Image courtesy of Daniel Hertzberg/theispot.com
The term platform is commonly associated with vibrant ecosystems that connect various sets of users — drivers with riders (Uber), property owners with renters (Airbnb), searchers with advertisers (Google), sellers with buyers (Alibaba), or social groups with app developers (Facebook). These digital platforms have generated unprecedented value, overshadowing many established companies that have dominated their industries with produce-and-sell value chains.1 Until recently, most traditional companies could not adapt their established business models to participate in the so-called sharing economy. But sensors and related technologies are changing that reality.
Consider Ford vehicles equipped with voice-activated technology that can order coffee through Amazon’s Alexa. Using data on weather, traffic, and the vehicle’s location, the car can request a coffee to be ready precisely when the driver arrives at the nearest Starbucks. The driver can pick up her coffee without waiting in line. And the FordPass app that contains her mobile payment information can automatically complete the transaction.
This kind of integration highlights two notable shifts from traditional practices.2 First, the established company (Ford) activates a new ecosystem consisting of consumers and third parties outside its value chain (Starbucks, Amazon, banks, and app developers). Such consumption ecosystems emerge after products are sold through linkages enabled by sensor data generated as products are being used.3 They are different from production ecosystems, which are built on linkages within value chains — such as those between suppliers, R&D, manufacturing, assembly, and distribution channels — that connect the parties involved in producing and selling. Established companies know their production ecosystems, and many use smart connected products within their value chains to improve their assembly processes, customer relationships, and after-sales service.4 But consumption ecosystems, which involve tracking products after they are sold and sharing sensor data with parties outside the value chain, are new. And they require new capabilities.
The second shift occurs within the established company’s new consumption ecosystem. In the coffee example, Ford must manage exchanges between drivers and third-party providers to offer a service. In so doing, Ford goes beyond its produce-and-sell role to become a platform creator and orchestrator.
Running a platform is new for many produce-and-sell companies, but the opportunity it represents is hard to ignore. Sensors and the internet of things (IoT) are expected to connect 20 billion to 50 billion smart devices and products in the coming years,5 creating new consumption ecosystems and fresh avenues for competition through platforms.
We call platforms where a product initiates digitally powered exchanges among users and third-party providers tethered digital platforms: tethered because their scope and competitiveness are tied to the product, digital because the value generated stems from sensor data, and platforms because of the exchanges among product users and third-party entities. (Product in this article refers to both products and services.)
Traditional businesses may ask, “Are our products suitable for platforms? How can we make them suitable? What should be our platform strategy?” This article offers a framework for managers to address such questions. Our premise: Established companies can compete not just through their products, but through the data their products generate. Below, we briefly outline the key components of tethered digital platforms, explain how managers can assess the worth of their sensor data, describe several ways that companies can compete in a platform world, and provide guidance on how to craft an effective platform strategy.
The Components of a Tethered Digital Platform
A tethered digital platform has four essential components: a sensor tied to the product; sensor data generated when the product is used; platform users, for whom exchanges are orchestrated; and a platform service that is generated through those exchanges.
A light bulb can have a sensor that detects motion. It generates data, for example, when someone walks into its sensing range. This sensor data can be exchanged across complementary smart objects or systems in the room connected through IoT, such as window blinds, clocks, or music systems. Furthermore, these exchanges can be orchestrated to offer specific services (opening blinds or operating a music system when a person enters a room, for example). The person, the objects, and the systems involved in the exchanges are all platform “users” that combine to form the bulb’s consumption ecosystem. This ecosystem grows when platform users increase, more complementary objects are added, or additional developers join to offer apps to enrich the service. By assembling these components, a bulb-producing company extends its product business into a tethered digital platform that provides a new service.
For service businesses such as banks, the path to a tethered platform is different. A bank could use the internet and a smartphone app as its sensors. It could analyze the app’s data to glean insights on a customer’s spending patterns, credit worthiness, and desired purchases to facilitate exchanges between that customer and merchants. The merchants could use the platform to compete for that customer’s spending.6 The platform would thus expand the bank’s traditional services into broader purchase experiences for customers.
The Value of Sensor Data
The sensor data will determine the core features a platform service offers by defining and shaping users’ interactions. Those interactions, whether they originate with an earth-moving excavator or a toothbrush, are crucial in attracting platform participants.
For a tethered digital platform to succeed, its platform services should ideally have strong market potential with few rivals, and they must provide seamless data exchanges among users to ensure ease of implementation. Three attributes of sensor data help traditional businesses assess such prospects: scope, uniqueness, and controllability.
Scope. The scope is the estimated value of services that the sensor data can drive to a tethered digital platform. It depends on the underlying nature of the services its exchanges facilitate. Consider the value of synchronization of construction activity services that Caterpillar’s sensor-equipped excavator could generate in coordination with other connected assets at a construction site. It is estimated that construction projects waste billions of dollars annually through rework.7 If Caterpillar can track where and when different assets begin and end each task, it can better coordinate project activities to reduce such waste, potentially saving construction companies money even if Caterpillar charges them a fraction of those savings.
The scope of sensor data widens through direct network effects as user participation rises.8 For example, Nike customers using sensor-equipped shoes for jogging can benefit from direct network effects through communities of runners that generate popular content such as interesting routes and training and safety tips. As more runners join, each one derives more value. Sensor data also can generate indirect network effects when complementary users join the platform.9 Nike customers, for example, can benefit from technologies linked to their shoes, such as a Fitbit or an Apple Watch, and from apps created by developers that their sensor data attracts.10
Uniqueness. When we talk about uniqueness, we are referring to the degree to which sensor data available to one product is unavailable to others. This attribute reflects how competitive a platform service market is likely to be. For a toothbrush, its sensor data is unique to toothbrush-tooth interactions. This kind of data is likely available only to competing sensor-equipped toothbrushes. In contrast, motion data collected by a light bulb’s sensors is not restricted to other smart bulb manufacturers but is available to other smart products in the same room or building, such as thermostats, fire alarms, or security cameras. Depending on the nature of product-user interactions, rivals with competing sensor data can emerge from outside a product’s traditional industry.
Such rivals could also compete for the chance to retrofit sensors on a company’s existing products. Trimble, a software company in the GPS space, is doing just that: installing sensors on construction equipment to locate and track assets in the field. Similar risks apply to service businesses (like banks) looking to generate unique sensor data through smartphone apps. Companies with omnibus platforms and apps, like Alibaba and Tencent, collect far richer data on the spending habits, credit histories, and loan requirements of the average Chinese consumer than what the Chinese banks can ever expect to capture from their own app-based sensors.11
Controllability. Sensor data’s controllability is the degree to which it can be used to facilitate exchanges among users and complementary entities without restrictions. Such interactions are necessary to implement a platform service. When they require intermediaries, a company might face constraints in sharing sensor data across complementary entities. GE Transportation’s sensor data from its locomotives, such as expected time of arrival, can potentially be used to generate exchanges among cargo shippers and receivers. The cargo shippers and receivers, however, are not its direct customers. They are customers of railway companies, which may restrict GE Transportation from using sensor data to drive such exchanges.
There also may be regulations or consumer privacy practices that curb sensor-data sharing. Customers of Abbott Laboratories’ sensor-equipped diabetes care product FreeStyle Libre, for example, may restrict the sharing of their real-time blood glucose levels with other companies.
Pick Your Platform Strategy
To maximize the prospects of its platform services, a company must craft a strategy that optimizes the scope, uniqueness, and controllability of its products’ sensor data. The following framework offers four potential tethered digital platform strategies: full, enabled, collaborative, and hybrid. In addition, for products and sensor data that won’t support a platform, companies can offer their sensor data as components to other services. (See “Deciding Which Platform Type Is Best” and “A Guide to Tethered Digital Platforms.”)
Full tethered digital platform. This approach is best suited for products with sensor data that is unique and faces few sharing restrictions on a platform. The product company can run its own platform and orchestrate data exchanges with full autonomy.
Example: Scientific, technical, and medical publishing company Elsevier digitized thousands of its proprietary research publications and then began collecting sensor data through online and app-based interactions with users. Elsevier uses this data to enable exchanges among researchers with common interests, create communities, and facilitate collaboration. Through premium subscription services, it is generating new revenues from researchers and institutions that expect to improve productivity.
Enabled tethered digital platform. This strategy works best when the product company has access to unique sensor data but lacks adequate control to share it freely across users and complementary entities. The company can serve as the back-end operator of the platform, while its clients own and manage the front-end value-added services.
Example: Intuit offers accounting software to small businesses that can collect sensor data, such as on their inventory and working-capital levels. The clients, however, own the data. Intuit enables its clients to exchange their data with banks, lenders, or suppliers to help coordinate their short-term loans or material supplies needs. The clients choose which entities can access their data, while Intuit facilitates the services. Intuit’s platform enhances its revenues through premium subscriptions.
Collaborative tethered digital platform. This approach is most effective for products with sensor data that is not unique but has a promising scope and few restrictions for sharing.
Example: Consider Whirlpool’s sensor-equipped refrigerators that capture data on stock levels of items like milk and eggs. Using this data, Whirlpool can orchestrate exchanges among refrigerator owners, grocery stores, and delivery services to replenish goods. Whirlpool is not alone in its data access, however. For example, Amazon could have access to the same information through its Dash ordering and delivery service or when a refrigerator user asks Alexa to refill low-stock items. One option Whirlpool has adopted: collaborating with Alexa. Whirlpool orchestrates exchanges through its own platform, but it also offers its services as part of Alexa’s broader platform. Whirlpool thereby avoids direct competition with Amazon. Amazon, meanwhile, may find Whirlpool’s subplatform attractive as an additional Alexa feature. Spotify’s music services, offered through Facebook’s platform, take a similar approach.
Hybrid platform. A hybrid strategy makes sense for products with sensor data that has both strengths and weaknesses. It’s a way to diversify approaches and test which one is most profitable.
Examples: Whirlpool may choose to offer a full tethered platform for some of its customers and also provide a collaborative subplatform on Amazon’s Alexa platform. GE Transportation could run its own full tethered platform with clients that offers free sensor-data sharing, while offering enabled platforms for other clients that place restrictions on that data.
Supplier to digital product platforms. This strategy is best suited for products that have a sensor but lack ways to generate data exchanges across users. Such products can serve as data suppliers to other digital platforms.
Example: Faucet maker Delta has introduced voice-activated products that take commands from Alexa and Google Home for its operation. The faucet does not orchestrate any exchanges on its own but is a component for Amazon’s and Google’s platforms.
Guiding Questions for Leaders
Modern digital technologies empower companies to generate value not just with their products but with the data their products generate. Yet for traditional businesses that have relied on their value chains to compete through product design, product quality, scale of operations, branding, or distribution channels, this entails a significant strategic shift.12 As businesses evaluate new opportunities offered by sensor data, three strategic questions can help sharpen their focus.
What is our sensor strategy? Given that sensor data primarily arises from how a product interacts with its users, maximizing the potential of product-user interfaces is central to a company’s sensor strategy. To do so, it may need to find ways to use its product-user interfaces beyond the core functionality of its products.
For example, the core function of iRobot’s vacuum cleaner, the Roomba, is cleaning. It is designed to sense obstacles to avoid when cleaning floor areas. Imagine if, with modifications, Roomba sensors could detect problems like mouse droppings, termites, or mold as the robot scans floors. Then iRobot could pursue a sensor strategy to expand into new services by inviting pest control vendors and home contractors to its tethered digital platform.
The startup Cimcon Lighting is pursuing a similar strategy. With sensors in streetlight bulbs that detect gunshots, Cimcon has launched a tethered platform to orchestrate exchanges across 911 calls, camera feeds, police departments, emergency rooms, and ambulances for street safety services designed for smart cities.13
To determine your sensor strategy, drill down and ask these questions:
- What is the data-generating potential of our product-user interfaces and sensors? How can we expand on that?
- How can we use our product design and innovation capabilities to identify new kinds of sensors and build new product-user interfaces?
What is our strategy to attract platform users? Sensor data is the platform foundation, and users represent the scaffolding, bricks, mortar, and other “building” materials. A tethered digital platform generates value-creating services by facilitating sensor data exchanges. So to attract platform users, companies can start by marketing sensor-equipped products to their existing customers. They also can partner with entities that offer complementary value.
For instance, a mattress maker such as Tempur Sealy that has introduced a line of mattresses with sensors to detect heart rates, breathing patterns, and snoring during sleep may first want to use its established channels to market these products to existing customers.14 The company could also offer to retrofit sensors on mattresses already sold. It could then identify complementary services that would help improve sleep by responding to sensor data, such as adjustable lighting or soothing music, and convene relevant third-party providers — perhaps even sleep apnea specialists — on a tethered platform. Those users would expand services provided for existing customers and broaden the appeal for entirely new customers.
Digital natives have long mastered strategies to attract platform users,15 notably through their use of application programming interfaces (APIs) that enable software programs to exchange sensor data and facilitate platform-based services.16 Platform APIs attract application developers and put the onus on them to find ways to complement one another and serve customers.17 Digital natives have also pioneered pricing strategies tailored to both attract and benefit from platform users. Facebook subsidizes its primary users with free access, and it profits from advertisers and app developers. Traditional businesses can seek similar ways to subsidize some users and generate revenues from others. These choices, however, entail substantial upfront costs and require persistence to succeed.
To sort out your strategy for attracting users, ask the following questions:
- Which customers are the most likely users for our sensor-equipped products?
- What kind of platform services would attract them? How do we reach them?
- Which entities can use our sensor data to complement our offering?
- What should be our API strategy?
- How should we set prices? Whom should we subsidize?
What is our optimal tethered platform strategy? Finally, a company must determine how best to leverage its sensor data and platform users to offer new services that generate competitive advantage. This is a two-step process.
First, assess the product category and evaluate its available sensor data — its scope, uniqueness, and controllability. Second, examine the strength of the company’s traditional competencies, such as its scale of operations or brand: How can it boost sensor data value, outperform rivals with similar data, and control how it shares data with external entities? The two steps should inform decisions about which tethered digital platform is optimal or whether being a supplier to a bigger platform is the best option.
Consider these two steps for an athletic shoe. The shoe manufacturer can estimate the value of its sensor data for generating exchanges among the shoe users and complementary fitness-related services the same way it would estimate the market value for any new product. Assessing the uniqueness of sensor data may reveal strong potential competitors like Apple, Garmin, or Fitbit. And controllability of sensor data may not be a significant hurdle if one assumes that most athletic shoe users would be willing to share their data for value-added services.
Now consider the company’s position. A market leader like Nike can marshal its formidable branding and operational scale in a business entailing fitness services. That makes a full tethered platform appear to be an optimal option. A second-tier company with less capital may find the threat of potential rivals more ominous. It may decide that a collaborative platform is better, or it may experiment with a hybrid approach. A smaller company might opt to be a supplier to a dominant fitness service platform unless it finds creative ways to build competitive platform services without the foundations that a larger company can leverage.
To home in on the most promising platform type for your business, ask these questions:
- What are the scope, uniqueness, and controllability of our sensor data?
- How can we leverage our traditional value-chain and product strengths to compete as a tethered digital platform?
- What do we lose if we do not compete as a tethered digital platform?
For decades, digital technologies — from enterprise resource planning software to customer relationship management systems — have made it possible for businesses to expand their production ecosystems. Smart connected products provide further opportunities to enrich these production ecosystems and boost a company’s traditional produce-and-sell capabilities.
But a different promise lies in the role sensor technologies can play after products are sold. Sensor data opens up new consumption ecosystems in which companies can add value to their products as they are used. A business can also invite complementary entities to join its product users on a platform to cocreate value through new platform services.
Consumption ecosystems thus provide new avenues for traditional businesses to create value through platforms. If they fail to act, digital natives will exploit those opportunities. Recent moves by Google, Apple, and Facebook into traditional industries such as entertainment, health care, insurance, and automobiles may be harbingers of competitive attacks through consumption ecosystems. Traditional businesses must find ways to proactively seize new opportunities and insulate themselves from such disruptive attacks. Tethered digital platforms represent a promising framework for evaluating the best strategies to pursue.
How Legacy Businesses Can Compete in the Sharing Economy
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