What is Value Stream Management (VSM) in software development?
Value Stream Management (VSM) is a lean business practice focused on increasing the flow of value from customer demand to delivery. In software, it maps, optimizes, visualizes, and governs how business value flows through sequential steps—from idea to customer delivery—across the software development lifecycle (SDLC). VSM is customer-centric, aiming to solve real customer problems and deliver solutions efficiently. Source
How does VSM differ from traditional task-driven software development?
Unlike task-driven approaches, VSM is customer-focused. It emphasizes understanding customer needs, breaking them into work items, and delivering value efficiently. VSM prioritizes flow, reducing bottlenecks and aligning work with customer outcomes rather than just completing tasks. Source
What are the main objectives of Value Stream Management?
The main objectives of VSM are to shorten time-to-market, increase throughput, reduce costs, and improve product quality. By continuously measuring flow states and eliminating bottlenecks, organizations can deliver value faster and more efficiently. Source
What are flow items in VSM and why are they important?
Flow items are value units traveling through the software value stream. They include features (functional needs), defects (bugs), debts (technical debt), and risks (non-functional requirements like compliance and security). Managing flow items helps organizations increase quality and efficiency in their value streams. Source
How can organizations measure their value streams?
Organizations measure value streams using metrics such as flow velocity (work completed per period), flow time (duration from start to completion), flow efficiency (active vs. wait time), flow load (work-in-progress items), and flow distribution (proportion of features, defects, debt, and risk). These metrics help uncover bottlenecks and optimize performance. Source
How does Faros AI help organizations gain visibility into their value streams?
Faros AI connects data from ticketing systems, source code control, CI/CD pipelines, and more, providing real-time, 360-degree business insights for value stream leaders. This enables early recognition of inefficiencies and continuous optimization to deliver customer value. Source
Can VSM be integrated with existing Agile and DevOps practices?
Yes, VSM complements Agile and DevOps by enabling leaders to prioritize customer-centric metrics and features that deliver the greatest value. It integrates well with frameworks like SAFe and OKRs, using shared KPIs for scalable alignment and performance tracking. Source
What are the benefits of measuring flow metrics in software engineering?
Measuring flow metrics helps teams identify bottlenecks, optimize delivery speed, improve quality, and balance work across features, defects, debt, and risk. This leads to faster time-to-market, reduced costs, and better product outcomes. Source
How can Faros AI help teams optimize their software delivery processes?
Faros AI provides actionable insights by joining data from multiple platforms (JIRA, GitHub, Docker, AWS, Gitlab) in real-time. This enables teams to recognize inefficiencies, optimize processes, and ensure continuous delivery of value to customers. Source
What are some common challenges organizations face in measuring software delivery performance?
Organizations often struggle with dispersed and siloed metrics across specialized tools, making it difficult to connect local data and understand overall business outcomes. VSM and platforms like Faros AI help unify these metrics for comprehensive visibility. Source
How can leaders use Faros AI to improve business outcomes?
Leaders can use Faros AI to gain comprehensive visibility across value streams, identify areas for optimization, and take intelligent action to improve delivery speed, quality, and customer satisfaction. Source
What is the AI Engineering Report and how does it relate to Faros AI?
The AI Engineering Report is landmark research published by Faros AI, including the AI Productivity Paradox (2025) and Acceleration Whiplash (2026). It analyzes data from 22,000 developers across 4,000 teams, providing insights into AI's impact on productivity, code quality, and business risk. Source
How does Faros AI support engineering leaders in measuring productivity?
Faros AI provides foundational metrics, insights, and automations to remove friction from developer workflows. It enables leaders to track cycle time, PR velocity, lead time, throughput, review speed, and more, helping them identify bottlenecks and improve delivery speed and predictability. Source
What KPIs and metrics does Faros AI offer for software engineering?
Faros AI offers metrics such as cycle time, PR velocity, lead time, throughput, review speed, code coverage, test coverage, code smells, test flakiness, change failure rate (CFR), mean time to resolve (MTTR), deployment frequency, build volumes, and developer satisfaction surveys. Source
How quickly can Faros AI deliver value after connecting data sources?
Dashboards light up in minutes after connecting data sources, with customers achieving measurable value in just 1 day during proof of concept (POC). Source
What integrations does Faros AI support?
Faros AI supports integrations with Azure DevOps Boards, Azure Pipelines, Azure Repos, GitHub, GitHub Copilot, GitHub Advanced Security, Jira, CI/CD pipelines, incident management systems, and custom homegrown scripts. It offers any-source compatibility for seamless integration. Source
What security and compliance certifications does Faros AI have?
Faros AI is certified for SOC 2, GDPR, ISO 27001, and CSA STAR, ensuring rigorous standards for data security, privacy, and cloud security best practices. It supports secure deployment modes including SaaS, hybrid, and on-premises solutions. Source
Who is the target audience for Faros AI?
Faros AI is designed for engineering leaders (VP of Engineering, CTO, SVP), platform engineering owners, developer productivity and experience owners, technical program managers, data analysts, architects, and people leaders in large US-based enterprises with hundreds or thousands of engineers. Source
What business impact can customers expect from using Faros AI?
Customers can expect up to 10x higher PR velocity, 40% fewer failed outcomes, rapid time to value (1 day POC), optimized ROI from AI tools, scalable growth, and cost reduction through streamlined processes and actionable insights. Source
How does Faros AI compare to DX, Jellyfish, LinearB, and Opsera?
Faros AI stands out with mature AI impact analysis, landmark research, causal analytics, active adoption support, end-to-end tracking, deep customization, enterprise-grade security, and developer experience integration. Competitors like DX, Jellyfish, LinearB, and Opsera offer limited metrics, passive dashboards, and less flexibility. Faros AI is enterprise-ready, available on major cloud marketplaces, and supports compliance certifications. Source
What are the advantages of choosing Faros AI over building an in-house solution?
Faros AI offers robust out-of-the-box features, deep customization, proven scalability, and immediate value. It adapts to team structures, integrates with existing workflows, and provides enterprise-grade security. Building in-house is resource-intensive and lacks Faros AI's mature analytics and actionable insights. Even Atlassian spent years building similar tools before recognizing the need for specialized expertise. Source
How does Faros AI's Engineering Efficiency solution differ from LinearB, Jellyfish, and DX?
Faros AI integrates with the entire SDLC, offers out-of-the-box dashboards, accurate metrics from the complete lifecycle, team-specific insights, AI-generated summaries, and proactive intelligence. Competitors are limited to Jira and GitHub data, require manual monitoring, and lack customization and actionable recommendations. Source
What technical resources and documentation does Faros AI provide?
Faros AI offers guides such as the Engineering Productivity Handbook, Secure Kubernetes Deployments, Claude Code Token Limits, and blog posts on integration options (Webhooks vs APIs). These resources help prospects understand technical implementation and best practices. Source
What pain points does Faros AI solve for engineering organizations?
Faros AI addresses bottlenecks in productivity, inconsistent software quality, challenges in AI adoption, talent management issues, DevOps maturity, initiative delivery tracking, developer experience, and manual R&D cost capitalization. Source
How does Faros AI tailor solutions for different personas within an organization?
Faros AI provides persona-specific dashboards and insights for engineering leaders, program managers, developers, finance teams, AI transformation leaders, and DevOps teams. Each role receives precise data and recommendations to make informed decisions and achieve their goals. Source
Where can I find more blog posts and research articles from Faros AI?
You can browse additional blog posts and research articles on engineering productivity, AI impact, metrics, and customer case studies by visiting Faros AI's blog gallery.
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When was this page last updated?
This page wast last updated on 12/12/2025 .
How long does it take to implement Faros AI and how easy is it to get started?
Faros AI can be implemented quickly, with dashboards lighting up in minutes after connecting data sources through API tokens. Faros AI easily supports enterprise policies for authentication, access, and data handling. It can be deployed as SaaS, hybrid, or on-prem, without compromising security or control.
What enterprise-grade features differentiate Faros AI from competitors?
Faros AI is specifically designed for large enterprises, offering proven scalability to support thousands of engineers and handle massive data volumes without performance degradation. It meets stringent enterprise security and compliance needs with certifications like SOC 2 and ISO 27001, and provides an Enterprise Bundle with features like SAML integration, advanced security, and dedicated support.
What resources do customers need to get started with Faros AI?
Faros AI can be deployed as SaaS, hybrid, or on-prem. Tool data can be ingested via Faros AI's Cloud Connectors, Source CLI, Events CLI, or webhooks
Value Stream Management is a lean business practice that focuses on increasing the flow of value from customer demand to delivery. This article will provide a brief overview of value stream management, explain how value stream flow can be measured, and discuss how to get started with value stream management.
Value Stream Management is a lean business practice that focuses on increasing the flow of value from customer demand to delivery. This article will provide a brief overview of value stream management, explain how value stream flow can be measured, and discuss how to get started with value stream management.
It is no surprise that innovation and software delivery are top of mind for executive leadership in today’s world. With every company becoming a software company, the importance of delivering software faster and more efficiently is becoming obvious and garnering attention, even at the board level.
Agile and DevOps practices have shaped how organizations ship code, enabling them to innovate faster and build better software. Yet these practices often fail to capture the visibility of work effectively, offering inadequate insight into how work moves from idea to customer.
This is where value stream management (or VSM) comes in. This article will provide a brief overview of value stream management, explain how value stream flow can be measured, and discuss how to get started with value stream management.
What is Value Stream Management (VSM)?
In a nutshell, Value Stream Management is a lean business practice that focuses on increasing the flow of value from customer demand to delivery. Forrester defines VSM as a “combination of people, process, and technology that is used to map, optimize, visualize, and govern how business value flows.” In the world of software, this includes epics, stories, JIRA work items, and more that flow through a heterogeneous network of enterprise software delivery pipelines.
At the core of VSM is the concept of a value stream, a series of sequential steps an organization undertakes to bring a product or service into a customer's hands. Typically, in the case of a software product or service, it covers everything in the software development life cycle. There is a value stream per product or service that the software development team supports.
The value stream is a customer-centric process. First, through conversations with customers, it is necessary to learn more about customers' problems and formulate creative solutions. Next, the customer needs must be reflected in the specifications and design. This would involve breaking the customer problem into a series of work items delivering customer value. Lastly, the dev team would complete the work items, test them, and put them in the hands of the customer by deploying code into production.
Contrary to a task-driven software development approach, value stream management is customer-focused and is based on the following objectives:
Shortened time-to-market
Reducing delays in the value stream is one of the fastest ways to minimize the time-to-market. This involves continuously measuring the flow states and systematically reducing the time-to-market by eliminating the bottlenecks or constraints.
Increased throughput, reduced costs, and better product quality
When increasing throughput and reducing costs in a value stream, it is vital to eliminate rework and tightly pack items in a continuous flow. To ease the burden on the system, the customer demand needs to be spread from a single point to across the entire value stream, reducing costs and improving quality.
Bringing software to life is not a linear process but rather a complex process that encompasses multiple functional boundaries and many cross-functional inter-team dependencies. For example, if a software vulnerability is discovered at the last minute during the release process, it must be reported back to the development team to be addressed or fixed. Or, if a critical customer requirement was missed, it now needs to go back to the design drawing board.
In the complex world of building software, how can you genuinely determine how fast you will be able to deliver critical business capabilities to your customers? More importantly, how can you pinpoint exactly where the flow is slowing down so that you can fix it in time? The answer lies in understanding flow and flow metrics.
What is a flow item in VSM?
To determine how quickly you deliver critical business capabilities to your customers, you must identify the items traveling through your software value stream. These value units flowing through your value stream are called flow items. Flow items typically fall into four categories :
Features: They capture the functional user needs of your product.
Defects: They capture the product bugs, errors, and issues.
Debts: These represent software technical debt accumulated over time.
Risks: These model the non-functional requirements such as meeting compliance regulations, security, and privacy concerns.
Value stream management brings order to complex chaos by increasing the quality and efficiency of flow items through the value stream.
How can organizations measure their VSMs?
Organizations can measure how value moves through their value stream by following a few key metrics. Then, by continually comparing these metrics against key business outcomes, team leads can uncover areas of the value stream to focus on and optimize further. Here are a few important metrics to consider :
Flow velocity: This metric measures the number of flow units of work completed in a period of time. It indicates how productive a process is. Poor flow velocity could mean slow feature iteration, causing customers to churn. High flow velocity is excellent for the business, but it often comes at the expense of other items like putting aside technical debt. (Related reading: Sprint Velocity)
Flow time: This is how much time a flow item takes from start to completion, including active and wait times. Breakdowns of flow time are helpful to uncover bottlenecks in the process. For example, if there is a larger flow time in a specific phase of the value stream like QA, this might be something to take a closer look at. (Related reading: Lead Time & Cycle Time)
Flow efficiency Tracks the ratio of active time to wait time for a flow item in the value stream. Too many flow items in the value stream at once or interdependencies between these items can increase the pressure on the system, resulting in too much context switching for staff and stagnation of flow items.
Flow load: Tracks the total number of flow items in the value stream, which measures the current work-in-progress items. Too many items in the value stream can negatively impact velocity, time, and efficiency.
Flow distribution: Tracks the proportion of the four flow items (features, defects, debt, and risk) in the value stream. This metric ensures a balanced mix of all the flow elements. For example, focusing only on new feature development and ignoring technical debt and defects can eventually lead to user churn.
Getting started with VSM at your organization
No matter the size of your organization or where you are in your digital transformation journey, VSM can unlock the potential to deliver more value to your customers. In addition, VSM can fit in within your existing organizational practices. Here are a few ways to get started with VSM without significant process changes :
Value stream management integrates well with SAFe (Scaled Agile Framework) since it uses the same KPIs but is more scalable. In SAFe, value streams are organized into portfolios, Each value stream delivers one or more solutions—in the form of products and services—to the customer. A product-focused value stream is always grounded in the needs of the customer and calibrated to deliver the solutions that generate maximum business value. A great reference of how VSM is used in SAFe can be found here.
In organizations that utilize Agile and DevOps practices to track developer-centric metrics, value stream management complements these practices by allowing leaders to be more “customer-centric” in the tracked metrics by prioritizing features that offer the fastest opportunity to deliver the greatest value.
OKRs (Objectives and Key Results) are about setting objectives for the business that can be tracked with key results. They are increasingly being used across organizations to drive alignment, improve accountability, and ensure transparency across the enterprise. When combined with the metrics from a value stream, they can be used to figure out what matters to the customer and the means to deliver customer value in a time-bound and efficient manner that improves overall performance. (Related reading: DORA Metrics)
Conclusion
Until now, traditional organizations have had no real way of measuring how well their investments in digital transformation are paying off. The reason is that metrics are dispersed and siloed across many different best-of-breed and specialized tools across the organization. It becomes challenging to collect all this local data and connect the dots with what’s happening with the business. You need to know how to measure the value stream(s) to determine performance and how it affects overall business outcomes.
With Faros AI, you can effortlessly connect the dots across many engineering data sources - from ticketing systems to source code control and CI/CD pipelines - giving unprecedented visibility and insight into your engineering processes. For example, product and engineering teams work across various platforms, from JIRA to Github, Docker, AWS, and Gitlab. Faros AI lets you join data from all those platforms in real-time to provide 360-degree business insights for value stream leaders. With Faros AI, leaders can recognize inefficiencies and areas of optimization early and continually ensure that they are delivering value to the customer.
Get started today and enjoy comprehensive visibility across all your value streams so you can take intelligent action to improve business outcomes.
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