Mastering Agile Product Delivery with SAFe

What is SAFe Agile Product Delivery?

SAFe Agile Product Delivery is a customer-centric approach to defining, building and releasing a continuous flow of valuable products and services.

SAFe Agile Product Delivery (ADP) reflects a profound shift from project-based to product-based delivery, hinged on creating value through a customer-centric approach. This customer-centricity involves continuously defining, building, and releasing products and services to deliver business value incrementally.

What is Business Agility according to SAFe?

Business Agility is the ability of an organization to compete and thrive by quickly responding to market changes and emerging opportunities with innovative business solutions.

In the Scaled Agile Framework (SAFe), Business Agility is defined as the intrinsic ability of an organization to adapt rapidly to market changes and seize emerging opportunities through innovative business solutions. It’s a multidimensional concept that touches every aspect of an organization’s operations.

Business Agility involves seven core competencies, and they are:

1. Lean-Agile Leadership: Leaders inspire and foster a Lean-Agile culture through modeling behaviors, teaching principles and practices, and guiding the organization toward agility.
2. Team and Technical Agility: Agile teams apply practical Agile and Scrum methodologies complemented by technical practices that ensure quality and efficiency.
3. Agile Product Delivery: As discussed earlier, a customer-centric approach to continuous value delivery.
4. Enterprise Solution Delivery: Large solutions are developed with Lean engineering, coordination practices, and DevOps capabilities (Leffingwell, 2018).
5. Lean Portfolio Management: Strategic alignment of the portfolio with enterprise strategy, decentralizing decision-making, and applying Lean budgeting.
6. Organizational Agility: The ability of an organization to transform its operations swiftly and flexibly, fostering innovation and driving faster market responses.
7. Continuous Learning Culture: A culture that encourages innovation, risk-taking, and continuous learning to drive growth and development.

The seven competencies form a holistic system, fostering Business Agility by enabling rapid responses to opportunities and threats, driving innovation, and promoting adaptive and resilient organizations.

What is the purpose of the SAFe Agile Product Delivery?

SAFe Agile Product Delivery continuously delivers value through customer-centric, flexible, and integrated product development and release processes.

SAFe Agile Product Delivery serves four essential purposes that support the continuous delivery of value in a customer-centric way, and they are:

1. Continuous Delivery of Value by releasing products and services when needed rather than following a rigid release schedule (Kniberg & Skarin, 2010).
2. Customer Centricity emphasizes understanding and meeting customer needs, fostering a customer-centric approach that drives business value and enhances customer satisfaction (Leffingwell, 2018).
3. Flexibility and Responsiveness: With ‘Develop on Cadence, Release on Demand,’ Agile Product Delivery allows organizations to respond swiftly and effectively to market changes and emerging customer needs.
4. Integration of Development and Operations: Through the continuous delivery pipeline, Agile Product Delivery unifies the development and operations aspects of software delivery, promoting efficiency and adaptability (Humble & Farley, 2010).

What are the objectives of the SAFe Agile Product Delivery?

The objectives of SAFe Agile Product Delivery are to understand customer needs, deliver value continuously, and maintain organizational flexibility and adaptability.

The SAFe Agile Product Delivery competency aims to fulfill the following five objectives:

1. Understand Customer Needs: By placing customers at the center of the product development process, Agile Product Delivery ensures that product and service offerings align with customer expectations and needs (Leffingwell, 2018).
2. Deliver Value Continuously: The goal is to consistently deliver value to the customer, following the cadence for development and releasing as per market demand (Kniberg & Skarin, 2010).
3. Ensure Organizational Flexibility and Adaptability: Agile Product Delivery helps organizations become agile and adaptable to respond to market conditions or customer requirements rapidly. This is achieved through the ‘Develop on Cadence, Release on Demand’ principle and the integration of development and operations via the Continuous Delivery Pipeline (Humble & Farley, 2010).
4. Streamline Development and Operations: By embracing DevOps and the Continuous Delivery Pipeline, Agile Product Delivery encourages organizations to break down silos between the development and operations teams, fostering a collaborative culture that speeds up value delivery.
5. Co-create with Customers: Agile Product Delivery promotes the co-creation of value with customers, improving the suitability of the product or service to customer needs and increasing customer satisfaction and loyalty (Leffingwell, 2018).

What are the three dimensions of SAFe Agile Product Delivery?

The three dimensions of SAFe Agile Product Delivery are Customer Centricity, Develop on Cadence with Release on Demand, DevOps, and the Continuous Delivery Pipeline.

Each of the three dimensions of SAFe Agile Product Delivery provides a unique aspect of the product delivery process supporting a continuous flow of value to the customer.

1. Customer Centricity promotes a deep understanding of customers’ needs and behaviors. By involving customers in co-creation, organizations ensure that products and services meet real customer needs, thereby driving business value (Leffingwell, 2018).
2. Develop on Cadence, Release on Demand advocates for a predictable development schedule but with flexibility in product release. It enables a rhythm to the work while allowing the organization to respond to market needs as they arise, delivering value when the customer or market demands it (Kniberg & Skarin, 2010).
3. DevOps and the Continuous Delivery Pipeline signifies the integration of software delivery operations and development aspects. It is a foundation for continuously releasing value through activities like Build, Continuous Integration, Continuous Deployment, and Release on Demand. This capability ensures a seamless value stream from idea to operational solution, promoting organizational responsiveness and adaptability (Humble & Farley, 2010).

Customer Centricity and Design Thinking

Customer Centricity focuses on delivering value by prioritizing customer needs, while Design Thinking uses empathy and experimentation to solve complex problems with innovative solutions.

Customer Centricity is a business approach that aligns the organization’s operations and strategy with customer needs and expectations, ensuring the delivery of maximum value (Kim & Mauborgne, 2014). It emphasizes building long-term relationships, leading to customer loyalty and business sustainability.

On the other hand, Design Thinking is a problem-solving framework that employs empathy, experimentation, and iteration to address complex issues (Brown, 2009). It encourages understanding the user’s perspective, ideating possible solutions, prototyping, and testing these ideas. This iterative process aims to innovate effectively, resonating with the end-users needs and preferences.

What is Customer Centricity?

Customer-centricity prioritizes customer needs in designing and delivering whole-product solutions, promoting positive experiences and value through all enterprise-offered products and services.

Customer-centricity refers to an organizational mindset that centralizes all activities around the customer’s needs and preferences. In the SAFe Agile Product Delivery context, this philosophy pertains to an enterprise’s entire product and service ecosystem (Denning, 2018). It involves a systematic approach to understanding customers’ wants, needs, and values.

A customer-centric approach impacts all aspects of an organization. An in-depth understanding of customer requirements informs product design, development, and delivery. Communication with customers is regular and meaningful, allowing the organization to respond proactively to customer needs or changes in market conditions.

In a SAFe Agile Product Delivery context, customer-centricity is about delivering complete solutions, not just isolated products or services. A holistic focus helps create experiences that meet or exceed customer expectations. This approach ensures that every aspect of the product or service, from initial design to final delivery, is aligned with the customers’ needs and contributes to their overall satisfaction.

Moreover, customer-centricity extends beyond mere transactions. It also involves building strong relationships with customers and fostering trust. By adopting this approach, businesses can engender loyalty, encouraging customers to advocate for the brand and its products or services (Beck & Fowler, 2001).

Why is Customer Centricity important?

Customer centricity drives profitability, improves employee engagement, and boosts customer satisfaction, leading to business sustainability, resiliency, and alignment with its mission.

Customer centricity’s importance stems from its profound impact on business success. By understanding and addressing customer needs, businesses can offer products and services that resonate with their target market, increasing sales and revenue (Anderson, 2016).

1. Customer-centric businesses tend to be more profitable. This is because products and services designed with a deep understanding of customer needs typically perform better in the market. Not only do they sell more, but they can also command higher prices, leading to increased margins.
2. A customer-centric culture boosts employee engagement. When staff members see the positive impact of their work on customers, it reinforces their sense of purpose and commitment to the organization. This can lead to higher productivity levels and improved performance across the board (Agarwal & Dutta, 2015).
3. Customer-centric businesses tend to have more satisfied customers. These customers are likelier to remain loyal to the brand, providing a stable revenue stream. Furthermore, satisfied customers recommend the company to others, leading to new business opportunities (Kumar et al., 2010).

In the public sector, customer centricity helps nonprofits and governments become more resilient, sustainable, and better aligned with their mission. By focusing on the needs of their constituents, these organizations can deliver services more effectively and efficiently, fulfilling their obligations and achieving their objectives.

What is the Customer Centricity Mindset?

The Customer Centricity Mindset centralizes customer needs in decision-making, cultivating positive experiences and engagement, and augmenting customer value through enduring relationships.

The Customer Centricity Mindset is a philosophy that places customer needs at the center of all business activities and decisions, fostering a value-oriented and customer-pleasing environment. This approach promotes cultivating long-term customer relationships, often yielding customer value in unexpected ways.

Five strategic actions hallmark this mindset:

1. Focus on the Customer: Agile teams utilize market research and user data to align the organization toward targeted user segments.
2. Understand the Customer’s Needs: A significant investment of time goes into discerning customer needs and creating solutions that address these needs, resulting in value-added products and services.
3. Think and Feel Like the Customer: Agile teams employ empathy to comprehend the world from the customer’s viewpoint, providing insights to meet or surpass customer expectations.
4. Build Whole Product Solutions: Organizations design comprehensive solutions to meet customer needs from initial use and long-term engagement, with the flexibility to adapt to changing customer needs.
5. Create Customer Lifetime Value: Organizations progress from a transactional mentality, focusing on nurturing customer relationships over the solution’s lifetime, fostering loyalty and sustainable revenue.

Focus on the Customer

Focusing on the customer involves employing user and market research to center and align the organization’s strategy on specific user segments.

“Focus on the customer” implies a business approach where organizations employ user and market research, develop personas, and strategically align themselves toward specific, targeted user segments. It emphasizes customer needs, desires, and behaviors, using these insights to guide decision-making processes throughout the organization. Essentially, it involves making the customer the nucleus of all organizational activity. By fostering a culture that prioritizes the customer, organizations can better understand and anticipate their needs, improve the customer experience, and ultimately build stronger, more fruitful relationships (Leffingwell, 2011).

Market Research

Market research involves systematic gathering, recording, and analyzing data about customers, competitors, and the market to aid strategic decision-making.

Market research systematically gathers, records, and analyzes data about customers, competitors, and the market. Its primary purpose is to enhance decision-making and reduce uncertainty by providing relevant data to solve marketing challenges. Market research provides detailed insights into the following five dimensions:

1. Customer behavior and preferences: This encompasses understanding customer purchasing habits, attitudes, and needs. It also helps predict how these trends might change (Armstrong & Kotler, 2010).
2. Competitive landscape: Understanding the competition, their strengths and weaknesses, and their strategy helps organizations effectively position their product or service.
3. Market trends: Identifying and predicting trends ensures the product or service aligns with market demand.
4. Market size and potential: Quantifying the market helps organizations assess viability and potential profitability.
5. Brand perception: Understanding how customers perceive and engage with your brand is essential for strategic planning and product development.

By using market research, organizations can make informed decisions, mitigate risks, and create strategies that align with their target audience’s needs and expectations.

User Research

User research involves understanding user behaviors, needs, and motivations through observation techniques, task analysis, and other feedback methodologies.

User research is a field of study that focuses on understanding user behaviors, needs, and motivations. This process involves various qualitative and quantitative methods, including observation techniques, surveys, and task analysis. The aim is to inform the process of product design and development, ensuring that the product aligns with the needs and expectations of its users. There are five aspects to user research, and they are:

1. User needs and expectations: Identifying and understanding what users want from a product or service (Norman, 2013).
2. User behavior: Observing how users interact with the product to understand their behavior, frustrations, and needs.
3. User feedback: Gather user feedback to improve the product or service and better meet their expectations.
4. Usability testing: Testing the product or service with users to evaluate its effectiveness, efficiency, and satisfaction.
5. Persona development: Creating detailed profiles of user types to aid in the design and development of the product or service.

Understanding the Customer’s Needs

Understanding the customer’s needs involves identifying and crafting solutions that specifically address these needs.

“Understanding the customer’s needs” encourages organizations to delve deep into their customer’s mindset, desires, and pain points. This understanding is typically achieved through direct customer interactions, surveys, market research, user testing, and data analytics. Organizations can better identify and build products or solutions that directly address customer needs by investing significant time and resources in this process. It involves understanding what customers want, why, and how the organization’s offerings can provide value. This understanding is fundamental to creating products and services that truly resonate with customers (Cohn, 2010).

Think and Feel Like the Customer

Thinking and feeling like the customer entails applying empathy to perceive the world from the customer’s perspective.

“Think and feel like the customer” involves empathizing with customers, striving to perceive the world from their perspective, and experiencing their challenges. This allows organizations to understand the emotional and functional needs of customers. It facilitates a deeper connection and the ability to anticipate and fulfill customer needs, often before they arise. Essentially, it’s about aligning with the customer’s journey and using their perspective to drive product development, marketing strategies, and overall business operations. Empathy, in this context, becomes a powerful tool for fostering customer-centric innovation (Denning, 2018).

Designing with Empathy

Designing with empathy involves creating solutions from the customer’s perspective, appreciating their difficulties, roles, and context to address their needs.

Designing with empathy is a principle that guides the development of products and services from the customer’s perspective. It requires teams to set aside their preconceived notions and instead, immerse themselves in the customer’s world using the following seven techniques:

1. Understanding the customer’s viewpoint: Teams learn and appreciate the challenges customers face, their roles, and the context in which they operate (IDEO, 2015).
2. Conducting empathic research: Teams undertake activities such as Gemba walks, which involve visiting the customer’s workplace to observe their processes firsthand, fostering a better understanding of their needs.
3. Addressing emotional and aesthetic needs: Designing with empathy moves beyond functional needs and considers how a product can meet the customer’s emotional and aesthetic desires.
4. Meeting ergonomic requirements: Consideration is given to physical attributes of the product, such as the placement of physical features, that impact user experience.
5. Incorporating implicit needs: Attributes that users might not explicitly requests, such as performance, security, and compliance, are considered as they’re essential for product viability.
6. Evaluating solution impact: Teams assess how the solution might impact the solution context and affected groups.
7. Considering solution architecture: The product’s design must support operations, maintenance, and customer needs.

Build Whole Product Solutions

Building whole product solutions involves designing comprehensive products for user needs, ensuring optimal initial and long-term user experiences.

“Build whole product solutions” advocates for designing and delivering comprehensive, end-to-end solutions that fully address the user’s needs. This means solving a specific problem for the user and ensuring that the entire user experience, from initial discovery to long-term usage, is optimal. It involves a holistic understanding of the customer’s journey and the touchpoints where the product interacts. A whole product solution evolves as needed, incorporating user feedback and adapting to changing user needs and market conditions. The goal is to deliver a seamless, integrated experience that enhances customer satisfaction and loyalty (Kim & Mauborgne, 2014).

Whole Product Thinking

Whole Product Thinking views a product beyond its features, focusing on the entire customer experience from purchase and use to support, ensuring comprehensive product value.

Whole Product Thinking emphasizes that a product is not just a collection of features or functionalities. Instead, it is the entire gamut of experiences that a customer goes through from the moment they consider purchasing the product, through usage, and finally, to any necessary support or upgrade options.

This paradigm stems from the understanding that customers derive value from the product’s core functionality and various aspects. A breakdown of this concept comprises five distinct stages:

1. Minimum Viable Product (MVP): This early product version is designed to validate or refute the benefit hypothesis. It provides real customers with a usable product, allowing enterprises to gather validated learning and establish the core product features.
2. Core Product: It fulfills the basic functional needs of the customer and is sufficient to perform the tasks minimally. However, it may lack certain features or attributes that customers expect from the product.
3. Expected Product: It includes the core product and the additional benefits customers expect. Examples include customer support during the warranty period, online help, documentation, etc.
4. Augmented Product: This level delivers additional features, benefits, attributes, or related services that differentiate the product from its competitors and delight customers. This could include free add-ons, unique services, or added functionality.
5. Potential Product: This stage envisions the features and other attributes needed to attract and retain customers indefinitely. It’s informed by market and user research, stimulating longer-term strategic planning and creating opportunities for sustainable product advantages.

While the journey starts with the MVP, the goal is to realize the potential product. Whole Product Thinking facilitates the growth and development of a product in a way that’s attentive to the needs and expectations of customers. By implementing this thinking, organizations meet and exceed customer needs, thus building a stronger, more robust relationship with their customer base. The end result is a product that’s competitive, customer-focused, and responsive to market dynamics (Kotler, Levitt, & Moore, as cited in Moore, G. A. (1999). Crossing the chasm: Marketing and selling high-tech products to mainstream customers).

Create Customer Lifetime Value

Creating customer lifetime value involves prioritizing the customer relationship over the product’s life rather than focusing solely on transactions.

“Create customer lifetime value” means shifting from a transactional mindset to a long-term relationship mindset. Instead of focusing solely on making a sale, it’s about cultivating and nurturing customer relationships over the product or service’s life. This involves providing continuous value through high-quality customer service, regular updates or enhancements to the product, personalized experiences, and rewarding customer loyalty. Investing in customer relationships increases customer satisfaction and loyalty and amplifies opportunities for repeat business and referrals. This, in turn, enhances the overall profitability and sustainability of the business. Creating customer lifetime value is a long-term investment that pays off through a loyal customer base and a sustainable revenue stream (Reichheld & Sasser, 1990).

Leveraging market rhythms and events

Leveraging market rhythms and events means optimizing product release timing in line with recurring market trends and significant one-time events to maximize customer value.

Leveraging market rhythms and events involves identifying and aligning the timing of product releases with these specific patterns and occurrences. In the SAFe Agile Product Delivery context, this concept is particularly relevant for achieving optimum customer value and satisfaction. It entails:

• Understanding recurring market rhythms and planning product enhancements or releases accordingly.
• Anticipating significant market events and strategizing product releases to maximize potential benefits or mitigate risks.

What are “market rhythms”?

Market rhythms are predictable, recurrent events influencing customer behavior and product value.

In the context of Agile Product Delivery, market rhythms refer to cyclical or seasonal trends that regularly occur in the market. These predictable patterns significantly influence customer behaviors, needs, and perceptions of product value. Understanding market rhythms allows organizations to monitor product releases or updates for maximum impact strategically. For instance:

• Retail businesses anticipate increased activity during the holiday season and may plan to roll out new features or enhance system capacity to handle higher transaction volumes.
• Tax preparation software companies might aim to release significant updates ahead of tax season when customers need these services the most.
• Fitness and wellness companies might release new programs or features at the beginning of the year, capitalizing on widespread New Year’s resolutions to improve health.

What are “market events”?

Market events are significant, often one-time occurrences that can materially affect a product or solution’s market standing.

Market events are specific, often one-time occurrences that substantially impact a product or solution. These events could be external, such as changes in government regulations or shifts in the competitive landscape, or internally created, like a company’s product launch or annual user conference. Anticipating market events enables organizations to strategically time their product releases or updates to optimize value and mitigate risks. Three examples of market events:

• A change in data privacy regulations might prompt a software company to update its product before the regulation’s implementation date.
• A significant competitor’s product launch could lead a company to strategically time its release to differentiate its product or address the competitor’s weaknesses.
• A company might time a significant product release to coincide with its annual user conference, leveraging the event to generate buzz and facilitate immediate user feedback.

What is “Design Thinking”?

Design Thinking is a customer-centric process focusing on understanding the problem, its context, and solution evolution for sustainable and profitable product development.

Design Thinking, a central concept within the SAFe’s Agile Product Delivery competency, is a methodology grounded in empathy and experimentation to innovate solutions. The process incorporates five stages – Empathize, Define, Ideate, Prototype, and Test- designed to encourage teams to understand their users, challenge assumptions, and redefine problems to identify alternative strategies and solutions. It is not a linear process; teams often iterate through stages multiple times before arriving at a solution.

In the SAFe Agile Product Delivery context, Design Thinking helps teams go beyond traditional feature-function focus. It promotes a deep understanding of the problem to be solved, the context in which the solution will be used, and the evolutionary nature of the solution over its lifecycle. This mindset enables the creation of desirable products that meet customer needs effectively while ensuring profitability and sustainability. The inclusion of Design Thinking within Agile Product Delivery competency reflects a commitment to delivering solutions that are desirable, feasible, viable, and sustainable (Leffingwell, 2020).

Why is Design Thinking important?

Design Thinking is vital as it ensures desirable, feasible, viable, and sustainable solutions, prioritizing user needs over mere requirement fulfillment.

Design Thinking’s importance emerges from its fundamental shift in approach to product development:

1. User-Centric Approach: Unlike traditional waterfall methods focusing on fulfilling stated requirements, Design Thinking puts user needs at the forefront. The aim is to avoid unusable or ignored features that frustrate users and fail to meet business goals (Leffingwell, 2020).
2. Fosters Innovation: The technique employs divergent and convergent methods to understand a problem, design a solution, and deliver it to the market. This approach encourages creative problem-solving and drives innovation.
3. Success Metrics: Design Thinking prompts the redefinition of success metrics. There are four essential design thinking success metrics, and they are:
   1. Desirable – Do users want the solution?
   2. Feasible – Can we effectively deliver the solution?
   3. Viable – Does solution creation offer more value than cost?
   4. Sustainable – Are we considering the product-market lifecycle proactively?
4. Evolution Over Lifecycle: Regular application of Design Thinking advances the solution’s natural market lifecycle, aligning product evolution with market needs and trends. This factor contributes to a product’s longevity and success.

Understanding the Problem

“Understanding the problem” in Design Thinking involves empathizing with users, defining needs, and contextualizing the issue. Discover and Design are integral activities in this process.

“Understanding the problem” signifies the start of the Design Thinking process. It emphasizes:

• Discover: Investigating the problem space by gathering and analyzing user data, examining the problem, and understanding its context. This phase reveals valuable insights that inform solution design.
• Define: Creating solution ideas for the problem discovered. This phase demands collaboration and creativity as the team brainstorms, selects, and refines ideas to address the problem (Liedtka, 2018).

The aim is to grasp user experiences, identify needs, and comprehend the problem’s impact concerning the product or service. This detailed understanding sets the groundwork for ideation and problem-solving, providing a clear direction for the design team (Cagan, 2018).

Discover

“Discover” involves researching to gather in-depth insights about the problem, the users, and the context, employing methods like gemba walks, market research, and user research.

The “Discover” phase in the Design Thinking process is an extensive exploration and research phase that builds on the understanding of the problem:

1. Gemba Walks: Direct observation of users in their natural environment offers a first-hand understanding of user experiences, behaviors, and needs.
2. Market Research: Market studies provide insight into the competitive landscape, trends, and market needs, supporting strategic decision-making.
3. User Research: Interviews, surveys, and other user research methods yield deep user insights, enriching the understanding of user perspectives.
4. Ethnographic Research: This method allows a deeper understanding of the cultural, social, and personal factors influencing user behaviors and preferences.
5. Synthesis: The findings from these activities are combined to form a comprehensive understanding of the user, the context, and the problem.

Define

“Define” refines and focuses the problem statement based on the discovery phase, using personas and empathy maps to represent users.

The “Define” stage in the Design Thinking process aims to crystallize the problem statement and establish a clear direction for ideation:

1. Personas: Fictional representations of user segments are created, consolidating user insights and facilitating user-centric design.
2. Empathy Maps: Empathy maps capture user thoughts, feelings, actions, and pains, enhancing empathy and insight.
3. Point of View Statements: These statements articulate the user’s needs and insights, forming the basis for solution ideation.
4. How-Might-We Questions reframe problems into opportunities, sparking creative problem-solving and innovative thinking.

Designing the Right Solution

“Designing the right solution” involves ideating, prototyping, and iterative testing for optimal user satisfaction.

Designing the right solution is a pivotal phase in the Design Thinking process. It focuses on the following:

• Develop: Refining selected solutions into functional products. The prototypes are iteratively improved based on user feedback to create a usable product that meets user needs effectively.
• Deliver: Bringing the finalized product to the market. This phase involves implementing the developed product and ensuring it delivers the intended value to end users (Kim, 2015).

The process commences with ideation, with the team generating a wide array of potential solutions to the defined problem. Prototypes are then created and tested with users, allowing the team to gather feedback and learn from their interactions. This iterative cycle of prototyping and testing continues until a solution offering maximum user satisfaction and value is identified.

Develop

“Develop” transforms the selected solutions into detailed designs using journey maps and story mapping.

The “Develop” stage of Design Thinking is a critical transition from ideation to tangible design:

1. Journey Maps: Teams create journey maps to understand and design user interactions with the solution over time.
2. Story Mapping: Story mapping breaks down the solution into user stories, offering a detailed view and prioritizing features.
3. Wireframes and Mockups: Teams create wireframes and mockups to visualize the solution, providing an early view of the user interface.
4. Feedback Loops: Regular user feedback and team reviews ensure the solution meets user needs and expectations.

Deliver

“Deliver” involves creating a tangible prototype or Minimal Viable Product (MVP), which is tested and iterated based on feedback.

The “Deliver” stage in the Design Thinking process brings the solution to life:

1. Prototype Creation: Teams build a tangible representation of the solution. Prototypes help test the solution’s viability and collect user feedback.
2. Iterative Development: Teams continually refine the prototype based on user feedback, ensuring the final product meets user needs and expectations. The feedback loop propels ongoing improvement.

What is “Lean UX”?

Lean UX is a team-based approach prioritizing iterative learning and user outcomes over ideal designs in product development.

Lean User Experience (Lean UX) denotes a significant paradigm shift in product development, placing considerable emphasis on the experiences of the user and customer outcomes. It aims to eliminate wastage, in line with the principles of Lean and Agile, by reducing the focus on documenting extensive design plans and concentrating on obtaining frequent and immediate feedback from users (Gothelf & Seiden, 2013).

Traditional UX roles, which primarily revolve around the execution of design elements and hypothesizing how users might interact with a system, get extended under Lean UX. This approach adopts a more comprehensive view of a Feature’s existence, necessary functionality, and benefits it delivers. It fosters a more profound understanding of users, accounting for their needs, wants, and constraints within their operational context.

UX is essentially the perception users have about a system’s ease of use, utility, and effectiveness of the user interface. Integrating UX design into rapid iteration cycles often proves challenging when using Agile methods. Teams may rework numerous designs while attempting to manage incremental deliverables’ development. However, Lean UX resolves this issue by integrating Agile development with Lean Startup implementation approaches, enabling teams to handle intricate and seemingly subjective user interactions more effectively.

SAFe Agile Product Delivery embodies this thinking within its principles and practices. Agile teams and Agile Release Trains (ARTs) employ Lean UX processes to maintain rapid development, quick feedback, and a holistic user experience that meets and exceeds user expectations.

Why is “Lean UX” Important?

Lean UX bridges the gap between user experience design and Agile methodologies, promoting fast feedback and user-focused outcomes.

Lean UX plays a significant role in mitigating challenges encountered when integrating UX design into Agile methodologies for four specific reasons, and they are:

1. Agile Integration: In Agile settings, it can be strenuous to concurrently facilitate rapid iteration cycles and full-stack implementations of new functionalities, particularly considering the subjective nature of user interactions. Lean UX streamlines this process, allowing Agile teams to manage complex user interactions (Nielsen, 2012) efficiently.
2. User-Centered Focus: By concentrating on iterative learning and quick feedback, Lean UX ensures the development of genuinely user-centric products. It uses real user feedback for iterative improvements, reducing reliance on assumptions and aligning better with business objectives.
3. Waste Reduction: Aligning with the Lean and Agile principle of waste reduction, Lean UX minimizes unnecessary reworks associated with traditional design processes, leading to more efficient resource usage.
4. Shared Understanding: Lean UX fosters a shared understanding within teams, resulting in less friction and more effective communication, enhancing overall team productivity.

What is the SAFe Lean UX Process?

Benefit Hypothesis

The “Benefit Hypothesis” is an initial assertion about a feature’s expected business result created by Agile teams and UX designers in the Lean UX process.

In the SAFe Agile Product Delivery Lean UX process, the “Benefit Hypothesis” step commences the design journey by formulating an assumption about the prospective business outcome of a feature. Agile teams and UX designers use this step to eschew Big Design Up-front (BDUF), recognizing the impossibility of predicting the perfect solution. Instead, they propose a hypothesis detailing the measurable benefit to the end user or business.

The Feature and Benefits (FAB) matrix, a tool provided by SAFe, assists in documenting this hypothesis as the design progresses through Continuous Exploration, part of the Continuous Delivery Pipeline (CDP). The matrix includes a concise phrase indicating the name and context of the feature alongside its corresponding benefit hypothesis.

Interestingly, practices rooted in Design Thinking propose a rearrangement of the feature benefit hypothesis elements. They recommend identifying the customer benefits first and then deciding the features that might meet these needs.

Outcome measurement occurs in the CDP’s Release on Demand segment, preferably employing leading indicators, as explained in “Innovation Accounting,” to assess how well the new feature fulfills its benefit hypothesis.

Collaborative Design

“Collaborative Design” in the SAFe Lean UX process involves collective ideation and refining of problem understanding, removing the need for early ‘pixel-perfect’ designs.

In traditional UX design, a few specialists, endowed with unique talents and training, were predominantly responsible for the design process. The goal was typically to create ‘pixel-perfect’ designs before implementation. However, Lean UX dramatically transforms this practice.

In the SAFe Lean UX process, “Collaborative Design” represents a significant shift from the traditional model, recognizing that many perspectives contribute to a successful design. This step integrates Continuous Exploration, which assists in refining understanding of the problem and soliciting input from a diverse group of stakeholders, including:

• Architects
• Customers
• Business Owners
• Product Owners
• Agile Teams

These participants work together to refine the problem and produce artifacts such as personas, empathy maps, and customer experience maps to represent their evolving understanding.

The “Collaborative Design” stage aims to deliver consistent user experience across different system elements or channels and even different products from the same company. Achieving this consistency requires balancing decentralized decision-making with centralizing certain reusable design assets. For instance, creating a design system with a set of standards that include:

• Editorial rules, style guides, voice and tone guidelines, naming conventions, standard terms, and abbreviations
• Branding and corporate identity kits, color palettes, usage guidelines for copyrights, logos, trademarks, and other attributions
• UI asset libraries, including icons, templates, standard layouts, and grids
• UI widgets, like button designs

These centralized assets form part of the Architectural Runway, supporting decentralized control while acknowledging the need for some centralized design elements.

Building a Minimum Marketable Feature

The “Building a Minimum Marketable Feature” step in the SAFe Lean UX process involves developing the smallest viable feature that provides customer value and validates the benefit hypothesis.

Building a Minimum Marketable Feature (MMF) in the SAFe Lean UX process comes after formulating a hypothesis and design. In this step, Agile Release Trains (ARTs) and teams work to implement the feature’s functionality at the minimum level at which customers can recognize any value. This MMF also allows teams to determine whether the benefit hypothesis is accurate.

The MMF builds upon SAFe Principle #4 – Build incrementally with fast, integrated learning cycles, aiming for rapid implementation and evaluation. Teams might use Set-Based Design to preserve options while defining the initial MMF, utilizing various approaches from low-fidelity mockups to a vertical thread of the MMF for feedback.

Evaluating

The “Evaluating” step in the SAFe Lean UX process involves assessing the Minimal Marketable Feature (MMF) using various methods to determine if it meets the desired outcomes.

Following the development of an MMF, its effectiveness and alignment with the benefit hypothesis is evaluated. The SAFe Lean UX process provides four methods to determine if a feature is yielding the expected outcomes, and they are:

1. Observation: Directly observing system usage allows one to understand user context and behaviors.
2. User Surveys: A straightforward end-user questionnaire can quickly garner feedback when direct observation isn’t possible.
3. Usage Analytics: Lean-Agile teams incorporate analytics into their applications to validate initial use and supply the telemetry needed for a Continuous Delivery model. This telemetry provides continuous operational and user feedback from the deployed system.
4. A/B Testing: This method involves comparing two samples to accommodate the reality that user preferences are unknowable beforehand. Teams can implement multiple alternatives for crucial user activities wherever practical and economically feasible. These alternatives can be tested using mockups, prototypes, or even full-stack implementations. Different versions might be deployed to multiple user subsets, possibly sequenced over time, and measured via analytics.

How do you implement Lean UX in SAFe?

Implement Lean UX in SAFe by establishing a LUXCE, preparing for the PI, participating in PI planning, and executing PI with Lean UX principles.

1. Implement a LUXCE: Establish a Lean UX Center of Excellence (LUXCE) for each value stream, responsible for design standards, governance, and decentralizing decision-making.
2. Prepare for the PI: Engage the LUXCE in economic prioritization, refine epics into features, and prepare benefit hypotheses to test early in the PI.
3. Participate in PI Planning: During the event, the LUXCE communicates the UX vision, consults with teams, and assists in crafting PI Objectives.
4. Execute PI with Lean UX: The LUXCE continues to support Agile teams in PI execution, manages shared backlogs, facilitates collaborative design, incorporates feedback, and focuses on building UX enablers.

How do you implement a Lean UX Center of Excellence (LUXCE) in SAFe?

In SAFe, a Lean UX Center of Excellence (LUXCE) is established to ensure consistency and governance and provide resources for decentralized decision-making within each value stream.

Implementing a LUXCE in SAFe involves the following steps:

1. Integration at All Levels: Lean UX is integrated at all levels of scaled development, from the value stream to the Agile team.
2. Decentralized Decision-Making: Most Lean UX decisions are made at the team level, as close to the problem as possible.
3. Lean UX Experts: While not typically sufficient in number for individual team collaboration, these experts maintain strong relationships with a few teams and ideally are embedded in a hybrid, decentralized model.
4. Lean UX Discipline: Including Lean UX expertise in an Agile team is essential for implementation, collaborative UX design, and testing Minimum Marketable Feature (MMF) hypotheses.
5. Establishing LUXCE: A small, centralized LUXCE is created for each value stream to provide consistency and governance across solution components.
6. Portfolio-Aligned Community of Practice: This additional layer of governance aligns the organization’s portfolios, communicating branding standards and other considerations across all solutions.

How do you prepare for the PI in the context of Lean UX in SAFe?

In SAFe Agile Product Delivery, preparing for the PI involves Lean UX thinking in economic prioritization, refining Epics, defining MMFs, setting benefit hypotheses, and creating UX enablers.

Preparing for the PI in Lean UX in SAFe includes six activities, and they are:

1. Lean UX Thinking: This is incorporated into the economic prioritization of the candidate recommended for the PI.
2. Involvement of LUXCE: LUXCE is a partner from the moment Epics enter the Portfolio Kanban funnel state, assisting in refining Epics into associated features.
3. Refining Epics: The goal is to create MMFs with clear, measurable, testable, and achievable benefit hypotheses within a PI.
4. Defining MMFs: These provide an economic Weighted Short Job First (WSJF) measure to prioritize the Epic into the implementing Portfolio Kanban state.
5. Setting Benefit Hypotheses: Using Set-based design and Principle #3, these hypotheses are developed to test early in the upcoming PI.
6. Creating UX Enablers: Like the Architectural Runway, a UX Runway is maintained through Lean UX enablers like design systems, libraries, style guides, and templates to facilitate quick testing with customers.

What is the role of the LUXCE during the PI Planning event in SAFe?

The LUXCE plays a vital role in PI Planning, contributing to communication, consultation, refinement, and planning around the PI vision with Agile teams and stakeholders.

During the PI Planning event in SAFe, the Lean UX Center of Excellence (LUXCE) has five key responsibilities, and they are:

1. Communication: The LUXCE communicates the UX vision and explains how it complements the strategies. They ensure a shared understanding of prioritized features, benefit hypotheses, and minimum necessary artifacts.
2. Consultation: During team breakouts, Lean UX experts should consult the teams they work with to facilitate the collaborative design process.
3. Refinement and Planning: Lean UX experts help to break out stories from features, plan benefit hypothesis tests, identify associated dependencies and Lean UX enablers, and maximize feedback incorporation loops into early PI iterations.
4. Coordinating Outputs: LUXCE experts contribute to crafting the PI objectives with Agile teams and trains, ensuring they are outcome-focused and aligned with end-user goals.
5. Addressing Dependencies: They highlight program-level dependencies, including UX enablers on the Program Board, contributing to successfully aligning the train’s shared vision.

What is the role of the LUXCE in PI execution in SAFe?

The LUXCE supports Agile teams during PI execution, balancing planning for future PIs and addressing current iteration needs.

During PI execution in SAFe, the Lean UX Center of Excellence (LUXCE) has six important roles, and they are:

1. Consultation and Planning: LUXCE members act as embedded consultants within Agile teams, balancing the need to plan for upcoming PIs and addressing just-in-time requirements for current iteration development.
2. Managing Shared Backlogs: Shared backlogs must reflect all work, including planning for future PIs and current iteration work. The LUXCE helps maintain this delicate balance.
3. Collaborative Design: The LUXCE works with Agile teams to execute the collaborative design, eliminating options in the first few iterations and learning and feedback from benefit hypotheses emerging.
4. Incorporating Feedback: During later iterations, feedback is incorporated to build the MMF (Minimal Marketable Feature). The LUXCE ensures the capacity for this feedback is allocated during PI Planning.
5. Empowering Agile Teams: The LUXCE helps Agile teams become less reliant on data-driven deliverables and more capable of making design changes through UX enablers.
6. Building UX Enablers: With capacity freed up, Lean UX experts focus on creating new benefit hypotheses, feedback from previously released MMFs, and continually building out UX enablers. This work is then planned into the next PI.

Prioritize and Manage the ART Backlog

What is the ART Backlog?

The ART Backlog is a Kanban system capturing and managing features and enablers to enhance a solution and extend its architectural runway.

The Agile Release Train (ART) Backlog is an integral part of SAFe Agile Product Delivery that functions as a repository for upcoming Features, Capabilities, and Nonfunctional Requirements (NFRs) meant to advance the solution. It utilizes a Kanban system for visualization and management, capturing the features and enablers required to enhance the solution and expand the architectural runway. These contents inform the necessary steps towards continuous value delivery to customers and provide a visual representation of work-in-progress, aiding teams to manage their work effectively.

How is the ART Backlog prioritized?

The ART Backlog is prioritized using Weighted Shortest Job First (WSJF), a method that ranks jobs based on the cost of delay and job size.

Prioritizing the ART Backlog involves using the Weighted Shortest Job First (WSJF) method. WSJF, a key element of SAFe, assigns a value to jobs or work items based on their cost of delay and job size. These values are then used to rank the items in the backlog, with the highest-ranking items being addressed first. This approach ensures that the most valuable and impactful work is completed quickly, improving delivery efficiency and business value.

What is WSJF?

WSJF, or Weighted Shortest Job First, is a prioritization method used in SAFe to rank jobs based on their value and size.

Weighted Shortest Job First (WSJF) is a prioritization model used in the SAFe Agile Product Delivery. It is used to sequence jobs, such as features or capabilities, to produce the maximum economic benefit in product development. WSJF calculates priority based on the cost of delay and the job size, ensuring that high-value and smaller jobs are prioritized and completed first to optimize the overall efficiency and value delivery.

How is WSJF Calculated?

WSJF is calculated by dividing the Cost of Delay (CoD) by the Job Size. The job with the highest WSJF value is considered first.

WSJF calculation follows a 5-step process as follows:

1. Identify the jobs for prioritization.
2. Determine the Cost of Delay (CoD) for each job, which includes factors such as user business value, time criticality, and risk reduction-opportunity enablement value.
3. Estimate the job size. This represents the effort required to complete the job.
4. Divide the CoD by the job size to get the WSJF score.
5. Rank the jobs in descending order based on the WSJF score. The job with the highest score gets the highest priority.

This method ensures that jobs with the highest potential value and the smallest size are given priority, resulting in maximum value delivery and efficient use of resources.

Who is involved in the WSJF Process?

The WSJF process involves key stakeholders including Product Management, Business Owners, and architects.

The WSJF process requires the involvement of 4 key roles, and they are:

• Product Management: They are responsible for defining and prioritizing the Program Backlog and contributing to defining the delay cost and job size.
• Business Owners: They have a crucial role in defining business value and understanding the cost of delay.
• Architects/Engineers: They help estimate job size by providing their technical expertise.
• Epic Owners: They provide the information required to assess the value and size of an epic, contributing to the WSJF calculation.

These stakeholders collaborate to ensure that the WSJF calculation accurately reflects the value and size of the jobs in the backlog.

How is WSJF used to facilitate discussions?

WSJF provides a shared language for stakeholders to discuss job value and size, promoting alignment and consensus around prioritization decisions.

WSJF serves as a facilitator for discussions in five ways, and they are:

1. Promotes alignment: WSJF creates a common understanding and shared language about what constitutes value and how to measure it, fostering alignment among different stakeholders
2. Quantifying decision-making: Using a numerical score, WSJF allows stakeholders to quantify their decision-making process. This reduces subjectivity and biases in prioritization discussions, fostering objective and productive dialogues.
3. Encourages holistic perspective: WSJF ensures stakeholders consider multiple factors, including business value, time criticality, and risk reduction, encouraging a more holistic perspective on the value of a job.
4. Facilitates trade-off discussions: With a clear WSJF score, stakeholders can have more structured conversations around trade-offs, discussing whether a lower-ranking job should be promoted due to unique circumstances.
5. Drives consensus: Calculating WSJF often leads to consensus among stakeholders. As they work together to estimate job size and the cost of delay, they reach a shared understanding of job priority.

By facilitating these discussions, WSJF is a critical tool for aligning stakeholders around job prioritization, ultimately ensuring that the most valuable jobs are addressed for the maximum economic outcome.

How does WSJF contribute to prioritizing the ART Backlog?

WSJF prioritizes ART backlog items based on their economic value. In the WSJF formula denominator, job size influences item ranking during pre-PI planning.

WSJF, or Weighted Shortest Job First, is a prioritization model used in SAFe that assigns economic value to each job, allowing teams to prioritize them effectively in the ART backlog. The unique aspect of this model is the inclusion of job size as the denominator in the calculation. By doing this, WSJF emphasizes that smaller jobs that deliver substantial value should be prioritized higher. During pre-PI planning, WSJF drives the ranking of features based on this principle. Features with high WSJF scores—representing a high economic value in relation to their size—get prioritized, ensuring that the most economically beneficial jobs get tackled first in the ART backlog.

How does job size affect feature ranking?

Job size directly influences feature ranking. Smaller, high-value jobs rank higher, which may lead to larger features being sliced to fit upcoming PI based on capacity allocation.

Job size is an integral part of the WSJF calculation and directly impacts the ranking of features in the ART backlog. The smaller a job is relative to its value (the ‘cost of delay’), the higher it ranks. This principle encourages an iterative process of feature slicing to increase a feature’s priority.

If a larger feature delivers substantial value but doesn’t fit into the upcoming PI based on capacity allocation, it may be sliced into smaller parts. Each part is then estimated and assigned a WSJF score, leading to an overall increase in priority. This process ensures maximum economic benefit by allowing valuable parts of larger features to be implemented sooner.

What are SAFe Features?

SAFe Features are services that fulfill stakeholders’ needs, generally fitting within a single Planning Interval (PI) and offering business benefits.

In SAFe Agile Product Delivery, Features denote service offerings that deliver value to end-users or the organization. They typically encapsulate a cohesive functionality that satisfies a particular business requirement, aligns with the broader system capabilities, and yields tangible benefits to the stakeholders.

What is the maximum size of a SAFe Feature?

The maximum size of a SAFe Feature can be developed, tested, and integrated within a single Planning Interval (PI).

A SAFe Feature should ideally be designed to be implemented within a single Planning Interval (PI), which traditionally spans eight to twelve weeks. This size constraint ensures that features are deliverable within a reasonable timeline, promoting fast feedback and iterative refinement.

How are Features estimated in SAFe?

SAFe Features are estimated using normalized story points or the Weighted Shortest Job First (WSJF) method.

In SAFe, Feature estimation employs two primary techniques, and they are:

1. Normalized Story Points: Teams estimate the effort involved by assigning story points, ensuring consistency across teams using a normalized scale.
2. Weighted Shortest Job First (WSJF): This method prioritizes features based on the cost of delay and size. It assigns a relative value to each feature, identifying the items that deliver maximum value with minimal delay.

Both methods work together to provide a comprehensive estimation, facilitating better decision-making and efficient backlog prioritization.

Who is involved in estimating SAFe Features?

SAFe Feature estimation involves collaborating with Agile teams, Product Management, and System Architects.

Estimating SAFe Features is a collective responsibility involving multiple parties:

1. Agile Teams: They play a significant role in estimating the size and effort required to implement features.
2. Product Management: They provide insight into business value and help prioritize features.
3. System Architects: They assess technical feasibility, inform about architectural impacts and dependencies, and help estimate features.

When are SAFe Features estimated?

SAFe Features are estimated during pre-PI and PI Planning and iteratively refined throughout the PI.

In SAFe, estimating the size of Features is a collaborative and iterative process that happens at different stages:

1. Pre-Program Increment (Pre-PI) Planning: Initial estimation begins before the Program Increment (PI) planning session. During this stage, high-level estimation of Features typically involves T-shirt sizing (i.e., S, M, L, XL) to provide a general understanding of their relative size and complexity.
2. Weighted Shortest Job First (WSJF) Calculation: Features are prioritized in the Program Backlog using WSJF, which considers both the size (i.e., the effort to implement) and the value the Feature delivers. The size used in the WSJF calculation is derived from the initial T-shirt size estimation.
3. Refinement Before PI Planning: As Features move closer to the upcoming PI, Agile Teams refine the initial estimates. This often involves reassessing the T-shirt sizes and adjusting the scope of the Features based on more detailed knowledge.
4. Program Increment (PI) Planning: During PI Planning, Agile Teams do their breakouts, create User Stories from Features, and estimate these User Stories. This information is used to refine the Feature estimates and to help inform capacity planning and forecasting. The overall size of a Feature can be inferred by adding up the Story Points of the associated User Stories.
5. Iteration Planning and Execution: During Iteration Planning and throughout the PI, teams may continue to refine Feature estimates as User Stories are completed, and new User Stories are identified. This ongoing estimation enables better predictability and allows adjustments as understanding the Feature and its implementation details evolve.

What mechanisms can be used to slice features?

Feature slicing mechanisms include preparing the input feature, evaluating the slicing, and applying slicing patterns like breaking out common enablers, addressing different user groups, or isolating special variations.

Feature slicing is a powerful technique to ensure a balanced, manageable Agile Release Train (ART) backlog. Several mechanisms can be used to slice features:

1. Preparing the Input Feature: Ensure the feature satisfies the INVEST criteria—Independent, Negotiable, Valuable, Estimable, Small, and Testable.
2. Evaluating the Slicing: Assess whether new features are roughly equal in size and if they fit into a Program Increment (PI).
3. Applying Slicing Patterns.

There are ten common patterns for slicing Product Features, and they are:

1. Break Out Common Enablers: Identify shared dependencies and create architectural features around them.
2. Find a Story Group: Focus on the most valuable stories and develop them into their own feature.
3. Keep It Simple (KISS): Identify the core functionality that provides the most value, and build that first.
4. Defer Optional Behaviors: Treat optional behaviors as separate features.
5. Separate Business Variations: Deliver one business variant at a time, starting with the simplest.
6. Separate Different Channels: Deliver one channel or technology at a time.
7. Isolate Special Variations: Treat specialized corner cases as separate features.
8. Address Different User Groups Individually: Each user group gets its own feature.
9. Consider Incrementally Sourcing Data: Deliver benefits with a subset of the data, consuming it incrementally.
10. Break Out a Spike: Use time-boxed research periods to answer the questions most holding you back.

By effectively slicing features, teams can create more manageable workloads and deliver value incrementally. This, in turn, helps in better backlog prioritization and management.

What are SAFe User Stories?

SAFe User Stories are short, simple descriptions of a feature told from the user’s perspective, typically defined by Agile Teams.

In SAFe Agile Product Delivery, User Stories are concise descriptions of functionality or feature written from the end-user perspective. They form the basis of Agile development, serving as the primary vehicle for expressing requirements within an Agile team and promoting communication and collaboration.

What is the relationship between SAFe Features and SAFe user stories?

SAFe User Stories are components of SAFe Features, detailing specific functionality required to deliver a complete Feature.

SAFe Features and User Stories have a hierarchical relationship. A Feature represents a business capability that delivers value when fully implemented. User Stories, on the other hand, are smaller, executable elements that contribute to realizing a Feature. Each Feature typically comprises multiple User Stories, with each Story providing a distinct piece of functionality contributing to the overall capability defined by the Feature.

What is the maximum size of a User Story?

A User Story should be small enough to design, code, test, and accept within a single iteration.

The size of a User Story is constrained by the duration of an iteration in SAFe, typically two weeks. This means a User Story should be sufficiently small to be developed, tested, and accepted within this timeframe. This constraint encourages the creation of manageable work units and facilitates quick feedback.

How are User Stories estimated in SAFe?

User Stories in SAFe are estimated using Story Points, a unit of measure that conveys the effort required for implementation.

Estimation of User Stories in SAFe employs Story Points, which represent a measure of effort required to implement a Story, including coding, testing, and integration. Agile Teams assign Story Points to each User Story based on its complexity, risk, and effort required, using techniques like Planning Poker or T-Shirt Sizing. The cumulative Story Points for all User Stories provide an estimate for completing a Feature or an iteration.

Who is involved in estimating User Stories?

Agile Team members, including developers, testers, and business analysts, are primarily responsible for estimating User Stories.

Estimating User Stories in SAFe involves the Agile Team members who will implement the Story. This typically includes developers, testers, and business analysts. The team collaboratively discusses each User Story, considering aspects like complexity, uncertainty, and effort before agreeing on a Story Point estimate. This collaborative estimation promotes shared understanding and commitment.

When are SAFe User stories estimated?

SAFe User Stories are estimated during PI Planning and Iteration Planning and are continuously refined throughout their execution.

In the SAFe framework, User Stories are estimated at different points in time to provide a more accurate understanding of their size and complexity. This happens in the following steps:

1. Program Increment (PI) Planning: Teams identify User Stories as they break down Features during PI planning. They perform an initial estimation of these User Stories as part of their capacity planning process. The estimates help understand the effort required and how much of the team’s capacity each User Story will consume.
2. Iteration Planning: At the beginning of each Iteration, teams have a dedicated session where they create, refine, and estimate User Stories for the upcoming Iteration. This session provides a more detailed and accurate estimate as teams better understand the work involved at this stage.
3. Continuous Refinement: Estimation is not a one-time activity. As teams work on User Stories, they continuously gain more information about the work involved and can refine the estimates accordingly.

This ongoing estimation and refinement process helps teams effectively manage their workload, improve predictability, and deliver value in a timely manner. It’s crucial to maintaining agility and responsiveness in a SAFe environment.

What mechanisms can be used to slice user stories?

Mechanisms include Workflow Steps, Operations (CRUD), Business Rule Variations, Variations in Data, Data Entry Methods, Major Effort, Simple/Complex, Defer Performance, and Spikes.

There are twenty commonly used methods for slicing user stories, and they are:

1. Simple/Complex: When a story seems increasingly complex, it might be beneficial to identify the most straightforward version and break it out, leaving the more complex variations as separate slices.
2. Workflow Steps: Break down the user story based on the steps in a workflow.
3. Operations (CRUD): User stories often involve multiple operations and can be split into Create, Read, Update, and Delete (CRUD).
4. Business Rule Variations: A user story may sometimes have different business rules. These rules can each be a separate slice.
5. Variations in Data: Complexity may arise from handling variations in data. Slice the story based on different data inputs or outputs.
6. Major Effort: Some stories may require significant effort for the initial setup, but subsequent similar stories could be relatively straightforward. Such stories can be sliced according to these ‘effort boundaries’.
7. Functional vs. Non-functional: Divide the user story into pieces that correspond to functional requirements (what the system should do) and non-functional requirements (how the system should be, in terms of performance, security, usability, etc.).
8. Data Entry Methods: A user story could have multiple data entry methods, offering opportunities for slicing.
9. By Persona: Separate the user story based on different users’ needs or roles (personas).
10. User Actions: This strategy focuses on what the user does, splitting stories based on different user actions within the same feature or functionality.
11. Interfaces: Break down the story according to different user interfaces or platforms (desktop, mobile, etc.).
12. Priority: If a story has more critical parts than others, it can be useful to split it according to priority.
13. Sequential vs. Parallel: This strategy involves breaking the story down based on whether the tasks can be done in parallel or if they need to be done sequentially.
14. Input Methods or Channels: This involves splitting the story using different input methods or channels.
15. Data Scope: Split stories based on the amount or type of data they handle.
16. Error Conditions: Create separate stories to handle different error conditions or exceptional cases.
17. Different Devices: You can split user stories based on users’ device preferences.
18. Defer Performance: In some cases, it makes sense to build a functional but slow version of a feature and then make it faster in a separate slice.
19. Break Out a Spike: If a story is large due to implementation uncertainty, a time-boxed spike (research period) can be used to investigate the issue, turning the implementation itself into a separate slice.
20. Technology or System Layer: Sometimes, you can slice the story according to the technology or system layer. This might include breaking it into frontend and backend tasks or tasks related to different parts of the tech stack.

What is the Product Vision?

Product Vision is a product’s strategic, long-term goal, articulating its purpose, target audience, and key benefits.

Product Vision is a high-level, strategic concept for a product that outlines its long-term goal. It describes the product’s purpose, target audience, and unique benefits. It’s a guiding force in product development, offering a direction for teams and helping align their efforts towards creating a product that fulfills its intended purpose and creates value for its users.

Why is the Product Vision important in Agile Product Delivery?

Product Vision in Agile Product Development offers strategic direction and sets the end goal for product evolution.

The Product Vision in Agile Product Delivery provides the overarching goal for product development. It’s crucial because it offers strategic direction, sets the purpose, motivates the team, and outlines the desired end state. It is the guiding light for all product decisions, from features to design elements.

How does Product Vision influence feature prioritization?

Product Vision shapes ART Backlog Management by influencing feature prioritization and defining product direction.

Product Vision and ART Backlog Management are intimately linked. The vision outlines the product’s aims, while backlog management operationalizes that vision. Features and user stories in the backlog should align with the product vision, guiding teams toward the desired product state.

How is Product Vision translated into Features and user stories?

Product Vision translates into features and user stories through requirement analysis and iterative planning.

Translating Product Vision into features and user stories is a systematic six-step process as follows:

1. Understanding Vision: First, deeply understand the Product Vision, which outlines the desired future state of the product.
2. Requirement Analysis: Break down the Product Vision into high-level requirements or Epics, representing large chunks of functionality or value.
3. Create Features: Decompose epics into features, representing smaller, more manageable functionality that can be developed within a Program Increment.
4. Develop User Stories: Further break down features into user stories, representing individual increments of value from a user perspective.
5. Prioritize: Prioritize the features and user stories based on their alignment with the Product Vision and the value they provide to users and the business.
6. Iterative Planning: Regularly revisit and revise the features and user stories, ensuring they align with the evolving Product Vision.

How does the Product Vision influence capacity allocation and balancing?

Product Vision guides capacity allocation and balancing by directing efforts toward priority areas aligned with strategic goals.

Product Vision influences capacity allocation by guiding where efforts and resources should be focused. It ensures that teams invest their capacity in areas that align with the product’s strategic goals. Balancing is influenced as teams adjust their workload to deliver on the vision, ensuring that no single area is overloaded while others are neglected.

Managing the ART Backlog

Who manages the ART Backlog?

The Product Management team manages the ART Backlog in the Scaled Agile Framework.

In SAFe Agile Product Delivery, the Product Management team is tasked with developing, maintaining, and prioritizing the Agile Release Train (ART) Backlog. Their responsibilities encompass the following:

• Collaborating actively with stakeholders including Customers, Business Owners, Product Owners (POs), and System and Solution Architects.
• Discovering the necessary features and capabilities to advance the solution.
• Ensuring a continuous flow of value to customers through a well-maintained and prioritized backlog.

This collaboration and continuous refinement ensure the alignment of the backlog with the evolving needs of the business and customers, effectively advancing the solution.

How is the ART Backlog built and refined?

The ART Backlog is built and refined through continuous discovery, definition, evaluation, and prioritization of features and capabilities.

Building and refining the ART Backlog is an ongoing process involving seven key activities as follows:

1. Discovering new features and capabilities needed to enhance the solution.
2. Reviewing and updating backlog item definitions, including acceptance criteria and benefit hypothesis development.
3. Identifying the enablers required to support new features and capabilities.
4. Applying Behavior-Driven Development (BDD) techniques or holding specification workshops to clarify features and capabilities.
5. Prioritizing the backlogs using Weighted Shortest Job First (WSJF) in collaboration with various stakeholders.
6. Briefing Agile Teams and stakeholders about upcoming features and capabilities for PI Planning.
7. Deleting aging and no longer relevant items.

These activities ensure the readiness of backlog items for implementation, maintaining a continuous flow of value and supporting successful PI planning and execution.

How is Kanban used to manage the ART Backlog?

Kanban manages the ART Backlog by facilitating the flow of Features and Capabilities through distinct states within the Continuous Delivery Pipeline.

The ART Backlog uses a Kanban system to manage and monitor the progression of Features and Capabilities. The system comprises eight stages that a Feature or Capability traverses as it is prepared for delivery, and they are:

1. Funnel: This initial stage welcomes all new ideas, usually expressed as Features or Capabilities.
2. Analyzing: Agile Teams further explore ideas aligning with the Solution Vision and Strategic Themes. This stage encompasses continuous exploration activities like customer-centricity and design thinking.
3. Ready: The highest-priority features approved by Product or Solution Management advance to this stage. They are prioritized with Weighted Shortest Job First (WSJF) and await implementation.
4. Implementing: Features move into this stage as teams work on them throughout the PI.
5. Validating on Staging: Features ready for feedback move to this state. Teams integrate and test them with the rest of the system in a staging environment and present them for approval.
6. Deploying To Production: Features ready for production are moved immediately in an automated Continuous Delivery environment or to the in-progress state for manual deployment when capacity exists.
7. Releasing: When there’s sufficient value, market needs, and opportunity, features are released to some or all customers to evaluate their benefit hypothesis.
8. Done: After a feature has been released and evaluated, it moves to the done state.

How are ART Epics Managed?

ART Epics are managed using a separate Kanban system to analyze, approve, and split them into features or capabilities for incremental implementation.

The management of ART Epics employs a specific Kanban system involving three stages as follows:

1. Funnel: This is the initial stage where all big initiatives are welcome. There’s no Work-in-Progress (WIP) limit at this point.
2. Reviewing: Subject Matter Experts (SMEs) and stakeholders review the epics and prioritize them using Weighted Shortest Job First (WSJF). If the epic exceeds the portfolio threshold that Lean Portfolio Management (LPM) sets, it’s moved to the Portfolio Kanban.
3. Analyzing: During this stage, SMEs and stakeholders refine size estimates, consider solution alternatives, identify potential Minimum Marketable Features (MMF) or Minimum Viable Products (MVPs), and forecast costs using a Lean business case. Approved epics are split into features or capabilities and transferred to the ART Kanban funnel for prioritization.

How is capacity balanced between Value Delivery and Solution Health in the SAFe ART?

The ART balances capacity between Value Delivery and Solution Health through WSJF prioritization and capacity allocation with the collaboration of Product, Solution Management, and Architects.

In SAFe Agile Product Delivery ARTs the balance between Value Delivery and Solution Health is achieved by three activities as follows:

1. WSJF prioritization: This approach helps in assessing and balancing work requirements.
2. Collaboration: Product and Solution Management work with Architects when the WSJF approach falls short.
3. Capacity Allocation determines the effort reserved for each activity in the upcoming Planning Interval (PI). The agreed capacity allocation is reviewed and adjusted regularly during backlog refinement for PI planning.

Develop on Cadence, Release on Demand

Develop on Cadence, Release on Demand separates solution development and value release, providing routine development and flexible releases, enhancing business agility in SAFe.

In SAFe Agile Product Delivery, Develop on Cadence ensures systematic, predictable development activities while Release on Demand controls the strategic value release. This dual process ensures stable development cycles and accommodates market fluctuations, customer demands, or business needs. It offers a robust framework for maintaining steady progress in a volatile environment, effectively improving business agility.

What does it mean to “Develop on Cadence”?

“Develop on Cadence” involves establishing a routine, synchronized development activities on a predictive rhythm to manage variability in SAFe product development.

Develop on Cadence refers to an approach within SAFe that seeks to establish regular, synchronized activities within a Program Increment (PI) cadence, thus creating a consistent, predictable rhythm. This approach is particularly effective in managing the inherent variability of knowledge work involved in product development. It uses synchronized team and ART events to provide a reliable schedule, optimizing for the variability and uncertainty in knowledge work.

Why Develop on Cadence?

Developing on Cadence manages product development variability through synchronized, predictable development activities, optimizing for highly variable knowledge work.

Developing on Cadence offers five benefits, and they are:

1. Predictability: Regular, synchronized PI cadence provides a reliable team and ART events schedule.
2. Variability Management: By establishing a predictable rhythm, teams can effectively manage the inherent variability in product development.
3. Alignment: Iterations within PIs align Agile Teams and enable a faster response to change.
4. Optimization: The approach optimizes for the variability in knowledge work, making development more efficient and predictable.
5. Clear Communication: Regular sync events help eliminate impediments, remove bottlenecks, and convey necessary adjustments to teams.

What is Release on Demand?

Release on Demand is a SAFe practice allowing value delivery when customers, the market, or the business necessitate, offering a strategic advantage.

In SAFe Agile Product Delivery, Release on Demand is a strategy that lets organizations release value as required by the customers, the market, or the business conditions. In collaboration with stakeholders, Product Management determines when and what to release and who should receive it. The practice provides a significant strategic advantage by allowing new functionalities to be delivered incrementally or all at once, aligning with user or market demand.

Why Release on Demand?

Releasing on Demand aligns value delivery with market needs, customer demands, and business requirements, providing a strategic edge in product management.

Releasing on Demand brings six advantages as follows:

1. Strategic Advantage: Releasing value as required gives organizations a competitive edge in dynamic markets.
2. Flexibility: An organization can respond rapidly to market rhythms and customer needs.
3. Stakeholder Collaboration: Product Management collaborates with stakeholders to decide the elements, timing, and recipients of releases.
4. Value Maximization: Releasing incrementally or immediately ensures value delivery aligns with user or market demand.
5. Learning Opportunity: It enables organizations to measure the effectiveness of releases, learn from the data collected, and prepare for the next learning loop through the Continuous Delivery Pipeline (CDP).
6. Continuous Improvement encourages a feedback cycle, enhancing overall product quality and customer satisfaction.

Agile Product Delivery Events

Agile Product Delivery events facilitate synchronization, feedback, learning, and continuous improvement across Agile Release Trains (ARTs) and Agile Teams within SAFe Agile Product Delivery.

ART Events:

1. PI Planning: Sets ART’s objectives and aligns teams.
2. System Demos: Demonstrates integrated, potentially shippable system increment.
3. Inspect and Adapt: Reflects and adapts system and processes.
4. ART Sync: Facilitates cross-team collaboration.
5. Product Owner, Coach Sync: Removes impediments and communicates adjustments.
6. Product Management, RTE Sync: Enables strategy alignment.

Agile Team Events:

1. Iteration Planning: Details the team’s work for an iteration.
2. Daily Stand-up: Discuss progress and impediments.
3. Iteration Review: Demonstrates working system increment.
4. Iteration Retrospective: Reflects on the team’s performance and identifies improvement areas.
5. Backlog Refinement: Prioritizes and details backlog items.

These events promote synchronization, alignment, feedback, learning, and continuous improvement within the Agile Teams and ARTs.

ART Events

This table outlines the required and optional attendees for each Agile Release Train (ART) event.

What is PI Planning?

PI Planning is a collaborative event in SAFe that sets ART’s objectives and aligns teams for a Program Increment duration.

Program Increment (PI) Planning is a crucial event in SAFe Agile Product Delivery that aligns all team members towards common goals over the upcoming PI, typically 8-12 weeks long. This event brings together all stakeholders—Agile teams, Product Management, and other key individuals—within an Agile Release Train (ART) to collaboratively discuss and agree on the work and objectives for the following PI. It creates a roadmap everyone understands and supports, promoting transparency and commitment. PI Planning also allows one to address dependencies, risks, and resource requirements in advance, ensuring smoother delivery and mitigating potential disruptions.

Who participates in PI Planning?

PI Planning involves Agile Release Train (ART) members, stakeholders, Product Management, System Architects, and business owners.

PI Planning includes four stakeholder groups, and they are:

1. ART Members: Consisting of teams, Scrum Masters, and Product Owners.
2. Stakeholders: Customers and business owners provide insight and approval.
3. Product Management: They define the vision and roadmap.
4. System Architects/Engineers: They provide architectural guidance.

What is the PI Planning agenda?

The PI Planning agenda includes preparation, presentation, drafting plans, aligning, finalizing plans, and retrospective.

PI Planning follows a six-step sequence as follows:

1. Preparation: The Product Management team readies the Program Vision, Roadmap, and Content.
2. Presentation: Product Management presents the Vision and Top Features.
3. Drafting Plans: Teams break out to create Iteration Plans and Draft Program Board.
4. Aligning: The Draft Plan Review and Management Review and Problem-solving occur.
5. Finalizing Plans: Teams complete their plans, vote on confidence, and adjust as necessary.
6. Retrospective: Teams reflect on the planning process.

What is the System Demo?

System Demos are events in SAFe showcasing an integrated, potentially shippable system increment to stakeholders.

System Demos represent an integral part of SAFe Agile Product Delivery, where Agile teams demonstrate the system increment developed during an iteration. It includes all the completed features and capabilities that are integrated, tested, and potentially ready to be shipped. The main purpose of these demos is to provide visibility of the product progress to all stakeholders—including customers, product management, and other teams—and to gather their feedback. This allows teams to validate that they are on track and aligned with the product vision.

Who participates in System Demos?

System Demos are attended by ART teams, stakeholders, Product Management, and business owners.

System Demo participation includes:

1. ART Teams: They present the integrated system increment.
2. Stakeholders: Internal and external, provide feedback and direction.
3. Product Management: They ensure alignment with vision and roadmap.
4. Business Owners: They provide a critical business perspective.

What is the System Demo agenda?

The System Demo agenda includes preparation, demo, feedback, and alignment.

The System Demo follows this sequence:

1. Preparation: ART teams prepare a demo of the new system increment.
2. Demo: The teams present the new features to stakeholders.
3. Feedback: Stakeholders provide feedback on the demonstrated increment.
4. Alignment: Any misalignment identified through feedback is addressed.

What is Inspect and Adapt?

Inspect and Adapt is a SAFe event for reflection, problem-solving, and process improvement at the end of a Program Increment.

Inspect and Adapt (I&A) is a significant event in the SAFe framework that occurs at the end of each Program Increment (PI). It’s a time for reflection where Agile teams, product management, and other stakeholders gather to assess the outcomes of the previous PI. This involves PI System Demo, Quantitative Measurement, and Problem-Solving Workshop. The demo showcases what has been achieved and measurement gauges performance metrics. In the Problem-Solving Workshop, teams use the data to identify systemic problems, brainstorm solutions, and decide on improvement backlog items to implement in the following PI. I&A promotes a culture of continuous learning and improvement, ensuring value delivery aligns with the business objectives.

Who participates in Inspect and Adapt?

“Inspect and Adapt” involves Agile teams, Product Management, stakeholders, and business owners.

Participants in Inspect and Adapt are:

1. Agile Teams: All teams involved in the ART participate.
2. Product Management: They ensure strategic alignment.
3. Stakeholders and Business Owners: They provide business context, feedback, and decision-making authority.

What is the Inspect and Adapt agenda?

The Inspect and Adapt agenda includes a PI System Demo, quantitative measurement, problem exploration, and improvement roadmap.

The Inspect and Adapt event follows this sequence:

1. PI System Demo: Demonstrating the integrated solution increment.
2. Quantitative Measurement: Reviewing the metrics and measures of the ART.
3. Problem Exploration: Identifying and discussing systemic problems.
4. Improvement Roadmap: Crafting a plan for implementing improvements.

What is the ART Sync?

The ART Sync is a SAFe event that fosters cross-team collaboration within an Agile Release Train.

The Agile Release Train (ART) Sync in SAFe is a recurring event where representatives from all Agile teams within a train come together to discuss progress, dependencies, and issues. It facilitates information sharing and problem-solving across teams, promoting a unified approach toward achieving ART objectives. By maintaining regular ART Sync meetings, teams are better equipped to mitigate risks, handle dependencies, and ensure a smooth flow of value through the train.

Who participates in the ART sync?

The ART sync includes Scrum Masters, Product Owners, and System Architects from each Agile team.

Participants in the ART sync are:

1. Scrum Masters: They share updates and synchronize work from each team.
2. Product Owners: They align work from their teams with the larger ART.
3. System Architects: They provide technical direction and address systemic issues.

What is the ART sync agenda?

The ART sync agenda includes synchronization, impediment resolution, and shared learning.

The ART sync follows this sequence:

1. Synchronization: Teams align on the progress, plans, and dependencies.
2. Impediment Resolution: Teams discuss and resolve systemic impediments.
3. Shared Learning: Teams share knowledge and successful practices.

What is the Coach Sync?

The Coach Sync is a regular meeting where Agile coaches discuss strategies, issues, and learning.

The Coach Sync is a periodic gathering of Agile coaches to discuss and align on coaching strategies, share learning, resolve challenges, and promote consistent Agile practices across teams and the ART. This event facilitates knowledge sharing and effective coaching implementation across the organization.

Who participates in the Coach sync?

The Coach Sync involves Agile coaches, Release Train Engineers, and sometimes Scrum Masters.

The Coach Sync is attended by:

1. Agile Coaches: They discuss and align on coaching strategies.
2. Release Train Engineers: They provide broader insight and support alignment.
3. Scrum Masters: They occasionally join to share their team-specific experiences and gain coaching insights.

What is the coach sync agenda?

The Coach Sync agenda includes coaching strategy alignment, problem-solving, and shared learning.

The Coach Sync follows this sequence:

1. Coaching Strategy Alignment: Coaches align on coaching strategies and approaches.
2. Problem-solving: Coaches discuss challenges faced and collaboratively develop solutions.
3. Shared Learning: Coaches share experiences, insights, and success stories to promote learning.

Team Events

This table highlights the attendance requirements for each Agile team event, providing a quick reference.

What is “Iteration Planning”?

Iteration Planning is a ceremony where Agile teams plan their work for the upcoming iteration, aligning with Program Increment objectives.

Iteration Planning is an essential event in Agile Product Delivery where each Agile team plans work for the upcoming iteration. The team reviews user stories, estimates effort, and commits to a specific workload aligned with Program Increment’s (PI) objectives (Leffingwell, 2020).

Who participates in “Iteration Planning”?

Iteration Planning involves Agile team members, the Product Owner, and Scrum Master.

Iteration Planning includes the following participants:

1. Agile Team Members: They collaboratively plan and estimate the work.
2. Product Owner: This role prioritizes the backlog and clarifies user stories.
3. Scrum Master: This role facilitates the planning session and resolves potential obstacles.

What is the “Iteration Planning” agenda?

The Iteration Planning agenda includes backlog refinement, iteration goal setting, planning, and commitment.

The Iteration Planning agenda encompasses the following steps:

1. Backlog Refinement: The Product Owner presents the prioritized backlog and clarifies doubts.
2. Iteration Goal Setting: The team agrees on the goals for the upcoming iteration.
3. Planning: The team breaks down user stories into tasks, estimates effort, and plans the work.
4. Commitment: The team commits to the work they believe they can deliver in the iteration, considering their velocity and capacity.

What is “Daily Stand-up”?

Daily Stand-up is a brief meeting where Agile teams align on tasks, share progress, and address obstacles.

Daily Stand-up, Daily Scrum, or Team Sync, is a short, time-boxed event every day during an iteration. Agile team members align on their tasks, share progress, and discuss potential obstacles. This synchronization promotes collaboration and helps to maintain a steady team rhythm (Leffingwell, 2020).

Who participates in “Daily Stand-up”?

Daily Stand-up involves Agile team members, the Product Owner, and the Scrum Master.

Daily Stand-up includes the following participants:

1. Agile Team Members: They share their progress and discuss impediments.
2. Product Owner: The Product Owner provides clarification and prioritization if required.
3. Scrum Master: The Scrum Master facilitates the meeting, ensuring focus and efficiency.

What is the “Daily Stand-up” agenda?

The Daily Stand-up agenda includes progress sharing, problem identification, and plan adjustment.

The Daily Stand-up follows this sequence:

1. Progress Sharing: Each team member briefly reports their accomplishments since the last meeting.
2. Problem Identification: Team members discuss the obstacles they are facing.
3. Plan Adjustment: If necessary, the team adjusts the plan for the upcoming work based on the discussed progress and problems. This ensures alignment and effective problem-solving.

What is “Iteration Review”?

Iteration Review is a meeting where Agile teams present their completed work from the iteration for feedback and acceptance.

Iteration Review, also known as Sprint Review in Scrum, is an event where Agile teams showcase the work completed during the iteration. This session encourages feedback and acceptance from stakeholders, promotes transparency, and allows adjustments to the product backlog based on new insights (Leffingwell, 2020).

Who participates in the “Iteration Review”?

Iteration Review involves Agile team members, the Product Owner, stakeholders, and the Scrum Master.

Iteration Review includes the following participants:

1. Agile Team Members: They demonstrate the work done during the iteration.
2. Product Owner: The Product Owner facilitates feedback and acceptance.
3. Stakeholders: Stakeholders provide feedback and steer future direction.
4. Scrum Master: The Scrum Master ensures an effective and efficient review process.

What is the “Iteration Review” agenda?

The Iteration Review agenda includes work demonstration, feedback collection, and backlog adjustment.

The Iteration Review follows this sequence:

1. Work Demonstration: The team showcases the completed work and functionality.
2. Feedback Collection: Stakeholders provide feedback, ask questions, and suggest improvements.
3. Backlog Adjustment: Based on feedback and new insights, the Product Owner adjusts the backlog to align with evolving needs.

What is the “Iteration Retrospective”?

Iteration Retrospective is a meeting for Agile teams to reflect on the iteration and identify areas for improvement.

Iteration Retrospective is an event in which Agile teams reflect on their processes and interactions during the completed iteration. They identify strengths, weaknesses, and areas for improvement, aiming to enhance performance and efficiency in future iterations (Leffingwell, 2020).

Who participates in the “Iteration Retrospective”?

Iteration Retrospective involves Agile team members and the Scrum Master.

Iteration Retrospective includes the following participants:

1. Agile Team Members: They share their experiences and suggest improvements.
2. Scrum Master: The Scrum Master facilitates the session, encouraging an open and constructive discussion.

What is the “Iteration Retrospective” agenda?

The Iteration Retrospective agenda includes reflection, improvement identification, and action planning.

The Iteration Retrospective follows this sequence:

1. Reflection: The team shares their experiences from the iteration, discussing what worked well and what didn’t.
2. Improvement Identification: Team members identify potential improvements in processes, tools, and interactions.
3. Action Planning: The team collaboratively develops an action plan for implementing identified improvements in the next iteration.

What is Release on Demand?

Release on Demand is a component of the Continuous Delivery Pipeline that enables functionality release based on business and customer requirements.

As the final aspect of the Continuous Delivery Pipeline, Release on Demand centers on delivering value through operational solutions in the end user’s environment, this strategy gives businesses the agility to release new functionalities immediately after deployment or incrementally at a time when it’s most economically sensible and beneficial to both customers and the business.

Why Release on Demand?

Release on Demand allows optimal timing of functionality releases, aligning with economic benefits and customer needs.

Release on Demand offers a strategic advantage by aligning solution delivery with customer needs and market rhythms. This approach empowers businesses to adapt to ever-changing environments and customer demands. Furthermore, it enables targeted promotional activities and scheduling confidence for sales teams, significantly improving business agility. It supports the principle of ‘develop on cadence; release on demand,’ adding value through the timing and frequency of solution delivery to end-users.

What are the Four Activities in SAFe Release on Demand?

The four activities in SAFe Release on Demand are Release, Stabilize and Operate, Measure, and Learn.

1. Release: This initial phase involves the delivery of the solution to end-users. It’s not a rigid all-or-nothing delivery but a flexible approach that allows for incremental delivery based on the most practical and beneficial. This could mean releasing a significant feature set all at once or rolling out smaller updates more frequently. Business needs, market circumstances, and customer demands define the release strategy.
2. Stabilize and Operate: Once the solution is in the users’ hands, ensuring it works as expected is essential. This goes beyond functional expectations and encompasses nonfunctional requirements (NFRs), such as performance, security, and usability. This phase involves diligently monitoring the solution in its live environment, troubleshooting any issues, and fine-tuning it to stabilize the system and keep it running smoothly.
3. Measure: Once the solution is live and stable, the next step is to determine its impact. This involves quantifying whether the newly-released functionality is delivering the intended value. Metrics for success can be diverse, ranging from user engagement statistics and customer feedback to business performance indicators like increased sales or reduced costs. The goal is to understand if the solution is achieving its intended objectives and driving the desired outcomes.
4. Learn: Finally, the process doesn’t stop after the solution is released and its impact is measured. A critical aspect of Release on Demand, and indeed of the agile approach, is learning continuously. This involves gathering feedback from all stakeholders, including customers, employees, and the market. It’s about understanding what’s working and what’s not, then using that knowledge to inform future cycles through the Continuous Delivery Pipeline (CDP). This ongoing learning and adaptation keep the solution relevant and valuable as customer needs and market conditions evolve.

Release Value to Customers

Releasing Value to Customers involves making a solution available to users once it’s in production and verified, considering timing is a critical business decision.

Releasing Value to Customers encapsulates the final product’s delivery process to end users after it’s been produced and tested. It’s a crucial business decision because it affects the economic impact of the product. Releasing too early or late might adversely affect the product’s perceived value.

In collaboration with stakeholders, Product Management devises policies that dictate the release process. Depending on the system’s complexity, the process might be automatic for qualified code or involve a formal review process with a manual gate.

Critical practices in the release process include:

1. Dark launches allow code deployment to a production environment without the functionality being released to end users, thus facilitating a test run in the live environment.
2. Feature toggles: This technique enables code to be turned on or off without requiring additional deployment, giving teams more control over the visibility and availability of features.
3. Canary releases: This practice involves releasing the solution to a specific customer segment and measuring the results before expanding the release to a broader audience.
4. Decoupled release elements: This technique involves identifying specific release elements that can be released independently, which provides more flexibility and control over the release process.

For instance, a company might have multiple, somewhat independent release cycles. Each of these cycles or ‘value streamlets’ represents an end-to-end flow of value within a Value Stream. Recognizing these streamlets is crucial as they allow different solution elements to be released independently, at their own pace (Leffingwell, 2020).

Stabilize and Operate

“Stabilize and Operate” refers to ensuring the solution works smoothly post-release, including resolving incidents, monitoring security, and addressing operational needs.

“Stabilize and Operate” is a phase following the release where the focus shifts to ensuring the deployed solution functions optimally in its live environment.

There are several practices involved in this phase:

1. Cross-team collaboration: Cooperation across the Value Stream is crucial for identifying and solving problems as they occur. Teams need to work together to develop and operate the solution.
2. Failover/disaster recovery: Failures will inevitably occur, so a failover mechanism is essential. Disaster recovery must also be planned, built into the service, and regularly practiced.
3. Continuous security monitoring: Preventing known vulnerabilities from reaching production is important, but services must be continuously tested for newly discovered vulnerabilities and detecting intrusions and attacks on services and infrastructure.
4. Architect for operations: Operational needs must be considered. High loads, security attacks, and incident responses require options from downgrading services to adding capacity.
5. Monitor nonfunctional requirements (NFRs): Teams must continuously monitor system attributes like reliability, performance, and scalability to avoid service disruptions (Leffingwell, 2020).

Measure

“Measure” refers to applying telemetry and innovation accounting to quantify if the business value was delivered as hypothesized.

“Measure” is a vital stage in the SAFe Release on Demand process, where businesses assess whether the deployed solution is providing the intended value. The goal is to verify if the initial hypothesis surrounding the solution was accurate. This stage relies heavily on two practices:

1. Application telemetry: This primary mechanism tracks and compares data usage against the original hypothesis. It involves collecting, processing, and interpreting data the software application generates during its operation.
2. Innovation accounting: This practice uses different metrics from those used to measure end-state working solutions. It focuses on assessing intermediate and predictive business outcomes during the initial stages of solution development and during the evaluation of the Minimum Viable Product (MVP).

Apart from measuring business value, other commonly measured elements in Agile product delivery include:

1. Product usage: Analyzing how users interact with the product, which features are most popular, and where users encounter difficulties.
2. Customer satisfaction: Understanding if the product meets customer expectations, often through surveys or Net Promoter Score (NPS).
3. Release frequency: Monitoring how often updates or new features are released to evaluate the efficiency of the delivery process.
4. Quality metrics: Tracking defect density, test case effectiveness, and time to resolution to assess product quality.
5. Performance indicators: Observe system performance aspects like load times, response times, and uptime to ensure that the product meets performance standards (Leffingwell, 2020).

Learn and React

“Learn and react” is analyzing release feedback, adapting future development efforts, and making strategic decisions about product features and epics.

“Learn and react” is the process where information gathered from the release is analyzed and used to inform future decisions. Three critical practices in this process include:

1. Lean startup thinking: This practice involves evaluating the benefit hypothesis for Minimum Viable Products (MVPs) and Minimum Marketable Features (MMFs). If the hypothesis isn’t proven, the organization must decide whether to continue development, stop it, or pivot to a new idea.
2. Value stream mapping: This is a crucial tool for improving the flow of value across the pipeline. It helps identify bottlenecks and problem areas in the flow, allowing teams to design future states and create Enablers to enhance the pipeline.
3. Relentless improvement: This mindset is central to SAFe Core Values. The Agile Release Train (ART) continuously improves the flow of value, achieving results and enabling customer value realization (Leffingwell, 2020).

What is Release Governance?

Release Governance is the process of planning, managing, and overseeing solution releases to align with business goals, ensuring they meet all relevant business criteria.

Release Governance in the SAFe Agile Product Delivery is a strategic process that ensures the organization’s releases align with business goals and meet all relevant business criteria, including internal and external security, regulatory, and compliance concerns.

Depending on the enterprise, Release Governance can be centralized (often termed Release Management), or the responsibilities can be shared among Agile Release Train (ART) and Solution Train leadership and other stakeholders.

There are several key considerations and activities involved in Release Governance:

1. Understanding and adhering to the organization’s release governance refers to ensuring that all releases comply with the organization’s set standards and policies.
2. Communicating release status: Regular updates to internal and external stakeholders about the status of the release are essential.
3. Deploying a suitable plan: An appropriate solution deployment plan must exist before the release.
4. Coordinating with relevant teams involves coordination with marketing Product and Solution Management teams for internal and external communications.
5. Validating solution quality and compliance criteria: Ensuring the solution meets the relevant quality and compliance criteria is crucial before deployment.
6. Participating in Inspect and Adapt (I&A): This is to improve the release process, value stream productivity, and solution quality.
7. Providing final authorization for the release: Release governance also involves providing the final approval.
8. Liaising with Lean Portfolio Management (LPM): This is crucial for aligning the release with portfolio-level objectives and strategic themes.

How do you enable Release on Demand with DevOps?

DevOps enables Release on Demand by implementing practices and tools that offer quick, low-risk activities, fast feedback, and alignment to business outcomes for swift and accurate customer delivery.

Release on Demand in SAFe Agile Product Delivery makes value available to customers when required. DevOps plays a crucial role in enabling this capability.

DevOps achieves this through SAFe’s CALMR (Culture, Automation, Lean, Measurement, and Recovery) approach and various technical practices:

1. Culture: DevOps promotes collaboration and shared responsibility between development and operations teams. This collaboration reduces silos and accelerates the time-to-market.
2. Automation: DevOps uses automation tools to reduce manual efforts, thus speeding up processes such as integration, testing, and deployment. It enables continuous delivery, ensuring the solution can be released anytime.
3. Lean: Adopting lean principles, DevOps focuses on value delivery and waste elimination. This accelerates flow and increases efficiency.
4. Measurement: DevOps uses measurements and telemetry for continuous improvement and to understand deployed solutions’ health, security, and value.
5. Recovery: In the case of failures, DevOps emphasizes quick recovery strategies. It helps maintain a resilient system capable of swiftly bouncing back from production issues.

Thus, DevOps empowers Release on Demand through a mix of cultural changes, automation, lean principles, measurement, and a focus on a quick recovery. It enables organizations to validate learning, maximize business value, and deliver customer value quickly and reliably.

DevOps and the Continuous Delivery Pipeline

What is DevOps and the Continuous Delivery Pipeline?

DevOps and the Continuous Delivery Pipeline represent the Agile workflows, automation, and activities from ideation to on-demand value release.

DevOps and the Continuous Delivery Pipeline (CDP) are vital components of Agile Product Delivery in SAFe. They encompass the automated procedures and workflows that guide new functionality from concept to an accessible value release. This pipeline includes Continuous Exploration (CE), Continuous Integration (CI), Continuous Deployment (CD), and Release on Demand, allowing Agile Release Trains (ARTs) to deliver new functionality more frequently (Scaled Agile, 2023).

Why is Continuous Delivery important?

Continuous Delivery accelerates the frequency of new functionality delivery, aligning with market demands and business goals.

Continuous Delivery is an approach that allows teams to deliver new features and improvements more frequently, thereby increasing business agility. Rather than delivering in large, monolithic chunks, smaller, more frequent releases are made possible through Continuous Delivery, meeting market demands more effectively. By decoupling various solution components, continuous delivery allows changes to be introduced as they’re ready, reducing risk and providing an adaptive, flexible approach to solution delivery (Scaled Agile, 2023).

What are the four aspects of the Continuous Delivery Pipeline?

The Continuous Delivery Pipeline comprises Continuous Exploration, Continuous Integration, Continuous Deployment, and Release on Demand.

Detailed Response: The four aspects of the Continuous Delivery Pipeline create a structure for delivering value consistently:

1. Continuous Exploration: Involves creating alignment on what to build by understanding market problems and potential solutions.
2. Continuous Integration: Focuses on implementing features from the Agile Release Train (ART) backlog and validating them in a staging environment.
3. Continuous Deployment: Deploys changes to production, where they’re verified and monitored to ensure correctness.
4. Release on Demand: Controls the release of value to customers based on market and business needs, ensuring optimal timing (Scaled Agile, 2023).

Continuous Exploration

Continuous Exploration (CE) is the initial phase of the Continuous Delivery Pipeline in SAFe, driving innovative product development by constantly probing market and customer needs.

As a core aspect of Agile Product Delivery, CE promotes a fluid exploration of market and customer needs, resulting in a continuous stream of prioritized features ready for integration. Unlike the static definitions of traditional waterfall methods, CE fosters dynamic alignment on product vision, roadmap, and features, transforming them into testable hypotheses. This continuous learning and adjustment approach creates customer-centric solutions that deliver optimal value to end users.

Hypothesize

Hypothesize in Continuous Exploration involves generating product ideas and defining measurements to validate them with customers.

In the Continuous Exploration (CE) process, Hypothesize is an initial step involving idea generation and defining measurements to validate them. Hypotheses originate from understanding market needs, strategic themes, portfolio vision, and roadmap. However, these ideas aren’t taken as facts but as hypotheses that require testing and validation. Some practices associated with hypothesis-driven development include:

1. Lean startup thinking, focusing on defining Minimum Marketable Features (MMFs) and Minimum Viable Products (MVPs), enabling quick evaluation of hypotheses with minimal investment.
2. Innovation accounting uses actionable metrics as leading indicators to answer whether progress is being made towards the outcome hypothesis and how we know this, thus improving economic decisions during solution development and evaluation.

Collaborate and Research

Collaborate and Research within Continuous Exploration involve input solicitation from diverse stakeholders to refine requirements.

The Collaborate and Research phase of CE involves active collaboration with stakeholders like System Architects, Customers, Business Owners, and Agile Teams, each contributing unique insights for requirement refinement.

• Stakeholders involved:
  • System Architects: They possess deep technical knowledge of solutions and understand them at system and use case levels.
  • Customers: They provide the primary source of feedback on the solution and its effectiveness in meeting their needs.
  • Business Owners and Stakeholders: They have the business and market knowledge to set the mission and vision.
  • POs and Teams: They create domain expertise through their work on the solution and are often closest to both technical and user concerns.
• Collaboration and research practices:
  • Primary market research: Helps develop insights through surveys, focus groups, questionnaires, and competitive analysis.
  • Customer visits and Gemba walks: Provides a first-hand understanding of stakeholder activities in their operational value streams.
  • Secondary market research: Helps understand customers and markets through techniques like trend analysis.
  • Lean UX thinking: Collaboratively defines MMFs and validates them quickly with customers.

Architect

The Architect phase in Continuous Exploration defines the minimum necessary architecture supporting the Solution and enabling continuous delivery.

In the Architect phase, the goal is to define the minimum amount of architecture necessary to support the Solution and enable continuous delivery. System Architects ensure the Architectural Runway is sufficient to deliver the required functionality and is designed to enable the Continuous Delivery Pipeline (CDP). They support the CDP through various practices:

1. Architecting for releasability: Design solutions to enable various incremental release strategies.
2. Architecting for testability: Build modular systems for continuous testing.
3. Separating deployment and release: Enable functionality to be moved into production but hidden from Customers.
4. Architecting for operations: Build telemetry and logging capabilities into every application and solution.
5. Threat modeling: Identify threats to proposed architecture, infrastructure, and applications early on.

Synthesize

Synthesize in Continuous Exploration distills acquired knowledge into a future state for the solution, aligning teams to a shared direction.

Synthesize in Continuous Exploration (CE) is about distilling the acquired knowledge into a future state for the solution. The synthesized knowledge, presented as vision, roadmap, and prioritized backlog, aligns the ART’s teams to a shared direction. This phase involves several practices:

1. Creating the solution vision: Provides the purpose for developing new features.
2. Maintaining the solution roadmap: Guides the prioritization of work and provides visibility into future plans.
3. Preparing for PI Planning: Enables alignment, transparency, and cross-team and cross-art collaboration in a face-to-face meeting.
4. Prioritizing the backlog: Helps to sequence the work to be done based on business value, risks, dependencies, and other factors.
5. Developing business cases: For significant investments, a business case is prepared to understand the cost, benefit, and impact of the proposed solution or feature.

Together, these practices provide a sense of direction and shared understanding to everyone involved in the Solution’s development. They also help manage and prioritize upcoming work for more effective and efficient execution.

How does DevOps enable Continuous Exploration?

DevOps promotes a culture of collaboration and rapid feedback, fostering innovation and ideation in Continuous Exploration through continuous integration, testing, and delivery.

In Continuous Exploration, DevOps enables faster experimentation and learning cycles. With continuous integration and delivery, teams can quickly validate hypotheses through early user feedback. This enables quick adaptations to customer needs and market conditions, facilitating a continuous process of exploration and ideation.

Continuous Integration

Continuous Integration (CI) is part of the Continuous Delivery Pipeline, where new features are developed, tested, integrated, and validated for deployment and release.

CI is a core technical practice for every Agile Release Train (ART). With continuous integration, the system is always operational and potentially deployable. The aim is to ensure constant readiness of the software, improve the overall quality, reduce risk, and establish a reliable pace of development, even amid the development process.

Develop

Develop refers to implementing stories, translating features into code, testing, and committing the work product into the source control system.

In the ‘Develop’ stage of CI:

• Features are broken into stories for continuous delivery and smooth integration.
• Behavior-Driven Development (BDD) is used for understanding requirements and improving quality.
• Test-Driven Development (TDD) is implemented, writing the unit test first, then the minimal code to pass the test.
• Effective version control is practiced for quick recovery and quality improvement.
• Built-In Quality practices are followed, focusing on flow, architecture & design quality, code quality, system quality, and release quality.
• Application telemetry and threat modeling evaluate hypotheses and identify possible vulnerabilities.

Build

Build is the phase where teams continuously integrate new code into the system, supported by automated build and test tools.

In the ‘Build’ phase, several practices are vital:

1. Continuous code integration happens on each commit, automatically triggering the compilation and testing of changes.
2. Build and test automation to verify changes and speed up the process.
3. Trunk-based development helps teams to quickly integrate code, ideally upon commit, working off a single trunk.
4. Gated commit ensures only validated modifications merge into the main branch.
5. Code analysis tools are used for application security, inspecting the code for vulnerabilities.

Test end-to-end

Test end-to-end activity involves system-level integration and testing to validate the solution’s functionality comprehensively.

Detailed response: When testing the solution end-to-end:

• Test and production environment congruity is maintained.
• Automated testing includes functional, integration, regression, and more.
• Test data management ensures consistency and realism, mirroring production as closely as possible.
• Service virtualizations simulate a production environment without requiring physical infrastructure.
• Nonfunctional requirements (NFRs), such as security, reliability, performance, scalability, and usability, are tested.
• Continuous supplier integration is practiced to reduce lead time and improve value delivery.

Stage

Stage involves validating the entire solution in a staging environment that resembles the production environment.

Detailed response: The ‘Stage’ process relies on:

• Maintaining a staging environment similar to the production setting.
• The blue/green deployment pattern involves live (production) and idle (staging) environments.
• Conducting system demos to evaluate the solution’s readiness for production deployment

How to enable a culture of Continuous Integration?

Enabling a “Culture of Continuous Integration” involves frequent integration, making results visible, prioritizing fixes, shared cadence, maintaining infrastructure, and applying supportive software engineering practices.

CI culture thrives when adopting certain key practices:

1. Integrate Frequently: More frequent integration identifies problems sooner, prompting quicker resolution and less rework.
2. Visibility of Integration Results: Displaying integration process failures, reasons, and solutions publicly promotes transparency and understanding.
3. Prioritize Fixing Failed Integrations: Emphasizing fixing integration failures supports a culture of building production-ready systems.
4. Establish a Shared Cadence: Consistent team rhythms make integration points more manageable.
5. Develop and Maintain Proper Infrastructure: Adequate test and staging environments are crucial for effective continuous integration. It necessitates a forward-looking investment approach.
6. Apply Supportive Software Engineering Practices: CI becomes easier with test-first development, planning for testability, modular solutions, and separation of concerns.

How does DevOps enable Continuous Integration?

DevOps enables Continuous Integration by fostering rapid development, frequent code integration, built-in quality, and compliance through its principles, practices, and tooling.

DevOps bolsters Continuous Integration by crossing multiple domains in solution development and pipeline flow through pre-production environments. Upon code check-in, the deployment pipeline automatically merges, conducts quality and security checks, and applies configurations to build deployable, full-stack binaries. All activities within Continuous Integration—developing, building, testing, and staging—are supported by DevOps via varied combinations of technical practices and tooling. This process promptly turns source code into tested, deployable solutions promptly, thus maximizing delivery speed and quality.

Continuous Deployment

Continuous Deployment (CD) is the automated migration of new functionality from a staging environment to production, enabling on-demand releases without affecting existing systems.

Continuous Deployment focuses on automating moving changes into the production environment, separating the deployment and release processes. This separation allows changes to be introduced without affecting the current system. Key features of CD include:

• Targeting specific customer functionality
• Enabling design thinking practices such as A/B testing
• Automating deployments in small batches
• Releasing based on business needs

Deploy

Deploy, an essential phase of Continuous Deployment, involves migrating changes into a production environment, focusing on automation and feature toggling for incremental changes.

During Deploy, changes are incrementally introduced into the production environment, called continuous deployment. The procedure includes the following six aspects:

1. Dark Launches: Deploy functionality without releasing it to end-users.
2. Feature Toggles: Facilitates dark launches with code-level controls.
3. Deployment Automation: Automates deployment from check-in to production.
4. Selective Deployment: Allows deployment based on criteria like geography or market segment.
5. Self-service Deployment: Allows moving solutions from staging to production using a single command.
6. Version Control: Maintains environments under version control for rapid deployment and recovery.

Verify

Verification in Continuous Deployment ensures solution changes operate as intended in production before releasing to customers.

After deployment, verification is required to ensure the solution changes operate in production as expected before releasing them to users. This is critical to prevent defects from disrupting the business flow. Verification practices include:

• Production testing using feature toggles or dark launches
• Test automation for speed and consistency
• Test data management to ensure consistency in automated testing
• Testing nonfunctional requirements (NFRs) to guarantee quality standards

Monitor

Monitoring in Continuous Deployment involves tracking and reporting issues in production, providing insights for performance and value over time.

Once deployed and verified, monitoring is crucial to track the feature’s performance and value over its lifespan. Monitoring enables teams to understand the health and efficiency of deployed solutions. It includes practices such as:

• Full-stack telemetry, which monitors problems across the entire stack
• Visual displays, which automate measurement display
• Federated monitoring, offering a holistic view of problems and performance

These capabilities offer valuable insights, increase responsiveness to production issues, and help analyze business value.

Respond

Respond in Continuous Deployment involves addressing production issues quickly, proactively detecting problems, and restoring services efficiently.

Responding to and recovering from unforeseen production issues is vital in Continuous Deployment. This ability helps maintain the flow of value through the pipeline and enhances delivery efficiency. Key practices to support this ability include:

• Proactive detection, creating faults to identify potential problems
• Cross-team collaboration, fostering cooperation to solve problems
• Session replay for researching incidents
• Rollback and fix forward for quick solution recovery
• Immutable infrastructure and version control for fast recovery

By detecting issues before they escalate and restoring services quickly, teams can ensure continuous deployment and smooth value delivery.

How does DevOps enable Continuous Deployment?

DevOps enables Continuous Deployment by automating the integration, testing, deployment, and monitoring processes, thereby speeding up the delivery and improving quality.

DevOps streamlines Continuous Deployment by integrating tools and practices that automate deployment. These include provisioning infrastructure, deploying solution binaries, verifying functionality, capturing runtime telemetry, and alerting on issues proactively. These mechanisms and collaborative efforts across disciplines maximize delivery speed and quality.

DevOps Mindset, Culture, and Practices

What is the SAFe DevOps Mindset, Culture, and Practices?

SAFe DevOps is a mindset and set of practices promoting shared responsibility, automation, lean flow, measurement, and recovery for fast value delivery.

SAFe DevOps involves:

• Shared Responsibility: It fosters a culture of collective accountability across functions like development, operations, security, compliance, and more to create value rapidly.
• Automation: It employs automation to minimize human involvement in the Continuous Delivery Pipeline (CDP), reducing errors and cycle time.
• Lean Flow: It limits Work in Process (WIP), reduces queue lengths, and works with smaller batches to ensure uninterrupted value flow.
• Measurement: It advocates understanding and measuring value flow for continuous improvement.
• Recovery: It advocates building systems for quick issue resolution, including automatic rollback and ‘fix forward’ capabilities.

Why are the DevOps Mindset, Culture, and Practices important?

DevOps importance lies in increasing product innovation frequency, decreasing deployment risks, accelerating time-to-market, improving solution quality, and reducing failure severity.

The importance of DevOps includes the following five aspects:

• Enhanced Product Innovation: It encourages increased frequency, quality, and security of product innovations.
• Decreased Deployment Risks: It mitigates risks through accelerated learning cycles.
• Speedier Time-to-Market: It expedites product releases.
• Improved Solution Quality: It enhances the quality of solutions and reduces lead time for fixes.
• Reduced Failure Severity: It decreases the severity and frequency of defects and failures, and improves Mean Time to Recover (MTTR) from production incidents.

What are the five dimensions of the SAFe DevOps Approach?

The SAFe DevOps Approach operates on five dimensions: Culture, Automation, Lean Flow, Measurement, and Recovery (CALMR).

SAFe’s ‘CALMR’ approach to DevOps includes:

• Culture: The approach fosters shared responsibility across all relevant departments for fast value delivery.
• Automation: It promotes automation to reduce human intervention in the Continuous Delivery Pipeline (CDP), mitigating errors and reducing release process time.
• Lean Flow: It encourages limiting work in process, smaller batches, and reducing queue lengths to ensure uninterrupted value flow.
• Measurement: The approach supports understanding and measuring the flow of value through the pipeline for continuous improvement.
• Recovery: It focuses on building systems that facilitate quick fixes of production issues, such as automatic rollback and ‘fix forward’ capabilities.

Culture

In DevOps, culture emphasizes customer-centricity, collaboration, risk tolerance, and knowledge sharing, forming an integral part of SAFe principles.

In the context of SAFe Agile Product Delivery and DevOps, culture is essential in shaping four key areas:

1. Customer-Centricity: The organization can understand and respond promptly to customer needs, ensuring everyone in the value stream shares this understanding.
2. Collaboration: Effective partnership among development, operations, security, and other teams ensures solutions are developed, delivered, and maintained to match evolving business needs.
3. Risk Tolerance: A thriving DevOps culture encourages risk-taking and understanding that each release is an experiment that may sometimes fail. It rewards continuous learning and relentless improvement.
4. Knowledge Sharing: Cross-team knowledge sharing about ideas, tools, practices, and learnings creates unity in the enterprise, enabling skills to shift left, thereby facilitating collective growth.

Automation

Automation in DevOps entails replacing manual processes with automated ones to enhance value delivery, productivity, and safety.

In DevOps, automation plays a crucial role in optimizing various processes:

1. Value Stream Management (VSM): VSM tools provide real-time visibility into the health and efficiency of the value stream from end to end.
2. Version Control: These tools manage source code and configuration file changes, defining solution behavior.
3. Infrastructure as Code (IaC): These tools allow computing infrastructure to be built, deployed, changed, and destroyed on demand.
4. Test Automation: This is a significant source of delivery acceleration, applying to almost all testing types.
5. Vulnerability Detection: These tools detect security vulnerabilities across the Continuous Delivery Pipeline.
6. CI/CD: These tools orchestrate build, integration, testing, compliance, and deployment activities.
7. Monitoring and Analytics: These tools collect and analyze data to provide insights into pipeline flow, solution quality, and delivered value.

Lean Flow

Lean Flow in DevOps enables rapid feature movement from concept to cash, accelerating value delivery.

Lean Flow in DevOps focuses on three main strategies:

1. Visualize and Limit Work in Process (WIP): Tools like Kanban boards make WIP visible to all stakeholders, helping to identify bottlenecks and balance workload.
2. Work in Smaller Batches: Smaller batches move through the system faster and with less variability, facilitating more frequent deployments and accelerated learning.
3. Reduce Queue Lengths: Managing and reducing queue lengths is essential for fast flow. Shorter queues lead to quicker delivery.

Measurement

Measurement in DevOps involves tracking pipeline flow, solution quality, and solution value to optimize performance and value.

Detailed Response: Measurement in DevOps typically involves:

1. Measure Pipeline Flow: This focuses on throughput and lead time from concept to cash. The Flow Framework defines four flow metrics: flow velocity, efficiency, time, and load.
2. Measure Solution Quality: Quality metrics gauge adherence to functional, nonfunctional, security, and compliance requirements, best obtained via automated testing tools.
3. Measure Solution Value: These metrics evaluate the business value of the work exiting the pipeline, sourced from full-stack telemetry, analytics engines, financial systems, and user feedback.

Recovery

Recovery in DevOps involves designing for low-risk releases and quick recovery from operational failure, emphasizing a ‘stop-the-line’ mentality.

Recovery in DevOps focuses on the following strategies:

1. Stop-the-line Mentality: An issue compromising solution value leads team members to pause and focus on problem resolution, creating permanent fixes to avoid recurrence.
2. Plan for and Rehearse Failures: Teams develop recovery plans and regularly practice them in production or production-like environments to minimize impact and maximize resilience.
3. Fast Fix Forward and Roll Back: Given the inevitability of production failures, teams develop capabilities to quickly ‘fix forward’ or revert to a known stable state, improving overall system resilience.

Cloud Computing as an Enterprise Enabler

Cloud computing disrupts traditional IT models, accelerating product development and increasing business agility. It’s essential to digitally-enabled solutions and innovative product advancement.

Cloud computing, a paradigm shift in technology and business, fundamentally redefines the approach to building, deploying, and maintaining digitally-enabled solutions. It provides on-demand resources to IT operations and engineering teams, enabling fast and reliable access to applications and improved collaboration. AI and ML capabilities bolster product innovation, allowing enterprises to respond to market dynamics quickly. The transformative influence of cloud computing bridges the gap between technology management and market delivery, establishing a resilient and agile business model.

Aligning Cloud to Value

Aligning cloud capabilities with value-generating activities maximizes business agility, accelerates development value streams (DVS), and fosters continuous value creation.

The cloud’s transformative impact extends beyond efficient IT operations to fostering rapid value creation. By aligning cloud capabilities with value-generating activities, enterprises can experiment quickly and deliver disruptive solutions. This alignment is critical in leveraging the unique benefits of various cloud strategies and implementation models. It enhances DVS, making it more reliable and efficient, thus speeding up innovation and business agility. As a result, the enterprise experiences operational efficiencies and generates value quickly and continuously, transforming the business landscape and market positioning.

Cloud for Enterprise Infrastructure and Operations

Cloud for I&O enables migrating business solutions to the cloud, automates infrastructure lifecycle, and provisions on-demand runtime environments.

In Cloud for I&O, business solutions are migrated from on-premises data centers to the cloud, significantly accelerating the flow from infrastructure ‘request’ to ‘retire’ and mitigating service request lead times. This model:

• It starts with a service request for storage, network, or compute resources.
• Automates provisioning of application and database servers, scaling hardware capacity, administering security patches, and retiring legacy infrastructure.
• Delivers on-demand access to production resources and configurations and enables rapid configuration changes in response to business needs.
• Consists of highly elastic physical and virtual machines, exposed as IaaS, PaaS, and SaaS capabilities.

Cloud for Enterprise DevOps

Cloud for DevOps involves shifting I&O services left in the delivery pipeline, facilitating continuous solution innovation through cloud-native technology.

Cloud for DevOps extends I&O services into the delivery pipeline, enabling Agile teams to utilize cloud-based resources for continuous innovation. This model:

• Triggers value flow with the arrival of feature requests in the ART Backlog.
• Runs workloads supporting the end-to-end solution delivery lifecycle, including Agile planning, CI/CD, version control, and security-as-code.
• Accelerates feature delivery, generating high-quality, cloud-native solutions that can be scaled and modified quickly for continuous innovation.
• Provides Agile teams and ARTs with necessary infrastructure, applications, and DevOps capabilities to fuel Continuous Exploration (CE), Continuous Integration (CI), Continuous Deployment (CD), and Release on Demand (RoD) activities.

Cloud for AI

Cloud for AI is a composite pattern that extends the capabilities of the I&O cloud, providing substantial computing power to drive AI-based solutions and the development of machine learning models.

Cloud for AI is a foundation for creating AI-driven enterprise solutions, leveraging the vast computing power required for sophisticated machine learning models. It involves:

1. Inputs: These are typically business-focused needs for an AI solution captured as Epics, Features, Capabilities, or Stories.
2. Workloads: These are activities related to acquiring and mapping datasets, developing and training machine learning algorithms, evaluating algorithms, and integrating and delivering the models.
3. Outputs: The pattern produces intelligent AI-driven solutions, benefiting external customers with better solutions and internal stakeholders with insightful data.
4. Architecture: The I&O cloud supplies the necessary resources, such as storage, network, and compute power, needed for executing the machine learning pipeline.
5. How SAFe helps: SAFe assists organizations in building and operating a reliable, value-aligned AI cloud by facilitating decision-making, scaling AI capabilities, enabling business agility, and managing big data.

Agile Release Train (ART) Flow

What is ART Flow?

ART Flow refers to the continuous delivery of valuable features by an Agile Release Train (ART) to the customer.

ART Flow involves Agile Release Trains (ARTs) working alongside extended stakeholders to deliver valuable products and services to customers without interruption. This methodology encapsulates the Lean-Agile principle of uninterrupted value flow, focusing on Continuous Delivery Pipelines (CDPs). The complexity of this digital transformation mandates a significant shift towards Lean-Agile practices, and although impediments may be present, the ART Flow’s potential to improve value delivery is limitless.

Why is ART Flow important?

ART Flow is essential because it enables continuous value delivery and improves business outcomes.

ART Flow is crucial as it aims to improve business outcomes by accelerating value delivery through products and services. It encourages a Lean-Agile mindset to facilitate digital transformation, paving the way for an effective flow of value delivery. Moreover, it identifies and systematically addresses flow interruptions, promoting continuous value delivery.

What are the benefits of ART Flow?

ART Flow improves business outcomes, accelerates delivery, and promotes Lean-Agile practices.

1. Improved Business Outcomes: By enabling a continuous flow of valuable features, ART Flow aids in enhancing business results.
2. Accelerated Delivery: ART Flow utilizes Continuous Delivery Pipelines to hasten the delivery of valuable products and services.
3. Lean-Agile Mindset: The implementation of ART Flow encourages a shift towards Lean-Agile practices, making the digital transformation process more manageable and efficient.
4. Continuous Value Delivery: It plays a vital role in identifying and systematically addressing interruptions to flow, thus ensuring a seamless value delivery.

What are SAFe’s 8 “Flow Accelerators”?

SAFe identifies eight key “Flow Accelerators”: (1) Visualize and Limit Work in Process (WIP), (2) Address Bottlenecks, (3) Minimize Handoffs and Dependencies, (4) Get Faster Feedback, (5) Work in Smaller Batches, (6) Reduce Queue Lengths, (7) Optimize Time ‘In the Zone,’ and (8) Remediate Legacy Policies and Practices.

These “Flow Accelerators” provide strategies for improving value delivery by accelerating flow in the Agile Team and Technical Agility Competency.

1. Visualize and Limit WIP: SAFe stresses the importance of limiting Work in Process (WIP) as it causes confusion in priorities, induces context switching, and increases waste and frustration, mirroring the congestion caused by rush hour traffic. By visualizing and restricting WIP, teams focus and streamline their workflow (Beedle et al., 2001).
2. Address Bottlenecks: A team’s productivity is often constrained by bottlenecks. These are due to insufficient skills, capacity, resources, or system/process limitations. For optimum team flow, these bottlenecks need to be continuously identified and addressed (Anderson, 2010).
3. Minimize Handoffs and Dependencies: SAFe encourages minimizing handoffs (work transitions from one process step to the next) and dependencies (where specific input is needed from another team or individual). Excessive dependencies and handoffs disrupt team flow, cause delays, and increase context-switching and overhead (Kniberg & Skarin, 2010).
4. Get Faster Feedback: Solution development relies heavily on feedback to guide the team’s work. Delayed or absent feedback leads to misunderstandings, rework, slow delivery, and unsatisfied customers. Emphasizing quick and regular feedback is thus crucial (Schwaber & Beedle, 2002).
5. Work in Smaller Batches: Large batches often lead to delayed feedback, significant rework, and high variability. Hence, working in smaller batches is encouraged to accelerate flow and reduce waste (Poppendieck & Poppendieck, 2003).
6. Reduce Queue Lengths: Long queues, or backlogs waiting for implementation, increase wait times for new functionalities. Reducing these queue lengths improve flow and delivery times (Reinertsen, 2009).
7. Optimize Time ‘In the Zone’: The ‘zone’ is a highly productive mental state that takes time to enter and maintain. By minimizing distractions and optimizing this time, team members improve their productivity and quality of work (Larsen & Derby, 2006).
8. Remediate Legacy Policies and Practices: Some legacy policies and practices often conflict with new Agile practices, slowing progress and creating internal friction. Identifying and addressing these discrepancies is crucial to fully embracing Agile and improving flow (Leffingwell et al., 2020).

How do you apply SAFe’s 8 “Flow Accelerators” to Agile Product Delivery?

Visualize and Limit WIP

What does it mean to Visualize and Limit WIP?

Visualizing and Limiting WIP involves managing and reducing the amount of work-in-progress (WIP) to enhance ART productivity and value flow.

To visualize and limit WIP, an Agile Release Train (ART) must accurately represent all features currently in process. Work-in-progress (WIP) tasks are managed in the ART Backlog Kanban system. Limiting WIP means actively reducing the workload to prevent overload and enhance productivity. It includes representing feature-related and non-feature-related work to address the ART’s total workload.

Why is it essential to Visualize and Limit WIP?

Visualizing and Limiting WIP is crucial to improve productivity, clarify priorities, and enhancing value flow.

1. Improved Productivity: Reducing WIP prevents overload, thereby enhancing ART productivity.
2. Clarified Priorities: Visualizing WIP helps to define clear priorities, reducing confusion and the occurrence of context switching.
3. Enhanced Value Flow: Limiting WIP helps maintain a steady and efficient flow of value within the ART.

How do you Visualize and Limit WIP?

Visualizing and Limiting WIP involves visualizing all features in progress and controlling capacity allocation.

1. Visualize All Features in Process: All ongoing features are visualized and managed within the ART Backlog Kanban system, which helps manage the inventory of WIP features.
2. Establish Control with Capacity Allocation: The ART’s total WIP is addressed by establishing capacity allocations for feature-related and non-feature-related work, which helps maintain a balanced workload.

Address Bottlenecks

What does it mean to Address Bottlenecks?

Addressing Bottlenecks means identifying and mitigating elements that constrain ART productivity and improving the overall flow of work.

Addressing Bottlenecks involves identifying and resolving constraints that limit the productivity of the Agile Release Train (ART). These constraints can emerge anywhere in the process, and identifying them may occur during PI Planning, execution, or Inspect and Adapt sessions. Once recognized, the bottleneck must be understood and addressed to improve the ART’s overall productivity and performance.

Why is it essential to address Bottlenecks?

Addressing Bottlenecks is key to enhancing ART productivity, improving value flow, and ensuring optimal performance.

1. Enhanced Productivity: Resolving bottlenecks reduces constraints and enhances ART productivity.
2. Improved Value Flow: Addressing bottlenecks removes obstructions, enabling a smoother flow of value.
3. Optimal Performance: Regular identification and resolution of bottlenecks ensure the ART’s optimal performance over time.

How do you address Bottlenecks?

Addressing Bottlenecks involves identifying the bottleneck, understanding its impact, increasing capacity, and bypassing when necessary.

1. Identify the Bottleneck: Bottlenecks can be identified during PI Planning, execution, or Inspect and Adapt sessions. Tools like Value Stream Mapping, the planning board, and the ART Kanban system may assist in this process.
2. Understand the Full Impact: Understanding how a bottleneck affects the flow of value is essential to addressing it effectively.
3. Increase Capacity: Once identified and understood, increasing capacity at the bottleneck, when possible, helps mitigate the constraint.
4. Bypass the Bottleneck: In cases where increasing capacity isn’t feasible, bypassing the bottleneck, such as by selecting the next-most-valuable feature without dependencies, can prove effective.

Minimize Handoffs and Dependencies

What does it mean to Minimize Handoffs and Dependencies?

Minimizing Handoffs and Dependencies means reducing unnecessary transitions and interdependencies in work processes to enhance flow.

Minimizing Handoffs and Dependencies entails reducing the instances where work needs to transition from one process step to another, known as a ‘handoff,’ or where a task relies on a specific individual or another team’s input, known as a ‘dependency.’ Minimizing these elements allows the Agile Release Train (ART) to function more smoothly, leading to more efficient and productive outcomes.

Why is it essential to Minimize Handoffs and Dependencies?

Minimizing Handoffs and Dependencies enhances flow, reduces delays, and fosters cross-team integration.

1. Enhances Flow: Reducing handoffs and dependencies allows smoother work process transitions, enhancing flow.
2. Reduces Delays: Minimizing these elements reduces the potential for delays and rework, improving productivity.
3. Fosters Cross-team Integration: Smaller, more manageable dependencies foster more frequent cross-team integration, promoting collaborative problem-solving.

How do you Minimize Handoffs and Dependencies?

Minimize Handoffs and Dependencies by visualizing dependencies, fostering incremental execution, synchronizing frequently, optimizing team structure, and managing external dependencies.

1. Visualize Dependencies: Use the ART planning board to visualize and track dependencies across teams, optimizing execution throughout the PI.
2. Foster Incremental Execution: Divide dependencies into smaller, more manageable items to foster frequent cross-team integration and a faster process.
3. Synchronize Frequently: Use the ART Sync and direct team communication to synchronize dependencies and handoffs.
4. Optimize Team Structure: Build cross-functional, cross-disciplinary Agile Teams and apply team topologies to reduce dependencies.
5. Manage External Dependencies: Identify, track, and effectively manage handoffs and dependencies with external parties.

Get Faster Feedback

What does it mean to Get Faster Feedback?

Getting Faster Feedback refers to reducing the time to receive customer responses or system performance metrics, enabling swift corrections and improvements.

In Agile Release Trains (ART) context, getting faster feedback involves actively seeking information indicating whether the team is building the right solution and doing it correctly. This means enhancing the speed and efficiency of communication lines between the ART, customers, and the system they are developing.

Why is it essential to Get Faster Feedback?

Faster feedback mitigates issues early, fosters better alignment with customer needs, and ensures solution quality, minimizing rework and enhancing satisfaction.

1. Mitigates issues: Swift feedback allows for early detection and correction of errors, reducing the accumulation of problems.
2. Aligns with customer needs: Rapid customer feedback ensures the product aligns with expectations, mitigating the risk of unsatisfactory outputs.
3. Ensures solution quality: Fast feedback on system performance allows teams to maintain quality standards and rectify any detected issues swiftly.

How do you Get Faster Feedback?

Achieve faster feedback by ensuring both types of feedback, providing solution telemetry, frequently engaging customers, regularly integrating and testing, and utilizing research spikes and MVPs.

1. Ensure both types of feedback: Engage with customers continuously for solution suitability and test for technology viability and quality adherence.
2. Provide solution telemetry: Capture system usage and behavior data to facilitate feedback on system performance.
3. Engage customers frequently: Showcase the product at every opportunity and test new functionality with select customers.
4. Integrate and test frequently: Regularly combine and evaluate all product elements to confirm correct implementation.
5. Utilize research spikes and MVPs: Use experimental design methods like spikes and Minimum Viable Products to gain insights about the customer and the solution.

Work in Smaller Batches

What does it mean to Work in Smaller Batches?

Working in smaller batches involves subdividing work into manageable portions, facilitating quicker completion, reduced variability, and swift feedback loops.

Working in smaller batches in an Agile Release Train (ART) signifies dividing the tasks into manageable parts. These manageable chunks make the work more efficient by reducing the complexity, speeding up the completion process, and making the feedback process quicker, thereby minimizing variability and rework.

Why is it essential to Work in Smaller Batches?

Working in smaller batches reduces information decay, accelerates feedback, minimizes rework, and lowers variability.

1. Reduces information decay: Small batches help maintain the relevance of work and avoid information loss or decay over time.
2. Accelerates feedback: Smaller work units enable quicker completion and rapid feedback, allowing for swift adjustments.
3. Minimizes rework: Frequent feedback helps correct issues early, reducing the likelihood of extensive rework.
4. Lowers variability: Small batches promote predictability and lower variability in the development process.

How do you Work in Smaller Batches?

Work in smaller batches by understanding batch types and sizes, adhering to cadence, managing team sizes, automating delivery pipelines, planning for smaller batches, and using thin vertical slices of work.

1. Understand batch types and sizes: Recognize the various batch types—planning, integration, testing, etc., and optimize their size to balance transaction and holding costs.
2. Adhere to cadence: Stick to iteration and PI durations to maintain small batch sizes in planning, integration, and customer feedback.
3. Manage team sizes: Apply recommended Agile Teams and ART sizes to reduce batch sizes.
4. Automate delivery pipelines: Implement an effective Continuous Delivery Pipeline to reduce integration, test, and deployment batch sizes.
5. Plan for smaller batches: Consciously plan for smaller batches to keep them under control.
6. Use thin vertical slices of work: Employ thin, manageable features and limit the number of features taken within each iteration to reduce batch sizes.

Reduce Queue Lengths

What does it mean to Reduce Queue Lengths?

Reducing queue lengths means limiting the backlog of feature work awaiting service in the Agile Release Train (ART) to expedite delivery to the customer.

In ART, reducing queue lengths involves managing the backlog of work or features that have been committed but are waiting to be serviced. Shorter queues mean new features will reach the customer quicker, enhancing responsiveness and customer satisfaction.

Why is it essential to Reduce Queue Lengths?

Reducing queue lengths shortens wait times for new features, enhancing market responsiveness and customer satisfaction.

1. Enhances market responsiveness: Shorter queues mean new features, often vital to respond to market changes, can be delivered more quickly.
2. Improves customer satisfaction: Customers get access to new features faster, increasing their satisfaction with the product or service.
3. Streamlines work: Keeping queue lengths shorter helps manage the workload more effectively, reduce waste, and improve efficiency.

How do you Reduce Queue Lengths?

Reduce queue lengths by keeping roadmaps flexible, establishing a strong Product Management function, and reserving capacity for emergent priorities.

1. Keep roadmaps flexible: Fixed long-term roadmaps can create long queues. Whenever possible, maintain flexibility in dates and the scope of work to respond to market changes and new learnings.
2. Establish a strong Product Management function: Long queues often result from the inability to prioritize work effectively. Empower Product Managers to exert strong scope management leadership.
3. Reserve capacity for emergent priorities: Unforeseen events can trigger new work. By allocating reserve capacity, teams can adjust their plans to accommodate such unexpected work.

Optimize Time in the Zone

What does it mean to Optimize Time in the Zone?

Optimizing ‘time in the zone’ means maximizing the uninterrupted, focused work time for individuals and teams in the Agile Release Train (ART).

Optimizing time ‘in the zone’ involves maximizing periods of high concentration and productivity, where teams and individuals can focus on their tasks without interruption. In the context of ART, it means minimizing distractions and disruptions that could affect the focused effort of team members while they work on complex tasks.

Why is it essential to Optimize Time in the Zone?

Optimizing ‘time in the zone’ increases productivity by allowing individuals and teams to focus more deeply on their tasks.

1. Increases productivity: Uninterrupted, focused work periods can significantly enhance the productivity of individuals and teams.
2. Boosts creativity: High-focus work periods can stimulate more creative thinking and problem-solving.
3. Improves quality: With fewer distractions and interruptions, the quality of work can be significantly improved.

How do you Optimize Time in the Zone?

To optimize ‘time in the zone,’ keep work-in-process low, frequently integrate work, maintain solution health, and ensure efficient events.

1. Keep work-in-process low: Limiting the number of active tasks reduces context-switching and work interruptions, keeping individuals and teams focused.
2. Frequently integrated work: Regular cross-team integration helps quickly resolve inconsistencies and issues, reducing frequent interruptions.
3. Maintain solution health: Continuously addressing technical debt helps teams stay focused and productive, reducing time spent chasing dependencies and defects.
4. Ensure efficient events: Optimize PI Planning systems demos and Inspect & Adapt workshops to maximize team productivity.

Remediate Legacy Policies and Practices

What does it mean to Remediate Legacy Policies and Practices?

Remediating legacy policies and practices involves identifying and updating outdated procedures that impede Lean-Agile transformation.

Remediating legacy policies and practices means identifying, challenging, and updating or eliminating old, entrenched policies and practices that hinder the adoption and effectiveness of Lean-Agile methodologies. These could be traditional project management structures, old quality systems and governance models, or practices that separate essential functions from Agile Release Trains (ARTs) and value streams.

Why is it essential to Remediate Legacy Policies and Practices?

It’s essential to remediate legacy policies to implement Lean-Agile practices and enhance organizational agility successfully.

1. Promote Lean-Agile transformation: Outdated policies may inhibit Lean-Agile practices, hindering transformation.
2. Increase efficiency: Removing redundant meetings and streamlining processes can increase efficiency.
3. Improve collaboration: Remediation can help break down silos and promote cross-functional collaboration.
4. Enhance customer value: Updating policies that prevent necessary changes to products or services can improve customer value delivery.

How do you Remediate Legacy Policies and Practices?

Identify legacy policies, acknowledge their impact, engage stakeholders, and make necessary changes, including training and coaching.

1. Identify impediments: Recognize legacy policies and practices that hinder flow and the Lean-Agile transformation.
2. Acknowledge their impact: Understand how these practices affect teams, workflow, and customer value.
3. Engage stakeholders: Involve key stakeholders in discussions about how to adapt or eliminate these policies.
4. Implement changes: Make necessary changes to these policies and practices. This could involve updating procedures or adopting new practices that align better with Lean-Agile principles.
5. Provide training and coaching: Ensure stakeholders understand and can effectively operate within the new policies through training and coaching.

How do you measure ART Flow?

Measuring ART Flow involves evaluating aspects such as predictability, time, load, and efficiency of an Agile Release Train (ART).

Measuring ART Flow is a critical part of SAFe Agile Product Delivery, helping to assess and enhance the ability to deliver innovative solutions rapidly. Six key measures help evaluate ART Flow: flow distribution, velocity, time, load, efficiency, and predictability. These indicators provide insights into the ART’s performance and can highlight areas that need improvement.

ART Flow Predictability

ART Flow Predictability measures the ART’s ability to meet its Program Increment (PI) objectives.

ART Flow Predictability measures how well an Agile Release Train can plan and achieve its Planning Interval objectives. High predictability reflects that the ART consistently meets most of its committed and sometimes uncommitted objectives. This measure is crucial for effective business planning and execution.

ART Flow Time

ART Flow Time is the total time to deliver new features, calculated from ideation to production.

ART Flow Time measures the elapsed time to deliver new features, typically calculated from ideation to production. It reflects the speed and efficiency of the Agile Release Train in translating ideas into deliverables. High flow time may indicate blockages or risks that need to be addressed.

ART Flow Load

ART Flow Load refers to the total amount of work in the ART system at a given time.

ART Flow Load measures the total amount of work in the ART system at any point, often represented as Work-in-Progress (WIP). This metric helps identify whether the ART is overloaded with tasks, which may impact productivity and efficiency, or if there’s room for more work.

ART Flow Efficiency

ART Flow Efficiency compares the active time to the total time an item takes to pass through the system.

ART Flow Efficiency is the ratio of active time (time spent working on an item) to the total time it takes to pass through the system. This metric reveals the degree of waste in the system due to waiting times and can guide actions for process optimization. Low efficiency indicates more time spent waiting than working, suggesting the need to address bottlenecks.

What is the SAFe Framework, and how does it relate to Agile Product Delivery?

The SAFe Framework is a method for scaling Agile practices across large organizations, where PI Planning is a key event for synchronizing all Agile teams on a shared mission.

The Scaled Agile Framework (SAFe) is a set of principles, practices, and workflows designed to implement Agile and Lean practices at enterprise scale. It facilitates alignment, collaboration, and delivery across multiple Agile teams. With respect to Agile Product Delivery, SAFe incorporates it as one of its core competencies, leveraging customer-centricity, DevOps, and a ‘Release on Demand’ strategy to deliver solutions that provide continuous value.

What are the SAFe configurations, and how do they relate to Agile Product Delivery?

SAFe configurations are levels of SAFe adoption—Essential, Large Solution, Portfolio, and Full—that correspond to an organization’s size and complexity, facilitating scaled Agile Product Delivery.

SAFe configurations are adaptations of the SAFe framework designed to meet diverse organizational needs based on size, complexity, and specific business objectives. There are 4 SAFe configurations, and they are:

1. Essential SAFe: This is the foundational level of the Scaled Agile Framework, which includes Agile Product Delivery, that provides the basic elements needed for teams to align on strategy, collaborate effectively, and deliver complex, multi-team solutions.
2. Large Solution SAFe: This configuration extends Essential SAFe to address the challenges faced when multiple Agile Release Trains are needed to deliver large-scale solutions that typically involve coordinating multiple teams across an organization.
3. Portfolio SAFe: This configuration adds strategic and portfolio management to the Essential SAFe configuration, providing a way to align enterprise strategy with portfolio execution and manage Lean-Agile budgeting, strategic direction, and investment funding.
4. Full SAFe: The most comprehensive configuration, Full SAFe integrates all other configurations to provide a complete approach to delivering large, integrated solutions while coordinating multiple Agile Release Trains and managing portfolios at the enterprise level.

Regardless of the configuration, PI Planning remains a central event within SAFe. It allows teams to align their goals, understand dependencies, and create an achievable plan for the upcoming Planning Interval. It’s a shared experience, irrespective of the chosen SAFe configuration, and a fundamental mechanism to achieve alignment, synchronization, and delivery predictability across different levels of the organization.

Is SAFe Agile?

Yes, SAFe is Agile, as it implements Agile principles on an enterprise scale.

While it’s accurate to say that SAFe is indeed Agile, it’s crucial to understand that SAFe applies Agile methodologies to an expanded context, specifically designed for large-scale businesses and corporations. Rooted in Agile principles, SAFe scales these principles and practices, making them applicable to the enterprise level. This includes concepts like iterative development, cross-functional teams, regular retrospection, and adaptive planning. SAFe uniquely enables synchronization across multiple Agile teams, which allows for coordinated strategic direction and execution. Therefore, rather than viewing SAFe as a departure from Agile, it’s more apt to consider it an extension of Agile, crafted to cater to the complexities and needs of larger organizations.

Is SAFe Agile Product Delivery truly Agile?

SAFe Agile Product Delivery is truly Agile; it maintains Agile principles while scaling to accommodate enterprise-level complexity and coordination.

SAFe Agile Delivery embodies Agile principles, including iterative development, responsiveness to change, and customer collaboration. While SAFe provides additional structure to handle the complexity of large-scale implementations, its Agile Product Delivery component focuses on customer-centricity, DevOps, and a ‘Release on Demand’ strategy. This approach fosters continuous value delivery and adaptability, core tenets of Agile. Therefore, despite its scalability, SAFe Agile Product Delivery remains true to Agile principles.

What are the SAFe Core Competencies?

SAFe’s seven core competencies, including Agile Product Delivery, provide a holistic approach to delivering value in a Lean, Agile, and sustainable manner.

The Scaled Agile Framework (SAFe) defines seven core competencies, and they are:

1. Lean-Agile Leadership: Inspires adoption of Agile practices.
2. Team and Technical Agility: Enhances team capabilities and technical skills.
3. Agile Product Delivery: Delivers customer value through fast, integrated delivery cycles.
4. Enterprise Solution Delivery: Manages large-scale, complex solutions.
5. Lean Portfolio Management: Aligns strategy and execution.
6. Organizational Agility: Enables quick, decentralized decision-making.
7. Continuous Learning Culture: Encourages innovation and improvement.

Agile Product Delivery is a crucial practice in SAFe, where the core competencies are applied to ensure value is continuously delivered to the customer. Lean-Agile Leadership cultivates a mindset that embraces agility and commitment to the Agile Product Delivery. Team and Technical Agility encourages cross-functional teams to work together to deliver timely quality solutions. Agile Product Delivery itself is central, focusing on delivering valuable outcomes, fostering user-centric design, and developing on cadence while releasing on demand. Organizational Agility empowers teams to respond rapidly to changes and adjust their strategy for product delivery accordingly. Enterprise Solution Delivery facilitates the delivery of large, complex solutions that require coordination across multiple teams. Lean Portfolio Management aligns strategy and execution by connecting portfolio execution to the enterprise strategy, which enables the teams to deliver the most valuable products. Continuous Learning Culture nurtures an environment of relentless improvement, directly impacting the product delivery cycle by making it more efficient and effective. Together, these competencies enable Agile Product Delivery to contribute significantly to the overall Business Agility of the organization.

SAFe Practices

What is the SAFe Requirements Model?

The SAFe Requirements Model combines Artefacts and activities that guide the creation of system solutions.

SAFe Requirements Model includes a combination of Artefacts – Epics, Capabilities, Features, and Stories, along with the corresponding activities necessary for defining and implementing a system. It’s a flexible model that can be adapted according to the needs of each organization. This model assists in breaking down large work items into manageable sizes, thus promoting incremental delivery.

What is PI Planning?

PI Planning represents a routine, face-to-face event where Agile Release Trains establish a plan for the upcoming Program Increment (PI).

Agile Release Train (ART) teams collaborate and align on a shared mission and vision in this event. PI Planning creates the framework for teams to understand their work in the broader context, set team and program PI objectives, and identify dependencies across teams. It involves two main parts: Day One focuses on business context, product vision, and team breakout sessions, while Day Two emphasizes draft plan reviews, management review, and problem-solving.

What is SAFe built-in Quality?

SAFe built-in Quality means integrating quality standards into every product increment, promoting high standards rather than fixing issues afterward.

Built-in Quality is one of the core values of SAFe and emphasizes prevention over cure. It encompasses flow, architecture and design quality, code quality, system quality, and release quality. Incorporating quality from the earliest stages of the development process reduces the cost of subsequent defects, promotes faster delivery times, and encourages frequent iterations.

What are SAFe Value Streams?

SAFe Value Streams identify the activities needed to deliver value to the customer through a product or service.

In SAFe, two types of value streams are identified: Operational and Development. Operational Value Streams are the steps that an organization uses to deliver the product or service to the customer. In contrast, Development Value Streams represent the organization’s steps to develop new products or services, underpinned by Agile Release Trains (ARTs).

What is SAFe Continuous Delivery?

SAFe Continuous Delivery refers to the development practice of always maintaining a releasable state of the product, enabling frequent and reliable releases.

SAFe’s continuous delivery pipeline consists of four aspects: Continuous Exploration, Continuous Integration, Continuous Deployment, and Release on Demand. Continuous Delivery allows teams to reduce the lead time of feature delivery, increase deployment frequency, enhance product quality, and heighten customer satisfaction by providing regular updates and improvements.

What are the SAFe Principles?

The SAFe Principles are a set of ten fundamental principles derived from Lean and Agile methodologies that guide the implementation of SAFe.

SAFe principles are guidelines derived from Agile practices and methods, Lean product development, and systems thinking to facilitate large-scale, complex software development projects. The ten principles that make up the SAFe framework are as follows:

1. Take an economic view: This principle emphasizes the importance of making decisions within an economic context, considering trade-offs between risk, cost of delay, and various operational and development costs.
2. Apply systems thinking: This principle encourages organizations to understand the interconnected nature of systems and components and prioritize optimizing the system as a whole rather than individual parts.
3. Assume variability; preserve options: This principle highlights the importance of maintaining flexibility in design and requirements throughout the development cycle, allowing for adjustments based on empirical data to achieve optimal economic outcomes.
4. Build incrementally with fast, integrated learning cycles: This principle advocates for incremental development in short iterations, which allows for rapid customer feedback and risk mitigation.
5. Base milestones on an objective evaluation of working systems: This principle emphasizes the need for objective, regular evaluation of the solution throughout the development lifecycle, ensuring that investments yield an adequate return.
6. Make value flow without interruptions: This principle focuses on making value delivery as smooth and uninterrupted as possible by understanding and managing the properties of a flow-based system.
7. Apply cadence, and synchronize with cross-domain planning: This principle states that applying a predictable rhythm to development and coordinating across various domains can help manage uncertainty in the development process.
8. Unlock the intrinsic motivation of knowledge workers: This principle advises against individual incentive compensation, which can foster internal competition, and instead encourages an environment of autonomy, purpose, and mutual influence.
9. Decentralize decision-making: This principle emphasizes the benefits of decentralized decision-making for speeding up product development flow and enabling faster feedback. However, it also recognizes that some decisions require centralized, strategic decision-making.
10. Organize around value: This principle advocates that organizations structure themselves around delivering value quickly in response to customer needs rather than adhering to outdated functional hierarchies.

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