"Der Tausch von digitalen Lösungen (Services, Fähigkeiten) ist der Handel des 21. Jahrhunderts; Plattformen sind die Boote der Eroberer"; Markus Warg, CIO.de
Spohrer, J.C., Maglio P.P., Vargo S.L., Warg M. (2022): Service in the AI Era: Science, Logic, and Architecture Perspectives, Business Expert Press
US Amazon site: https://www.amazon.com/ Germany Amazon site: https://www.amazon.de/ Business Expert Press site: https://www.businessexpertpress.com
Are you prepared for the coming AI era? AI advances will profoundly change your daily service interactions, so this book provides readers with a necessary understanding of service, the application of resources (e.g., knowledge) for the benefit of another. In just minutes, you can learn about today’s use of early-stage AI for automation and augmentation, and essential ele- ments of service science, service-dominant (S-D) logic, and Service Dominant Architecture (SDA).
Ultimately, improved service for all is possible with human-level AI and digital twins — but requires investing wisely in better models: Better models of the world both complex natural and social systems (science), better mental models in people to improve interactions (logic), better cultural and structural models of organizations to improve change (architecture), and better trusted and responsible AI models.
The service innovation community studies and builds better models to improve interactions and change in business and society.
The book challenges all responsible actors — individuals, businesses, universities, and governments — to invest systematically and wisely to upskill with AI (the X+AI vision). The service innovation community is a growing transdiscipline harnessing all disciplines to become better T-shaped professionals. Extensive end notes, bibliography, and index are provided.
What is architecture, and why does it matter? Over the past 20,000 years (a thousand generations)—since the early cities with specialized skills and roles—the architecture of buildings, organizations, and technologies has been changing. Most people are familiar with the architecture of buildings, but organizations have architectures as well. For example, historically, empires relied on coercion and trade to grow the scope and scale of their operations and holdings, meaning the design pattern of their organizational architecture or enterprise architecture included both military and supply chains distributed across an interconnected network of cities. The architecture of cities and places where you live and work affects the ease of getting things done and your quality of life and your well-being. Homes, cities, and organizations (as enterprises)—places of work, learning, health care, and so on—are the places you spend the most time and are designed to support your daily activities.
Making Simple Changes Easy and Hard Changes Possible
Good architectures make simple changes easy (e.g., rearranging furniture) and hard changes possible (e.g., moving a wall with plumbing and electrical). If nothing much changed in human activities, architecture would be easier. But every society, every city, and every enterprise is in a state of perpetual change, a process of becoming, striving to become a better future version of itself. The primary reason that enterprise architecture matters is because some architectures allow the needed change to improve service functions more easily than others.
As technologies and strategies change, the demands on enterprise architecture are increasing. Openness to collaboration, rules for coordinating actors in actor-to- actor networks, and skills such as integrating and orchestrating external resources are required.
In the era of artificial intelligence (AI), good enterprise architecture allows new offerings (customer solutions) to be created and changed rapidly and with flexibility in how datasets are used to drive business growth. Data-driven insights trigger tactical or strategic business moves and data-driven network effects. This results in further requirements for the enterprise architecture and in particular for the patterns of how data are collected, analyzed, and used in context.
How Architectures Become Dominant Architectures
What is a dominant architecture? As in the previous chapter, dominant refers to how many people adopt and embrace a particular mindset and worldview, including both users (practitioners) and influencers (scholars and educators). Architecture can, therefore, be called dominant when its design patterns for change become part of social and cultural practices and are reused over and over again in different social, organizational, and technological contexts.
Here, we focus on enterprise architecture. Put simply, the architecture of a building includes interconnected room structures (floor plan) that provide service, and the architecture of an enterprise includes interconnected organization functions (organization plan) that provide service. Economic actors are in a race to find the best enterprise architecture. The race is on to become the dominant architecture that can best support the required changes, constantly adapting to multiple environmental factors (e.g., competitors, regulations, technologies, customer preferences, employees, partners, shareholders, etc.) while competing for collaborators.
About only a 100 years ago (five generations of people), the modern corporation arose. Recently, in the era of digital transformations, the rise of platform companies, such as Airbnb and Uber, are giving a new meaning to traditional notions of return on assets. With the divorce of ownership from control, a new design pattern for management and governance — and by means of these — a new design for enterprise architecture emerged. By facilitating continuity regardless of the succession plan and opening up new forms of financing, the pattern is being actively reused across industry sectors and is still rapidly evolving today.
Emergence of Service-Oriented Architecture
About 60 years ago (three generations of people), computer program- ming languages like COBOL were designed for enterprise business use. The power of mainframe computers with large-scale batch and transac- tion processing made possible the integration and operation of more and more applications that incorporate business knowledge. In this way, business processes, such as accounting, controlling, or personnel planning, were gradually transferred from humans to machines. The downside of decades of integration, expansion, and further development is the emer- gence of monolithic applications and monolithic enterprise architectures, characterized by high complexity and dependencies of interwoven pro- grams, by head monopolies of few employees, by accompanying closed- ness, high maintenance requirements, and slowness resulting from long release cycles.
In the late 1990s, service-oriented architecture (SOA) emerged as a paradigm for organizing and using shared modular service capabilities to enable modularity, flexibility, and openness. SOA service modules are built in a way that represents repeatable business activities. The underlying SOA design pattern always consists of the three roles of service provider, service broker, and service customer. Combined with principles, such as loose coupling, compatibility, and reusability of the service module, it became possible to create component-based applica- tions with high interoperability and without technology lock-in. In this way, SOA enables organizational benefits, such as openness to the use of service modules outside the enterprise, speed, scalability, and cost advantages. The SOA enterprise architecture has evolved significantly over the last 20 years (one generation) with improved governance and maturity models.
Emergence of Digital Attacker Platform Architecture
Today, traditional industries are under attack by digital rivals (such as Airbnb, Uber, and even Amazon) with business models and business operations based entirely on digital platforms. Despite the growing sophistication of traditional enterprise architecture, such as the SOA enterprise architecture, they are still being disrupted, as they do not allow fast-enough change against digital attackers.
Based on cloud technologies and open-source software platforms, companies do not have to install and operate software on their own. Software, infrastructure, and even whole technological platform stacks offered as microservices facilitate the emergence of platform companies based on the pattern of openness and connectivity. Platform companies are char- acterized by five roles: platform owner, platform provider, value proposition provider, complementor, and beneficiary. The strength of these digital platform architectures is to enable these roles by bringing together resources and data at breathtaking speed. Combined with low copying costs, digital platforms aggregate digital resources and thus build up an immensely high resource density—not simply more transistor per unit area on chips, but more interconnected fast-changing components from more vendors orchestrated more easily. And with it, the opportunities for the next attackers who will define the rules of the race by bringing the design pattern to act on this resource density to the table.
Emergence of Service Dominant Architecture
Service Dominant Architecture (SDA) is grounded in service-dominant (S-D) logic and service science and provides an organizing logic for shaping companies, service platforms, and service ecosystems through design patterns aimed at making it possible to build and orchestrate capabilities in a systematic way. SDA allows for rapid change and adoption of new technologies, including AI, to accelerate digital transformation and to turn resource density into true, market-accelerating service innovations. The goal is to make businesses better — more agile, more sense-and-respond, better able to keep up with and drive meaningful human-centered change in a fast-paced world, while also maintaining privacy, security, and regulatory compliance.
Based on platform technologies, SDA is a set of design patterns that enables responsible actors (e.g., individuals, companies, and organizations) to act in the context of openness and connectivity in a meaningful way and to organize service as a transdisciplinary process of value cocreation. SDA provides a transcending perspective on enterprise architecture by reimagining the enterprise in the terms of S-D logic, supporting five specific roles: (1) sense-and-respond cocreation interactions with actors (e.g., customers), (2) frictionless onboarding and participation of part- ners, (3) rapid integration of operant resources (including employees), (4) improved insights from data for all stakeholders, and (5) actor coordination by institutions as rules and norms (service catalog).
Consider again the example of buying a car. SDA’s roles allow it to onboard other partners such as telematics providers to collaborate on personalized value propositions, such as changing tires or picking up to inspect the vehicle based on driving behavior. Integrating the resources of more and more partners enables new combinatorial opportunities and value propositions that cover the entire spectrum of mobility, such as car sharing, bike rental, e-scooters. The customer interacts to benefit from the application of the capabilities offered by continually improv- ing value propositions. In this process, resources are integrated, and service is exchanged for service. With each transaction, all stakeholder data are updated in the data lake (set of operational data stores), leading to improved insights with the help of AI. This enables win-win-win relationships; on the one hand between car sellers and buyers with con- stantly improving mobility offers, and on the other hand, the data and the insights gained from it benefit the entire network.
The technical implementation of SDA can be compared to Lego. Open-source and cloud platform technologies form the base plate. Technical, functional, and business services are implemented as generic or specific bricks. Each brick is preconfigured with the five roles as systems. The base plate and the bricks are coordinated via the SDA service catalog that sets the rules and standards.
Once the bricks (technology systems consisting of microservices) are used by actors (service system), the process of actor engagement and value cocreation is organized and structured. After value is delivered in one sys- tem (e.g., by accumulating data), the system drives value for other SDA systems. For example, data are fed into the data lake (facilitating data ana- lytics), advanced forms of collaboration between human and technologi- cal actors — such as, workforce management as combinations of employer + AI, employee + AI, technology + AI —are enabled, capabilities become exchangeable and tradeable via the service catalog, and resource density is built.
Thus, SDA facilitates the reshaping of operating architectures of enterprises, service platforms, service ecosystems, and markets by mak- ing simple changes (e.g., digital solutions as value propositions) easy and hard changes (e.g., digital transformation and platform organizations) possible.
In a world of constant change and transformation, it is important to understand the ways that good architecture can make simple changes easy, and complex changes possible. While actor-to-actor networks spread and new connections are made, the density of resources and capabilities increases, and with it, the need for enterprises and other organizations to have a construction plan for reshaping the operating architecture. SDA is an emerging architecture based on S-D logic and service science that aims to clarify what enterprises should consider to better reshape their oper- ating model to be prepared for continuous upskilling (e.g., by exploiting AI) and to engage in the process of value cocreation.
The case of SIGNAL IDUNA Group
Braasch T. (2021) The agile insurer (https://www.strategyand.pwc.com/de/en/industries/financial-services/agile-insurer.html), strategy&
Digital health ecosystems: Voices of key healthcare leaders (2021), survey among key health leaders on how services in the ecosystem become relevant
Unleashing the power of digital health through ecosystems (2020, services and data as key enablers of health ecosystems)
Digital ecosystems for insurers: No one size fits all (2021, 5 basic principles for insurers in ecosystems)
Ecosystems and platforms: How insurers can turn vision into reality (2020)
How insurers can act on the opportunity of digital ecosystems (2021)