For many years I’ve specialized in helping organizations improve how work flows across teams, departments, and systems to deliver meaningful results. One of the most commonly used tools in that effort is value stream mapping (VSM)—a powerful technique from Lean that helps teams visualize and analyze how value is delivered.
Value stream mapping is a catchy and often unfamiliar term in many organizations. In these environments, the phrase carries no historical baggage. Its Lean manufacturing origins are typically unknown, so introducing the term usually works just fine. In fact, I have successfully applied this term for many years.
Why We Need a New Term
As I’ve continued to work with more diverse organizations—particularly those outside of traditional manufacturing or those not organized around formal value streams—I’ve found that reusing the term “value stream mapping” can often create confusion without any offsetting benefit from using the term. Here are three of the more important reasons why:
1. Reusing a term outside of its intended context
2. “Value stream” can prompt tunnel vision
3. “Value and outcome” are not the same thing
Let’s explore each in more detail.
1. Reusing a Term Outside of Its Intended Context
Use the term value stream mapping in a Lean manufacturing context and there is fairly universal shared understanding of what that means and the practices that it entails. Outside of Lean manufacturing, it invites questions like, “Is what we’re doing really value stream mapping in the Lean sense?” In many cases, the answer is no, or certainly not in its entirety.
In the strictest sense, the term “value stream mapping” doesn’t actually describe what we’re doing when we model flow in an organization. So, rather than stretch or reinterpret a term with a very specific meaning in Lean, I’ve begun using the new term: Outcome Flow Mapping.
Using this new term, I explain that we’re mapping how work flows to deliver meaningful outcomes—a framing that resonates with most teams and leaders. The emphasis on “outcomes” feels right and aligns with many corporate goal-setting frameworks like OKRs.
2. “Value Stream” Can Narrow the Focus Too Early
While value stream mapping emphasizes “value,” the technique is typically centered on a specific type of flow—what Lean calls a value stream, such as a product, service, or customer-facing business process.
But in modern knowledge work, we often analyze the flow of work across units of focus that aren’t formally defined as value streams. These might include:
• A product or product line
• A business capability
• A customer journey
• Or yes, a formal value stream, if that’s how the organization is structured
Calling every one of these a “value stream” can feel forced—and can make the mapping technique seem inaccessible to teams who aren’t organized around that concept.
The term Outcome Flow Mapping is intentionally more flexible. It highlights that we’re mapping the flow of work toward a meaningful result, regardless of what kind of unit of focus we’re working with.
3. “Value” and “Outcome” Are Not the Same Thing
The more significant reason for preferring the term Outcome Flow Mapping over Value Stream Mapping is that value and outcome are not the same thing.
• An outcome is a measurable result you want to achieve—a change in behavior, performance, or experience.
• Value is the benefit derived from that outcome—and it’s often subjective, context-dependent, and time-sensitive.
For example:
Outcome: Increase 30-day retention by 10%
Value: Higher customer lifetime value, reduced churn costs, improved forecasting
You can measure both outcomes and value—but outcomes are typically easier to measure directly, while value often requires interpretation about what matters, to whom, and why.
We also include outputs in this analysis for completeness, as they are often confused with both outcomes and value.
To illustrate these distinctions, let’s look at three examples: OKRs, assumption validation, and a humanitarian aid scenario.
OKRs (Objectives and Key Results)
OKRs are a goal-setting framework used by many organizations to define what they want to achieve (objectives) and how they will measure success (key results).
Well-crafted OKRs define an outcome as a measurable goal, not an activity.
Objective: Improve user engagement
Key Result: Increase weekly active users from 15,000 to 25,000
This key result is a clear outcome—a specific change in user behavior. However, it is not in itself the value. The value might be improved customer retention, increased revenue, or more upsell opportunities that result from greater engagement. Value is derived if the outcome holds and is sustained.
Many teams mistakenly write OKRs that reflect outputs:
❌ Launch onboarding redesign
❌ Publish five new knowledge base articles
❌ Complete CRM migration
These are outputs, not outcomes. They describe effort, not impact. By focusing on outcomes and understanding the value they are meant to unlock, teams clarify what success looks like—and then use assumption validation and experimentation to discover how to get there if the path is uncertain.
Assumption Validation
Many modern organizations pursue outcomes using an iterative, hypothesis-driven approach. In this approach:
• The outcome is the goal: what you’re trying to achieve.
• The assumption (or hypothesis) is your belief about how to achieve it.
• The output is the prototype, experiment, spike, or minimal implementation (e.g., minimum viable product) you build to test that assumption.
• Validation is the process of testing whether the assumption holds—not whether the outcome is valid.
Example:
Outcome (goal): Increase 30-day retention by 10%
Assumption: Adding live chat during onboarding will help achieve that outcome
Output: A lightweight live chat prototype integrated into onboarding flow
Validation: Run the experiment and observe whether retention improves
If the retention rate doesn’t improve, the assumption may be wrong. You discard the assumption, not the outcome. You then move on to test the next best assumption. However, if multiple well-informed experiments fail to move the needle, you might revisit the outcome itself—perhaps it’s not realistic, not aligned with actual user needs, or not as valuable as expected.
|
Element | Definition | Live Chat Example |
Assumption | A belief about how to achieve a desired outcome | Adding live chat during onboarding will improve 30-day retention |
Output | A prototype, experiment, spike, or minimal implementation (e.g., MVP) used to validate the assumption | Lightweight live chat feature deployed to onboarding flow |
Outcome | The measurable result you are aiming to achieve | 10% increase in 30-day retention |
Value | The benefit realized if the outcome is achieved and sustained | Higher customer lifetime value, improved ROI |
Humanitarian Aid Example
Let’s revisit the distinction one more time with a humanitarian example:
Imagine a public health initiative to combat malaria.
• Output: 1,000,000 malaria vaccines are delivered to the port in an affected country.
• Outcome: Vaccines are administered, leading to a 50% reduction in malaria infections.
• Value: Healthier population, reduced mortality, stronger local economy.
|
Concept | Definition | Malaria Vaccine Example |
Output | What is produced or delivered | 1,000,000 vaccines shipped to port |
Outcome | What changed as a result of the output | 50% reduction in malaria infections after vaccination |
Value | The benefit derived from the outcome | Improved public health, reduced mortality, stronger economy |
A Note on Value in Lean vs. Outcome Flow Mapping
In Lean, value is strictly defined from the perspective of the end customer—any activity that doesn’t directly add value to the customer is considered waste. Value Stream Mapping in Lean focuses on identifying and eliminating those non-value-adding steps.
In Outcome Flow Mapping, we adopt a broader lens. While customer outcomes remain important, we recognize that businesses define very specific outcomes that deliver value to potentially many different constituencies (e.g., customers, shareholders, society as a whole). These benefits may not always be visible to the end customer but are critical to sustaining the business and guiding strategy.
By making outcomes the focal point, we shift the focus to delivering on outcomes/goals/objectives while allowing “value” to take on a broader, more encompassing scope than just “performing value-adding activities.”
To be clear, like Lean and traditional value stream mapping, Outcome Flow Mapping is absolutely concerned with identifying and eliminating waste from the flow of work. Whether you call the process Value Stream Mapping or Outcome Flow Mapping, waste is still a killer of good flow!
Benefits of Outcome Flow Mapping
Outcome Flow Mapping delivers several important benefits that go beyond simply drawing flow diagrams:
It centers outcomes as the anchor for alignment and learning.
By focusing on measurable outcomes—rather than just activities or deliverables—teams clarify what they are trying to achieve and how progress will be assessed.
It broadens and clarifies the concept of value.
In Lean, value is defined strictly from the customer’s perspective. In Outcome Flow Mapping, value can include benefits to multiple constituencies (e.g., customers, shareholders, teams, society). This broader framing encourages thoughtful discussion about why an outcome matters and to whom—making value explicit, rather than assumed.
It links work to strategic intent.
Outcome Flow Mapping connects day-to-day activities to broader organizational goals by mapping the flow of work to intended outcomes and then to the forms of value they are expected to deliver. This helps ensure effort is aligned with purpose and impact.
It supports multi-stakeholder dialogue.
Because value may look different to different groups, Outcome Flow Mapping provides a shared language and structure for engaging executives, customers, team members, and regulators in meaningful conversations about success.
It creates a natural feedback loop.
If outcomes are achieved but value does not follow, Outcome Flow Mapping helps teams trace backward—through assumptions, flows, and decisions—to uncover what needs to change.
It supports hypothesis-driven improvement.
By articulating assumptions about how outcomes generate value (e.g., “If we improve onboarding, customer retention will increase”), teams can test, validate, and refine their thinking. This injects scientific rigor into strategic execution.
It helps eliminate waste.
Staying true to its Lean roots, Outcome Flow Mapping remains focused on surfacing bottlenecks, handoffs, and steps that do not meaningfully contribute to delivering outcomes. Waste is still the enemy of flow—regardless of what you call the process.
Conclusion
The distinction between output, outcomes, and value matters. In many organizations, we celebrate outputs (feature launched, code shipped, campaign released) without asking whether they produced the desired outcomes. And even when outcomes are achieved, we rarely ask: did this create the value we expected?
Outcome Flow Mapping brings that clarity. It surfaces the actual path work takes to reach outcomes, and whether our structure, process, and decision-making support fast learning and effective delivery.
If your organization is already comfortable with the term value stream mapping and it’s helping you achieve better outcomes and deliver value—keep using it. There’s no need to change what’s working.
But if the term causes confusion—or doesn’t fit how your organization thinks about flow, experimentation, or structure—consider adopting Outcome Flow Mapping. Personally, I will be defaulting to the use of Outcome Flow Mapping, but will use Value Stream Mapping in contexts where that term already has an established presence.
In a future article, we’ll focus on how to use Outcome Flow Mapping as a practical tool to analyze and improve flow across teams and systems.
Want to Learn More About Outcome flow Mapping?
If you want to learn more about Outcome Flow Mapping, reach out for a discussion.