Business Model Innovation: Digital transformation typically requires a new business model. Designing the new business model should start with the customer, then clearly determine and validate value propositions for the customer to be created through digital transformation, and then, only then, design products and services, business processes, business resources, external partners, etc. Design thinking can be followed in designing the new business model to ensure the new product and services to be developed are desirable by the customer, feasible with the current business, technical and workforce capabilities, and viable with respect to sustaining profitable growth.
Popular methods for business model design such as business model canvas, TOGAF business architecture framework, and ArchiMate are helpful in clearly describing and communicating the design, reaching a consensus among stakeholders, and providing a high-level design for business analysts and technical architects who can then decompose and elaborate the design into detailed system requirement specifications. The business analysis expertise pattern for IT service business applies here too.
Integrated modeling tools such as Visual Paradigm support maintaining consistency and traceability between a high-level business architecture design in ArchiMate and detailed requirement specifications in formal modeling notation such as BPMN 2.0 and UML 2.0. IoT development methods, such as Ignite (D. Slama, et al., Enterprise IoT, 2015: http://enterprise-iot.org/) and IIC IoT Lifecycle Process (https://www.iiconsortium.org/IIC_PUB_G1_V1.80_2017-01-31.pdf), all starts with business model design and then proceed to system analysis and design. Refer to the Business Analysis page in this web site for more details on software requirement engineering for digital transformation.
IoT-Enabled Operations: Many digital businesses are based on various use cases of IoT for innovating operations. IoT can be applied to operations at different levels of sophistication: monitoring, control, optimization and autonomy, each building on the preceding one. (M. Porter & J. Heppelmann, How Smart, Connected Products are Transforming Competition, Harvard Business Review, Nov. 2014.) For example, the CGM device from Meditronic, a medical device company in Ireland, inserts glucose sensor under the skin and monitors, displays and alerts glucose levels for diabetes patients. ABB Robotics, an industrial robot supplier in Switzerland, remotely monitors, analyzes, controls, upgrades, reconfigures and preventively maintains industrial equipment. GE Brilliant Factories combine lean manufacturing, advanced and additive manufacturing with advanced software analytics to maximize productivity. They embed sensors onto their machines, leverage software to gather data, and use analytics to gain insights to optimize performance, reduce costly unplanned downtime and ultimately drive greater productivity. Caterpillar manufactures mining equipment which use sensors, data and central computer operations with wireless and fiber networks to perform mining operations autonomously without workers on site, both in and above the ground.
IoT-Enabled Product Design: Softwarization of manufacturing products (i.e., making products smart and connected) adds sensors, computing capabilities, data storage, actuators and communication ports to the products. Once product functionalities are implemented by software instead of hardware, the product becomes more like software whose intrinsic nature is far different from hardware as mentioned at the beginning of this blog. Recall that software does not wear out, its reproduction cost is near zero, and it can be changed anytime remotely, which are all impossible with hardware.
There are many innovations made possible by softwarization of products. Product design can be varied via software for a single physical product. John Deere, an agricultural machinery manufacturer in the U.S., used to manufacture multiple versions of engines, each providing a different level of horsepower. It now can alter the horsepower of a standard physical engine using software alone.
Such a product line variation can be done even at run time, enabling so called "dynamic" software product lines. Tesla Motors, an electronic car manufacturer in the U.S., after batteries in two Tesla Model S cars were punctured and caught fire in 2013, was able to reconstruct the road conditions and speeds leading to the punctures, and then sent a software update to all vehicles that would raise their suspension under those conditions, significantly reducing the chances of further punctures.
Softwarization combined with IoT enables companies to continuously monitor real-world performance data, identify design problems, and unearth powerful insights by identifying patterns in thousands of readings from many products over time. Once a design problem and its causes are understood, the problem can be fixed remotely via software, enabling "evergreen" product design.
IoT-Enabled CRM: The data from smart connected products provides a much sharper picture of product use, showing, for example, which features customers prefer or fail to use. By comparing usage patterns, companies can do much finer customer segmentation. Marketers can apply this deeper knowledge to tailor special offers or after-sale service packages, create features for certain segments, and develop more-sophisticated pricing strategies. Companies are beginning to see the product as a window into the needs and satisfaction of customers, rather than relying on customers to learn about product needs and performance. For example, Nest Labs, a home automation supplier in the U.S., uses its Learning Thermostat installed in over 1 million homes as a platform to offer energy management services to utilities. Utilities companies use the Nest services to better understand their customers' energy usage and reduce overall electricity requirements by 50% in peak times thus saving significant money.
Customer service and support is another area greatly benefiting from IoT. With smart connected products, technicians can diagnose problems remotely, and have supporting information for executing the repairs at the customer site. In many cases, a product can even be repaired by remote technicians by rebooting it, delivering a software upgrade. Smart connected products improve service and efficiency and, using predictive analytics, enable a fundamental shift from reactive service to preventive and proactive service. Bosch, an automotive components supplier in Germany, established the Industry 4.0 initiative that includes IoT-based manufacturing analytics and preventive maintenance. For example, ultrasonic or vibration sensors attached to spindles in milling machines identify the patterns of a fragile spindle. By analyzing the sensor data, it is possible to predict when the spindle is about to break, and schedule a preventive maintenance.
Digital Value Chain: As indicated by the above three patterns (IoT-enabled operations pattern, IoT-enabled product design pattern and IoT-enabled CRM patterns), digital businesses can "digitize" business operations and management across the value chain from R&D, marketing to manufacturing, sales and customer support. Successful implementation of digital business entails fluid digital communication across the value chain--this continuous flow of data is the "digital thread". (J. Nanry, et al. Digitizing the Value Chain, McKinsey Quarterly, March 2015.) The best way to design and implement a well-functioning digital thread is to analyze end-to-end business processes across the value chain and find the steps of the process flow where various IoT sensor data or insights derived from them can be fruitfully utilized. Typically a piece of information can be utilized in multiple places. For example, product malfunction sensed by a smart connected product may be useful information for product design as well as customer service.
Analytics are best utilized when embedded in business processes. Intelligent business process management suites (iBPMSs) support highly intelligent applications that seamlessly integrate advanced decision automation technologies—such as predictive analytics and artificial intelligence (AI)—to automate business processes that require more situationally adaptive behavior. An iBPMS is a type of high-productivity application platform as a service (HP aPaaS). Business analysts can use iBPMS such as Pegasystems, Appian, BizAgi, IBM Process Transformation Manager, Oracle Process Cloud Service, for rapid continuous improvement of a business process or experimentation with new operating models. An iBPMS provides real-time insights supporting "BizOps"--viz., continuous process improvement and reinvention at the pace of DevOps. (Gartner, Magic Quadrant for Intelligent Business Process Management Suites, 2017.) Business analysts need to master modeling languages such as BPMN 2.0 and UML 2.0, and modeling methods for process, data, use case and service modeling to be able to use iBPMS effectively. An iBPMS as a type of HP aPaaS is also classified as a low-code development platform (LCDP) which supports model-driven development with minimal coding.
Product Servitization: Servitization of manufacturing products comes in several different fashions: service bundling, product as a service, product sharing and productless service.
Service bundling is to provide connected value-added services directly to buyers of a manufacturing product, enabling new ongoing customer relationships and disintermediation of channel partners or maintenance partners. Schneider Electric in France provides cloud-connected digital services to customers owning their building products to gather volumes of data about energy consumption and other building performance metrics and provide advisory services in reducing energy use and other costs.
Product as a service allows customers to pay the usage-based fee without buying the product and the manufacturer assumes responsibility for and associated cost of maintenance. Kaeser Compressors in Germany has sold machinery including air compressors since 1919. But once it began putting sensors on those compressors and examining the data it collected, Kaeser found a new way to generate revenue. With a better understanding of its machines and the ability to analyze them continuously, Kaeser now sells air by the cubic meter through compressors it owns and maintains. It’s “air as a service.”
Product sharing let service subscribers share the product without buying it. Daimler provides the car sharing service called car2go in urban areas in Europe, North America and China. It offers exclusively Smart ForTwo and Mercedez-Benz vehicles and features one-way point-to-point rentals. Users are charged by the minute. Cars are user-accessed via a downloadable smartphone app wherever they parked.
Productless services provide IoT-based information services or owner-user matching services without manufacturing or even owning the product. OnFarm is a SaaS company in the U.S. that aggregates disparate agricultural data available from diverse agricultural equipment manufactured by other companies into a single farmer-friendly platform and provides farm management tools and API services.
API Business: Digital economy is also called API economy because devices, businesses and consumers are all connected via APIs. Even for e-business and social business, API was very important to businesses. For example, 7 billion worth of items were transacted through APIs on eBay, and the API had 10 times more traffic then the website at Twitter in 2010.
In digital business, smart connected products provide open APIs to allow customers and partners to assemble the parts of the solution—both the products involved and the platform that ties the system together—from different companies, and to enable 3rd party players including app developers to create value-added applications augmenting the product functionalities. Many digital businesses further provide an API portal with an SDK to allow developers register for, learn about and leverage APIs to speed app development and maximize app quality. Nest Developers, Philips Hue API, GM Developer are just a few examples of the app developer site established by manufacturers. Some vendors provide API hubs to simplify the integration and orchestration of a variety of smart connected products. IFTTT is a free PaaS to create applets that are triggered by events in other web services; for instance switching on a light when a motion is detected by an associated compliant device in a room (https://ifttt.com/discover). Samsung SmartThings is another example of an API hub that can connect a wide range of smart home devices such as voice assistants, speakers, lighting, electrical outlets, sensors, cameras, thermostats,door locks, etc. (https://www.smartthings.com/)
Pace-Layered Application Architecture: Pace-layered architecture is s segmentation strategy for application portfolio based on the required pace of change to deliver different business capabilities in an enterprise. Gartner suggests three layers: system of record, system of differentiation and system of innovation. (Gartner, Use Bimodal and Pace-Layered IT Together to Deliver Digital Business Transformation, 2018) IoT applications enabling digital business certainly belongs to the system of innovation, of which the development requires rapid iterations for experiments (or Mode 2 style of work as defined by Gartner). The continuous deployment pattern of SaaS business applies here, too, which favors a combination of design thinking, lean startup, agile development and DevOps. Low-code development platforms (LCDPs) introduced above in the digital value chain pattern are often used to develop systems of innovation. To facilitate development of the systems of innovation, the system of record, mainly composed of legacy applications, had better be modernized into service-oriented architecture, so that functionalities and data in the legacy applications are readily reusable via APIs when experimenting with new digital business applications. Such modernization (or technical debt pay-off) is important for the same reason why the asset-based service pattern and service-oriented architecture pattern are important for IT service business.
System of Systems: The partner ecosystem pattern of SaaS business may require a more complex architecture in the ecosystems of digital businesses. Take the Moovel-based mobility service as an example. Business processes of Daimler and those of all partnering transit agencies should be seamlessly integrated. This requires a modeling of business processes and business semantics across the entire supersystem encompassing many independent systems. That is, an ecosystem of SaaS business could be designed at the software architecture level, while an ecosystem of digital business may require a design at the business architecture level.
It is best when connected systems are all built in the service-oriented architecture pattern exposing APIs so that the integration, orchestration and choreography of those systems do not depend on implementation details of individual systems. However, it requires much more than just interconnecting a number of software via APIs to build a system of systems for an IoT business. The business modeling as well as software architecting of the entire supersystem becomes critically important.
IoT evolved from M2M which can be regarded as Intranets of Things--closed environments with little connectivity outside of the device estate or solution in question. The natural next step is to connect these solutions to the outside world including adjacent products, services and other Intranet of Things. This stage of development will be driven by common ownership of data sources typically within an enterprise or common cause among data owners such as a community of intelligent building providers that come together to form a common platform. This stage is called Subnets of Things. (Refer to: D. Slama, et al., Enterprise IoT, O'Reily, 2016.) A full-scale Internet of Things may connect stakeholders across the boundaries of conventional industries as can be seen in Figure 5 (M. Porter & J. Heppelmann, How Smart, Connected Products are Transforming Competition, Harvard Business Review, Nov. 2014.), where farm equipment vendors, irrigation systems, weather data systems and seed optimization systems are connected to create a digital business of farm management. Daimler's intermodel mobility service is another example of full-fledged IoT system which is a system of systems.