Avoiding Digital Dissonance in an AlphaGo World

Avoiding Digital Dissonance in an AlphaGo World

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For brands, the transition from the digital marketing age to the digital innovation age isn’t a linear one.

Alpha’s Miracle

A few weeks ago, Google’s AlphaGo AI engine beat Lee Se-Dol, the world’s top Go player in a series of 5 games. Through a disruptive machine learning algorithm, AlphaGo managed a feat that popular consensus held to be at least 20 years away, if not downright impossible.

On the surface, this event seems misleadingly simple. After all, computers have been beating humans at games for years, chess being the most obvious example. AlphaGo seems to fit into a linear progression pattern that conforms nicely to our existing frameworks.

The surface, however, is deceptive. A simple fact puts Go’s mind-numbing complexity into perspective: there are much more possible Go combinations than atoms in the observable universe. Go is exponentially more complicated than chess and AlphaGo fits into an exponential progression pattern, the same pattern that brands face when thinking about their digital futures.

How do we make sense of such disruptive technologies? How do we project their implications? How do we integrate them and make decisions based on them? AlphaGo symbolizes the issue of digital dissonance.

What is digital dissonance? Digital dissonance occurs when the sheer complexity of the technologies involved and the magnitude of their implications exceed our existing mental frameworks. We see the technologies, we see the changes they bring, we instinctively understand their importance but we don’t know how to make sense of them or take action based on their impact.

It is a logical consequence of how “Digital” has become increasingly complex for brands, shifting from a support function to a marketing tool to a strategic driver of brand innovation.

The Evolution of Digital

Digital first became relevant during the IT age — when the terms "Digital" and "IT" were considered synonymous. It could be understood as a support function with an inward focus on process optimization and internal efficiencies. Digital investment was largely disconnected from customer insights and brand experience.

Then came what can be dubbed the age of digital marketing. Web 2.0, social media and the early days of mobile drove considerable excitement and sizeable investment in digital marketing initiatives. While digital became more central to the brand experience, it was still largely circumscribed to marketing and communication.

Today, we have entered what we call the age of digital innovation. From transportation to hospitality, entire industries are being upended, value chains are being redrawn, business models re-defined and brand experiences re-shaped. Digital is changing the fundamentals of how people interact with brands and products, in many cases changing the very definition of what a product can be. From IoT to AI, we are also faced with technologies whose complexity and potential impact far exceed anything we were used to.

For brands, the transition from the digital marketing age to the digital innovation age isn’t a linear one, just like the transition from chess-playing AI to AlphaGo. Most importantly, the transition isn’t driven as much by technology as it is by mindset. AlphaGo does not rely on processing power (the raw technology to run it has been around for about 10 years) but on a new approach to machine learning and neural networking.

As an exercise, we can ask ourselves: what would it take for a brand to make sense of and exploit a technology like AlphaGo?

 

Digital Mindsets

Exponential Thinking: So unexpected was AlphaGo’s victory that Lee Se-Dol did not take the first game seriously — he confessed to being caught off-guard by his virtual opponent’s performance. Like many brands, Lee discounted the possibility that any digital creation could rival his human mastery — he did not think exponentially.

Digital leaders realize that the age of digital innovation isn’t about digitizing existing experiences, but about creating new ones: imagining new products and services, drawing new value chain structures and inventing new business models. Brands’ digital visions should be transformative in nature, anticipating changes and leading them rather than reacting to them.

Strategic Initiative: Technology represents the raw material, but it is strategy that utilizes it to its highest potential. The machine learning algorithms that underpin AlphaGo have virtually endless applications from diagnosing cancer to making self-driving vehicles feasible. But harnessing a technology as powerful as AlphaGo means understanding the implications and uses for your brand. This calls for a systematic approach to digital strategy planning that links technological opportunities back to brand vision, business goals and customer insights. Brands must articulate this strategy in a long-term digital vision expressed in terms of outcomes, not technical features or narrow KPIs.

Cross-disciplinary Thinking: AlphaGo’s potential applications cut across all dimensions of the brand experience, from customer support to commerce, from product innovation to internal process improvement. Its full implications can indeed only be understood through cross-disciplinary thinking. Technologies like AlphaGo represent the shift from digital as a useful tool for certain functions or teams to digital as a force that impacts every single brand action. Applying digital solutions to all types of problems, liberating digital expertise and diffusing it throughout the organization are imperatives for the future of your brand.

Operational Capabilities: Advanced technologies such as machine learning require a sustained culture and governance of digital leadership. Because they transcend traditional platform silos, they require an approach to digital strategy that is driven from the very top of the company. They demand intense coordination between different functional teams and between IT and business teams. They also require a culture of risk taking and a high-degree of operational agility to be integrated quickly and efficiently.

AlphaGo is only one example and is highly representative of the questions and challenges brands will have to tackle in thinking about their futures. From high-level strategy down to operational execution, a new toolkit is needed — both in terms of mindset and in terms of capabilities.

So today we ask you: is your brand ready for an AlphaGo world?