David Rogers: How Businesses Can Thrive In The Digital Age

David Rogers: How Businesses Can Thrive In The Digital Age

David Rogers: How Businesses Can Thrive In The Digital Age

I spoke to David Rogers, who is a member of the faculty at Columbia Business School, is a globally-recognized leader on digital business strategy, known for his pioneering model of customer networks and his work on digital transformation. He is author of four books, including “The Network Is Your Customer,” and his new book, “The Digital Transformation Playbook: Rethink Your Business for the Digital Age” (April 2016). In the following brief interview, Rogers talks about how businesses can adapt to the digital age, the types of experiments needed for digital transformation and what sets teams apart.

Dan Schawbel: How does a business started before the Internet adapt to thrive in the digital age?

David Rogers: What I’ve learned in my own work, and the research that went into this book, is that digital transformation is not about technology—it’s about upgrading your strategic thinking.

Transforming a pre-digital businesses is a very different challenge than building a new start-up from scratch. These companies have a lot of strengths (existing customers, products, distribution, reputation), but they also have a lot of established habits, processes, and organizational culture rooted in their pre-digital years.

For a traditional business to achieve its next stage of growth in the digital era, it needs to rethink its approach to strategy in five domains—customers, competition, data, innovation, and value.

  • Customers: Companies today need to shift from thinking of customers as passive targets, to seeing them as dynamic networks. This flips the whole model for how marketing works—how you attract, engage, and retain customers. It also allows for new insights into the changing path to purchase for today’s connected customers—from the omni-channel shopper on her phone in your retail store, to the business buyer being influenced by a web of content and peer relationships.
  • Competition: We used to think of competition as a zero-sum contest with other firms that look just like us. Today, we are much more likely to be competing and partnering with the exact same firms (think of Google paying Apple $1 billion a year to appear on the iPhone). Our biggest threats come from asymmetric competitors, who have completely different business models, but solve the same problem for our customer (why buy a second Toyota, if you can just call an Uber?). And competition is increasingly driven not by products, but by platforms—businesses that create value by bringing together others and facilitating a value exchange between them (think of Airbnb).
  • Data: Instead of data being treated as an operational input, in the digital era, it is turning into a key strategic asset, and a driver of new innovation for every business. This requires liberating data from silos in your firm, and learning to use new unstructured data types to gain a holistic view of your customer, your market, and your operations. I describe in the book how Las Vegas-based Caesar’s Casino uses data to measure the lifetime value of loyal customers and manage their experience in real-time. If a valued customer is on a losing streak at the blackjack table, Caesar’s data analytics may send an employee to surprise them with steak dinner or theater tickets, to ensure they leave with a smile and keep coming back.
  • Innovation: In the digital era, the process of innovation is shifting from top-down planning and decisions by HiPPOs (“highest-paid person’s opinion”), to a process of constant and rapid experimentation. For larger enterprises, the imperative is not just to “fail fast,” but to fail smart. That means designing innovation experiments that generate maximum learning for minimal cost. It means applying market feedback to your strategy, but also sharing it with others. In large organizations, we too often try to “bury the bodies” of failed innovation projects. Scaling up a winning idea is also very different within large organizations vs. in a small start-up. Digital technologies enable experiments to be run constantly, iteratively, and at scale, but they need a different innovation culture in place for innovation to really succeed.
  • Value: Finally, businesses in the digital era have to learn to constantly question and re-assess their value to the market. Traditionally, we define our value in terms of our industry: “we make cars” or “we’re a newspaper company.” But today, industry boundaries are blurring, and every organization must learn to continuously adapt the value that it aims to deliver to customers. I look in the book at The Metropolitan Museum of Art, and how it’s rethinking the value of a museum in the digital age. The way we experience art, history, and culture is evolving, so The Met is using data, mobile apps, gaming interactions, and social storytelling to engage audiences around the world in the incredible art works in their collection. They understand their challenge is not just to compete with other museums, but to fight for attention and relevance in a world of Netflix and Pokemon Go.

Schawbel: Can you say a little more about experimentation? You talk in the book about two different kinds of experiments that are essential to digital transformation.

Rogers: Sure. I tried to make this book very practical, so there are nine step-by-step planning tools to show managers how to apply the different frameworks. Two of the tools relate to managing innovation through rapid experimentation.

One tool is for managing what I call “divergent experimentation.” This is when you don’t know what you don’t know. It’s relatively early in an innovation process, and your goal is to explore and uncover new opportunities or possible solutions to a problem. This is the kind of experimentation you see in design firms like IDEO, in software companies like Intuit, and in business model innovation at new firms like Rent The Runway. In this method, innovation is designed as a series of tests of your assumptions, to bring you closer to finding a product, or service, or experience that both works for the customer and delivers value to the firm.

The other tool is for what I call “convergent experimentation.” This is useful when you are trying to answer a specific question or set of questions. It is applied later in the innovation process, and is great for optimizing and improving a known strategy. A/B tests and randomized experimental trials all fall in this category. It’s what Amazon and Google and Facebook use every day, constantly running real-time experiments on every aspect of their customer experience to tweak, improve, and try out new features. But I found that even political campaigns and convenience store retailers like Wawa are using convergent experiments to innovate faster, better, and with real impact on their bottom line.

I found that a lot of great ideas for innovation have percolated out of Silicon Valley, but they need some translation in order to move from the model of a startup to the enterprise. We can’t all just “pivot or persevere” like a startup—eventually that can leave you broke and living in your mom’s basement. Which may work for a start-up, but not for the product manager in a bank! So, we need to adjust the means of experimentation to bring it into larger firms.

Schawbel: What sets teams apart where you have advised—such as GE, Google, Toyota and Visa—from other companies who are still struggling to digitally transform?

Rogers: On the team level, a few things seem to be critical to real digital innovation. 1) Small size. I’m a big believer in the two-pizza-rule: If your innovation team can’t be fed with two pizzas, it’s too big. 2) Diverse perspectives. This can be employees from different departments in your company, those with different backgrounds and industry experience, and of course demographic diversity. 3) Passion. You don’t want to force people to be at the leading edge of your digital transformation; they need to be inspired and self-motivated. Don’t worry if that’s not everyone today: change doesn’t require 100% buy-in across an organization; it just needs a critical mass.

It’s also critical that there is the right kind of leadership from above. That means a mandate for change from the C-Suite. It means a vision for how digital is going to transform the business (look at GE’s brilliantly articulated vision of becoming a “digital industrial company”). But it also means putting in place processes to answer three critical questions:

  • How will we allocate funding for digital transformation efforts? (Innovation won’t happen if funds are held hostage by existing profit centers. Where does funding come from and how do we decide where to invest?)
  • How will we measure these efforts? (New ventures can’t be judged by the metrics of an old business model. What will you agree on as markers of success?)
  • How will we recognize, promote, and reward the individuals involved in digital transformation? (Traditional career tracks and quarterly reporting don’t support risk-takers and corporate entrepreneurs. How will you use incentives to support change and evolution in your strategy?)

The key lesson of the book is that, contrary to the Silicon Valley myth, every pre-Internet business is not a dinosaur waiting to be disrupted! There are numerous examples of traditional businesses finding a profitable path forward in the digital era. Digital transformation is possible, and we have a playbook now to make it happen.

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