How often does the Innovation and Planning (IP) Iteration occur?
The Innovation and Planning (IP) Iteration is a special iteration that occurs during every Program Increment (PI). It serves as an estimating buffer for meeting PI Objectives and provides dedicated time for innovation, continuing education, PI Planning, and Inspect and Adapt events.
What are the minimum requirements for a Feature?
The minimum requirements for a feature are a name, a benefit hypothesis, and acceptance criteria12. A name is a brief and descriptive phrase that summarizes the feature. A benefit hypothesis is a statement that describes the expected outcome and value of the feature for the customer or user. Acceptance criteria are a set of conditions that the feature must satisfy to be accepted by the customer or stakeholder12.
Some additional information that might be helpful for you are:
* The other options (A, C, and D) are not the minimum requirements for a feature, but rather additional or optional elements that may be included in the feature definition.
* Data models are representations of the data structures and relationships that the feature requires or affects. Data models are not mandatory for a feature, but they may be useful for complex or data-intensive features3.
* Priority is the relative importance or urgency of a feature compared to other features. Priority is not a requirement for a feature, but it is a factor that influences the feature selection and sequencing4.
* Non-functional requirements (NFRs) are system qualities that guide the design of the solution and often serve as constraints across the relevant backlogs. NFRs are not specific to a feature, but they may affect the feature implementation or testing5.
* Architecture is the design and structure of the system that supports the solution. Architecture is not a requirement for a feature, but it is an enabler that facilitates the feature delivery.
What is a pattern for splitting Features into Stories?
A pattern for splitting Features into Stories is to use variations in data, which means identifying different types of data that the feature can handle and creating a story for each type. For example, a feature that allows users to upload files can be split into stories for different file formats, sizes, or sources. This way, the stories are independent, testable, and valuable12
* Story - Scaled Agile Framework
* User stories splitting by data variations and interfaces
What is defined as a product, service, or system delivered to the Customer?
A solution is defined as a product, service, or system delivered to the customer in SAFe. A solution can be a small mobile application built by a single Agile Release Train (ART) or a large automotive system of systems built by a network of Development Value Streams (DVSs) in a supply chain1. A solution may also be an insurance or banking product offered by a financial institution. Solutions can be the products a company sells or the internal products they use to run the business. They may provide direct value to an end-user or may be a component of a larger solution1.
* Solution - Scaled Agile Framework
What increases the effectiveness of System Demos?
Considering how and what to demo during Iteration Planning increases the effectiveness of System Demos, which are events that provide an integrated view of new features delivered by the Agile Release Train (ART) in each Iteration12. By thinking ahead of how and what to demo, the teams can:
* Align on the product vision and roadmap and ensure that the work items are aligned with the customer value and the PI objectives12.
* Define clear and testable acceptance criteria for each work item and plan how to verify them in the demo12.
* Identify and resolve any dependencies, risks, or impediments that may affect the demo12.
* Prepare the demo environment and the necessary tools and data to support the demo12.
* Practice the demo and rehearse the script and the roles of the presenters12.
Some additional information that might be helpful for you are:
* The other options (A, B, and C) are not actions that increase the effectiveness of System Demos, but rather actions that may reduce it.
* Spending a lot of time preparing for the demo may not be effective, as it may take away time and focus from the actual development and testing of the work items. Instead, the teams should aim for continuous integration and built-in quality practices that enable them to demo the work items as soon as they are done12.
* Limiting team attendance to minimize disruptions to the team may not be effective, as it may reduce the feedback and collaboration opportunities that the demo provides. Instead, the teams should invite and engage all the relevant stakeholders, such as Business Owners, executive sponsors, other Agile Teams, development management, and customers, to the demo12.
* Focusing on team-level metrics may not be effective, as it may not reflect the true value and progress of the integrated work across the ART. Instead, the teams should focus on system-level metrics, such as PI objectives, solution quality, and customer satisfaction, to evaluate the outcome and impact of the demo12.