Lean Systems Engineering Competency

Which roles would benefit from mastering this competency?

Solution Managers, Solution Architects, Engineering Leaders and Managers, and the engineers responsible for building large solutions and systems.

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Learning about Lean Systems Engineering

A traditional approach to systems engineering emphasized technical performance, often involving a “Big Design Up Front” approach, where major decisions and detailed specifications are made early, before development or testing begins. The goal was to create an ideal system specification and schedule to deliver it. The result often led to inefficient execution, delayed feedback and learning, and an inability to adapt. A Lean approach to systems engineering addresses these problems by applying a Lean mindset, exploring alternatives, and accelerating learning cycles.

Apply a Lean Mindset

To create a Lean, flow-based engineering process, systems engineers start by understanding what the customer truly needs and is willing to pay for. They move beyond static requirements to explore a user experience perspective and consider factors like system performance, usability, reliability, cost-effectiveness, and delivery timeline.

Once the value is understood, map the value stream by documenting the steps required to deliver the system. Identify and remove non-value-adding activities such as unnecessary handoffs, excessive documentation, rework due to defects, or waiting times between development phases. Then ensure that the remaining steps flow smoothly without interruption, delays, or bottlenecks. 

This requires decomposing work into small, manageable features that can flow through the system more efficiently, as well as breaking down organizational silos to foster cross-functional collaboration. As features flow through the system more efficiently, teams can accelerate feedback loops and gain early insights. This rapid feedback is then used to continuously improve both the system itself and the engineering processes that deliver it.

Explore Alternatives

Large solution and systems development inherently carries uncertainty and risks, and exploring alternatives is a crucial step in finding optimal solutions, moving away from premature, single-point design decisions. Set-based design is a practice where multiple design options are explored and evaluated concurrently, rather than committing to a single design early in the process. This approach helps reduce risk and enhances flexibility by allowing teams to gain a deeper understanding of various potential solutions and their implications before making final decisions. It promotes validated learning and preserving options, ultimately leading to more robust and adaptable solutions.

Accelerate Feedback and Learning Cycles

Accelerating learning cycles is critical for developing large-scale solutions, enabling organizations to adapt to change, mitigate risks, and continuously deliver value. By fostering rapid feedback and integrating insights quickly, solutions can evolve through continuous experimentation and refinement. Breaking down work into smaller increments enables engineering to develop, demonstrate, and receive feedback. Visualizing and limiting work in process (WIP) through a Kanban system increases focus and improves flow. A regular cadence synchronizes all solution builders to regular synchronization points for integration, learning, and adjustment.

Applying the Lean Systems Engineering Competency

Building on the foundational elements outlined in the learning section above, we now specify six practices that will help organizations transform their approach to developing large, complex solutions and systems, as shown in Figure 2.

1) Developing Solutions Incrementally

Organizations can develop solutions more incrementally by adopting a flow-based, value-driven model. This involves decomposing solutions into smaller, manageable components and capabilities, which are then built by multiple Agile Release Trains (ARTs) and teams. Managed interfaces enable ARTs and teams to independently evolve their designs without being tightly coupled to other dependent systems. These interfaces also facilitate frequent testing, as teams can replace dependent systems with stubs or test doubles that simulate their behavior. This approach supports parallel development for both software modules and hardware subsystems, thereby reducing integration risks and enabling more frequent and reliable integrations.

Actions to get started

• Design software solutions for change: Decompose solutions into small, manageable components and capabilities that can be independently delivered by ARTs and Teams. There are many well-known design principles and patterns that provide guidance on how to decouple system elements – Domain-Driven Design, Design Patterns (Factory, Singleton, etc.), Architectural Patterns (layered, event-driven, microservice, etc.), high coupling/low cohesion, SOLID (Single Responsibility, Open/Closed, Liskov Substitution, Interface Segregation, and Dependency Inversion), fracture planes (Team Topologies), to name a few. Ensure that all solution builders are well-versed in applying these patterns and utilize them to decouple system elements.
• Design hardware solutions for change: Hardware systems often prioritize unit and manufacturing costs over the ability to modify the system, often because the cost of delay associated with making a change is not well understood. Use reprogrammable components, such as FPGAs, over cheaper, fixed-logic ones like ASICs. Consider connection permanence and use connectors and clips instead of solder and welds. 
• Manage and evolve interfaces: Establish and manage interfaces between components to independently evolve their designs. Implement a versioning strategy that supports the evolution of interfaces. Define the process for evolving interfaces, including a review process and decision-making authority to approve changes. Maintain backwards compatibility by implementing adapters to connect new interfaces to legacy components. This applies to both software and hardware. 
• Facilitate independent testing: Utilize managed interfaces to enable teams to replace dependent components with stubs or test doubles, allowing for frequent testing and supporting the next practice, frequent integration.

2) Frequently Integrate the End-to-End Solution

Frequently integrating the end-to-end solution is paramount, as a system can evolve no faster than its slowest integration point. Organizations should establish a robust continuous integration and deployment strategy (CI/CD) that prioritizes automation and cross-team collaboration across the entire development value stream. For software components, this involves setting up automated build, test, and deployment pipelines that continuously integrate small software changes. At scale, software components are integrated into larger components, which are then integrated into the products and systems that deliver the overall solution. Frequent integration requires an understanding of the end-to-end flow through the component hierarchy, as shown in Figure 3.

Actions to get started (for software)

• Map the full value stream: Select a product for value stream mapping and identify the component integration and testing activities required to build it. Repeat the process for each sub-component until you arrive at a core component. Some components will be delivered to multiple downstream products and systems. Measure the deployment frequency and lead time for change at each level (sub-component, component, and product) and map the end-to-end flow of value for the large solution. Where possible, instrument telemetry in the delivery infrastructure to automate metrics collection.
• Accelerate flow: Simplify the end-to-end process by removing unnecessary steps, addressing bottlenecks, and eliminating handoffs across one or more processes. Optimize the processes by reducing batch sizes and remediating legacy policies and practices. Some of these issues require engineering leaders to actively drive change across multiple areas of the organization.
• Automate: Don’t automate a poor, wasteful process. After optimizing your process with the previous improvements, invest in automation. Find areas where manual activities are causing the largest delays in value delivery and automate them. Leverage existing build, test, and deploy automation products and solutions. Apply an Infrastructure as Code (IaC) approach to ensure the code and infrastructure are managed together.
• Apply AI and machine learning (ML): Emerging technologies, such as AI and ML, are being increasingly used to make CI/CD pipelines more intelligent and proactive. They can analyze historical pipeline data to predict potential issues before they cause a failure. ML-driven test systems can generate and prioritize test cases based on which parts of the code have changed, improving test coverage and speed. AI can also detect and resolve common problems, such as a temporary network issue, to prevent pipeline failures
• Manage complexity: At a large scale, frequent integration is challenged by dependencies, component versions, performance, and reproducibility. Select a version control strategy, either monorepo or polyrepo, which will dictate your CI/CD strategy. Use a repository to manage versioned artifacts and dependency management tools (Bazel, Nx) to manage large, complex builds. Design modular pipelines that can run builds in parallel. Manage the overall integration flow, including trigger management for dependent builds and failure detection, with robust logging, monitoring, and alerts.

Emerging hardware technologies are transforming the speed and efficiency of integrating hardware components, as shown in Figure 4. Environments on the left provide faster and more cost-effective integration and testing, though at a lower level of fidelity. Learning can only go so far in each before we must move to the next, higher-fidelity environment to validate the assumption we are making in the current environment. This approach significantly accelerates feedback cycles and reduces the cost and time associated with physical builds.

First, we enable component and subsystem teams to learn and iterate on their designs more quickly through the horizontal integration of the delivery pipeline. Second, integrate vertically within each environment to more frequently integrate components into subsystems and subsystems into systems, as shown in Figure 5. Regular, synchronized integration points are essential for bringing together components from various teams and suppliers, ensuring that the overall solution remains cohesive and functional.

Actions to get started (for hardware)

• Invest in digital modeling and simulation: Invest in a comprehensive digital modeling and simulation environments that incorporate real-time digital twin technologies. This provides engineers a risk-free environment for accelerated design, testing, and operational insights. Virtual components can be designed, tested, integrated, and validated before physical parts are built. Integrate digital models 
• Invest in digital rapid prototyping: Some hardware requires testing and validation of physical parts. Provide access to digital rapid prototyping technologies
• Capture data: The true value of digital twins lies in their integration with real-world data. Design systems with embedded sensors into physical assets to measure environmental, operational, and behavioral data, which can then be transmitted via wired or wireless networks for processing. Also embed telemetry into the simulation, prototype, and manufacturing environments to improve the solutions (lower cost, increase performance, and improve the way we build the solution (address bottlenecks, improve flow). 
• Rethink the engineering design and delivery process: Make these environments and feedback from them part of the normal engineering development cycle, not just for one-off experiments and exploration. Begin with small pilots to determine the right technology and infrastructure for your context. Scale to other products and parts of the organization.

3) Applying Multiple Planning Horizons

As teams accelerate development cycles, the need for adaptive planning becomes critical. Traditional approaches that depend on fixed, detailed schedules cannot support the rapid adjustments demanded by accelerated learning cycles. Instead, Agile practitioners use roadmaps to manage and forecast work, and quickly adjust them as new information emerges. At a large scale, multiple planning horizons utilize multiple layers of roadmaps, allowing organizations to balance long-term vision with near-term flexibility and adapt to changing conditions.

Actions to get started

• Define a powerful vision and intent: Define the large solution’s purpose and its benefits to the organization and society, including a high-level objective to achieve over time. Communicate the new customers, markets, and the new operating models and journeys our users will experience. This helps align all value streams to deliver a comprehensive solution, enabling decentralized decision-making across all solution builders.
• Build a large solution roadmap: Run a Large Solution Roadmapping Workshop to create alignment across all the solution builders. This results in an agreed-upon roadmap for the large solution that all value streams can support. And each value stream leader understands the work they need to perform each PI in support of the large solution. Note: The details of this workshop are described in the Large Solution Roadmapping Competency (see the link at the end of this article).
• Continually maintain alignment: Use regular sync events at all levels (ART, Solution Train, and Large Solution) during execution to monitor progress and make appropriate adjustments.

4) Specifying the Solution Incrementally

In SAFe, a vision and roadmap drive the team’s and ART’s work, not a detailed specification. A traditional, “big design up front” approach front-loads major decisions before any actual development or testing begins. It delays the discovery of potential issues, incorrect assumptions, and evolving customer needs. Instead, specifications must evolve in tandem with the solution itself. This continuous flow model acknowledges that requirements and understanding deepen as the solution is built and validated. Figure 6 illustrates this approach with the team’s backlog driven by the vision and roadmap. Each increment, the term performs the necessary work to evolve the solution and the specifications managed in the solution intent.

SpaceX is well-known for evolving specifications along with the solution, as shown in Figure 7. SpaceX employs a learn-as-you-go iterative design process, transitioning from the complex, heavily instrumented Raptor 1 to the drastically simplified, yet more powerful, Raptor 2 and 3. This continuous refinement involved integrating components, eliminating excess hardware, and internalizing plumbing to reduce mass, improve manufacturability, and dramatically increase thrust and efficiency with each new version. It would have been impossible to specify the Raptor 3 without the learnings from Raptor 1 and 2.

Actions to get started

• Replace “big design up-front” activities with continuous exploration: Agile teams are driven by backlogs, not specifications. Instead of building specifications, systems engineers drive innovation and foster alignment on what should be built by continually exploring the market and customer needs, defining a vision, roadmap, and set of features for a solution. These activities drive backlogs for ARTs and teams.

• Use the language of ‘intent’: Don’t overly constrain teams and stifle their ability to innovate. Instead of using fixed language in backlog items and other requirements, provide teams with the intent behind them. For example, use language like ‘The vehicle shall be able to travel between charging stations in targeted geographic regions’ instead of ‘The vehicle shall have a minimum range of 420 miles’.
• Prepare and evolve the solution intent: Large solutions will have requirements and design specifications as needed to support activities like compliance. Define the structure sufficiently for the teams to populate each increment as they evolve the solution and the specifications. Demonstrate the solution and specifications every increment to ensure we are progressing towards building the right solution and gathering the proper data needed to deploy, manufacture, and operate.

5) Continually Address Compliance Concerns

With the solution now available earlier through incremental development, organizations can apply quality practices for verification and validation sooner, effectively shifting compliance activities left alongside engineering efforts. Typically, quality management and compliance efforts have relied on a traditional approach, often assuming or even mandating early commitment to unvalidated specifications and design decisions, detailed work breakdown structures, and document-centric, phase-gate milestones.

This has led to compliance activities being performed in a large batch at the end of the development cycle. However, with the shift to incremental development and earlier system availability, compliance teams must also adapt their practices to perform these activities continually, integrating them into the regular flow of value delivery rather than treating them as separate, end-of-lifecycle gates. 

SAFe defines the following practices to move towards a Lean approach to quality and compliance:

• Build the solution and compliance incrementally – The solution and its necessary compliance artifacts are developed together in small increments throughout the process.
• Organize for value and compliance – The organizational structure must be designed to not only deliver value but also to continuously meet all relevant compliance requirements.
• Build quality and compliance in – Quality practices are integrated directly into the development activities from the start, rather than relying on checks performed late in the process.
• Continuously verify and validate – Continuous checking is performed to ensure the system meets its functional and non-functional requirements (NFRs) and achieves its intended purpose
• Release validated solutions on demand – Solutions that have been continuously verified and validated are released when the business needs them, decoupling the release timing from the development cycle.

Actions to get started

• Evaluate progress towards compliance at each increment: Compliance standards govern both the solution and the process used to design and build it. Evaluate the solution by demonstrating that it meets regulatory constraints with component and system-level tests. Evaluate the process by generating and gathering the necessary information from the solution intent and other sources. Demonstrate compliance progress every increment at the Solution Demo. Based on the results, adjust the engineering practices to ensure the solution and necessary objective evidence are ready for the next release.
• Include compliance personnel on the teams and ARTs: Agile teams require all the necessary skills and authority to deliver their solutions. Therefore, compliance representatives should participate as active members of the ART, capturing compliance requirements in backlogs, contributing to the definition of done with compliance in mind, and incrementally performing required compliance activities (e.g., approvals, sign-offs) to remove bottlenecks for the teams. 
• Automate compliance tests along with functional tests: Agile teams already automate functional tests. Automate the compliance tests that show the solution meets regulatory requirements and quality standards throughout the development lifecycle, rather than performing these checks as a separate, late-stage activity.
• Continually perform compliance activities: Perform compliance activities (including reviews, audits, verification, and validation) incrementally, rather than in a large batch at the end. Where possible, include these activities as part of the definition of done for features and stories (Figure 8). This reduces the risk of not meeting compliance objectives and makes the final sign-off activity a quick, uneventful event instead of a large, high-risk one.
• Capture requirements and design information in the solution intent: The solution intent described above manages the requirements, design, and traceability information needed to support compliance. Ensure teams incrementally evolve the solution intent by updating it as part of their regular flow of work, ideally as part of their definition of done, as shown in Figure 8 below.

6) Evolve Deployed Systems

Since the solution and compliance data evolve frequently, we can deploy the product, systems, and infrastructure into the operational environment earlier and more frequently. This continuous evolution offers significant business advantages. By deploying minimum viable solutions early, organizations can quickly capture market share, generate revenue sooner, and gain a competitive edge. This approach minimizes the risk of investing heavily in solutions that may not meet market needs, as early feedback allows for course correction and adaptation.

Early and continuous deployment accelerates feedback loops, providing invaluable insights into system performance, user behavior, and market reception. This rapid learning enables teams to validate assumptions, identify and address issues promptly, and refine the solution based on real-world data rather than theoretical models. This iterative process fosters a culture of continuous improvement, where experimentation and adaptation are encouraged, resulting in more robust, efficient, and ultimately more successful large-scale systems.

Actions to get started

• Fund the product, not the project: Large solutions deliver significant value for many decades and require continuous investment to support evolving technology and business needs. A typical project-based approach commits substantial funds for the initial development but requires separate ‘modernization efforts’ to evolve it. A product-based approach to development recognizes that solutions evolve continuously and funds a development value stream that continually flows value to customers.
• Get good at releasing: In large solution development, the word ‘release’ often signifies a critical, high-stakes event where significant value, risk, and responsibility are transitioned to an operational environment. Many of the practices described above (build incrementally, build quality and compliance in) fundamentally impact this idea by shifting the focus from infrequent, large-scale events to a continuous, predictable, and low-risk process. As you adopt these practices, change your organization’s mindset towards continuous delivery and more frequent releases.
• Go faster with higher quality: Traditionally, execution speed and higher quality were seen as a trade-off. However, faster delivery and higher quality are interconnected and mutually reinforcing goals that can be achieved through process optimization and efficiency. Going fast requires significant technology investment and a culture shift. Invest in automating the end-to-end delivery pipeline, including the quality and compliance checks.
• Use telemetry to improve the organization: Use real-time data to monitor system health, identify issues promptly, optimize resource utilization, and gain a deeper understanding of the development process for these complex systems. This allows engineers to identify integration bottlenecks across multiple value streams and drive systemic improvements. Expert engineers also lead the charge in evolving deployed systems, ensuring that the integration pipeline supports continuous value delivery even after the initial release.

Mastering the Lean Systems Engineering Competency

Mastering this competency recognizes transitioning from a project management approach to one that optimizes and accelerates value delivery. For the individual, it means becoming an orchestrator of complex system development, capable of identifying and eliminating waste, accelerating learning cycles, and fostering a culture of continuous improvement. This level of expertise allows engineers to lead the charge in designing for change, facilitating rapid integration, and evolving deployed systems with a focus on both speed and quality.

Systems engineers who master this competency blend collaboration skills, domain knowledge, engineering skills, and operational expertise, focusing on the reliability, scalability, and efficiency of large-scale systems. Here are some next steps they can take towards mastering Lean Systems Engineering:

• Shift left for earlier feedback and risk reduction: By integrating quality, compliance, and operational considerations from the earliest stages of development, the Lean Systems Engineer ensures systems are inherently reliable, creating a proactive approach to preventing issues.
• Optimize for flow and minimize waste: Align goals across ARTs to ensure systems run efficiently and reliably, delivering value consistently without unnecessary impediments.
• Relentlessly automate tasks. Lean Systems Engineers will automate compliance checks, integration processes, and even aspects of design exploration to accelerate flow and reduce manual errors.
• Embrace data-driven decision making: Leveraging telemetry and real-time data, Lean Systems Engineers will continuously analyze performance, identify bottlenecks, and inform improvements across the entire value stream.
• Champion a culture of blameless postmortems and continuous learning: A Lean Systems Engineer fosters an environment where failures are seen as learning opportunities, driving continuous improvement in both processes and solutions.
• Cultivate strong interpersonal skills: Effective communication, collaboration, and negotiation are crucial for Lean Systems Engineers to work across diverse teams, align stakeholders, and drive consensus in large solution development.

Assessment Questions for Lean Systems Engineering

This self-assessment provides a simple method for evaluating your progress towards the application and desired outcomes of this competency.

1. How are you improving flow in your value stream?
2. How do you leverage telemetry to optimize resource use and identify bottlenecks?
3. Do you effectively explore multiple alternatives to avoid premature design decisions?
4. Are you decomposing your large solutions into independently deliverable components?
5. Do you manage evolving interfaces across the components built by multiple ARTs and teams?
6. Do you have a strategy for frequently integrating hardware and software components?
7. Do your large solution development efforts balance long-term vision with near-term planning flexibility?
8. Do you continuously evolve specifications?
9. How do you integrate compliance activities incrementally into your process?
10. What strategies do you use to accelerate feedback loops in large solutions?

Continuing Your Journey Through the SAFe Competencies

Last Update: 13 February 2026