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Solution definition

With an agreed-upon scope and use case, the project team can begin the process of defining the solution and selecting technologies to be used. The solution definition focuses on the system usage and the functional viewpoint. In addition, the information domain guides the data and analytic requirements for the solution.

The solution definition describes the market segment and business value, the current situation from an IT and OT perspective, the challenge, and the proposed solution. The solution definition also maps the functional requirements to the cross-cutting functions and system characteristics, security being the most important. 

A gap-fit analysis is useful to identify existing capabilities and gaps that need to be filled. In addition to identifying the gaps, the capabilities should be categorized as to what is common (platform foundation), and what is one-off (use case-specific).

Here is an outline for defining a solution definition:

  • Solution introduction
    • Describe the current situation from an IT and OT perspective
    • Describe the challenge
    • Propose the solution, or use case description
    • Identify the application domain: industry, line of business, functional
    • Identify dependencies
  • Business viewpoint
    • Business vision: Business perspective of the overall system, defines the why and what of the use case, and provides the criteria for validation.
    • Market segment: Defines the target market the use case is addressing.
    • Business value: Economic, societal, commercial, and good-will benefits. The value answers the why question from the business vision.
    • System objectives: Key objectives from the business viewpoint, as pertaining to the use case.
  • Describe the context, or target environment
    • Technology: Required technologies, existing technologies, legacy systems, integration requirements
    • Regulatory: Compliance and regulatory requirements, export restrictions, and so on
  • Usage and operational scenarios
    • Description
    • Participants and actors
    • Stakeholders and concerns
    • Pre-conditions
    • Workflow
    • Post-conditions
  • Key capabilities:
    •  Data:
      • Physical properties: Monitoring and action
      • Volume and velocity: Size and speed of the expected dataset processing
      • Aggregation: Aggregation requirements for communications and analytics
      • Variability: Anticipated growth, shrinkage of the data volume
    • Computations: Processing and computations required
    • Communication: Network details, scale, and connectivity requirements
    • Performance: Varies with the domain (for example, sensor readings per second)
    • Interoperability: Entities, actors, systems integrations required for the use case
    • Accuracy: Error tolerance and level of uncertainty
  • Key characteristics
    • Security, trust, and privacy
      • Reliability: Level of robustness and failure prevention
      • Resiliency: Level of fault-recovery capabilities
      • Behavioral: How the system behaves and interacts with humans or other systems
  • System requirements
    • Challenges and risks
      • Business challenges: Business model, competitive factors, regulations, and so on
      • Technical challenges: Performance, scaling, maturity, and unknown factors
      • Implementation challenges: Interoperability, testing, updating, and system migrations
      • Regulatory challenges: Government-mandated privacy, security, control, permissions, and so on
      • Deployment challenges: Integration, politics, and so on

 

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