Continuously Delivering Value Competency

Which roles would benefit from mastering the Continuously Delivering Value Competency?

DevOps Practitioners, Scrum Masters/Team Coaches, Release Train Engineers (RTEs), Product Owners, Product Managers, System Architects, Solution Architects, Software Developers, Engineering Managers, Technical Leads

---

Learning about the Continuously Delivering Value Competency

Understanding Value Streams

Value Stream – The concept of a value stream is central to SAFe. SAFe identifies two types of value streams, operational and development. Defining, visualizing, and measuring your value streams provides the opportunity to improve the flow of value through them.

• An Operational Value Stream (OVS) is the sequence of activities needed to deliver direct value to a customer. Think of it as the end-to-end journey from customer request to customer fulfillment. Examples include fulfilling an order, admitting and treating a medical patient, providing a loan, or delivering a service.
• While the OVS delivers operational value, a Development Value Stream (DVS) is the sequence of activities we use to build a digitally enabled product or solution that the OVS uses to carry out its operational work or that the OVS might sell or provide to the customer.

This competency focuses on the DVS (Figure 1). It’s the process of transforming an idea into a Feature or Capability within a system, product, or solution. The development value stream contains all the activities, people, systems, information, and materials needed to deliver value. 

• Trigger – a new feature request triggers the value stream, though many new requests are moving through at the same time.
• Steps – these are the activities needed to define, build, validate, and release new value.
• Bar – the bar between steps shows information and materials flowing from one process to the next. It also implies the typical information handoffs as people in different steps add value to the flow.
• Ellipses (…) – these show delays between steps, typically contributing to long lead times. Decreasing delays is usually the fastest and most efficient way to reduce lead time.

The output of the DVS is a new increment of the product or solution, which is the added value of the new features released. Read more about development value streams in the article below.

Introducing the Continuous Delivery Pipeline

The Continuous Delivery Pipeline (CDP) is an important part of accelerating product development flow. Each Agile Release Train (ART) builds and manages, or shares, a pipeline with the tools and resources to deliver value independently. A CDP allows Agile Teams and ARTs to deliver new functionality to users as needed. In some instances, ‘continuous’ may mean daily or even multiple releases per day. In others, this may mean weekly or monthly releases to satisfy market demands and business goals.

Building a Continuous Delivery Pipeline with DevOps

DevOps is crucial for continuously delivering value as it bridges the gap between development and operations, fostering a culture of collaboration, automation, and continuous improvement. It integrates practices like continuous integration, continuous delivery, and monitoring into a cohesive workflow.

In relation to value streams, DevOps enables the optimization of the entire DVS, from ideation to delivery, ensuring a smooth and efficient flow of value to the customer by breaking down silos and accelerating feedback loops. Watch the short overview of DevOps. Additional guidance on the CALMR approach to DevOps is also included for those who want to go more in-depth.

Elements of the Continuous Delivery Pipeline

The CDP contains four elements: Continuous Exploration, Continuous Integration, Continuous Deployment, and Release on Demand. Each of the guidance articles below describes these elements further.

Applying the Continuously Delivering Value Competency

Applying the Continuously Delivering Value competency requires a systematic approach and a focus on practical strategies.

Run a Value Stream Mapping Workshop

The first step to improving value flow is mapping the current pipeline. After mapping the pipeline, teams collect and record metrics on the value stream map to note delays (Figure 3). This helps the Agile Release Train (ART) find ways to improve, like eliminating delays or cutting down on rework. Start by identifying current bottlenecks and inefficiencies in the delivery process. Begin with small, incremental changes and gradually expand the scope. Automate repetitive tasks, such as building and testing, and establish clear feedback loops to monitor progress. It’s vital to work collaboratively across teams, breaking down silos and promoting shared responsibility.

Watch the following video to understand more about Value Stream Mapping, and download and run the Value Stream Mapping workshop to identify your opportunities to improve the continuous delivery pipeline.

Optimize the End-to-End Development Value Stream

Adding the SAFe DevOps class is a great way for you and your colleagues to develop a shared understanding of the current state of your continuous delivery pipeline. Everyone will also gain renewed alignment on the techniques that can be used collectively to enhance the pipeline’s flow.

Additionally, you will be able to reflect on how to utilize tools and technologies that support CI/CD, DevOps, and AIOps. Integrating testing at every stage of the delivery pipeline and ensuring robust monitoring to detect and resolve issues quickly. Leveraging data and metrics to measure the effectiveness of implemented changes and make informed decisions.

Enabling this Competency with AI

AI is a huge enabler of continuously delivering value. As you apply this competency, consider using AI practices and tooling such as:

• Intelligent Automation: Explore using AI-powered tools to automate more complex tasks beyond building and testing code, such as anomaly detection in deployments, predictive analysis for capacity planning, or intelligent test case generation.
• AI-Driven Insights: Leverage AI and machine learning to analyze feedback data from various sources. Identify patterns and gain deeper insights into user behavior and system performance to inform prioritization and process improvements.
• AI-Assisted Decision Making: Integrate AI-powered analytics into your value stream to provide data-driven recommendations for optimizing flow, identifying potential risks, and predicting delivery timelines.
• AI for Continuous Improvement: Employ AI to monitor the effectiveness of process changes and automatically suggest further optimizations based on performance metrics.

By strategically incorporating AI, you and your organization can further enhance the speed, efficiency, and intelligence of your value delivery pipelines.

Mastering the Continuously Delivering Value Competency

Mastering the competency of Continuously Delivering Value involves not only applying the practices but also driving continuous improvement and innovation. Rather than seeing this as a one-time activity, regular retrospectives and reviews should be conducted to identify areas for improvement and refine the approach. Based on learnings and feedback, adapt and iterate.

Additionally, renewing and refreshing the aligned view of the value stream map is critical. You will want to gauge not only whether the improvements everyone identified are actually making a difference but also whether new technologies, systems, processes, and services delivered will change the mapping over time.

Some measures that are of particular benefit to pay regular attention to are: 

• Flow Time: Measures the total time elapsed for all the steps in a workflow and is, therefore, a measure of the efficiency of the entire system. Flow Time is typically measured from ideation to production. Still, it can also be useful to measure Flow Time for specific parts of a workflow, such as code commit to deployment, to identify opportunities for improvement.
• Flow Efficiency: Measures how much of the overall flow time is spent in value-added work activities vs. waiting between steps.
• Cumulative Flow: Flow load indicates how many items are currently in the system. Keeping a healthy, limited number of active items (limiting work in process) is critical to enabling a fast flow of items through the system.

Furthermore, across the organization, mastery looks like being able to see the patterns across multiple value streams that require attention and improvement as a systemic improvement. The VMO, LACE, and members within the development value streams should become adept at leveraging data analytics and AI to optimize processes and predict potential problems. Members of product and architecture exemplify mastery through proactively seeking out new technologies and approaches to stay at the forefront of industry trends. They then prioritize creating capacity across Agile Teams to apply what they discover. All members of the organization champion a culture of continuous learning, experimentation, and adaptation, enabling the organization to remain Agile and competitive in a rapidly changing landscape.

From Fog to Flow: A Journey to Continuous Delivery

Nimbus Networks, a leading AI and cloud services company, was bursting with potential but hampered by sluggish deployment cycles. Their releases felt like navigating a digital fog, promising but often late and unclear. Dissatisfied clients began seeking clearer skies elsewhere. Nimbus’s leadership understood they had to master the “Continuously Delivering Value” competency or risk becoming obsolete.

They initiated change incrementally, like a single server booting up a crucial service. The engineering teams, guided by a seasoned architect named Cirrus, started automating their infrastructure provisioning and code deployments. Cirrus often said, “Even the smallest automated task contributes to a more reliable system.” Gradually, their teams began to function with the efficiency of a distributed network. The marketing department, once prone to overpromising future capabilities, learned to align its announcements with actual release schedules.

They visualized their delivery pipelines as intricate data flows. They identified manual approvals and outdated processes as bottlenecks, like network congestion slowing down vital data packets. They systematically streamlined these processes. Their CI/CD pipeline evolved into a high-speed connection, delivering updates as seamlessly as cloud services scale on demand. They integrated AI-powered monitoring tools, nicknamed “Sentinel,” to anticipate system anomalies and prevent service disruptions, ensuring continuous uptime.

The transition wasn’t immediate. There were periods of instability and unforeseen errors. Yet, they persevered, learning and evolving. They conducted post-incident reviews that helped them update their value stream maps to analyze failures and identify areas for improvement. They celebrated successful deployments, like a successful migration to a more robust cloud region.

Ultimately, Nimbus Networks transformed from a company with fragmented resources to a highly efficient cloud ecosystem. They delivered new features and updates with speed and reliability, like a well-tuned API. Their clients, once uncertain, now relied on Nimbus’s consistent performance. The company thrived, a clear example of the impact of mastering continuous delivery in the cloud era. Cirrus frequently reminded the organization, “Even the most complex cloud infrastructure starts with a single line of code deployed efficiently. Consistent delivery is the key to sustained growth.”

Continuing your Journey Through the Team and Technical Agility Discipline

Although each team will benefit from addressing the competency specific to their needs, the following competencies represent common next steps in a learning journey.

Last Update: 2 July 2025