mei-ling experiences physical discomfort at the thought of standing still and this subcommittee leadership role ignites her passion for growth; however, she does not have a formal data science background. A design thinking enthusiast, is she willing to risk the successful end of her career and a stable retirement on a “process” of innovation?
Returning to her desk, she instinctively hits refresh on her LinkedIn feed as her mind slams into adrenaline-fueled overdrive. Her fear is exacerbated as post after post on blockchain, machine learning, and artificial intelligence fill the screen. Embracing a core tenant of design thinking, “simplicity lives on the far side of complexity,” she grabs her notebook and heads into the field.
As a design thinker, her first stop is not with the CIO or his staff. She knows the process of Discovery involves seeking “new and unusual information” from those who interact with the data daily: warehouse sorters, delivery drivers, and end customers. After a dozen Discovery interviews with participants, Mei-ling saw the value of employing empathy and seeing the same situation, but through another’s eyes. These fresh observations led to new Insights that reframed the opportunity through a series of, “how might we?” questions.
With our guidance, she applied our COE-creation framework’s three growth lenses: core (economies of scale), organic (economies of scope), and exponential (innovation) to understand the opportunity.
Core innovation focuses on improving the efficiency of the primary business. If volume increases five percent, “how do we make our processes run five percent faster for five percent less cost?” In Mei-ling’s world, she might ask, “what data do we generate that upon analysis can inform and improve our core business operations?” Examples she listed include: begin and end dates and times of the warehouse process, target delivery window, date and time of delivery, position in the delivery sequence, duration of the stop, image(s) of item(s) delivered, and any damage to the package.
Organic innovation leverages the enhanced brand image from Core innovation and delivers an improved product or service to the market. To an entrenched leadership team, this strategy is madness. They believe innovations are like oranges, only discarded once all the juice is gone. Reframed as a new car, we realize innovations begin losing value the moment they reach internal production. Disseminating an internally-developed product or service into the market with utmost urgency ensures maximum value capture.
(Here we pause because our experience shows Core and Organic growth fills the average leader’s “9 to 5.” Exponential growth, outlined below, requires dedicated executives in a focused org structure.)
Exponential innovation is the white space of real growth. Mei-ling framed it well by asking, “what data, whether it exists or not, do we not know we need?” We diverged, or generated a large amount of ideas, beyond existing solutions of diesel, biodiesel, and CNG vehicles and thought about electric-powered delivery vehicles. What data would they generate to produce novel human productivity measures? How might they inform the maintenance shop with predictive repair schedules based on kW/kWh consumption data? Here we catch Mei-ling flash the wry smile of opportunity. Instead of working to make the company's existing infrastructure faster, Mei-ling can present ideas to flip deeply-held assumptions within the organization, or orthodoxies, on their heads and drive exponential success.
While Mei-ling’s work with the data and analytics subcommittee is ongoing, her confidence as a leader is strengthened by, “trusting the process of design thinking and doing the work.” Upon accepting the CEO’s “invitation” to lead the subcommittee, she projected confidence and organization by framing the opportunity through the COE-creation framework. Similarly, in her subcommittee’s kick-off meeting, Mei-ling presented the collective process and language of design thinking as a foundational model that remains iterative as new information and insights are discovered.