The idea of a more detailed design document may seem old fashioned to someone who is used to working in small, agile development teams. After all, the Agile manifesto itself values working software over comprehensive documentation and emphasizes The most efficient and effective method of conveying information to and within a development team is face-to-face conversation. However, in large-scale, multiteam, multisite projects, a certain amount of documentation is required to ensure that all teams and stakeholders are aligned and working in synch. Working across organizational boundaries will add to the need for more detailed documentation of requirements and design decisions. Finally, some types of procurement contracts will require detailed specifications and SLAs (see Sourcing_and_Procurement). Given that an AIoT-enabled product or solution will contain different building blocks, such as AI, hardware, software, embedded components, etc., it is likely that it will face many of these constraints. Consequently, the AIoT Playbook proposes to create and maintain a product/solution architecture that captures key requirements and design decisions in a consistent manner.
AIoT Design Viewpoints and Templates
To provide a consistent and comprehensive design for AIoT-enabled products or solutions, the AIoT Playbook proposes a set of design viewpoints, each with a specific set of design templates:
- Business Viewpoint: Builds on the input from the Business Model, adds KPIs and planning details
- UX Viewpoint: Focus on how users are interacting with and experiencing the product or solution
- Data/Functional Viewpoint: Focus on the data and functional components of the AIoT solution
- Implementation Viewpoint: Adds details on the implementation aspects
- AIoT Product Viewpoint: Mapping to the agile product development perspective
It is important to note that the AIoT Playbook does not propose an excessive, RUP/waterfall-style level of documentation. The general idea is to provide a comprehensive yet lightweight set of design documents that enable efficient communication between the main stakeholders. The key to success here is to keep the design documentation on a level of detail where it is meaningful but not overly complex. The agile teams must be able to apply their own mechanism to derive requirements for their backlog and provide feedback to the overarching architecture in return. As will be discussed in the following, a central story map can be a powerful tool for keeping the design decision and the individual sprint backlogs in synch.
Important Design Considerations
It is important to accept that design documentation can rarely be seen as a stable document. The waterfall approach of fixing requirements and design decisions first will not work in most cases because of the inherent complexity, volatility of requirements and too many external and internal dependencies. The agile V-Model, for example, is specifically designed to support continuous updates of the overall system design. Each v-sprint (1) in the agile v-model must return to the design and match it against the learning from the previous sprint (2). This also means that the design documentation cannot be too detailed, since otherwise it will not be possible to perform a thorough review during each sprint planning session. The design templates provided in the AIoT Playbook aim to strike a pragmatic balance between comprehensiveness and manageability. The sprint backlogs for the different teams must be in synch with the overall design (3).
In most AIoT projects there will be certain parts of the project that will require a higher level of stability for the design documentation than others. This is generally true for all areas that require more long-term planning, e.g., because of procurement or manufacturing requirements, or to manage complex dependencies across organizational boundaries. This is a key problem that the solution design team must address. In many cases, this will also require some kind of architectural layering, especially in the data/functional viewpoint. In particular, the design must ensure that no stable system components have any dependencies on more volatile components. Otherwise, the changes to the volatile components will have a ripple effect on those components that are supposed to be stable (4).
Finally, it is important to keep in mind that product/solution design and organizational structure must be closely aligned (Conway's law). The design will usually include many features that require support from different technical layers. For example seat-heating-on-demand, which requires a smartphone component, a cloud component, and different components on the vehicle to work together to deliver this feature. The AIoT Playbook is proposing to define feature teams that are working across the different technical layers. Properly deriving the setup of these feature teams from the product/solution design will be key to success (5).
The design section of the AIoT Playbook is based on the fictitious ACME:Vac example, which is used to illustrate the different viewpoints and design templates. Robotic vacuum cleaners -- or short robovacs -- have become quite popular in the last decade and represent a multi-billion dollar market, with a number of different players offering a variety of different models. Many of the advanced models today utilize AI to optimize robovac operations, including automatic detection of room layouts, navigation and cleaning path optimization. As such, they are a very good example of a smart, connected product provided by a Digital OEM. Differences between the design requirements of an AIoT-enabled product (Digital OEM perspective) and a solution (Digital Equipment Operator perspective) are highlighted in each section.
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