book summary: the digital transformation playbook - David L. Rogers, Dispense di Management Theory

Scarica book summary: the digital transformation playbook - David L. Rogers e più Dispense in PDF di Management Theory solo su Docsity! of 1 81 1. The Five domains of digital transformation — customers, competition, data, innovation, value You may remember the Encyclopoedia Britannica. First published in 1768, it represented the definitive reference resource in English for hundred of years before the rise of the Internet. When, after 244 years, Encyclopoedia Britannica, Inc., announced it had printed its last edition, the message seemed clear. Another hidebound company for before the arrival of the Internet had been disrupted — wiped out by the irrefutable logic of the digital revolution. Except that wasn’t true. Wikipedia was not, in fact, its first digital challenger. At the dawn of the personal computing era, Britannica sought to shift from print to CD-ROM editions of its product and suddenly faced competition from Microsoft, a company in a totally different industry: Microsoft’s Encarta encyclopedia was a loss leader, given away free on CD-ROM with purchases of Windows software as part of a larger strategy to position personal computers as the primary educational investment for middle-class families. Britannica understood that customers’ behaviours were changing dramatically with the adoption of new technologies. significantly, it maintained a focus on its core mission: editorial quality and educational service. With this focus, it was able not only to pivot to a purely online subscription model for its encyclopedia but also to develop new and related product offerings to meet the evolving needs for classroom curricula and learning. The story of Britannica may seem surprising precisely because the setup is so familiar: powerful new digital technologies drive dramatic changes in customer behaviour. The old business model is invalidated. Inflexible and unable to adapt, the “dinosaur” business gets wiped out. Overcoming Your Digital Blind Spots Back during the first wave of the Industrial Revolution, factories were dependent on fixed sources of power—first, water power from waterwheels located along rivers and, later, steam power from coal- fired engines. Although these power sources enabled the rise of mass production, they set fundamental constraints as well. h the spread of electrification to factories at the end of the nineteenth century, all of this changed. Electrical power eliminated all the constraints that had defined factories up until that point. Machinery could be arranged in the optimal order of work. These new firms loaned electric motors for free to manufacturers just to get them to try the new technology. Progress was slow at first, but it turned out the utilities could teach some old dogs new tricks. By the 1920s, a new ecosystem of factories, workers, engineers, products, and businesses had taken shape, with electrical power at its centre. Today, our digital-born businesses (such as Google or Amazon) are like the electrical companies of the early electrification era. And our savvy digital adopters (such as Britannica) are like the factories that learned to retool and advance into the next industrial age. Both types of businesses recognise the possibilities created by digital technologies. Five Domains of Strategy That Digital is Changing 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. But today the relationship is much more two-way: customers’ communications and reviews make them a bigger influencer than advertisements or celebrities, and customers’ dynamic participation has become a critical driver of business success. Digital technologies transform how we need to think about competition. More and more, we are competing not just with rival companies from within our industry but also with companies from outside our industry that are stealing customers away with their new digital offerings. Increasingly, our competitive assets may no longer reside in our own organisation; rather, they may be in a network of partners that of 2 81 we bring together in looser business relationships. Digital technologies have changed our world perhaps most significantly in how we think about data. In traditional businesses, data was expensive to obtain, difficult to store, and utilised in organisational silos. Just managing this data required that massive IT systems be purchased and maintained. Today, data is being generated at an unprecedented rate—not just by companies but by everyone. Moreover, cloud-based systems for storing data are increasingly cheap, readily available, and easy to use. 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. Today, digital technologies enable continuous testing and experimentation, processes that were inconceivable in the past. Prototypes can be built for pennies and ideas tested quickly with user communities. Constant learning and the rapid iteration of products, before and after their launch date, are becoming the norm. Finally, digital technologies force us to think differently about how we understand and create value for the customer. Taken together, we can see how digital forces are reshaping five key domains of strategy: customers, competition, data, innovation, and value. These five domains describe the landscape of digital transformation for business today. Across these five domains, digital technologies are redefining many of the underlying principles of strategy and chaining the rules by which companies most operate in order to succeed. Customers The first domain of digital transformation is customers. Customers were seen as aggregate actors to be marketed to and persuaded to buy. The prevailing model of mass market focused on achieving efficiencies of scale through mass production and mass communication. In the digital age, we are moving to a world best described not by mass markets but by customer networks. In this paradigm, customers are dynamically connected and interacting in ways that are changing their relationships to business and to each other. Their use of digital tools is changing how they discover, evaluate, purchase, and use products and how they share, interact and stay connected with brands. Competition The second domain of digital transformation is competition: how businesses compete and cooperate with other firms. Traditionally, competition and cooperation were seen as binary opposites: businesses competed with rival businesses that looked very much like themselves, and they cooperated with supply chain partners who distributed their goods or provided needed inputs for their production. We are moving to a world where our biggest challengers may be asymmetric competitors. Digital “disintermediation” is upending partnerships and supply chains. At the same time, we may need to cooperate with a direct rival due to interdependent business models or mutual challenges from outside our industry. Digital technologies are supercharging the power platform business models, which allow one business to create and capture enormous value by facilitating the interactions between other businesses or customers. The net result of these changes is a major shift in the locus of competition. Data The next domain of digital transformation is data: how businesses produce, manage, and utilise information. Traditionally, data was produced through a variety of planned measurements that were conducted within a business’s own processes. 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. These big data tools allow firms to make new kinds of predictions, uncover unexpected patterns in business activity, and unlock new sources of value. Data is becoming the lifeblood of every department and a strategic asset to be developed and deployed over time, it is a vital part of how businesses operate and generates new value. of 5 81 Adapt your value proposition To master value creation in the digital age, businesses must learn how to continuously adapt their value proposition. That means they need to learn to focus beyond their current business model and zero in on how they can best deliver value to their customers as new technologies reshape opportunities and needs. Continuous reconfiguration of a business may involve discovering new customers and application for its current products. It may mean evolving a business’s offering while its old business model is under severe threat: Encyclopædia Britannica, Inc., has re-envisioned itself as an educational resource. Adaptation may mean aggressively developing a new suite of products in anticipation of rapid customer changes, as Facebook did during its pivot to mobile platforms. To proactively adapt your value proposition, you need to understand these elements: the different key concepts of market value, the three possible paths out of a declining market position, and the essential steps to take to effectively analyze your existing value proposition, identify its emerging threats and opportunities, and synthesise an effective next step in its evolution. Getting Started on Your Own Digital Transformation Where do you get started on digital transformation if you are an established firm? Many books on digital innovation and strategy focus heavily on startups. But the challenges of launching a blank-slate, digital-first business are quite different from those of adapting an established firm that already has infrastructure, sales channels, employees, and an organisational culture to contend with. Leaders face very different challenges applying the same strategic principles — of customers, competition, data, innovation, and value — apply. But the path to implementing these principles is different, depending on the point from which one starts. 9 Tools for Digital Transformation Customer Network Strategy Generator Platform Business Model Map Competitive Value Train Data Value Generator Convergent Experimental Method Divergent Experimental Method Value Proposition Roadmap Disruptive Business Model Map Disruptive Response Planner These tools can be categorized as follows: - 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, 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, 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, Value Proposition Roadmap) of 6 81 2. Harness Customer Networks Rethinking Customers On-demand, customisable, connected, sharable — the same qualities that LifeChurch.tv offers to engage its digital-age parishioners are what customers seek from every business today. The first domain of strategy that we need to rethink is customers. Customers have always been essential to every business as the buyers of goods and services. In order to grow, companies have targeted them with mass-marketing tools designed to reach, inform, motivate, and persuade them to buy. Another industry where this changed relationship is crystal clear is the music business. Today, customers expect to listen to any song at any time, streaming from a variety of services on a variety of devices. They discover music through search engines, social media, and the recommendations of both friends and algorithms. Musicians may skip the record label and go directly to the customers themselves. They ask customers to help fundraise for an album before it is even recorded, to share it on their playlists, and to connect their favourite bands to peers in their social networks. 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 behaviours—access, engage, customise, connect, and collaborate—that drive customers in their digital experiences and interactions. And they need to leverage these behaviours to invent new communications, products, or experiences that add value to both sides of the business-customer relationship. The Customer Network Paradigm Today, customers’ behaviour—how they find, access, use, share, and influence the products, services, and brands in their lives—is radically different than in the era in which modern business practices arose. In the twentieth century, their only significant role is to either purchase or not purchase, and companies seek to identify the product or service that will suit the needs of as many potential customers as possible. Mass media and mass production are used to deliver and promote a company’s offerings to as many customers as possible. Today, however, we are in the midst of a profound shift toward a new paradigm — the customer network model. The new roles of customers create a more complex relationship. of 7 81 In a market defined by customer networks, the roles of companies are dramatically different as well. Yes, the firm is still the greatest single engine for innovation of products and services, and still the steward of its brand and reputation. But while delivering value outward to customers and communicating to them, the firm also needs to engage with its customer network. One of the main points in the model of customer networks is that a “customer” can be any key constituency that the organisation serves and relies on. Customers may be end consumers purchasing a product or businesses purchasing professional services. The Marketing Funnel and the Path to Purchase The marketing funnel (sometimes called the purchase funnel) is one framework for understanding how customer networks have such great impact on businesses’ relationships to customers. This classic strategic model is based on “hierarchy of effects” psychological research dating to the 1920s. It maps out the progression of a potential customer from awareness, to consideration, to preference, to action. At each stage, the number of potential customers inevitably diminishes (more will be aware than consider) — hence the tapering shape of the funnel. A further stage — loyalty — was added. The enduring utility of the marketing funnel stems from the fact that it is a psychological model, based on a progression of psychological states. In the mass-market era, businesses developed an array of broadcast marketing tools to reach and influence customers at different stages of the funnel. Television advertising, direct mail coupons and promotions, rewards programs: all help nudge customers from initial sale (action) to repeat business (loyalty). At the same time, however, at each stage of the marketing funnel, today’s customers are also influenced by customer networks. Search engine results are now one of the biggest drivers of customer awareness for any new brand or business. Customer reviews are hugely influential in the consideration stage as consumers evaluate different brands. With the Internet at their fingertips via smartphones, customers are engaging in online research for products that were once “impulse” buys—purchases driven solely by shelf placement and packaging. After purchase, companies now have many more ways—from e-mail marketing to social media—to maintain a relationship with these customers and drive them to loyalty. Today’s customer networks, however, of 10 81 Access Strategy: The access strategy for business is to be faster, be easier, be everywhere, and be always on for your customers. Where an access strategy might have once meant offering e-commerce for the first time, today it might mean providing a mobile-optimised website, more rapid delivery, or order tracking. The use of cloud computing, mobile devices, and location-based geo-targeting has brought a wave of new innovations that grant greater access to consumers and business customers alike. An access strategy may therefore take a variety of approaches, including mobile commerce, omni-channel experiences, working in the cloud, and on-demand service. - Mobile commerce: Travellers are already accustomed to using QR codes on their phone screens as tickets to board planes and trains. Example: Starwood hotel — use your smartphone to unlock room doors. With mobile payment systems and in-store targeting, customers can receive discounts, redeem coupons, purchase, and recommend, all from their small screen. - Omni-channel experiences: Increasingly, businesses are recognising that customers are looking for an integrated experience across all digital and physical touch-points. - Working in the cloud: With the shift from downloaded MP3s on iTunes to streaming music services like Spotify, consumers are quickly becoming accustomed to paying for products that reside entirely in the cloud. Likewise, businesses are shifting more and more of their work processes to the cloud with software-as-a-service (SaaS) providers like Google Apps, Salesforce, Dropbox, and Evernote. The result is much lower IT costs for businesses and greater flexibility for an increasingly mobile and collaborative workforce. - On-demand services: Increasingly, services that used to require the customer to be in a specific location at a specific time are now accessible to customers anywhere at any time. Retail banks that used to advertise the number of local ATMs they had are now touting all the banking services customers can manage via their phone. The keys to an access strategy are simplicity, convenience, ubiquity, and flexibility. Offering a product or service one step closer, easier, or faster helps your business to continuously create additional value for customers and win their loyalty. Engage Strategy: The engage strategy for business is to become a source of valued content for your customers. Businesses today face an increasingly challenging environment in seeking to communicate with their customers. Businesses must expand their approach beyond interruption advertisements — messages that customers see only because they piggyback on or interrupt content that customers are genuinely interested in, and need to adopt a different mindset. An engage strategy may take a variety approaches, including product demos, storytelling, utility, and brands as publishers. - Product demos: Content that demonstrates the value proposition of a business or product in a compelling and engaging way can be extremely effective. Example: l’Oréal & Zombie boy. - Storytelling: In other cases, brands can reach a broader audience by creating an emotionally compelling story that is less product-specific. - Utility: Content can also be about utility. Brands can effectively engage customers by providing useful content at just the right time. - Brands as publishers: In some cases, brands move beyond individual pieces of content and engage customers by becoming publishers in their own right. The key to an engage strategy is to think like a media company, focused everyday on earning the attention of your audience. of 11 81 Customise Strategy: The customise strategy for business is to make your offering adaptable to your customers’ needs. Customisation is increasingly possible due to the spread of e-commerce; automation in inventory and shipping; digitisation of media products; advances in 2D and 3D printing technologies; and the accessibility of big data on consumers’ preferences, location, and behaviours. As customers seek more choice and more personalised experiences, businesses need to find ways to meet their demands without overwhelming them with choice or unnerving them with excessively personal messaging. - Recommendation engines: Example — Netflix, measures how frequently customers bother to use the search bar to find a show to watch. - Personalised interfaces - Personalised products and services - Personalised messages and content: one of the easiest ways to customise an offering for customers is through media and messaging. The keys to a customise strategy are identifying the areas where your customers’ needs and behaviours diverge and finding the right tools to either personalise on their behalf or empower them to personalise their own experiences. Connect Strategy: The connect strategy for business is to become part of your customer’s 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. - Social listening: Customer conversations can be a tremendous source of market insight for businesses, which can listen and learn with the help of numerous tools. - Social customer service: if a business is able yo answer questions successfully, it can impress not only one customer but a network of others as well. - Joining the conversation - Asking for ideas and content - Hosting a community The keys to a connect strategy are focusing on the social media your customers use and engaging in conversations to solve problems, learn about your market, and become closer to your customers. The goal is not conversation for its own sake but value creation for your business. Collaborate Strategy: The collaborate strategy for business is to invite your customers to help build your enterprise. A collaborate strategy is distinct from a connect strategy in that the company invites customers not just to share information but also to work together in a focused way toward a shared goal or objective, using open platforms. Example — Wikipedia. - Passive contribution: Sometimes collaboration can involve as little as customers’ consent so that actions they are already taking can be used to power a collective project — Waze. - Active contribution: CNN’s iReport allows anyone to contribute photos, videos, or eyewitness reports to a crowdsourced journalism website. - Crowdfunding: A type of active contribution that has become quite widespread, crowdfunding is the process of seeking collaborators to contribute to and raise funds for a new project, product launch, or initiative. - Open competitions: Some problems cannot be easily divided among contributors. In these cases, competitions can be used to enlist a diverse group to find the best answer or solution. - Collaborative platforms: In this approach, the business creates a context for collaboration but lets the network of collaborators define the challenges to be addressed. The keys to a collaborate strategy are understanding the motivations of your contributors, giving everyone a stake allowing participants to contribute at their proper level of expertise, and offering freedom for contributors to bring their own ideas while providing enough guidance to shape an effective final outcome. of 12 81 Tool: the customer network strategy generator The Customer network strategy generator is designed to help you develop new strategic ideas for engaging and creating value with networked customers. Step 1: objective setting It is valuable to define objectives at two levels: direct objectives and higher-order objectives. - Direct objectives: these are the objectives that you are directly responsible for addressing in your project. - Higher-order objectives: It is also important to identify what overarching, or higher-order, objectives you are seeking to support through your initiative. These are objectives that you are not solely responsible for but that your project should support. Step 2: Customer selection and Focusing Start with selecting which customer segments are most relevant to your stated objectives. Then you need to focus on these segments to understand them in the context of your project’s specific objectives. That involves answering three key questions: 1. Whats is my unique objective for each customer segment? 2. What is my unique value proposition for each customer segment? 3. What are the unique barriers to success for each customer segment? Step 3: Strategy Selection You should begin by looking back at the five core customer network behaviours and the broad strategies that derive from them: access — engage — customise — connect — collaborate. Although all five strategies can be valuable for your business in the abstract, you are now looking to generate ideas for a specific project. You may decide that more than one of the five broad strategies make sense for your goals. of 15 81 3. Build Platforms, Not just Products Competition Rethink 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 (e.g., rental properties and trained service staff) and which can be managed through new kinds of external relationships. These platform businesses are part of a broad transformation of the domain of competition and the relationships between firms. In the past, Businesses created value within their own organisation and in partnership with their suppliers and sales channels. But in the digital age, the boundaries between industries are blurring, and so is the distinction between partners and competitors. Every relationship between firms today is a constantly shifting mix of competition and cooperation. But as digitisation has transformed media, HBO has found itself competing with Netflix, an asymmetric challenger that is going after the same customers with a different pricing model and a completely different means of distribution. The digital revolution is redefining competition and relationships between firms in several ways. It is supercharging the growth of platform businesses like Airbnb. For businesses like HBO, it is disinter-mediating and reshuffling channel and partner relationships. Lastly, digital technology is increasing the importance of “co-opetition,” where companies that compete directly in some arenas find it valuable to act as partners in other areas. Competition: Changes in Strategic Assumptions from the Analog to the Digital Age From To: Competition within defined industries — Competition across fluid industries Clear distinctions between partners and rivals — Blurred distinctions between partners and rivals Competition is a zero-sum game — Competitors cooperate in key areas Key assets are held inside the firm — Key assets reside in outside networks Products with unique features and benefits — Platforms with partners who exchange value A few dominant competitors per category — Winner-takes-all due to network effects Rise of the platform Airbnb is just of one of many new digitally powered businesses that act as platforms—bringing together two or more parties to create and exchange value through the business rather than trying to create all the value themselves. Platform businesses are everywhere, appearing in a wide range of industries: - Retail: Taobao, eBay, Amazon Marketplace - Media: YouTube, forbes.com - Advertising: Google, Baidu, Craigslist - Finance: PayPal, Kickstarter, Alipay - Gaming: Xbox, PlayStation - Mobile computing: iOS, Android, Xiaomi - Business software: SAP, Salesforce - Home appliances: Philips, Nest - Hospitality: Airbnb, TripAdvisor - Transportation: Uber, Didi Kuaidi - Education: Coursera, Udemy - Recruiting and job search: LinkedIn, Glassdoor - Freelance work: Upwork, Amazon Mechanical Turk - Philanthropy: Kiva, DonorsChoose of 16 81 Platforms represent a fundamental shift in how businesses relate to each other—from linear to more networked business models. Platform businesses can often be very light in assets but generate large revenues. Instead of building features and seeking to get customers to use their own products, they build ecosystems by getting customers to interact with each other. What is a platform business model? In tech circles, a platform may be any underlying software on which additional programs are built. In media industries, it may mean a distribution channel. In marketing, it may refer to any brand or product line that could be used to launch additional products. In the context of this chapter, however, we will be discussing platforms in a specific sense—as a kind of business model. Origins of platform theory 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. Their work examines pricing and competition in markets where one business serves two different types of customers that are dependent on each other. They found that the two sides often show different price sensitivity and that in efficient markets one side often subsidies the other The study of two-sided markets led, in turn, to the realisation that the same effects could be seen in markets with more than two types of customers. This led to the more general concept of multisided markets. At the same time, the theory began to shift from looking at the market dynamics, to looking at the kind of business that make them possible. It is by applying these economic theories that we can begin to understand the power and unique value of businesses like Airbnb, Uber, or Xiaomi. A definition of platforms Andrei Hagiu and Julian Wright — A platform is a business that creates value by facilitating direct interactions between two or more distinct types of customers. Three key points: - Distinct types of customers: To be a platform, the business model must serve two or more distinct sides, or types, of customers. The unique dynamics of platforms arise because they bring together different parties that each play different roles and contribute and receive different kinds of value. - Direct interaction: Platforms must enable these two or more sides to interact directly—that is, with a degree of independence. In a platform such as Airbnb or eBay, the two parties are free to create their own profiles, set and negotiate pricing, and decide how they want to present their services or products. - Facilitating: Even though the interactions are not dictated by the platform business, they must take place through it and be facilitated by it. Our definition does not include a franchise business like McDonald’s or H&R Block. Although franchisors do, in some sense, enable commerce between the franchisees and end consumers, that commerce does not flow through the original corporation, and only one party is in any way affiliated with the original franchisor company. Platforms and the Customers They Bring Together Platform — Distinct customers, interacting directly, facilitated by the platform Airbnb — Hosts Renters Uber — Freelance drivers Riders DonorsChoose — Schoolteachers seeking grants Donors PayPal — Account holders Merchants Banks YouTube — Video viewers Video creators Advertisers Google search — Search engine users Website creators Search advertisers Forbes.com — Independent writers (not employees) Readers Advertisers of 17 81 Android operating system — Phone and tablet users Hardware manufacturers App developers In- app advertisers Salesforce.com — Software users App developers creating additional integrated services Four types of platforms - Exchanges: These types of platforms bring together two distinct groups of customers for a direct value exchange, with each group attracted by the number and quality from the other side — eBay & Airbnb. - Transaction systems: These platforms act as an intermediary between different parties to facilitate payments and financial transactions — PayPal & Apple Pay. - Advertising-supported media: In this case, the platform typically plays an additional role of creating (or sourcing) media content that is attractive to consumers - Hardware/software standards: These platforms provide a uniform standard for the design of subsequent products to enable their interoperability and benefit the ultimate consumer. But not every standards competition ends with a single winner. Today’s smartphone market is roughly divided between Apple’s iOS and Google’s Android. This list is not exclusive; new platform businesses could well arise that don’t quite fit any of these four types. But these categories provide a useful way of thinking about the differences among current platform businesses. Direct and indirect network effects One of the key features of platforms is that their value increases as more customers use them. This phenomenon is commonly called network effects, but there are actually two different kinds of network effects that can impact the growth of a business. Direct network effects (or “same-side” network effects) occur when the increasing number of customers or users of a product drives an increase in value or utility for that same type of user. Direct network effects occur in platforms such as Facebook, which is a platform because (unlike a fax machine) it brings together not just users but advertisers, publishers, and app developers as well. For platforms, the more common type of network effect is indirect network effects (or “cross-side” network effects). These occur when an increase in the number and quality of customers on one side of the platform drives increasing value for customers on the other side of the platform. Are indirect network effects reciprocal? Not always. In advertising supported media, the indirect network effects usually run only one way: as the number of readers increases for a newspaper, its value to advertisers increases as well, but increasing the number of ads in each issue does not directly increase the value for readers. For media companies, that imbalance is critical in determining pricing for both sides. But for platforms other than ad-supported media, the indirect network effects usually do work both ways. Airbnb renters like to see more hosts to choose from, and hosts want to see more potential renters on the site. The platform spectrum Any business today faces a strategic choice of whether to pursue a platform model or a more traditional business model. But the choice is not a simple “all or nothing” decision. The right business model may be somewhere on a spectrum from platform to non platform. Consider the second defining quality of platforms: they allow direct and independent interaction between the parties they bring together. In practice, this independence may happen by degrees. But whereas RelayRides lets riders offer their own price, Uber imposes standardisation around rates. Some companies successfully employ a mix of platform and non platform business models, even within the same business unit. amazon.com started as a pure e-commerce business, buying and selling products just like a physical retailer. In some cases, both parts of the business may be significant: in 2014, Amazon reported that 42 percent of its units sold were from its Marketplace partners. In other cases, one business model may serve only particular customers. Evernote of 20 81 categories until they vanish (This is why Facebook bought Instagram and WhatsApp and tried to buy Snapchat. Economic efficiency 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, skills) that otherwise could not be effectively used. The result is a profusion of platforms that bring together lone actors and empower them to contribute economically. The individual actor would never have the resources to find the right matching project, need, or customer. But by reducing the transaction costs and aggregating a community of partners, platforms can unleash untapped economic capacity. This phenomenon is often mislabeled the “sharing economy.” In actual fact, very few platforms have been established to share assets or labor free of charge, and those that do are all small. The popular platforms that are commonly cited as evidence of the sharing economy are, in fact, better described as a “rental economy”, a “resell economy”, or a “freelance economy”. Competition between platforms Platforms don’t compete just with traditional businesses. They also compete against other platforms. But how do platforms compete with each other the same category? Platforms tend to compete on five areas of value. - Network-added value: Due to network effects, the platform with the most current customers is often the one most likely to draw future customers. The quality of goods and services customers offer is often important as well. The data provided by one group of customers can also increase the ability of a platform to attract customers of another group. - Platform-added value: In some cases, the value provided by the various types of customers is not enough to make a platform competitive. The platform itself has to develop unique features and benefits to attract customers. - Open standards: Another important way that a platform competes is by offering more-open and easier-to-use standards than its competitors. The rapid growth of platforms like YouTube is aided in large part by the self-service Web or app interfaces they offer, which make it easy for anyone to upload content or join a platform’s network - Interaction tools: Once a platform has attracted customers and made it easy for them to come on board, it can compete by providing them with the best tools to find and interact with the right partners. - Trust enablers: The last way that platforms compete to attract customers is by offering better methods to enable trust among the parties they bring together. These can include identification systems, such as social log-ins through Facebook, Google, Twitter, or LinkedIn. Trust can also be enabled by financial safeguards, such as insurance to cover losses incurred by customers or mediation of billing disputes by transaction platforms like PayPal. Tool: the platform business model map The Platform Business Model Map is an analytic and visualisation tool designed to identify all the critical parties in a platform and analyse 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 (customers that provide revenue to the platform) - Rectangle: The sweeteners (customers that provide no revenue but help to attract other valuable customers) - Spikes: The number of other customer types that are attracted (e.g., publishers have one spike because they attract only users, but users have four spikes because they attract publishers, advertisers, app developers, and more users like themselves) of 21 81 - 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 (e.g., the platform’s share of revenues). - Value not in parentheses is passed through the platform and is provided to other customers. The business model is a mix of two of our four types of platforms: ad-supported media and software standard (for the app developers). The platform is fuelled by cross-side network effects (different types of customers are attracted to each other) and also by same-side network effects (users are attracted by more of their own kind). If you are launching your own platform, you can use the Platform Business Model Map to answer these important questions: - Whom do you need to bring on board to make your platform work? - How will you monetise? - Who are your most important customers? (These are likely both the primary payer and the linchpin.) - Is your business model in balance? Does each party receive enough value to attract its participation? Does each party contribute enough value to justify its inclusion? Analysing another firm’s platform will help you to answer these important questions: - Who are the platform’s key customers? - What is the role, or value contribution, of each customer type? - What draws each party to the platform? - How does the platform monetise? - What value do you provide if you are a customer of the platform? of 22 81 - How could you extract or leverage more value from the platform? The shifting landscape of competition Platforms offer a fundamentally different model for how businesses relate to each other—not as suppliers, distributors, and rivals but as networked partners. In a traditional view, we think of competition as happening between rival businesses of the same kind in the same industry. We think of collaboration as occurring between a business and the firms that serve as its sales channels and suppliers. But in the digital era, any relationship between two businesses is a shifting mix of competition and cooperation. This is because digital technologies are contributing to three major shifts in the competitive landscape. First, competition with rivals is changing, becoming less of a direct contest and zero-sum game. Second, industry definitions and boundaries are becoming more fluid, leading to conflict between more asymmetrical competitors. Finally, the relationships of businesses to their channel and supply chain partners are being regularly reshuffled and reorganised. Co-opetition The aim of business is to win to the be the best and to beat the competition. In the business as contest view, competition is a zero-sum game: for one side to win, the other side must lose. Michael Porter, perhaps the most famous management thinker on competition, criticizes this view of “competition to be the best” and warns that it is a path to mediocre performance. A zero-sum view of competition sets up a race to the bottom that no one can win. Strategy calls for even direct competitors to find ways to work together cooperatively in certain arenas. 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. The authors apply game theory to business relationships to show why the right strategy for rival businesses is often a mix of competition and cooperation on different fronts. Digital platforms are increasingly a factor in driving strategic cooperation among business rivals. The reason for all this cooperation is clear: the power of platforms. The power of Google in search, Amazon in media distribution, Facebook in social networks, and Apple and Android in mobile operating systems means that none of these businesses can afford to cut off their competitors from their own customers. Fluid industries and asymmetric competitors Much of our thinking about competition takes the industry as the unit of analysis. 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 — BMW and Mercedes-Benz Symmetric competitors also deliver that value with similar business models. One carmaker may be larger or smaller, with different economies of scale or other factors, but the broad model is the same—manufacturing plants, dealerships, pricing for sale and lease. Asymmetric competitors are quite different. They offer similar value propositions to customers, but their business models are not the same. Disintermediation and intermediation One of the biggest impacts of digital technologies has been on the relationships of businesses to the partners in their supply chain—the companies that supply critical inputs for the primary businesses’ own products or that create additional value and distribute or sell those products to their eventual consumers. 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. The Internet is widely known to have been a powerful force for of 25 81 Applying the competitive value train You can use the tool to predict and assess possible moves by partners, competitors, and new entrants in your value train. You can also use it to analyse possible competitive moves that you are considering. It is particularly useful for understanding the dynamics of disintermediation and intermediation as well as any shifts in the relationships between your firm and its sales channels or its suppliers or both. This can include a business leapfrogging over its current partners—for example, launching a direct-to-consumer business to become its own distributor. Organisational challenges of competition As businesses adapt to the growing importance of platforms and the shifting landscape of competition and cooperation between firms, many of the challenges that arise are not just strategic challenges but also organisational ones. Shifting roles midstream Reshuffling the roles and relationships of a company’s value train can be difficult for an enterprise that has a long-standing business model and relationships with both upstream suppliers and downstream 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. Shifting channel strategies is particularly difficult for a business because of its vested interest in existing channels and the risk of cannibalising its current sales in pursuit of a new opportunity. The trade-offs are quite real. When e-commerce first offered the promise of selling directly to consumers, many brands embarked on plans to set up their own online stores. Most failed due to lack of sufficient demand, lack of technical capability, or both. When companies do launch a direct-to-consumer channel in competition with their primary sales channel, they need to establish clear boundaries. These may be geographic boundaries: some insurance companies that rely on sales agents have initiated their first direct-to-consumer sales in geographic markets where they are not well established. Warfare mentality Both co-opetition and the search for leverage in value trains require leaders to look at competition as more than a zero-sum contest. In organisations where the “competition is war” metaphor and mindset run deep, cooperating with rivals and competing with partners can pose a cultural challenge. There are certainly times for fierce competition with rivals. But to succeed in the dynamic ecosystem of business today, leaders need to know when to fight and when to make peace. Openness 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. This requires a hands-off approach that may not be possible for some leaders or some company cultures. of 26 81 Conclusion To operate successfully in the digital age, businesses must have a dynamic understanding of how firms compete and cooperate. Rather than a simplistic view of bitter enemies and unalloyed partnerships, businesses need to see all their inter-firm relationships as a shifting mix of competition and cooperation. They must understand the value of cooperating with direct rivals, the threat of asymmetric competitors who look nothing like them, the importance of leverage within their relationships with partner businesses, and the power of digitally enabled platform business models to bring together different parties and drive new value creation. Relationships with other firms, in short, have become just as networked and interconnected as relationships with customers. In both relationships, the increasing digitisation of interactions is yielding another product as well: data. Every interaction with customers or with businesses is producing streams of information that can now be recorded, captured, and analysed in ways that were impossible only a short while ago. Understanding how to utilise this data strategically, as a source of new value for businesses, is the next important domain of digital transformation.
 of 27 81 4. Turn Data into Assets — Data Data The role of data for businesses is changing dramatically today. Many companies that have used data as a specific part of their operations for years are now discovering a data revolution: data is coming from new sources, being applied to new problems, and becoming a key driver of innovation. One innovator is The Weather Company (TWC). Data has always been part of that business model: every day vast quantities of weather data need to be captured, analysed, the same data that the firm collects, manages, and analyses constitutes a key strategic asset and, increasingly, a source of new innovation and value creation. Weather has a powerful impact on a wide range of businesses. By one estimate, up to one-third of the U.S. economy is shaped by variations in weather. The company also works directly with brand advertisers—in categories like allergy medication, fleece jackets, and snow tires—to predict the best time for them to spend on ad placements. With digital advertisements (inserted on websites or in apps like TWC’s own), brands now have the opportunity to adjust and target their message on the fly, choosing which image to show specific viewers based on the weather where they are standing. TWC is even using its data to create new products and services for industries like the insurance sector. The company is even collaborating with some of its most avid customers to grow and improve its data asset. Every day TWC crowdsources data from a community of 25,000 self-described “weather junkies” who pay to subscribe to a service called The Weather Underground. TWC has evolved from a media company that simply produces data as part of running its core operations to a company that is treating data as a source of innovation, new revenue, and strategic advantage. Rethink data 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. Mainly used for measuring and managing business processes and assisting in forecasting and long-term planning. Data was expensive to produce, to store. Today, generating data is often the easiest part. But for data to become a real source of value, businesses need to change the way they think about data. They need to treat it as a key strategic asset. of 30 81 New tools to wrestle unstructured data The second trend shaping big data is the rise of new technological capabilities for handling and making sense of all this unstructured data. A range of technological developments is expanding our abilities to use the unstructured data that technology is producing. The continuing exponential growth of computer processing power is a big factor in our improved ability to use data. ENIAC, the first modern computer, was built in 1946 and filled a room of the size of a small gymnasium. By 1983, Texas Instruments pocket calculator had more processing power than ENIAC. Recent technologies have further enabled data processing on a large scale with acceptable costs. In- memory computing can accelerate analytics to the kind of real-time computing that allows digital advertising to select the ad seen by each visitor to a webpage. Hadoop is an open-source software framework that enables distributed parallel processing of huge amounts of data across multiple servers in different locations. Other tools focus less on increasing power and more on making sense out of the chaos of unstructured data. Perhaps the biggest advances in managing unstructured data have come from new developments in “cognitive” computing. Natural language processing, for example, can interpret normal human language, whether from spoken commands, social media conversations, or books or articles, without adaptation. Another key development is machine learning — As computers are modelled around neural networks, they go beyond just spotting patterns in unstructured data: they receive feedback from their environment or human trainers (indicating which conclusions were wrong and which were correct) and reprogram themselves over time. System like IBM’s Watson, which can read vast amounts of written language and develop ever more accurate inferences by using feedback and coaching from human experts. Watson and similar technologies will be at the forefront of the next wave of big- data analytics—informing everything from customer service, to fraud detection, to advertising media planning. Big data on tap from the cloud An additional trend is shaping the impact of big data: a revolution in the storage and accessibility of both data and data processing. In the old data paradigm, for a business to manage data, it needed to invest in owned infrastructure to collect and hold all of the data as well as any tools to analyse it. Today, businesses no longer need to store their own data, and even small businesses are increasingly able to access the leading tools for using unstructured data. The reason is the rise of cloud computing. All our device needs is a steady connection so that it can send our voice to a remote server with all the power necessary to process that unstructured data and respond in real time. Cloud computing has profound implications for scalability and small business. Services like Watson are available “on tap” to businesses, just like cloud-based storage and customer databases are for small businesses. This means that big data is not the exclusive terrain of the world-class companies with huge IT departments. Any business can tap into best-in-class analytics tools today—from cloud providers like SAP and IBM—paying only for the data and the processing it uses. Three myths of big data Myth 1: the algorithm will figure it out Making sense of big data still requires a lot of involvement by skilled human analysts. There are several reasons for this. The quality and accuracy of the data are critical. How was the data collected? Is there a margin of error? Is it truly a representative sample? Are different data sets in the same format so they can be accurately compared? Much data wrangling is still done by human analysts, as these issues are not yet fully automated by software. Biases can also exist in the algorithms used to look at the data, based on the assumptions of those who program them. Most importantly, you need managers to ask the right questions of your data. of 31 81 Myth 2: Correlation is all that matters Spotting a pattern is not (always) enough. The belief is that underlying patterns across data sets are a truth unto themselves that does not need to rely on foggy human ideas of cause and effect. This is simply not true. It is critically important that managers understand the difference between simple correlation and causation—and know when this difference matters and when it doesn’t. A simple rule of thumb: if you are only making predictions, data correlation is sufficient. But if you are looking to change the precondition, you need to know there is causation as well. Myth 3: All the good data is big data It would be a mistake to conflate big data with data strategy. In many cases, companies can build valuable data assets and apply them to strategic ends without delving into the messy world of big data. Data does not always need to be “big” (i.e., unstructured) in order to be useful to a business. Powerful insights can be derived from the analysis and application of traditional, more structured data such as customer clickstream behaviour. The point of your data strategy should be to generate value for your customers and business. Sometimes that will involve big data, and sometimes it won’t. Where to find the data you need Important sources of data from outside your organisation include customer data exchanges, lead users, supply chain partners, public data sets, and purchase or exchange agreements. Customer value data exchange One of the best ways to generate additional data is to invite customers to contribute data as part of interacting with your business or in direct exchange for value you offer them. What makes consumers willing to share their information with businesses? 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. Lead user participation Lead users (a term coined by Eric von Hippel) are your most active, avid, or involved customers. Their greater needs lead them to have greater interest in interacting with your products or business, and they can often be a unique and powerful source of data. By engaging lead users, brands can solicit input and feedback from much more selective and important communities. Supply chain partners Business partners can be crucial sources of additional data for building your data asset. Power, leverage, and levels of trust can greatly influence who shares data with whom in many industries. Increasingly, data partnerships will be a key element of how businesses negotiate terms of working together. Public data sets Another important source of new data is publicly accessible data sets. Some of these are in online public forums. Many social media platforms, like Twitter, are easily searchable for real-time data. In addition, governments are increasingly providing public access to large data sets in machine- readable format. The U.S. government’s census data, for example, has been in huge demand since being made available. of 32 81 Purchase or exchange agreements Firms should seek out the many reputable services that enable anonymised data comparisons. Anonymised data lets a company learn things like the conversion rate of offers. The company’s data shows which customers got the offer, the retailer’s data shows who made a purchase, and the third-party service measures the conversion rate without revealing customer identities. Sometimes data can be received through an exchange or donation. During the 2014 World Cup, Waze shared anonymous driver data with city governments in Brazil to help them identify and respond more quickly to traffic buildups and road hazards. By receiving real-time data from highway sensors and information on construction projects and city events, Waze is improving its own data asset. There are many more sources of data available today. Turning customer data into business value: Four templates As organisations gather more data and develop it into powerful assets, the next challenge is to continuously apply these assets to create new value for themselves. We’ve seen examples of how product or service data provides value by enabling a business’s core service to customers. If we look at customer data, we can find recurring patterns of best practices used to add value across differing industries and organisations. Four templates for creating value from customer data: insights: revealing the invisible; targeting: narrowing the field; personalisation: tailoring to fit; and context: providing a reference frame. Insights: Revealing the invisible The first template for value creation is insights. By revealing previously invisible relationships, patterns, and influences, customer data can provide immense value to businesses. Data can provide insights into customer psychology. Data can reveal patterns in customer behaviour. place?). Data can also be used to measure the impact of specific actions on customers’ psychology and Behaviour. Today, many businesses have access to large quantities of customer data in the form of online conversations about their products and brands. Targeting: Narrowing the field The second template for data value creation is targeting. By narrowing the field of possible audiences and identifying who is most relevant to a business, customer data can help drive greater results from every interaction with customers. In the past, customers were often divided into a few broad segments for targeting based on factors like age, zip code, and product use. Today, advanced segmentation schemes can be based on much more diverse customer data and can produce dozens or even hundreds of micro-categories. Using data for targeting can even have a powerful impact in a field like nonprofit health care, thanks to a practice known as “hot spotting.” Dr. Jeffrey Brenner, a family physician in Camden, New Jersey, studied medical billing records from hospitals in his hometown and discovered that 1 percent of the town’s population was responsible for 30 percent of its health-care costs. Personalisation: Tailoring to fit Once businesses are targeting micro-segments of customers, the next opportunity is to treat them each differently, in ways that are most relevant and valuable to them. This is the third template for creating value: personalisation. By tailoring their messaging, offers, pricing, services, and products to fit the needs of each customer, businesses can increase the value they deliver. British Airways has launched a service personalisation program known internally as Know Me. Its goal is to bring together diverse data to create a “single customer view” that will help airline staff to make of 35 81 After developing these strategic ideas, you will need to test the assumptions behind each. Can you, in fact, get the data? Organisational challenges of data Mike Weaver — director of data strategy for Coca-Cola company, “We must understand consumers’ passions, preferences, and behaviours so we can market to them as individuals”. the biggest challenges, Weaver told me, were organisational, not technical. He compared the process of shifting business practices at “the world’s greatest brand/mass media company” to turning an aircraft carrier at sea. But before installing all the data centres and analytics models that would allow for real-time targeting of customers, the company first had to plan out the changes to its business processes. Before a brand can take advantage of its ability to differentiate customer segments in real time and deliver targeted messaging to them, it first needs to learn how to create messages in a very different way. Embedding data skill sets The first challenge in the transition to a more data-driven organisation is finding people with the right skill sets. This starts with data scientists. Depending on the organisation, it may be using an outside partner for analytics, hiring a single analyst, or building an entire team. 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. Part of this is educating the workforce about the ways data can be applied in their business. Another part must be developing a company culture that embraces data and analytical thinking. Lastly, the company may need someone who can bridge two worlds: the world of quantitative analysts and that of business decision makers. Bridging silos Sometimes the biggest challenges to sharing data are within the organisation. At Coca-Cola, Weaver found that website analytics data was sitting in one database while data on consumer purchase behaviour from loyalty programs was being kept somewhere else entirely. In order to create a complete picture of the customer, he first had to bring all the data together in a unified way. In large organisations operating in different locations, another important question is whether or not to centralise data analytics. This is partly a matter of where the data is warehoused but also where the data scientists are. Should each business unit have its own analytics team so it is closer to local decision making? As large organisations mature in terms of their data capability, they seem to be centralising analytics while striving to raise the data savvy of managers in each business unit. Sharing data with partners Data sharing is critical not only within an organisation; it is becoming a key element of negotiations with business partners. Contracts and deals of all kinds are no longer just about who pays what to whom but what data will be shared as well. As data becomes more essential to business strategy, data sharing will become a key element of every important business partnership with suppliers, distributors, media channels, and more. Cybersecurity, privacy, and consumer attitudes As businesses gather and utilise 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 centre for senior leadership now. When Target suffered a huge data breach in 2013, with 40 million customer credit cards stolen, it was not just an IT problem but also a brand reputation of 36 81 issue. Part of data strategy is developing a legal, risk management, and security plan. Rather than letting fear of risk postpone action (and likely not really reduce risks), leaders need to establish assessment, responsibility, and planning, with appropriate outside partners to support them. The risks of data theft are unavoidable, but they can be reduced if risk reduction is a leadership priority. Consumer attitudes are also crucial to data strategy. Beyond the threats of identity theft and cybercriminals, many consumers are more generally concerned about privacy and the increasing amount of information businesses gather about them. Much of the data about customers is collected in ways that the public is only vaguely aware of, at best. With rising concerns about ownership of personal data, it is increasingly important that any data strategy be based on a transparent value exchange with the customer: an exchange in which the customer knows that data is being collected and sees the benefits they are receiving in return. This is the foundation of loyalty programs with points and rewards. Conclusion: The strategic challenge for business is to develop the clear vision and the growing capability needed to put data to work in the service of innovation and value creation. By treating data as a key intangible asset to build over time, every business can develop a data strategy that informs critical decision making and generates new value for business and customer alike. Data allows us to continually experiment, learn, and test our ideas. This means data can do more than power products, optimise processes, and deliver more-relevant customer interactions; it can also help change the way organisations learn and innovate. This different kind of learning— through constant experimentation—is at the heart of a profoundly different approach to innovation.
 of 37 81 5. Innovate by Rapid Experimentation Innovation We can define innovation as any change to a business product, service, or process that adds value. This change can range from an incremental improvement to the creation of something totally new and unprecedented. For Google, an innovation may be launching a completely new product such as Gmail, Android phones, Google Maps, or its Chromebook laptop line. But innovation at Google also includes the continuous process of refining, adding and subtracting features, and evolving the user interface and experience → the company is constantly experimenting, testing each of its new ideas, measuring customer response, and iterating on what it learns. The fourth domain of digital transformation is innovation: the process by which new ideas are developed, tested, and brought to the market by businesses. Traditionally, innovation was singularly focused on the finished product. Testing ideas was relatively difficult and expensive, so decisions and early ideas were based on the analysis, intuition, and seniority of managers involved in the project. Actual market feedback tended to come very late in the process (sometimes after public release), so avoiding a marked failure was an overriding concern. In the digital age, enterprises need to innovate in a radically different fashion, based on rapid experimentation and continuous learning. Rather than concentrating primarily on a finished product, this approach focuses on identifying the right problem and then developing, testing, and learn- ing from multiple possible solutions. Before, during, and even after launch of a product, assumptions are tested and decisions are made based on validation by customer and market responses. Digital technologies make it easier and faster to test ideas, this new approach to innovation is essential to bringing new ideas to market faster and with less cost, less risk, and greater organizational learning. → digital technologies are making experimentation both more possible and more necessary of 40 81 The type of experiment you use may be shaped by the area of your business in which you are innovating. - For innovations intending to improve your existing core business, you are more likely to rely on convergent experiments. - For innovations intending to develop new business areas and generate substantially new products, services, or processes, you are more likely to rely on divergent experiments. The two types of experimentation may also happen at different stages within the same innovation project. Why Digital Is Impacting Both Digital technologies are making rapid experimentation both more possible and more necessary than ever before. They are offering new tools for experimentation and increasing the speed at which companies must innovate to keep up with a rapidly changing environment. - Convergent experimentation is becoming increasingly powerful and affordable due to new technologies. As companies in every industry develop digital products and services for customers (and processes for employees and partners), these digital innovations are inherently much easier to test in real time and at low cost. At the same time, new software tools are becoming available that allow even small firms with limited budgets to easily conduct A/B tests, run multivariable analyses on the results, and determine the optimal sample size for an experiment. - Divergent experimentation is gaining new tools from digital technology as well, particularly in the form of new ways to prototype ideas cheaply and rapidly to show customers. For new physical product offerings, both 3D printing and computer simulations decrease the time and cost involved in creating prototypes. For digital products and services, newer programming languages and repurposable code make it easier to develop “good enough” prototypes to test with customers. → Fortunately, thanks to digital tools, all companies are able to run more experiments—both convergent and divergent—cheaply and quickly and accelerate the pace of innovation. As technological change continues to impact every industry, experimentation will become more important than ever as a means of reducing uncertainty and accelerating innovation. Seven Principles of Experimentation The seven principles apply for any business experiment, whether convergent or divergent: 1. Learn Early 2. Be Fast and Iterate 3. Fall in Love with the Problem, Not the Solution 4. Get Credible Feedback 5. Measure What Matters Now 6. Test Your Assumptions 7. Fail Smart of 41 81 Learn Early The first principle is to start experimenting from the very beginning of your innovation efforts so that you can learn as early as possible in the process. Learning in the early stages of your project avoids heavy financial losses In the process of rapid experimentation customers are brought in much earlier to provide the feedback that helps the company decide which ideas are even worth pursuing. With much earlier learning, the failure rate for the company’s product ideas did not decrease, but the cost of failure dropped dramatically. In any innovation effort, you are dealing with uncertainty and inevitably will face a significant failure rate among your new ideas. With experimentation, the ideas that don’t work should fail early in the development process, long before your product gets to the public and while the cost of changing course is much lower. Be Fast and Iterate The second key principle of experimentation is speed. Increasing the speed of experimentation may require infrastructure, too. Fall in Love with the Problem, Not the Solution First, this keeps you focused on the customer and their needs. By forcing yourself to describe the customer’s problem first (rather than the ingenious solution you are developing), you take an important step to ensure the innovation process is focused on customer value. Second, focusing on the problem prods you to consider more than one possible solution. If your goal is the solution itself, there’s a temptation to stop generating new ideas when you hit on one idea that appears promising to your team and to move on prematurely to building it The third is that you inevitably become attached emotionally to a creative solution Get Credible Feedback Once you have solutions in mind, it is essential that you gather credible feedback on your ideas. That credibility starts with the people you speak to. They need to be real customers or potential customers In a convergent experiment, as we’ve seen, the feedback is based on the actual product, service, or experience you would ultimately provide. In a divergent experiment, the goal is to use prototypes. This allows you to save the expense of building an offering you have not yet designed but gives the customer enough stimulus to respond to. → can’t use focus groups to get credible feedback on a product or service that has never been in the market. of 42 81 Measure What Matters Now It is important to take measurements in any experiment. But as interactions become more digitised, the number of things that can be measured is growing. One solution is to try to identify the most important single metric for the success of your innovation. But the one metric that matters most will change over time as a start-up moves from the early stages of customer definition to solution testing and eventually to revenue and scaling a business. The same is true when innovating within an existing enterprise: the one metric that matters most will change over time. Although it is important to know the most critical metric for the cur- rent stage of your innovation, you should gather data on other metrics as well. This data may help explain the changes you see in your key metric. Test Your Assumptions Another key principle of experimentation is to test your assumptions. Although this is essential to eliminating risk in any new venture, it is especially important for innovations that take your business into unknown territory. For an established company, used to operating in its known territory, it is easy to overlook the step of testing your assumptions when you are planning an innovation. In their book Discovery- Driven Growth, Rita McGrath and Ian MacMillan explain how successful firms take on undue risk by not identifying the underlying assumptions of their new ventures. The authors suggest methods to identify such assumptions and test them, and they tie this process to development milestones on any new project. This mindset is essential to good experiment-driven innovation. Fail Smart 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 actually an essential part of experimentation. It is needed to eliminate bad options quickly and to build on the learning that testing generates. 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. 
 
 of 45 81 Step 7: Share Learning Once you complete your analysis, it is essential to capture and share the learning of your experiment. If you are doing a battery of experiments on the same variables, this process can happen at the end rather than after each step. But it is critical to both document what you learned and communicate your findings to others in your organisation who could benefit (and could avoid any of the same mistakes). Tool: The Divergent Experimental Method 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 organisation. Innovation projects using divergent experimentation tend to be highly iterative and may span weeks or months. You can see the ten-step Divergent Experimental Method whose steps fall into three stages: preparation, iteration (steps that repeat several times), and action. of 46 81 Step 1: Define the Problem The first step of a divergent experiment is to define the problem you are seeking to solve. The problem should be rooted in an observed customer need or market opportunity and be a challenge that your organisation is particularly well suited to solve. The advantage of defining your innovation in terms of a problem is that it forces you to take the customer’s point of view. Your innovation should always focus on delivering value to the customer. The problem definition may include a quantified goal, but that goal should be both challenging and broad → the challenge is not technical but describes the benefit or experience from the customer’s point of view. Step 2: Set Limits The second step is to set limits for your innovation process. Because diver- gent experimentation is iterative and because we are naturally inclined to defer or delay before admitting failure, it is easy for your innovation project to keep running even when the prospects for success are dim. It is therefore essential to set limits at the outset. Any divergent experiment should begin with three kinds of limits defined: - Time limit: Finite time should be allotted for the project and its key approval stages. Many companies, including Mondelez, AT&T, Intuit, and Amazon, use three months as a limit for iterative project development before a crucial decision is made on whether to proceed. - Money limit: Budgeting for innovation projects is often best done in approval stages. As assumptions are tested and project risks are reduced, additional budget can be released. - Scope limit: Companies should define up-front what they are not seeking to accomplish. This provides helpful boundaries for even the most wide-open experiments. Step 3: Pick Your People The last step of the preparation phase is to pick which people will work on your innovation experiment. The first question is the size of your team. As a general maxim, an innovation team should be as small as possible—but no smaller. (generally 5 people) In addition to size, diversity of team composition is crucial. This should include diverse skill sets that relate to the nature of your project. You should also strive to include participants with diverse biases and backgrounds. It is valuable to change the innovation team over time rather than keeping the same group for every project. You may want to introduce an element of competition as well, with multiple small teams competing (at least in the initial stages) to develop the best solution to a common challenge. of 47 81 Step 4: Observe The iterative development of ideas for your innovation begins with observation. Observation informs and provides the insights you need to solve the next stage of the problem you are working on. The goal of observation is to both deepen your understanding of the problem itself and broaden the range of ideas you bring to bear in finding a solution. You should focus first on observing the customer’s context—to better understand the problem you’re trying to solve. Learn everything you can about the customer, the nature of the problem, and the context into which your solution needs to fit. In addition, look for ideas from further afield. Look at other markets (how other customers deal with the same issue) and other industries (benchmarking from beyond direct competitors in your industry). You can also look to ideas generated in previous innovation efforts. Step 5: Generate More than One Solution The next step is to generate ideas to solve the defined problem. This is the stage where your own intuition plays its proper role in innovation: to help create new ideas and possible solutions. The only strict rule here does not cover how you generate ideas; rather, it requires that you generate more than one idea. Rather, your goal in ideation should always be to generate multiple viable ideas. Step 6: Build an MVP In this step, you need to translate your ideas into prototypes. In the start- up world, the focus is on a minimum viable product, often an early website or app launched publicly so customers can start using it, responding to it, and identifying bugs or missing features. For an established enterprise, where it may not be appropriate to share early design ideas in public, I prefer the term minimum viable prototype. Either one can be abbreviated as MVP. The most important point is that your MVP should absolutely not be a full-blown or finished product. The most common way to inflate innovation budgets is to overdevelop prototypes (through long and expensive technical development) before validating them with real customers. → the goals of an MVP: minimal cost + maximum learning Step 7: Field Test After building a minimum viable prototype of your idea, the next step is to actually test it. This is where market validation takes place, as you get feedback on your MVP and test your assumptions. In choosing how and where to test, you should aim for as natural an environment as possible— that is, as close as is feasible to the actual context where the ultimate solution will be used. You should also test your prototype with an audience as similar as possible to the customers you expect will be using the final version of 50 81 Requirements for successfully scaling up an innovation in each quadrant. 
 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. That is, your first public release will be a minimum viable product offered to a limited set of customers. The relative ease of this path is one upside to being a little-known start-up: you can iterate and learn with real customers without much public scrutiny. MVP Launch In this quadrant, your business is forced to iterate very quickly after launching your innovation because you are not able to effectively limit the scope of the launch. One reason this path may be necessary, even for a digital service, is that the business has to rely on network effects. Polished Rollout 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. It therefore needs to be much more polished at the point of release. Still, you are able to take advantage of rolling your innovation out in stages by validating your initial findings and testing how it is received by different customers or in different markets. Retail design typically follows this path. of 51 81 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. This creates maximum pressure for your company to polish and carefully test an innovation before its public release. This is the path for innovations like new automobiles, pharmaceuticals, and hardware products. In cases where a physical product can be updated in a year or less (e.g., some consumer electronics), you may want to aim for a streamlined first product, withholding some of your eventual features until the first edition is on the market. (Apple) Organisational Challenges of Innovation Putting rapid experimentation at the heart of the innovation process is not easy for many large or traditional organisations. Rethinking innovation requires significant organisational changes, beginning with how decisions get made. Building a Test-and-Learn Culture For a business to embrace experimentation requires the recognition they can fail. Companies can compensate for the fallibility of management’s own judgment if they install in their employees a culture of testing and learning about every aspect of their business. Involving Everyone Some firms do find it useful to sequester innovation teams, isolating them at least partially from the politics and priorities of those maintaining the current business. This may make sense if you are trying to pursue innovation in an area outside your current business or ventures that may cannibalise or challenge parts of your existing business model. Other firms seek to engage the entire organisation, but they do so during innovation “sprints” or “boot camps.” Typically, these are open to all employees, with an innovation challenge, a crowdsourced vetting process for picking the ideas to receive funding, team coaching on innovation methods, and a limited time frame within which final results are announced. The last, and likely hardest, approach is to try to train everyone in the organisation to adopt experimental methods year-round in their daily work. Planning to Fail and Celebrating It The hardest challenge for many organisations as they learn to embrace innovation by experimentation is accepting, planning for, and even celebrating failure. Learning through failures is the process that takes us to the goal of great innovation. of 52 81 But an organisational culture that shuns failure poses three severe risks to any innovation efforts: - Incremental innovation efforts: The first big risk is risk aversion. When those involved in failed projects are punished or stigmatised, employees tasked with innovation will shy away from any unknowns, including big growth opportunities for the firm - Loss of learning: When failures are punished, there is no incentive to bring failures to light. Even innovation teams that find successful solutions are unlikely to reveal the early blunders and blind alleys they stumbled through along the way. If teams aren’t comfortable sharing their mistakes, then the learning at the heart of experimentation will never be captured by the organisation - Throwing good money after bad: When failures are punished, any team with a budget will find a way to justify their underperforming initiative adjusting their future projections and endlessly postponing any decision to shut it down. To avoid these three hazards, businesses need to plan to fail and celebrate smart failure. Planning to fail simply means developing a process for evaluating every innovation initiative on a predefined schedule, against predetermined criteria, and with incentives to encourage employees to declare their own project fit for termination. Failure planning should be structured so that shutting down one project is directly tied to freeing up resources (indeed, reallocating the same people) to work on new opportunities for innovation. Conclusion To innovate in the digital age, businesses must learn to experiment continuously and effectively. By continuously iterating and testing new ideas and by getting real data and real customer feedback, even the largest enterprises can become as agile as a lean start-up. Only then will they be able to innovate in a way that is fast enough, cheap enough, and smart enough to create new value for customers in a constantly changing world. However, launching new products and new ventures and refining existing ones are not the end of the story if businesses are to innovate and evolve. 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. Rather than waiting until a profound change is essential to survival, or even until it is too late to change, businesses in the digital age need to develop a forward-looking attitude. The new imperative is for businesses to adapt their value to customers when they can rather than when they must. of 55 81 New Value + New Customers In some cases, a third route out of a shrinking market may be possible with both new value and new customers. Usually, this may come when a dramatic shift in the value proposition succeeds in capturing a new market of customers. (Marvel Comics- company decided to redefine its value proposition entirely by creating a movie studio). → for any business in a shrinking market, focusing on adapting its value proposition to provide new relevance to customers is absolutely essential. Adapt Before You Must There is no need to wait for a crisis, though. Value proposition adaptation is a strategy that every business can apply even when it appears to be doing well. This attitude toward customer value can be clearly seen in today’s digital titans, whether Google, Amazon, Facebook, or Apple. Even as they are achieving great success, they are looking ahead to shifts in customer needs and preparing to enter new markets with new value propositions. Five Concepts of Market Value Value proposition is just one of several strategic concepts available for thinking about your offerings and value to the market. The four of the most common ways of thinking about market value: - Product: Thinking about products is something every manager is comfortable doing. Product thinking is useful (indeed essential) when making decisions about engineering, design, launch dates, pricing, and other factors as you prepare to go to market. But thinking about products can limit your vision. It allows you to ignore the customers who are actually using the product as well as the value that it may provide them. - Customer: Another very common approach is to think about your business in terms of your customers. By focusing deeply on customers, you can begin to learn which customers matter more, have different needs, and should therefore be treated differently. - Use case: it is the context within which a customer utilises your product or service. The use case concept combines a focus on the customer with a focus on the context, which helps you think about the value being delivered. The use case concept combines a focus on the customer with a focus on the context, which helps you think about the value being delivered. - Value proposition: 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. It is a concept that is both value-centric and customer-centric. → Value proposition is especially useful when you face the challenges of adapting and evolving your value to customers in response to changing needs and new opportunities posed by technologies. of 56 81 Tool: The Value Proposition Roadmap The Value Proposition Roadmap is a tool that any organisation can use to assess and adapt its value proposition for its customers. You can use it to identify new and emerging threats as well as new opportunities to create value for your customers. It will help you synthesise those findings into a plan to create new, differentiated value in a changing landscape. → it uses a six-step process to map out new options for your business Step 1: Identify Key Customer Types by Value Received The first step is to identify your key customer types, distinguished by the different kinds of value they receive from your business. Step 2: Define Current Value for Each Customer The next step is to define your current value proposition for each customer type. This starts with a list of value elements—the various benefits that each customer type gains from the relationship with your business. After listing the value elements, write a summary statement of the value that this type of customer receives from your business—the overall value proposition. → Your value proposition should always be defined in terms of benefits that matter to your customers. (not money) Customer types may have some value elements in common, but no two customer types should have identical lists of value elements. of 57 81 Step 3: Identify Emerging Threats It is important to understand emerging threats that could undermine it. They could do so by competing with the value you offer, substituting for it, or simply making it less important to your customers. Three sources to consider for potential threats to your current value proposition: - New technologies: Look for emerging technologies that seem relevant to your industry and your customers’ experience. - Changing customer needs: These can include changes in consumers’ habits, lifestyles, and social behaviors. - New competitors and substitutes: A threat to your current value proposition can often come from an asymmetric competitor entering from another industry. Step 4: Assess the Strength of Current Value Elements You can now assess the strength of the specific elements of value that you provide. For each value element that you listed, ask three questions: - Are there any ways that this is a source of decreasing value to the customer? This decrease could come from one of the emerging threats - Are there any ways that this is a source of increasing value to the customer? New innovations by your business may mean you are increasing the value you deliver through this particular element. Or the value may be increasing due to this element’s growing importance to the customer, scarcity in the market, or differentiation compared to your competitors. 
 - What is the overall verdict? Based on these combined factors, you should now make an overall assessment for each value element. Is it strong (still a powerful source of value for your customer); challenged (under threat and perhaps not as strong a source of value as in the past); or disrupted (no longer relevant or meaningful to this customer type and uncertain to recover in value). Step 5: Generate New Potential Value Elements Your next step is to try to identify new value elements that you could offer to this customer type. This is a chance to examine some of the exter- nal forces that may be weakening your value proposition and use them as a source of opportunity for new value that you can create for your customers. To generate new value elements that you could offer to your customers, look in three areas: - New technologies: How could new technologies allow you to create additional elements of value for your customers? of 60 81 7. Mastering Disruptive Business Models The first tool, the Disruptive Business Model Map, allows you to assess any emerging threat to determine whether it truly poses a disruptive challenge to your business. If you are dealing with a true case of disruption, the second tool, the Disruptive Response Planner, reveals the full scope of the threat and helps you choose among the six responses possible for an incumbent business under attack. Disruption Defined 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. - Existing industry In order for something to be disruptive, something else must be disrupted. When we see a radically innovative new business or product, we sometimes leap to the conclusion of disruption before considering its impact on exist- ing industries. - Offers far greater value to the customer: Whenever disruption occurs, it is because a new offering is suddenly much more attractive to customers than the offering that the existing industry provides. - Cannot compete with directly: In traditional competition, roughly similar businesses duke it out to offer the customer better product features, lower prices, or greater personalization and service. A disruptive challenger is not selling a different version of the same product or service. It meets the customer’s needs with a product, service, or business model that the existing industry does not, and cannot, offer. The most important lesson to take from a clear definition of disruption is this: not all innovation is disruptive. Any new business ideas create new customer value but most of these innovations don’t actually disrupt the preexisting shape of the market. The result is a better product or a new brand but not disruption. Disruption in the Digital Age Digital technologies are rewriting the rules of business. These new rules have created opportunities for countless new challengers to take on long- profitable businesses that have failed to adapt. No industry is immune. New digitally powered business has created great value for the customer while weakening or undermining the position of the traditional incumbent businesses. Although the digital challenger is eating into their profits, traditional incumbents find themselves unable to respond by competing directly with the same offer. of 61 81 The exact strategy of the digital disrupter may vary. It may be offering a new service for free, like Craigslist. It may use intermediation, like Grub- Hub, to place itself between traditional businesses and the final consumer. → In every case of disruption the challenge arises from a new business offering new value to the customer. Theories of Disruption The first major theorist of business disruption was the Austrian economist Joseph Schumpeter → he wrote influentially on a phenomenon he called “creative destruction,” whereby capitalism inherently destroys old industries and economic systems in the process of innovating new ones. Clayton Christensen → offered our first theory of how disruption happens. The theory shows how disruptive challengers can unseat long-standing incumbents. The disrupter always starts out selling to buyers in a new market—that is, buyers who are outside the market of customers currently served by the incumbent. This “new market” disrupter offers an innovative product that is inferior in terms of performance and features but is cheaper or otherwise more accessible to those who cannot make use of the incumbent’s offering. Over time, though, the performance of the challenger’s innovation gets gradually better while it remains much cheaper or more accessible. At a critical juncture, the new technology becomes good enough to be a viable alternative for the incumbent’s own customers, and they begin to defect rapidly in favor of the much cheaper or more accessible alternative. The incumbent, who has remained wedded to its long-standing product and business model, finds it almost impossible to compete. Rapid decline follows. → Christensen’s theory of new market disruption is actually a specific case of the broader theory that the book presents. A Business Model Theory of Disruption This theory begins with the assumption that the best lens through which to view disruption is business models. Many of today’s biggest disrupters are not introducing a new fundamental technology to the market. Instead, they are apply- ing established technology to the design of a new business model. Business disruption is, at its core, the result of the clash of asymmetric business models. * business model specifically used as a predictor of business disruption, of 62 81 Two Sides of a Business Model 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. Due to the extreme importance of value creation and its role in business disruption, for this framework I’ll consider it on par with all the other elements of a business model combined. 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. → Once we can see any business model in terms of these two sides— value proposition and value network—we are ready to apply them in a new theory of how disruption happens. The Two Differentials of Business Model Disruption 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, otherwise its just traditional competition. f the challenger’s offer is merely incrementally better, then there may be some loss of business, but the incumbent can simply respond with normal competitive tactics to catch up, close the gap, or minimize losses. For disruption, the challenger’s offer must be dramatically better. Without the second differential, however, an incumbent would simply be able to watch the success of an innovative new challenger and profit- ably imitate it with a copycat offering of its own. An incumbent that gets disrupted is unable to replicate its challenger for varied reasons, but they all stem from the value network that the incumbent established in build- ing its business. Value Proposition Differential Every disrupter requires a difference in value proposition that dramatically displaces value provided by the incumbent. That difference can come from many possible sources → value proposition generatives: - Price: Digital business models often allow for the same product or service to be offered at a substantially lower price. - Free or “freemium” offer: Research has shown that free offers stimulate many more customer trials than a low price, even a penny.18 Many new business models add customer value with a of 65 81 Digital Disrupters: iPhone, Netflix, Warby Parker Let’s see how this model applies to three recent cases of business disruption. All three are in consumer businesses, and the disruption did not follow the traditional new market theory of disruption. iPhone Versus Nokia Why did Apple’s iPhone so thoroughly supplant Nokia’s mobile phones? - Physical design (provided a totally different customer experience) - Simplicity (Phone’s operating system offered a much easier user inter- face) - Integration (user had all integrated functions into one device) - Apps (also outside developers to create programs) Why couldn’t Nokia compete? Difference between the value networks and proposition of Apple. - highly developed design capabilities - partnership Apple had struck with its retail partner : AT&T - covering most of the consumer purchase price of the iPhone and rolling it into consumers’ monthly payments for data over two years. - Apple itself: its skill in designing simple computing operating systems and iTunes music platform - App Store : explosive growth in users and sales attracted an ecosystem of tens of thousands of developers who learned to program apps for the iPhone. → Taken together, these differences in the companies’ value networks made it impossible for Nokia to imitate the iPhone’s strategy. of 66 81 Netflix Versus Blockbuster How Netflix’s original DVD service defeated the leading retail chain for movie rentals, Blockbuster. Netflix chose to compete by offering a dramatically different value proposition to the customer. Difference between the value networks and proposition of Netflix. - Elimination of late fees: Netflix flat monthly fee that allowed the customer to keep three movies at home at a time, - Product was also more accessible: customer simply picked the movies out on Netflix’s website. A few days later, they arrived in the mail. - Much wider product choice than at any of Blockbuster’s retail stores - Sophisticated recommendation tool * Once the threat of Netflix’s service was clear, the Blockbuster tried to launch its own mail-order service. But differences in network’s value were evident: - Pricing model (subscription pricing vs. per product fees) - Netflix’s website and recommendation engine (Blockbuster could build an e-commerce website, it lacked the massive data sets as well as the sophisticated recommendation engine) - Sophisticated ware- house and mail distribution system (maximum automation, minimum errors, the fastest possible turnaround, and minimal cost) - Netflix lacked the overhead costs of running 9,000 retail stores. → After years of rapid decline, Blockbuster closed its final 300 stores in 2014. of 67 81 Warby Parker Versus Luxottica Warby Parker is an American eyeglasses brand that is seeking to disrupt the way prescription glasses and sunglasses are sold to consumers. Luxottica Group, which controls more than 80 percent of major eyewear brands. Warby Parker offers its own brand of fashionably designed glasses primarily through e-commerce sales. Does Warby Parker pose a disruptive threat to the incumbent? Difference between the value networks and proposition of Warby Parker: - Lower price - Access: avoid multiple trips to a store or who don’t have many retailers in their area, the online service may be another big advantage. - Social cause: donates one pair of glasses, via nonprofit Vision- Spring, for each pair that it sells to consumers - Online sales channel and its much lower retail costs - Keeps prices low due to its vertical integration → Clearly, Warby Parker poses a disruptive threat for Luxottica—having a much better value proposition that the incumbent cannot emulate. However many customers are willing to pay the higher prices for global brands, or prefer to shop in a nearby store, or won’t care as much about social causes. of 70 81 Step 1: Challenger What is the potentially disruptive business? The first step of the Business Model Disruption Map is to answer this question: What is the potentially disruptive business? The challenger you identify here may be a new competitor to your own established business. It may be your own start-up, attempting to disrupt an existing industry. Or it may be a potential new venture or initiative within your organization whose disruptive potential you are seeking to judge. The point of the map is to apply business model disruption theory to analyze the challenger, incumbent, and customer to determine if there really is a threat of disruption. Step 2: Incumbent Who is the incumbent? You may choose either a category of related businesses (e.g., video rental retail chains) or a leading example of the category (e.g., Blockbuster) in order to make the analysis more concrete as you compare the business models of the challenger and the incumbent. The other key point here is that, as we have seen, a challenger may pose a disruptive threat to more than one incumbent. Whenever you do identify more than one possible incumbent, you should complete the map multiple times—once per incumbent. You may well find that your new business model poses a disruptive threat to one incumbent industry but that another incumbent can accommodate the success of your model or can co-opt and imitate it. Step 3: Customer Who is the target customer? This is the customer being served by the challenger. In some cases, it may be a direct customer of the incumbent, but it also could be another key business constituency. Once again, it is possible that a challenger could aim to usurp the incumbent’s relationship with more than one type of customer. In this case, you should also complete the map multiple times— once per cus- tomer type. Step 4: Value Proposition What is the value offered by the challenger to the target customer? The focus here is exclusively on the benefit to the customer: What value could they gain from the challenger’s offer? You can refer back to the list of value proposition generatives earlier in this chapter to consider some of the many ways that digital business models provide value for customers. of 71 81 Step 5: Value Proposition Differential How does the challenger’s value proposition differ from that of the incumbent? The point here is to identify those elements of the challenger’s value proposition that are unique and different—this is the value proposition differential. There is certain to be some overlap between the values offered by incumbent and challenger. You do not need to include those commonalities here. The differences in value proposition may all be positive—that is, they are ways that the challenger offers additional customer value. In other cases, the value proposition differential may include benefits but also deficits. Step 6: Value Network What enables the challenger to create, deliver, and earn value from its offering to the customer? You can refer back to the list of value network components earlier in this chapter as you map out the value network that makes the challenger’s offer- ing possible. Your goal is to identify everything—people, partners, assets, and processes—that enables the challenger to offer its value proposition. If the challenger is new and unproven, this step should help to identify unanswered questions about its business model and whether it will actually be able to deliver the value proposition it is promising to the market. Step 7: Value Network Differential How does the challenger’s value network differ from that of the incumbent? Again, there may be some points of overlap between the challenger and the incumbent. If so, you can leave these out. The point here is to identify those elements of the challenger’s value network that are unique and different. The set of all differences between the challenger and the incumbent is the value network differential. Step 8: Two-Part Test Does the challenger pose a disruptive threat to the incumbent? As described by the business model disruption theory, this question is answered by a two-part test. The first question of the disruption test, then, is this: Does the challenger’s value proposition dramatically displace the value proposition provided by the incumbent? If the answer is no, then the challenger does not pose a disruptive threat to the incumbent. The challenger may be a great innovator with a terrific new value proposition for customers. But if that offer grows to threaten too much of the incumbent’s business, the incumbent should be able to respond by matching, or remaining closely competitive with, the challenger’s value to the customer. If the answer to the first test is yes, then you can move to the second test of disruption. of 72 81 Here you need to assess the barriers that are posed by the differences in value networks between incumbent and challenger. The second question of the disruption test is this: Do any of the differences in value networks create a barrier that will prevent the incumbent from imitating the challenger? If the answer is no, then the challenger does not pose a disruptive threat to the incumbent. It may be a dire asymmetric competitor, but there is no fundamental obstacle to the incumbent responding by matching its strategy. The incumbent may have to sacrifice some of its current profit margins in the process, just as it would in a price war with a traditional competitor. But the challenger is not truly disruptive. On the other hand, if the answer is yes, then the challenger has passed both tests of business model disruption. The value it offers to the customer will dramatically outstrip or undermine the value delivered by the incumbent, and the incumbent will face intrinsic structural barriers that prevent it from responding directly. → 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. Tool: The Disruptive Response Planner 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.
 The first three steps help you to assess the threat from the disrupter in terms of three dimensions: customer trajectory, disruptive scope, and other incumbents that may be affected. You can then use these insights in the last step to choose among six possible incumbent responses to a disruptive challenger. of 75 81 - 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 When assessing a disrupter to your business, it is easy to focus on its impact on only one industry (your own). But to understand the competitive dynamics at work, it is critical to expand your reference frame to consider other incumbent businesses and how they will be impacted and respond to the disrupter. VALUE TRAIN The first place to look for additional businesses that may be disrupted is in your own value train. Start by asking which product or service the disrupter most resembles. Then ask which of these different types of companies may be disrupted if the new business model is successful? SUBSTITUTION Another way of identifying additional incumbents is to think of products or services for which the customer may substitute the disrupter’s offering. Ask yourself two questions: - If a customer starts spending more money on the disrupter’s product or service, where else might they spend less money? - If the customer starts spending more time on the disrupter, where might they spend less time? One other question about substitutes is worth asking: If the disrupter’s current product continues to become much better in terms of performance and quality, for what other products or services might it start to become a substitute? LADDERING The last way to identify more incumbents who may be impacted by a disrupter is to look at both immediate and higher-order customer needs. You start by asking these questions: What problem or need does the disrupter solve or meet for its customers? Who else tries to solve that problem? Next you can attempt to unearth higher-order customer needs through a process known as laddering. In this market research technique, you ask a customer a series of “Why?” questions to get at the reasons behind their immediate motivations. This kind of laddering can reveal products or services that are made less necessary for customers by the disrupter, even though the dis- rupter doesn’t appear to be competing directly. IMPLICATIONS By looking at value trains, different means of substitution, and different lev- els of customer needs, you may have identified multiple incumbents—types of companies that will be disruptively challenged by the same new disrupter. As an incumbent, it is always valuable to know who else of 76 81 may be threatened by the same disrupter that is threatening you. In planning your own response, it is important to see how these other incumbents are responding or consider how their responses might parallel yours. You may also find allies in response to the disruptive threat. Step 4: Six Incumbent Responses to Disruption The final step of the Disruptive Response Planner is to plan your response as an incumbent. To do so, you will use what you have learned regarding the trajectory, scope, and other incumbents of the disrupter you are facing to help you choose which strategic responses are most promising for your circumstances. As an incumbent, you have six possible responses when faced with a disruptive challenger:
 THREE STRATEGIES TO BECOME THE DISRUPTER (seek to occupy the same ground as the disrupter) 1. Acquire the disrupter 2. Launch an independent disrupter 3. Split the disrupter’s business model THREE STRATEGIES TO MITIGATE LOSSES FROM THE DISRUPTER (seek to reduce its impact on your core business) - Refocus on your defensible customers - Diversify your portfolio - Plan for a fast exit These six strategies are not exclusive; you can combine them (and, in fact, some of them work best together). Depending on your own circumstances, only one or a few of these incumbent responses may be workable, so it is best to be familiar with each of them. ACQUIRE THE DISRUPTER The most direct response for an incumbent faced with a disruptive challenger is to simply acquire the challenger. ex. This is how Facebook dealt with the challenge of WhatsApp If you are considering buying your disrupter, knowing who the other incumbents are will help you predict who else might compete with you to drive up the price. That means the disrupter you own will continue to steal customers from your core business (and possibly at a lower profit margin). But if you don’t take measures to keep the acquired disrupter independent, you will inevitably put the interests of your core business above the goal of serving of 77 81 your customers. And that will create an opportunity for someone else to launch a similar business and steal away your disappointed customers. Acquiring the disrupter is not always possible. A start-up with sufficient venture capital may refuse to sell, as was the case with Facebook’s failed $3 billion bid for messaging app Snapchat. Or the disrupter may be part of a bigger company than the incumbent. LAUNCH AN INDEPENDENT DISRUPTER The second incumbent response is to launch a new business of its own that imitates the business model of the disrupter. Instead of purchasing the disrupter outright, the incumbent leverages its scale and resources to try to beat the disrupter at its own game. In order to launch your own disrupter, however, you, the incumbent must be willing to cannibalize your own core business. After all, you are try- ing to re-create the very business model that is disruptively attacking your traditional business. This strategy again requires you to keep the new disruptive initiative walled off in an independent part of your company. You should run it on its own P&L, with no responsibility to save or support your core business. Although the independent unit should have access to some of the main company’s resources, it should maintain a small and lean organization so that it can evolve quickly rather than becoming a sclerotic version of the nimble disrupter it is trying to beat. You may even launch an independent disrupter preemptively—as you see a possible new business model based on emerging trends and technology. It is not easy, but it is plausible if the differences in value networks are your company’s organizational culture, cost structure, revenue model, and customer segments. You can potentially overcome these kinds of barriers by insulating the self-launched disrupter from the rest of your business. SPLIT THE DISRUPTER’S BUSINESS MODEL What if the incumbent lacks some core capabilities—like intellectual property, brand reputation, essential skills, or the right partners—that are needed to re-create the disrupter? In that case, simply insulating a new initiative from the rest of the organization is not sufficient. But the incumbent may still be able to re-create the disrupter’s business model by splitting the job with other businesses. This may be a good strategy if your prior analysis uncovered multiple incumbents and their value networks are complementary to your own. The key to splitting a disrupter’s business model is to find other busi- nesses that complement your own value network and partner with them to bridge the gaps that are preventing you from launching your own disrupter. Ideally, those partners are also threatened by the same disrupter, so they will be motivated to collaborate. of 80 81 and at a very rapid pace. The curse of successful enterprises is often their very size and scale: their enviable resources can become a trap as future decisions are held hostage by past success. To develop true organizational agility, your business needs to focus on three areas: Allocating resources: How will you decide what to invest in? Are you able to disengage from initiatives and lines of business that lack future potential? Can you apply resources from older business lines to sup- port new ventures? Changing what you measure: What outcomes are being measured by senior decision makers? Do they simply relate to existing business practices, or can they support new directions? What should you be measuring at different stages of a transition to a new business model? Aligning incentives: What kind of behavior is enabled, supported, and rewarded in your organization? What are managers held accountable for? How are they assigned to new positions? Do compensation and recognition support or hinder the necessary changes in your strategy? It may be helpful to conduct an audit of your business’s readiness for digital transformation. At the end of this book, you can find such a diagnostic tool, titled Self-Assessment: Are You Ready for Digital Transformation? It includes questions to assess your own organization’s current readiness for digital transformation—in terms of both strategic thinking and agility to carry out new strategies. You can think about the challenge of digital transformation in terms of mastering two different kinds of management. To succeed in any trans- formation, 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. This is quite a differ- ent task—and one that is particularly hard for large organizations. The head of British Airways’ Know Me program explained to me how the company is tackling this transition. Having built a powerful data asset, developed tools to capture customer insight and apply it in customer inter- actions, and launched pilot programs to prove the impact for the business, she now faces a different challenge. The next stage is to scale up the pro- gram, to embed the use of data for customer service into the company’s DNA, and to transition Know Me from an innovative initiative to a part of British Airways’ day-to-day operations. My colleague Miklos Sarvary, who teaches in my digital strategy executive programs at Columbia Business School, talks about this transition as a shift from “incubation” (seeding and nurturing new strategies) to “integration” (building the best ones into the fabric of the organization). But incubation and integration require very different skills in an organization. The ability to incubate is seen best in start-ups and venture capital firms. It 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. By contrast, the ability to integrate and replicate successful ideas at scale is most often seen in larger enterprises. It 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. of 81 81 The organizations that flourish in the digital age will combine the right strategic mindset with the right leadership skill set. They will understand the new strategic fundamentals of the digital age and use them to craft new products, services, brands, and business models. Whatever their size, they will maintain the organizational agility to seize new opportunities, and they will balance the art of incubating and learning like a start-up with the art of scaling and integrating like an enterprise. These organizations will be guided, as their strategies and business models change, by a focus on continuous value creation. Going back to Peter Drucker, management thinkers have argued that the true and ultimate purpose of business should always be creating value for the customer: “to create a customer,” as Drucker wrote, or “to get and keep a customer,” as Ted Levitt put it.3 Today, though, this doctrine may require a slight update. Amidst constant digital change, no business can thrive for long just deliver- ing the same value proposition to customers. The need for value creation is now intertwined with the need to constantly relearn and reinvent what that value will be. The purpose of business, then, may be thought of as the continuous creation of new value for the customer. The digital revolution is still just getting started. With an ever-unfold- ing cascade of new technologies and all the potential they provide, it is impossible to predict how the digital future will impact your business or any industry. But if you are savvy, your business can choose to use each new wave of change as an opportunity to create new value for your customers.