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David L. Rogers: The Digital Transformation Playbook (Columbia Business School Publishing

Digital transformation is not about technology — it is about strategy and new ways of thinking.

The Five Domains of Digital Transformation: Customers, Competition, Data, Innovation, Value

There is absolutely no reason upstart digital companies have to supplant established firms. There is no reason new businesses have to be the only engines of innovation.

If electrification was transformative because it changed the fundamental constraints of manufacturing, then the impact of digital is even bigger because it changes the constraints under which practically every domain of business strategy operates.

Digital technologies change how we connect and create value with our customers. Digital technologies transform how we need to think about competition. Digital technologies have changed our world perhaps most significantly in how we think about data. The biggest challenge today is turning the enormous amount of data we have into valuable information. Digital technologies are also transforming the ways that businesses innovate. Finally, digital technologies force us to think differently about how we understand and create value for the customer.

The prevailing model of mass markets focused on achieving efficiencies of scale through mass production (make one product to serve as many customers as possible) and mass communication. In the digital age, we are moving to a world best described not by mass markets but by customer networks. Digital technologies are supercharging the power of platform business models, which allow one business to create and capture enormous value by facilitating the interactions between other businesses or customers.

Today we are faced with a data deluge. Most data available to businesses is not generated through any systematic planning like a market survey; instead, it is being generated in unprecedented quantities from every conversation, interaction or process inside or outside these businesses.

In the digital age, relying on an unchanging value proposition is inviting challenge and eventual disruption by new competitors. The only sure response to a shifting business environment is to take a path of constant evolution, looking to every technology as a way to extend and improve our value proposition to our customers. Today, creating an effective customer strategy requires that you understand such key concepts as customers as strategic assets, the reinvented marketing funnel, the digital path to purchase and the five core behaviors of customer networks (accessing, engaging, customizing, connecting and collaborating).

Developing a digital-age competitive strategy requires that you understand these principles:

  • platform business models,
  • direct and indirect network effects,
  • co-opetition between firms,
  • the dynamics of intermediation and disintermediation
  • and competitive value trains.

To create good data strategy, you must begin with an understanding of the four templates of data value creation, the new sources and analytic capabilities of big data, the role of causality in data-driven decision making and the risks around data security and privacy.

  • Strategic ideation tools: Tools for generating a new solution to a defined challenge by exploring different facets of a strategic phenomenon (Customer Network Strategy Generator and Data Value Generator).
  • Strategy maps: Visual tools that can be used to analyze an existing business model or strategy or to assess and explore a new one (Platform Business Model Map, Competitive Value Train and Disruptive Business Model Map).
  • Strategic decision tools: Tools with criteria for evaluating and deciding among a set of generic options available for a key strategic decision (Disruptive Response Planner).
  • Strategic planning tools: Step-by-step planning processes or methods that can be used to develop a strategic plan tailored to a specific business context or challenge (Convergent Experimental Method, Divergent Experimental Method and Value Proposition Roadmap).

For every Britannica, there is a Kodak or a Blockbuster — a business that failed to recognize that the rules of the game had changed and that did not manage to change its strategy to match digital reality.

Harness Customer Networks

As we begin to build our playbook for digital transformation, the first domain of strategy that we need to rethink is customers.

Customers in the digital age are not passive consumers but nodes within dynamic networks — interacting and shaping brands, markets and each other.

Businesses need to understand the five core behaviors: access, engage, customize, connect and collaborate — that drive customers in their digital experiences and interactions.

The Customer Network Strategy Generator, an ideation tool for developing breakthrough strategies to engage your networked customers and achieve specific business objectives.

In the customer network model, current and potential customers have access to a wide variety of digital platforms that allow them to interact, publish, broadcast and innovate — and thereby shape brands, reputations and markets. Customers are just as likely to connect with and influence each other as they are to be influenced by the direct communications from a firm. One of the main points in the model of customer networks is that a “customer” can be any key constituency that the organization serves and relies on. It is important to look at a range of interconnected constituencies that are all within an organization’s customer network: end consumers, business partners, investors, press, government regulators and even employees.

The progression of a potential customer from awareness (knowledge that a product or company exists) to consideration (recognition of potential value) to preference (intent to purchase or choice of a preferred company) to action (purchase of a product, subscription to a service, voting for a political candidate, etc.).

The enduring utility of the marketing funnel stems from the fact that it is a psychological model, based on a progression of psychological states (awareness, etc.).

Today’s customer networks, however, make their biggest impact on the marketing funnel through an additional level, which I call advocacy. At this psychological stage, customers are not just loyal; they advocate for the brand and connect the brand to people in their network. Each customer’s advocacy thus feeds back up to the top of the funnel and has the potential to increase the magnitude of awareness, consideration and so on through the funnel. This extended, or looped, marketing funnel is sometimes renamed the customer journey.

An omni-channel experience uses design to integrate the path to purchase as it moves from one touchpoint to the next.

One of the most important questions any business must face today is: “How much are my customers worth?” Customer lifetime value can be shaped by various factors: frequency of purchase, volume of purchase, price point, reliance on discounting and loyalty or attrition rate. To build a model, you will need historical data and the involvement of your finance team.

In a networked world, though, customers add value in more ways than just their transactions over time. Increasingly, new business models are being built where the customers’ participation, data and collective knowledge are a business asset and a key competitive advantage. The challenge in acquiring a firm for its customer network is that continued customer loyalty is not assured.

There is a recurring pattern of five behaviors that drive the adoption of new digital experiences. I call these the five core behaviors of networked customers:

  • Access
  • Engage
  • Customize
  • Connect
  • Collaborate

The access strategy for business is to be faster, be easier, be everywhere, and be always on for your customers. An access strategy may therefore take a variety of approaches, including mobile commerce, omni-channel experiences, working in the cloud and on-demand service. The keys to an access strategy are simplicity, convenience, ubiquity and flexibility.

The engage strategy for business is to become a source of valued content for your customers. An engage strategy may take a variety approaches, including product demos, storytelling, utility and brands as publishers. The key to an engage strategy is to think like a media company, focused every day on earning the attention of your audience.

The customize strategy for business is to make your offering adaptable to your customers’ needs. A customize strategy may take a variety of approaches, including recommendation engines as well as personalized interfaces, products and services, and messages and content. The keys to a customize strategy are identifying the areas where your customers’ needs and behaviors diverge.

The connect strategy for business is to become a part of your customers’ conversations. A connect strategy may take a variety approaches, including social listening, social customer service, joining the conversation, asking for ideas and content, and hosting a community. The keys to a connect strategy are focusing on the social media your customers use.

The collaborate strategy for business is to invite your customers to help build your enterprise. We see a few well-established broad approaches to a collaborate strategy, including passive contribution, active contribution, crowdfunding, open competitions and collaborative platforms. The keys to a collaborate strategy are understanding the motivations of your contributors.

The Customer Network Strategy Generator is designed to help you develop new strategic ideas for engaging and creating value with networked customers. The tool follows a five-step process for generating new strategic ideas.

  • Step 1: Objective Setting
  • Step 2: Customer Selection and Focusing.
    • Three key questions: What is my unique objective for each customer segment?
    • What is my unique value proposition for each customer segment?
    • What are the unique barriers to success for each customer segment?
  • Step 3: Strategy Selection
    • Now that you know your objectives for your customer strategy and have a strong understanding of the customers you are trying to reach, you are ready to start the strategy ideation process.
  • Step 4: Concept Generation
    • Now you are ready to start generating specific strategic concepts based on the broad strategies, objectives and customers you have selected. A concept is a specific, concrete idea for a product, service, communication, experience or interaction you design for customers. This step is fundamentally a creative, idea-generating effort.
  • Step 5: Defining Impact.
    • At this point, you should bring each of your ideas back to the business objectives you set for yourself in step 1.

Having completed all five steps, you should now have a set of compelling new customer strategies for your team to consider for implementation. Still to come would be any planning to test your strategic concepts, validate them, allocate resources to them, refine their metrics and (if appropriate) move to a public launch.

Some of the challenges that a traditional, pre-digital-era enterprise may face in rethinking its assumptions about customers.

  • Organizational Challenges of Customer Networks
  • Enabling the Network Inside
  • A firm’s internal customer network—its own employees— is critical to the digital transformation of a business.

In order to leverage customer networks outside the firm, businesses are having to acquire a host of new skills. These skills include social media and community management, journalistic content creation, new media buying and measurement, e-commerce and more. The challenge for established businesses is to avoid outsourcing these tasks to expert agencies. Outsourcing delays the process of integrating new skills into the organization.

In many companies, these new networked skills exist but are unevenly distributed.

Some firms, like Motorola, have gone so far as to merge the CMO and CIO into a joint position. The strongest argument for bridging the traditional silos of a company is the need to integrate the total customer experience with a firm and its brand.

The interactions between businesses are being similarly transformed. What used to be fairly simple, even binary relationships (partner or competitor) have become more complex and interconnected.

Build Platforms, Not Just Products

Much of Airbnb’s success comes down to building trust between the two parties. Building trust begins with mutual ratings and reviews for both hosts and travelers but goes far beyond that. The company waits to release rental payments to the host until after the renter has checked in and verified, they are happy with the property; it likewise holds onto the renter’s deposit until after they have left and the host has verified their home is in good shape. Rethinking Competition Airbnb is an example of a platform — a class of businesses that are rethinking which competitive assets need to be owned by a firm.

The digital revolution is redefining competition and relationships between firms in several ways. It is supercharging the growth of platform businesses. It is shifting the locus of competition: competition is happening less within industries and less between similar companies that seek to replace each other; it is happening more across industries and between partners who rely on each other for success. Lastly, digital technology is increasing the importance of “co-opetition”.

Platforms represent a fundamental shift in how businesses relate to each other — from linear to more networked business models.

The idea of platforms as business model has its origins in the economic theories of two – sided markets developed by Jean – Charles Rochet and Nobel laureate Jean Tirole along with Thomas Eisenmann, Geoffrey Parker Marshall Van Alstyne and others. The term in economics for the business model at the center of a multisided market is a multisided platform or just platform.

To condense their thinking, I offer this definition: A platform is a business that creates value by facilitating direct interactions between two or more distinct types of customers.

Important elements of platform:

  • Distinct types of customers
  • Direct interaction
  • Facilitating

David S. Evans and Richard Schmalensee identify four broad types of platform businesses:

  • Exchange
  • Transaction system
  • Ad-supported media
  • Hardware/software standard

One of the key features of platforms is that their value increases as more customers use them. This is direct network effects. In communications theory, this is commonly dubbed Metcalfe’s law. For platforms, the more common type of network effect is indirect network effects.

Any business today faces a strategic choice of whether to pursue a platform model or a more traditional business model. The right business model may be somewhere on a spectrum from platform to non-platform.

Digital technologies are supercharging the growth and power of multisided platforms. These enabling technologies include:

  • the Web;
  • on-demand cloud computing;
  • application program interfaces (APIs),
  • which increase the interoperability of data and functionality;
  • social media
  • and mobile computing devices.

Four key elements of platforms:

  • Frictionless acquisition
  • Scalable growth
  • On – demand access and speed
  • Trust

Platform businesses can achieve extremely high operating margins on a percentage basis. Platform businesses can grow extremely quickly. Once a platform is widely established in its category, it is extremely hard to launch a direct challenger with a similar service—a result of the power of network effects. winner-take-all total consolidation is likely to happen when three factors are present:

  • Multihoming — using more than one platform — is hard for the customer
  • Indirect network effects are strong
  • Feature differentiation is low

One of the most striking benefits of platform business models is that they enable the efficient usage of distributed pockets of economic value (labor, assets and skills) that otherwise could not be effectively used.

The popular platforms that are commonly cited as evidence of the sharing economy are, in fact, better described as a “rental economy” (renting assets on Airbnb), a “resell economy” (selling used assets on eBay) or a “freelance economy” (selling labor on Uber).

How do platforms compete with each other in the same category? Not on the same factors — features, benefits, price, location — that differentiate traditional products and services. Instead, platforms tend to compete on five areas of value:

  • Network-added value
  • Platform-added value
  • Open standards
  • Interaction tools
  • Trust enablers

The Platform Business Model Map is an analytic and visualization tool designed to identify all the critical parties in a platform and analyze where value creation and exchange take place among the different customers and with the platform business itself.

Shapes indicate the key parties within the business model:

  • Circle: The platform
  • Diamonds: The payers
  • Rectangle: The sweeteners
  • Spikes: The number of other customer types that are attracted
  • Double-borders: The linchpin (the customer type with the most spikes; the king of network effects)

Arrows indicate value exchange:

Arrows in each direction show the value provided, or received, by each customer type.

Value in boldface is monetary value. Value in parentheses is provided by the platform itself or to the platform itself. Value not in parentheses is passed through the platform and is provided to other customers.

A detailed guide on how to draw, and use, the Platform Business Model Map can be found at http://www.davidrogers.biz under Tools.

The term co-opetition was coined by Novell founder Ray Noorda and popularized by Adam Brandenburger and Barry Nalebuff in a book of the same name.

In Brandenburger and Nalebuff’s view, rival companies must cooperate to “grow the pie” at the same time that they compete with each other to “divide the pie”.

Today, the boundaries of industries are much less static due to rapid technological change. Companies can expect to compete with more and more businesses that do not look much like them. We can think of this as a shift from symmetric to asymmetric competitors. Symmetric competitors offer similar value propositions to customers.

Asymmetric competitors are quite different. They offer similar value propositions to customers, but their business models are not the same.

Rita McGrath advises thinking about competition less in terms of industries and more in terms of arenas — companies that have a similar offer, for the same market segment, in the same geographic location.

One of the biggest impacts of digital technologies has been on the relationships of businesses to the partners in their supply chain.

This disruption and reconfiguration of business relationships is mostly talked about in terms of disintermediation — the removal of an intermediary or middleman from a series of business transactions.

Digital platforms are also fueling a reverse phenomenon, which is best described as intermediation. In these cases, a new business manages to insert itself as an intermediary between the customers and a company that used to sell directly to them.

The Competitive Value Train is a tool I designed to analyze competition and leverage between a firm and its business partners, direct rivals and asymmetric competitors. Porter’s value chain is a popular tool for examining the various processes that add value to a product or service within a company’s own operations. The supply chain is a widely used tool for modeling the processes across different companies that contribute to a product’s manufacture, distribution and sale. The value train focuses on competition by looking at the leverage between the companies in a supply chain and their potential substitutes and by mapping how a particular product or service reaches a particular group of customers. By depicting both partners and their symmetric and asymmetric competitors, the value train aims to provide a multidimensional view of competition and cooperation.

Looked at through the lens of the value train, it becomes clear that the goal for any business is not simply to defeat, or even outperform, its direct competitors (e.g., the Washington Post vs. the New York Times). The overriding competitive goal is to gain more leverage in its value train. In a value train, the first creator and the final distributor to the end consumer each have additional influence by virtue of their positions. By contrast, the parties in the middle tend to be boxed in and lose influence relative to the creators and end distributors.

Channel conflict is the common term for the situation where a business is balancing both working with a key sales channel and going around it.

One of the biggest challenges of a platform business model is letting go of some of the value creation process. By their nature, platforms grow by letting their distinct outside parties each bring their own value to the platform and interact with a substantial degree of independence.

Relationships with other firms, in short, have become just as networked and interconnected as relationships with customers. In both relationships, the increasing digitization of interactions is yielding another product as well: data.

Turn Data into Assets

The third domain of the digital transformation playbook is data. Growing a business in the digital age requires changing some fundamental assumptions about data’s meaning and importance. By designing new customer experiences with data in mind, companies can extend this model of providing customer benefits in return for customer data gained. The shift to cloud computing is putting ever more powerful data management tools into the hands of small and mid-sized businesses.

The following five principles should guide any organization in developing its data strategy.

  • Gather diverse data types
    • Key Data Types for Business Strategy
    • Business process data
    • Product or service data
    • Customer data
  • Use data as a predictive layer in decision making
  • Apply data to new product innovation
  • Watch what customers do, not what they say
    • Behavioral data is always the best customer data— it is much more valuable than reported opinions or anything customers tell a market researcher in a survey. That is not just because people lie in surveys but also because, as humans, we are extremely fallible at remembering our behavior, predicting our future actions or considering our motivations.
  • Combine data across silos

The term big data first appeared in the mid-1990s, introduced in tech circles by John Mashey, chief scientist of Silicon Graphics. The phenomenon of big data is best understood in terms of two interrelated trends: the rapid growth of new types of unstructured data and the rapid development of new capabilities for managing and making sense of this kind of data for the first time. The impact of these two is shaped by a third trend: the rise of cloud computing infrastructure.

The big-data era has been marked by the profusion of new types of unstructured data.

  • Social data is attitudinal.
  • Another new kind of unstructured data is location data.
  • The biggest emerging source of unstructured data is the sensors This phenomenon, known as the Internet of Things.

The second trend shaping big data is the rise of new technological capabilities for handling and making sense of all this unstructured data.

  • In-memory computing can accelerate analytics to the kind of real-time computing.
  • Hadoop is an open-source software framework that enables distributed parallel processing of huge amounts of data across multiple servers in different locations.
  • New data-mining tools.
  • Perhaps the biggest advances in managing unstructured data have come from new developments in “cognitive” computing.
  • Another key development is machine learning.

An additional trend is shaping the impact of big data: a revolution in the storage and accessibility of both data and data processing and the rise of cloud computing.

Three Myths of Big Data

  • Myth 1: The Algorithm Will Figure It Out
  • Myth 2: Correlation Is All That Matters
  • Myth 3: All the Good Data Is Big Data

What makes consumers willing to share their information with businesses? In a global research study that I conducted at Columbia University with Matt Quint, we observed four key factors: the type of value or rewards offered, the presence of a trusted relationship with the business, the type of data being requested and the industry of the business.

Four templates for creating value from customer data:

  • insights: revealing the invisible,
  • targeting: narrowing the field,
  • personalization: tailoring to fit and
  • context: providing a reference frame.

Custora is a data analytics company that helps e-commerce businesses determine the likely customer lifetime value (CLV) of their website visitors. That is, not just their likelihood to buy in this visit but their likely profit potential in the future. This is done by analyzing historical customer data and applying both a CLV model and Bayesian probabilistic models.

The Data Value Generator. The tool follows a five-step process for generating new strategic ideas for data.

  • Step 1: Area of Impact and Key Performance Indicators. The first step is to define the area of your business you are seeking to impact or improve through a new data initiative. Once you have defined the area of impact, you should identify your primary business objectives in that area.
  • Step 2: Value Template Selection
  • Step 3: Concept Generation. At the concept generation stage, you want to produce specific ideas for putting the data to work in your business.
  • Step 4: Data Audit. Now that you have a strategy in mind, you need to assemble the data that it will require.
  • Step 5: Execution Plan. The last step is to plan for the execution of the key pieces of your data plan.

The first challenge in the transition to a more data – driven organization is finding people with the right skill sets. In order to truly build data into a strategic asset, everyone in the business has to adopt a mindset that includes using data and the questions they pose to it, as a part of their daily process. Lastly, the company may need someone who can bridge two worlds: the world of quantitative analysts and that of business decision makers.

The most commonly cited obstacle to using data effectively was internal sharing. Data sharing is critical not only within an organization; it is becoming a key element of negotiations with business partners. As businesses gather and utilize more and more data, particularly customer data, they also bring on additional security risks. Cyberthreats that used to be the concern of CIOs are going to be front and center for senior leadership now. When customers can easily see both the ways that companies are gathering data and the benefits they are gaining as a result, they will be more likely to allow sustainable access to businesses. Data allows us to continually experiment, learn and test our ideas. This means data can do more than power products, optimize processes, and deliver more-relevant customer interactions; it can also help change the way organizations learn and innovate.

Innovate by Rapid Experimentation

The fourth domain of digital transformation is innovation — the process by which new ideas are developed, tested and brought to the market by businesses. In the digital age, enterprises need to innovate in a radically different fashion, based on rapid experimentation and continuous learning. Experimentation can be defined as an iterative process of learning what does and does not work. This is very different than a traditional innovation process: analyze the market, generate ideas, debate internally, pick a solution and then develop it through many stages of quality testing before launching it and getting feedback from actual customers.

This shift toward a more iterative, learning-based model for innovation has been growing for several years and in many quarters.

With the rise of digital A/B testing, constant experimentation has become the norm for more and more products, services and communication channels.

We can see two types of business experimentation that are suited for two types of learning. I will call these two types convergent and divergent because I prefer to name them by their function rather than their form. Convergent experiments are best suited for learning that eliminates options and converges on a specific answer to a clearly defined question. Divergent experiments are best suited for learning that explores options, generates insights, asks multiple questions at the same time and, when done right, generates new questions to explore in the next iterative stage. Some of the key writers on divergent experimentation include Nathan Furr and Jeff Dyer (for established businesses) and Eric Ries and Steve Blank (for start-ups).

Digital technologies are making rapid experimentation both more possible and more necessary than ever before.

These seven principles apply for any business experiment, whether convergent or divergent:

  • Learn Early
  • Be Fast and Iterate
  • Fall in Love with the Problem, Not the Solution
  • Get Credible Feedback
  • Measure What Matters Now
  • Test Your Assumptions
  • Fail Smart

Many firms measure the costs of running experiments (which in some industries can still be expensive), but very few attempt to measure their cost savings when learning from experiments.

Failure is inevitable. We can define failure as trying something that doesn’t work. Obviously, that is not the ultimate goal of innovation, but it is an inevitable part of the process of innovation. Smart failure is simply a series of cheap, effective tests that show you the gaps between where you are and where you need to get.

Tool: The Convergent Experimental Method This experimental method is particularly useful for innovating on existing products, services and processes.

  • The first step of any convergent experiment is to define the question you are seeking to answer.
  • The next step is to select who will conduct the experiment.
  • Step 3: Randomize Your Test and Control
  • Next you need to make sure you have a valid sample size.
  • Step 5: Test and Analyze
  • After analyzing the results of your convergent experiment, it is time to make a decision based on the findings.  
  • Once you complete your analysis, it is essential to capture and share the learning of your experiment.

The second tool is a guide for running divergent experiments. This method is particularly useful for innovations that are less defined from the outset, such as new products, services and business processes for your organization. The ten-step Divergent Experimental Method:

  • The first step of a divergent experiment is to define the problem you are seeking to solve.
  • The second step is to set limits for your innovation process. Any divergent experiment should begin with three kinds of limits defined: Time limit, money limit, scope limit.
  • The last step of the preparation phase is to pick which people will work on your innovation experiment. J. Richard Hackman has studied team collaboration and found that the number of network links between team members poses an upper threshold for effective group size. As the number of group members increases linearly, the necessary lines of communication increase exponentially, as n (n–1)/2. Hackman advises that a group of five is ideal and warns against ever going above ten.
  • Step 4: Observe The iterative development of ideas for your innovation begins with observation.
  • Step 5: Generate More than One Solution The next step is to generate ideas to solve the defined problem.
  • Step 6: Build an MVP.
  • Build prototypes. In the start-up world, the focus is on a minimum viable product.
  • Step 8: Decide At the end of each field test of an MVP, you will face a decision point.
  • For an established business, the decision after each field test is one of four options. Proceed, pivot, prepare to launch, pull the plug.
  • Step 9: Scale Up.
  • Step 10: Share Learning.

MVP Rollout This is the easiest path for introducing an innovation because you can start your rollout with a limited test market and then iterate rapidly as you gain additional feedback from customers.

MVP Launch The second path for scaling up is harder. In this quadrant, your business is forced to iterate very quickly after launching your innovation because you are not able to able to effectively limit the scope of the launch.

Polished Rollout The third path for scaling up is also harder than the first — but for different reasons. In this quadrant, you are able to launch your innovation in limited locations or for limited customers, but you cannot quickly iterate it once it is public.

Polished Launch The fourth path for scaling up a new innovation is the hardest of all. In this quadrant, you must offer your new innovation to all customers at once and you are unable to iterate it quickly.

In Silicon Valley, it is commonly said that HiPPOs make the decisions at more-traditional firms. No, not the river-dwelling mammal you see in the zoo. This is decision based on the Highest Paid Person’s Opinion.

When faced with deep and profound changes in market needs, businesses and entire industries can find that the value they offer to customers is no longer the same or as relevant, as it used to be. This uncertainty means that every business must be prepared to adapt its value proposition to customers over time.

Adapt Your Value Proposition

The fifth and final domain of digital transformation is your business’s value to its customers. Traditionally, a company’s value proposition has been treated as fairly constant, ideally a source of sustained competitive advantage for the long haul. But in the digital age, unswerving focus on executing and delivering the same value proposition is no longer sufficient.

There may be many reasons that businesses face a declining market. New technologies can bring rapid changes in customer needs, the appearance of substitute offerings or a decline in the relevance of a once-valued product or service.

  • The first route out of a shrinking market is to find new customers to buy your same offering.
  • The second route out of a shrinking market is to continue serving your same customers but to adapt your value proposition to stay relevant to their changing needs.
  • In some cases, a third route out of a shrinking market may be possible with both new value and new customers.

Value proposition is just one of several strategic concepts available for thinking about your offerings and value to the market.

Four of the most common ways of thinking about market value:

  • Product: Thinking about products is something every manager is comfortable doing.
  • Customer: Another very common approach is to think about your business in terms of your customers — who they are and how they differ from one another.
  • Use case: This concept arose in software engineering and is credited to Ivar Jacobsen, but it has been applied more broadly in design and marketing. In the broader sense, a use case is the context within which a customer utilizes your product or service.
  • Job to be done: This concept has been popularized by Clayton Christensen and Michael Raynor. In the job-to-be-done framework, the concern is not just the context in which a customer is using a product but also the customer’s purpose for using it.

Value proposition: This term was coined by Michael Lanning and Edward Michaels. It has come to be used broadly in marketing and strategy as a concept that defines the benefits received by a customer from a company’s offering. The Value Proposition Roadmap is a tool that any organization can use to assess and adapt its value proposition for its customers. The Value Proposition Roadmap uses a six-step process to map out new options for your business.

  • The first step is to identify your key customer types, distinguished by the different kinds of value they receive from your business.
  • The next step is to define your current value proposition for each customer type.
  • Now that you understand your current value to customers, it is important to understand emerging threats that could undermine it. Following are three sources to consider for potential threats to your current value proposition: New technologies, changing customer needs, new competitors and substitutes.
  • At this point, you should return to the lists of value elements you developed for your customer types in step 2. You can now assess the strength of the specific elements of value that you provide.
  • Your next step is to try to identify new value elements that you could offer to this customer type. To generate new value elements that you could offer to your customers, look in three areas. New technologies, trends in your customers’ sociocultural or business environment, unmet customer needs.
  • The final step of the Value Proposition Roadmap is to synthesize everything you have learned about your value proposition for each customer type.

Review your value elements and place each into one of four columns:

  • Core elements — to build on
  • Weakened elements — to bolster
  • Disrupted elements — to deprioritize
  • New elements — to create

Business needs additional tools: a theory to understand the difference between competition and true disruption. Successful leadership today requires an updated theory of disruption for the digital age.

Mastering Disruptive Business Models

Business disruption happens when an existing industry faces a challenger that offers far greater value to the customer in a way that existing firms cannot compete with directly.

Not all innovation is disruptive. Even an innovative business model is not necessarily disruptive — as long as the jobs and revenues it creates are entirely additive to the market. The first major theorist of business disruption was the Austrian economist Joseph Schumpeter. Schumpeter identified industry disruption as an inherent pattern in capitalism. Business disruption is, at its core, the result of the clash of asymmetric business models. A business model describes a holistic view of how a business creates value, delivers it to the market and captures value in return.

A detailed business model may comprise several components. Alexander Osterwalder and Yves Pigneur describe it as including nine “building blocks”:

  • customer segments,
  • value propositions,
  • channels,
  • customer relationships,
  • revenue streams,
  • key resources,
  • key activities,
  • key partnerships and
  • cost structure.

For the purpose of understanding disruption, let’s split the business model into two sides. The first side is the value proposition — the value that a business offers to the customer. The second side of the business model is the value network — the people, partners, assets and processes that enable the business to create, deliver and earn value from the value proposition.

The theory of business model disruption is simply this: in order to disrupt an existing business, a challenger must possess a significant differential on each side of the business model:

  • A difference in value proposition that dramatically displaces the value provided by the incumbent (at least for some customers).
  • A difference in value network that creates a barrier to imitation by the incumbent
  • Business disruption happens when both of these conditions are met — and only then.

Key value proposition generatives that are common to digital disrupters include the following:

  • Price
  • Free or “freemium” offer
  • Access
  • Simplicity
  • Personalization
  • Aggregation
  • Unbundling
  • Integration (or rebundling)
  • Social

Key components to consider in analyzing a challenger’s value network include the following:

  • Customers
  • Channels
  • Partners
  • Networks
  • Complementary products or services
  • Brand
  • Revenue model
  • Cost structure
  • Skills and processes
  • Physical assets
  • IP assets
  • Data assets

Three important variables that complete the theory of business model disruption are customer trajectory, disruptive scope and multiple incumbents.

Business model disrupters can enter the market through one of two trajectories:

  • Outside-in
  • Inside-out

The second important variable in cases of business model disruption is the likely scope of the disruption. In many cases of business disruption, the scope is not 100 percent.

The third variable to consider is multiple incumbents. A single disruptive business model can actually disrupt more than one incumbent. By multiple incumbents, I don’t mean similar companies in the same industry (e.g., the iPhone disrupting Motorola along with Nokia). But entirely different industries or classes of companies that are each challenged by the same new disruptive business model.

Disruptive Business Model Map. This strategy mapping tool is designed to help you assess whether or not a new challenger poses a disruptive threat to an incumbent industry or business.

  • Step 1: Challenger. In describing the challenger, you need to include its key offering.
  • Step 2: Incumbent
  • Step 3: Customer
  • Step 4: Value Proposition
  • Step 5: Value Proposition Differential
  • Step 6: Value Network
  • Step 7: Value Network Differential
  • Step 8: Two – Part Test

Does the challenger pose a disruptive threat to the incumbent?

Business disruption happens when an existing industry faces a challenger that offers far greater value to the customer in a way that existing firms cannot compete with directly. The challenger is a disruptive threat.

The Disruptive Response Planner is designed to help you map out how a disruptive challenge will likely play out and identify your best options for response.

  • Step 1: Customer Trajectory. The first step in predicting the possible impact of a new disruptive business model is to understand its customer trajectory.
  • Step 2: Disruptive Scope. Disruptive scope can be predicted by looking at three factors: use case, customer segments and network effects. Three likely outcomes of a disruptive business model. One is a niche case, where the disrupter is attractive to only a very specific portion of the market. Other disrupters may wind up splitting the market, with the disrupter’s and the incumbent’s business models each taking large shares. And in cases of a landslide, the disrupter quickly takes over the entire market, pushing the incumbent into obscurity.
  • Step 3: Other Incumbents

Laddering is market research technique, where you ask a customer a series of “Why?” questions to get at the reasons behind their immediate motivations.

Six possible responses when faced with a disruptive challenger:

    • Acquire the disrupter
    • Launch an independent disrupter
    • Split the disrupter’s business model
    • Refocus on your defensible customers
    • Diversify your portfolio
  • Plan for a fast exit

Incumbents don’t have to react just by becoming the disrupter; they can also act defensively in shoring up their own core business. The next way that incumbents can mitigate the disruption of their core business is by diversifying their portfolio of products, services and business units. Diversification allows you to leverage the strengths in your value network in new business areas. The last strategy for an incumbent response to disruption is the least desirable one. When a disruptive challenger poses an irresistible threat to an incumbent’s entire market and there is no feasible way to launch a disruption of its own, the incumbent needs to plan for a fast exit.

Responding to disruption requires that a business be willing to question its own assumptions and focus on the unique mission of how it serves customers.

Digital transformation

Digital transformation is fundamentally not about technology but about strategy. Although it may require upgrading your IT architecture, the more important upgrade is to your strategic thinking. Traditionally, digital leaders, such as CIOs, were tasked with focusing on automating and improving the processes of an existing business. Today, digital leadership requires the ability to reimagine and reinvent that business itself.

Why are so many of our institutions struggling to adapt and keep up? One of the key reasons is organizational agility. To develop true organizational agility, your business needs to focus on three areas:

  • Allocating resources
  • Changing what you measure
  • Aligning incentives

You can think about the challenge of digital transformation in terms of mastering two different kinds of management. To succeed in any transformation, your organization must be able to develop truly new ideas, processes, ventures and ways of thinking. But it must also be able to spread these ideas or processes throughout the organization.

Having built a powerful data asset, developed tools to capture customer insight and apply it in customer interactions and launched pilot programs to prove the impact for the business. The next stage is to scale up the program, to embed the use of data for customer service into the company’s DNA. We should see transition as a shift from “incubation” (seeding and nurturing new strategies) to “integration” (building the best ones into the fabric of the organization).

The ability to incubate relies on specific skills: tolerating risk, seeding diverse ideas with resources, welcoming outsiders who don’t fit your organizational culture, empowering entrepreneurs, developing a robust innovation process based on discovery and assumptions testing, maintaining a customer-centric view and being willing to let new ventures cannibalize existing ones.

The ability to integrate involves a different set of skills: building a compelling business case, developing a clear proof of concept, selling new ideas to diverse internal constituencies, finding the right executive sponsorship, working with budgets based on business outcomes, managing accountability to multiple stakeholders and being able to scale up operations.

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