February 23, 2021

059 - How Design Thinking Helps Organizations and Data Science Teams Create Economic Value with Machine Learning and Analytics feat. Bill Schmarzo

43 minutes

With a 30+ year career in data warehousing, BI and advanced analytics under his belt, Bill has become a leader in the field of big data and data science – and, not to mention, a popular social media influencer. Having previously worked in senior leadership at DellEMC and Yahoo!, Bill is now an executive fellow and professor at the University of San Francisco School of Management as well as an honorary professor at the National University of Ireland-Galway.

I’m so excited to welcome Bill as my guest on this week’s episode of Experiencing Data. When I first began specializing my consulting in the area of data products, Bill was one of the first leaders that I specifically noticed was leveraging design thinking on a regular basis in his work. In this long overdue episode, we dug into some examples of how he’s using it with teams today. Bill sees design as a process of empowering humans to collaborate with one another, and he also shares insights from his new book, “The? Economics of Data, Analytics and Digital Transformation.”

In total, we covered:

Why it’s crucial to understand a customer’s needs when building a data product and how design helps uncover this. (2:04)

How running an “envisioning workshop” with a customer before starting a project can help uncover important information that might otherwise be overlooked. (5:09)

How to approach the human/machine interaction when using machine learning and AI to guide customers in making decisions – and why it’s necessary at times to allow a human to override the software. (11:15)

How teams that embrace design-thinking can create “organizational improvisation” and drive greater value. (14:49)

Bill take on how to properly prioritize use cases (17:40)

How toidentify a data product’s problems ahead of time. (21:36)

The trait that Bill sees in the best data scientists and design thinkers (25:41)

How Bill helps transition the practice of data science from being a focus on analytic outputs to operational and business outcomes. (28:40)

Bill’s new book, “The Economics of Data, Analytics, and Digital Transformation.” (31:34)

Brian and Bill’s take on the need for organizations to create a technological and cultural environment of continuous learning and adapting if they seek to innovate. (38:22)

Quotes from Today’s Episode

There’s certainly a UI aspect of design, which is to build products that are more conducive for the user to interact with – products that are more natural, more intuitive … But I also think about design from an empowerment perspective. When I consider design-thinking techniques, I think about how I can empower the wide variety of stakeholders that I need to service with my data science. I’m looking to identify and uncover those variables and metrics that might be better predictors of performance. To me, at the very beginning of the design process, it’s about empowering everybody to have ideas. – Bill (2:25)

Envisioning workshops are designed to let people realize that there are people all across the organization who bring very different perspectives to a problem. When you combine those perspectives, you have an illuminating thing. Now let’s be honest: many large organizations don’t do this well at all. And the reason why is not because they’re not smart, it’s because in many cases, senior executives aren’t willing to let go. Design thinking isn’t empowering the senior executives. In many cases, it’s about empowering those frontline employees … If you have a culture where the senior executives have to be the smartest people in the room, design is doomed. – Bill (10:15)

Organizational charts are the great destroyer of creativity because you put people in boxes. We talk about data silos, but we create these human silos where people can’t go out … Screw boxes. We want to create swirls – we want to create empowered teams. In fact, the most powerful teams are the ones who can embrace design thinking to create what I call organizational improvisation. Meaning, you have the ability to mix and match people across the organization based on their skill sets for the problem at hand, dissipate them when the problem is gone, and reconstitute them around a different problem. It’s like watching a great soccer team play … These players have been trained and conditioned, they make their own decisions on the field, and they interact with each other. Watching a good soccer team is like ballet because they’ve all been empowered to make decisions. – Bill (15:30)

I tend to feel like design thinkers can be born from any job title, not just “creatives” – even certain types of verytechnically gifted people can be really good at it. A lot of it is focused around the types of questions they ask and their ability to be empathetic. – Brian (25:55)

(Is there another quote from me? So many good ones in this episode from Bill though so if not, i understand)

The best design thinkers and the best data scientists share one common trait: they’re humble. They have the ability to ask questions, to learn. They don’t walk in with an answer…and here’s the beauty of design thinking: anybody can do it. But you have to be humble. If you already know the answer, then you’re never going to be a good designer. Never. – Bill (26:34)

From an economic perspective … The value of data isn’t in having it. The value in data is how you use it to generate more value … In the same way that design thinking is learning how to speak the language of the customer, economics is about learning how to speak the language of the business. And when you bring those concepts together around data science, that’s a blend that is truly a game-changer. – Bill (36:03)

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By Brian T. O’Neill from Designing for Analytics

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