Data-led creativity has reached an inflection point. As a result, the era of art and commerce is giving way to a new age of art and science. We are amidst a data transformation revolution and the customer topography has never been more complex. Finding the right mix of algorithm and humanity is the Holy Grail or ultimate brand hack, no matter who you are, what you’re marketing, or who you are selling to.

Consequently, a palpable need to formulate best-in-class “brand alchemy” is the new strategic imperative. This is the reason the past generation of “artists of business” I hailed in my book WE-Commerce, is quickly giving way to a new breed of executive that I am calling “artists of science”.

Consequently, I’ve decided to launch a new Brand Alchemy Q+A series in parallel with my Ask the CMO column. I’ve done this to get into the minds of this new species of leadership, as I believe they will ultimately emerge as the creative Darwinists defining the future of both business and brand. For my second conversation in this special series, I sat down with Kurt Kendall, recent Chief Insights + Analytics Officer at GSK who has years of experience sitting at the nexus of creativity, technology and science at leading companies such as Under Armour and McKinsey. Following is a recap of our conversation:

Billee Howard: I’d love to talk to you first about the new age of data transformation that’s emerging because I think it’s part of the reason we’re seeing science emerge so prolifically inside the world’s leading brands. What are your thoughts?

Kurt Kendall: The fundamental challenge companies are grappling with is how to remain relevant and competitive in a world that is digital and where consumers are setting the rules.  Companies that understand how to use data to inform decision making are the ones winning in this new environment. They are using science-based approaches including artificial intelligence and machine learning to surface insights that then allow them to improve their consumer experiences.

Howard: Another thing that I’d love to discuss is how to leverage data to actually improve intelligence, user experience and overall agility.  A lot of people talk a lot about data, but don’t really know how to derive value from it.

Kendall: Companies are now able to collect massive volumes of data.  Whereas we all used to marvel at terabytes of data, it’s now common to consider data sets that are measured in petabytes.  What’s relevant isn’t how much data a company has but how are they activating it. One of the early, but still dominant, applications is in consumer marketing and using data to drive better consumer experiences.   The business proposition is that better consumer experiences will increase a consumer’s lifetime value. 

To realize this opportunity, companies are making substantive investments to build capabilities in the people and tools necessary to create value from data. They are also establishing external partnerships, and in some cases even acquiring companies, to accelerate their progress.  This has the added benefit of allowing companies to expand into new areas that otherwise might take them years to do so. 

Howard:  I think that makes a lot of sense. I believe that people are trying to do that because they need to move past personalization to this whole new idea of commercial intimacy at scale. How do science, creativity and technology need to come together to cater to today’s dynamically responsive consumer?.

Kendall:  The combination of science and creativity is the critical unlock for commercial intimacy. Technology platforms like Amazon Web Services, Google Cloud Platform, and Microsoft Azure have quickly become the standard for cost effective data storage.  More importantly, they function as a robust analytics platform where data scientists can build algorithms that surface insights, predict consumer behavior, and shape consumer experiences in real time. However, what’s important to keep in mind is that it’s not just science alone but the combination of science and creativity that make this possible.  It simply isn’t the case that you can extract human creativity from this process and expect to succeed.  

Howard: A lot of what you talked has a very heavy focus on reimagining the customer experience, which is obviously what I’m very interested in, as are the readers. I’m curious about the impact on each C-Suite function as technology, science and creativity need to increasingly work together in an environment that fosters collaboration to do so. 

Kendall: One of the biggest changes in last decade is the blurring of the historical divide between the CIO and the CMO.   Marketing is driving much of the investment roadmap for CIOs, and the innovative technology CIOs are introducing to companies often times is focused on marketing.  Another big change is the emergence of several new C-level roles including Chief Customer Officer (CCO), CAO (Chief Analytics Officer), CDO (Chief Data Officer), and CTO (Chief Technology Officer) that reflect the elevated importance of the consumer, data, and technology.  These roles bring new competencies to the executive team but also help bridge the legacy divides. If you look at my role as Chief Analytics Officer, I spend a majority of my time not building algorithms but working across the organization in collaboration with my business partners to ensure we realize the value from the data, analytics, and insights.  I see my job as focusing on unlocking value from the data in a way that drives competitive advantage through improved business decisions and better consumer experiences. 

Howard: Something you said to me when we first spoke has resonated the more that I’ve talked to people: “if you can’t keep up today, you can’t catch up.” I mean that’s always been true, but not at the level it is today. Can you explain?

Kendall: Yes, I very much believe this having seen the carnage across multiple industries including in recent years retail.  I think there’s a bit of a false hope with a lot of companies that while they’re not necessarily competitive today, from a capability standpoint, that over time they’ll be able to catch back up.  It’s a false hope. It’s not to say that there are not exceptions, but for the vast majority of laggard companies, it’s much more likely they will simply fall even further behind. Companies that are winning have the courage to move quickly, adapt to the continually changing competitive and consumer landscape, and be prepared to build for the future. 

Companies have to keep up with the changing expectations of consumers.   A great example of this is what’s happening in the retail and consumer products industry.   Consumers preferences and expectations are changing faster than many companies can respond.   The biggest catalyst for this is the digital revolution which is both empowering the consumer and enabling new competitive entrants.  Consumers expect to be able to order products online and get them when and where they want. They could care less if a company makes money doing this; and many companies these days don’t.  You are also seeing the emergence of new brands that are taking advantage of these changed expectations and the digital platforms to take market share.

Howard: Every person that I speak to regardless of what industry they’re in, is focusing on how to build a DTC business in some way, shape or form. Any insights on that?

Kendall: You look at industries like consumer products or health care, which traditionally had indirect consumer engagement models and they are both feeling the pressure from consumers and competitors to build a DTC model.  However, the struggle for companies is that most haven’t yet adapted their legacy value proposition and operating model to the new realities. When they do try, often times they quickly face constraints in their internal capabilities and then lack the financial flexibility to make the necessary investments.

The priority then to build a DTC business is to address these two constraints head on.  The leadership for this has to come from the CEO and then most likely another member of the C-Suite is tasked with owning the success of the transformation.   They then focus not just on building capabilities but driving the requisite cultural changes. Usually the DTC transformation agenda will begin with on one or two key areas to start.  Frequently that will entail building a direct-to-consumer marketing or direct-to-consumer fulfillment capability. But you will also see companies explore value added offerings like mass customization capabilities to allow consumers to personalized products.  Besides creating additional revenue streams, this allows consumers to express their personal and unique relationship with the brand.

Howard: So, can you give any context of how in your role you bring about the organizational changes you’ve discussed??

Kendall:  I think organizational change needs to happen at four levels. The first, and usually easiest, is at the foundational capability level, which is for the most part, what people think of as the technology.  The second level is around the evolution of the business processes. How are you operating and really becoming data driven and consumer centric in the day to day processes of the company? The third is bringing new consumer value propositions into the equation.  And finally, it’s about the cultural changes that need to happen. All four really have to come together for change to be successful.

 I think one of the things that’s different now than even five years ago, is that the cost of technology has come down.  However, the overall investment necessary to drive the organizational change hasn’t decreased similarly. Companies don’t appreciate that as they’re looking to drive value from data that it’s not just about investing in the technology and data science.  It’s about investing in the transformation of how they’re operating. And for many, investing the innovation of their core products and services as well. Companies that historically sold a physical product are now beginning to offer more holistic solutions that solve a consumer’s need and where the product plays a lesser role.   The consumer experience has evolved from how do I get you to buy something to how do we build a relationship?

Howard:  As we’ve discussed, I’m really looking at this idea of how much more important science is becoming each and every day to the overall enterprise but in shaping the customer experience. As a data scientist at one of the leading organizations in the world, what is your view? 

Kendall: Science is at the core of unlocking value from data but there is so much more to it.  Math is the foundation that the algorithms are based upon. However, as with science more broadly it’s critical to apply the scientific method in your approach.  It’s very easy to be over overwhelmed and led astray by the volume of available data. You simply can’t randomly explore the data. Starting with a hypotheses, grounded in business knowledge, is key. It has to start with “what’s my hypothesis?” How do I use the data that I have to validate that hypothesis? Then you’re continually iterating and testing the hypothesis with market feedback.

If you’re being effective as a data scientist, what you’re really doing is conducting an iterative process for hypothesis generation. What’s also really critical here is having data scientists who have the intellectual curiosity and creativity to be able to go beyond just the math. It’s very easy these days to have the data and then just apply open source algorithms.  Too many fall to the belief that this can all be done at the push of a button. The problem is the answer you get will often times be wrong. What’s required is someone who looks at the data and is able to see the patterns. Who ask the question “what happens if you look at this problem in a different way”? Sometimes it’s actually less science and more creativity that gets to the true insight.

The last piece to making this come together is realizing that all of the data science work falls within a broader ecosystem.  This isn’t academia it’s business. Our role as data scientists is to ensure our business partners have the right information at the right time to make the most effective decision.  Taken to its logical conclusion, this can translate into moving to automated decision making versus a more traditional deliberative decision making process. We all experience what this new decision model looks like every day when we surf the Internet.  Our entire web experience is driven by automated algorithms making decisions about what we see. That happens because data scientists have worked closely with our marketing colleagues to design the optimal consumer experience. 

Howard: Tell me your thoughts about the future of data-led creativity? In my view, man won’t be replaced by machine creatively, just made better, stronger, faster. Agree?

Kendall:  Completely.  I’ve spent a lot of time thinking about the limitations of a purely science led approach.   There is a significant role for art in the scientific process. But what is also true is that there is a role for science in creative artistic process as well.  Of the two, I think the latter is actually more nascent than the former. We need much greater collaboration between the creative and science communities within organizations.  The good news is we are beginning to see this happen in areas such as marketing and product design. That is then leading data scientists to pursue advancements in areas such as natural language processing and image recognition which then feed back into the creative processes like writing and video production.

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