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You’ve likely invested heavily in Agile, DevOps, or SAFe®. Yet you still face the same questions from the boardroom, such as:
The truth is, traditional reporting has failed to bridge the gap between delivery metrics and strategic impact. So, we want to help you focus on the signals that matter and translate delivery progress into business language your executives trust.
In this article, you’ll see how the Flow Framework helps you track product value streams end-to-end, align investments with results, and turn delivery data into business insight.
First, though, let’s see what the Flow Framework actually is.
The Flow Framework, introduced by Mik Kersten in Project to Product (2018), gives you a way to manage software delivery with the same discipline you apply to financial or operational systems.
Instead of tracking activity in isolation, you measure value streams (the full path from idea to customer impact).
This helps you answer important questions your current reports can’t. For example, which initiatives deliver business value, where investments stall, and how delivery speed connects to customer outcomes.
You can apply it across Agile, DevOps, SAFe®, or hybrid environments because it’s tool-agnostic. That means you don’t have to abandon your existing stack.
Value Stream Management platforms like Axify already support the framework by translating raw engineering data into business-aligned insights.
Even so, the Flow Framework does have detractors.
Some critics, for example, argue it’s a repackage of Lean or Agile thinking. But the reality is that it provides the missing structure leaders need to connect delivery work with business performance.
Make sure to check out this YouTube video if you want to learn more, before we discuss more of how Flow Framework differs from Agile thinking:
Both the Flow Framework and the Flow of Work in the Scaled Agile Framework (SAFe®) share a common goal. That's to help you optimize how value moves through your system. Each:
The difference lies in precision and application.
The Flow Framework is metrics-based, with five defined metrics and a value stream network model. This lets you track results with consistency across toolchains, regardless of whether you use Agile, DevOps, or hybrid delivery models. It’s tool-agnostic by design, so you can apply it without being locked into one methodology.
In contrast, the Flow of Work in SAFe is a conceptual layer inside the broader framework. It draws on Lean flow principles but doesn’t define standardized metrics. Because it’s tied to SAFe practices, terminology, and artifacts, its scope is more limited.
That means you may find the Flow Framework more practical when you need data-backed insights. It helps you turn those insights into measurable improvements in delivery performance.
It’s important to separate Mik Kersten’s Flow Framework from the AWS Flow Framework for Java, which uses the same name, but has an entirely different purpose.
The AWS Flow Framework for Java is a programming library that helps developers coordinate automated workflows across distributed applications.
Instead of focusing on value streams or business metrics, it deals with coding tasks like scheduling background jobs and handling retries. If you confuse the two, you risk framing the wrong solution to leadership.
Keeping the distinction clear ensures that your discussions about flow stay centered on strategy and outcomes. It also helps you focus on measurable impact on delivery performance.
DORA metrics give you a focused way to assess delivery health. Deployment frequency, lead time for changes, change failure rate, and time to restore service show how efficiently code moves into production.
The Flow Framework works at a broader level. It helps you see whether those improvements translate into value delivered across product streams. That’s because it doesn’t stop at deployment, but rather tracks how work types like features or risks connect to customer needs and outcomes.
Bottom line: DORA tells you how fast and stable you are. Flow shows whether that speed creates a measurable business impact.
Mik Kersten developed the Flow Framework to help you connect software delivery with business performance. He saw that despite major investment in Agile and DevOps, leaders still struggled to show how delivery efforts created measurable outcomes.
The framework gives you a structured way to answer those questions with data.
Kersten’s work starts from the problems you deal with every day. Research from Planview notes these recurring challenges:
The Flow Framework gives you a set of tools to counter those risks with measurable improvement. Formalizing flow metrics and value stream models helps you tie engineering output to business outcomes.
Here are the benefits you can expect:
The thing is, Kersten didn’t create the Flow Framework as another methodology. He created it because leaders like you needed a way to connect delivery to outcomes in a language the business understands. That’s what sets it apart from other approaches.
The Flow Framework gives you a way to measure and manage how work moves from idea to customer impact. It combines five core metrics, four work item types, and three layers of networks to create an end-to-end view of delivery performance. That structure turns fragmented data into actionable insights for leaders.
We’ve covered flow metrics in detail in a separate article, but here’s a short recap for context. Each metric addresses a different dimension of flow and helps you pinpoint where work is delayed or resources are misused.
Here are the flow metrics:
The Flow Framework defines four types of work items: features, defects, risks, and debt. These categories matter because they give you a common language to discuss trade-offs.
Tracking the mix of these items allows you to make informed decisions about whether the current work aligns with the strategy. For example, if flow distribution shows 60% of work goes into defects, you know customer experience is suffering and new features will be delayed.
Kersten describes three layers that make the framework work in practice. These ideas were further developed in Planview’s materials:
It’s one thing to understand the framework conceptually. It’s another to see it in practice. This is where the Value Stream Management tool in Axify helps you.
Let's take the case of Development Bank of Canada (BDC), where two software teams used Axify to evaluate their flow.
When they analyzed pre-development, QA, and bug-handling activities, they saw that large portions of work stalled before development even began.
Axify’s dashboards made these delays visible by showing a high percentage of time spent outside active coding. With this insight, teams restructured planning and QA practices.
The results were amazing:
These directly improved delivery efficiency and financial performance.
A second example comes from Newforma, where the issue was related to deployment frequency. Using Axify, they automated more of their delivery pipeline and shifted testing earlier in the cycle. Flow metrics revealed how manual QA slowed throughput, so leadership invested in automation.
The outcome was 22 times more frequent releases. This created a stronger connection between engineering output and business outcomes.
Axify’s dashboards make this possible by:
When you apply the Flow Framework through a platform like Axify, the theory becomes actionable. You know that bottlenecks exist, and because of that, you can measure them and address them with concrete steps.
Implementing the Flow Framework isn’t always easy. Here are the common challenges you’re likely to face and why they matter for both delivery and business impact.
If you don’t see across value streams, you can’t connect flow insights to business decisions. This is a widespread issue because 76% of businesses report lacking end-to-end visibility across their supply chains, which directly harms timely decision-making and efficiency.
In a delivery context, this blind spot means leadership won’t know where investments stall or why business outcomes lag.
Flow requires integrated data. Yet 84% of executives report that silos create negative impacts across their organizations.
If Jira, CI/CD, and support systems don’t connect, your metrics stay fragmented.
That makes it impossible to see how technical bottlenecks translate into missed customer deadlines or revenue impact.
Adopting this framework requires cultural change, and resistance is common. Oak Engage’s Change Report shows that 37% of employees resist organizational change.
Reasons include lack of trust in leadership (41%), lack of clarity on purpose (39%), and fear of the unknown (38%). If leadership doesn’t address this, adoption stalls, and skepticism grows across the organization.
Flow metrics demand consistent data, but many teams aren’t ready. Research shows that 54% of organizations sit at the lowest levels of change management maturity.
In those environments, change management is ad hoc or applied to isolated projects. That creates fragmented adoption and undermines the reliability of metrics.
Some leaders treat the Flow Framework as just another layer of engineering metrics. If you fall into this trap, you miss its strategic purpose, which is linking delivery with business performance. Without that shift, you risk turning the Flow Framework into another reporting exercise that doesn’t drive investment decisions.
Measuring efficiency is useful, but it can’t be your only focus. If you optimize for efficiency alone, you might speed up the delivery of the wrong work. The outcome is faster cycle times, but poor alignment with customer or product value.
Flow relies on connected systems. Yet 71% of organizations take three weeks or more to bring a single integration to market.
That slow pace makes it difficult to connect VSM tools with CI/CD, issue tracking, and ITSM platforms. Without integration, flow metrics lose credibility, and leadership can’t act on them.
Implementing the Flow Framework requires more than picking the metrics you want to follow. These are the practices that help you prove value, avoid missteps, and build support across the organization.
You get the most traction when you start small. A cross-functional pilot gives you a safe environment to prove value and show measurable outcomes before scaling. Organizations that use cross-functional teams see technology adoption rates 34% higher than siloed approaches.
That’s because pilots with diverse expertise (from engineering, product, and operations) create richer insights into bottlenecks and investment priorities. With one pilot, you also reduce risk, since leadership can validate outcomes before funding wider rollout.
End-to-end visibility is important. Without it, you may optimize engineering activities while customer outcomes stagnate. Yet 62% of organizations rate their visibility across value streams as mediocre or poor, which shows how widespread the gap is.
To make flow successful, you need to see the entire journey from backlog to production and not just sprint metrics. This requires connecting customer-facing systems, delivery pipelines, and operational support data so leaders can link investments to results.
Flow metrics only work when you capture accurate data. That’s where Value Stream Management (VSM) tools like Axify come in. They connect across issue trackers, CI/CD systems, and QA environments to give you real-time flow insights. Without this tooling, your metrics remain incomplete, and executives will challenge their credibility.
Metrics aren’t useful if they sit in a dashboard. You need to embed them in reviews and retrospectives. That means discussing flow time trends in sprint reviews, using flow efficiency to guide WIP limits, or referencing flow distribution when prioritizing roadmaps. Actionable use creates accountability and ensures that metrics drive change.
Flow is not just an engineering exercise. If leadership doesn’t understand its business relevance, they’ll view it as another reporting fad. Education sessions should explain how flow metrics connect to ROI, customer satisfaction, and financial performance. That builds confidence in the data and accelerates adoption across executive teams.
Optimizing delivery speed without linking it to customer value is a dead end. You need to show how flow metrics align with customer outcomes such as faster onboarding, lower defect rates, or improved satisfaction scores. This connection makes the framework relevant to product and finance leaders who judge success by impact and not activity.
Flow metrics provide breadth, but they should not replace existing measures. Reviewing flow data alongside DORA metrics and business KPIs ensures you connect speed, stability, and impact. This combined view prevents tunnel vision and gives executives the balanced reporting they expect.
Here are the DORA metrics you can track alongside flow in Axify:
Flow metrics generate a lot of data. If you chase perfection, adoption slows. Instead, take an iterative approach. That means reviewing the results, making one or two adjustments, and measuring the impact. Continuous improvement makes the data practical and avoids the fatigue that comes from over-analysis.
Internal momentum matters. Sharing results from pilot teams builds belief and accelerates wider adoption. Recognition also drives engagement.
According to YourThoughtPartner, engaged employees see about a 20% improvement in performance and an 87% reduction in the desire to leave when they feel recognized. Framing flow as a success story and not a compliance requirement makes adoption far easier.
The Flow Framework gives you a structured way to connect delivery with business impact, but success depends on more than theory. You need accurate data, actionable insights, and tooling that helps you identify bottlenecks and show results executives can trust.
Case studies prove that when organizations apply flow with Axify, they achieve faster delivery, lower costs, and higher returns on investment. The next step is to run a pilot, track outcomes, and validate results with your leadership team.
Book a demo with Axify to see how it can accelerate your adoption of flow.
Flow in Agile refers to how smoothly work moves from idea to delivery. Instead of focusing only on iterations, you measure whether work items progress without long waits or bottlenecks.
Scrum organizes work in sprints, while flow looks at the end-to-end movement of work across the value stream. Flow helps you measure throughput, delays, and efficiency regardless of sprint boundaries. Both can coexist, but flow gives you a broader perspective on delivery performance.
A flow describes how value moves through a system, measured with metrics like flow time or flow load. A workflow is a predefined sequence of tasks, usually set in tools like Jira or ServiceNow.
Tools like Axify give you visual dashboards that show how features move from backlog to production. You can see bottlenecks in pre-development, QA, or bug handling phases. This view helps you act on data rather than intuition when deciding where to adjust processes.
Yes. Axify tracks flow metrics such as flow time, flow load, and flow distribution. It turns them into real-time dashboards so you can measure where delays occur and whether delivery aligns with business priorities. This makes reporting more credible for leadership teams.
Absolutely. Axify shows where work in progress spends the most time waiting. This visibility helps you cut wasted effort, accelerate delivery, and make smarter investment decisions.
Traditional workflow tools show you task progress within a single team or system. Axify’s VSM connects data across tools like Jira, CI/CD, and QA platforms to map the entire value stream. That gives you end-to-end visibility and ties delivery metrics back to business outcomes such as ROI and customer satisfaction.
