This article starts by laying down the key principles of EBM applied within an OT-inspired org change. It starts by providing a crisp description of both methods and then dives into describing how they are seen working together to reinforce a systemic org change with a strong focus on measuring value.
Org Topologies recognizes Measure and Improve Value with EBM (for Enhanced Performance and Agility) as one of the Elevating Katas - a set of principles, methods, and guides for moving an org design closer to the upper right on the Org Topologies map.
If you know both methods, jump to the later section where the methods are being compared, contrasted, and integrated. For a complete guide on Evidence-Based Management, refer to the Scrum.org EBM page.
In this article, we claim the following to be true:
OT provides the actionable changes and EBM provides the measure of success, enabling a scientific approach to organizational evolution.
EBM identifies the symptoms, OT treats the root cause, and EBM then measures the treatment’s effectiveness.
EBM measures act as a compass ensuring Org Topologies changes truly lead to agility.
Org Topologies: Principles and Methodology
Org Topologies (OT) is a framework for strategic organizational design and change. It is described as the first “human-centric plus AI-friendly” approach to organizational change. This means it emphasizes the human side of change (people need to own their change and find it engaging) while anticipating the integration of AI into the workforce.
Key principles and components of Org Topologies include:
Psychology of Change: OT recognizes that lasting change occurs when people across the organization participate and take ownership, rather than having changes imposed top-down. It provides a visual and collaborative mapping process so everyone can “visualize, discuss, understand, and shape the change” together. This shared understanding creates a common language for organization design and engages everyone in the transformation.
Fit-for-Purpose Design: Org Topologies aligns organizational structure with the organization’s strategic goals or “North Star.” Different business goals (e.g. rapid delivery, adaptability, resource efficiency, innovation) require different tailored org designs. OT helps leaders define the right target design to achieve their specific objectives and keep the organization “fit for purpose” as those objectives evolve. It works at any scale – entire enterprise or subdivisions – to ensure structure, strategy, and change process are all aligned.
Organization Mapping and Archetypes: A core methodology in OT is mapping the current organization into archetypes on a two-dimensional grid. The two axes represent fundamental dimensions of org design, such as the growing scope of skills mandate (depth of cross-functional skills) and scope of work mandate (breadth of product/customer scope). OT defines a set of common patterns (archetypes) for how teams or units are structured and operate. In the latest version, there are 16 archetypes organized into four groups and positioned along the two axes. This Org Topologies Map is a visual tool to assess where the organization is today and identify mismatches between the current design and the capabilities needed to meet business objective.
Topologies and Organizational Patterns: The archetypes are further grouped into three broad topologies – often described as Resource, Delivery, and Adaptive topologies. Each topology represents a distinctive way the organization coordinates work:
Resource Topology (traditional model): characterized by specialized, siloed teams managed via centralized coordination (emphasis on resource utilization). Directing units (like PMOs or managers) decide work, and Doing units execute, often leading to hand-offs and dependencies (not directly cited, but implied by context). This can maximize local efficiency but often sacrifices adaptability and speed.
Delivery Topology: focuses on the fast flow of outputs by using cross-functional teams and removing inter-team dependencies. Teams are structured as “complete” delivery units (often called feature teams or “feature factory” style) that can produce a steady stream of features with short lead times. However, work definition (the “what to build”) is usually still driven by separate planning or analysis roles (discovery is handled apart from the delivery teams). This topology excels when the main challenge is predictable, rapid delivery of known features rather than exploring unknown market needs.
Adaptive Topology: aims for maximum adaptiveness and innovation. It merges directing, doing, and delivering into one unified unit. In this model, teams (or “team-of-teams” networks) are empowered to both discover and deliver value continuously, often working with a broad product scope and high synchrony across the organization. Humans, AI agents, and even robots collaborate in these “Driving” units to solve complex problems, learn, and adapt on the fly. The Adaptive topology’s goal is to enable quick, cheap responses to change and to “discover and deliver higher-impact customer outcomes”, supporting long-term business resilience. This design is fit for organizations where growth, learning, and customer-centric innovation are paramount.
Intended Application of OT
Org Topologies is intended for any industry or domain seeking to improve organizational agility and performance – from software product companies to farms or construction firms. It is especially useful in agile and digital transformations, where existing structures hinder fast delivery, adaptability, or innovation. By using OT, leaders gain a “critical managerial tool” to drive performance via org design. For example, OT can be overlaid with frameworks like SAFe, LeSS, or even non-tech models like Haier’s Rendanheyi to map and enhance an Agile Release Train or a networked organization. Overall, Org Topologies helps organizations “align all the moving pieces” – structure, strategy, and change efforts – to achieve strategic goals in a sustainable way
Evidence-Based Management (EBM): Principles and Methodology
Evidence-Based Management (EBM) is a framework developed by Ken Schwaber and Scrum.org to help organizations continuously improve by making decisions based on evidence and measurable outcomes. EBM is built on three core pillars: clearly defined Goals, targeted Measures, and the discipline of Empiricism. These pillars work together—our goals set the strategic direction, the measures (including KVAs) provide evidence, and empiricism drives continuous learning and adaptation. The method provides a disciplined, empirical approach for management and teams to achieve strategic goals in the face of uncertainty. Key principles and components of EBM include:
Empiricism and Experimentation: EBM advocates that organizations tackle complex, uncertain challenges through intentional experimentation and frequent feedback. Rather than making big up-front plans, teams and leaders set incremental goals, run experiments, and use data to decide the next steps. In practice, this means forming a hypothesis about how an improvement or change might move the organization closer to its goals, implementing that change on a small scale, and measuring the results against expected outcomes. Based on the evidence gathered, the organization adapts its tactics or even revises its goals. This iterative loop mirrors Scrum’s empiricism at a management level, ensuring that decisions are grounded in real-world data rather than assumptions.
Value-Focused Goals: In EBM, all efforts are oriented toward improving outcomes (value delivered), not just outputs. Organizations are encouraged to express their aspirations at multiple levels – a Vision (the ultimate change they seek to make in the world), a Mission (why they are uniquely positioned to achieve that vision), and concrete Goals that lead toward fulfilling them. However, EBM notes that many organizations struggle to create effective goals that drive real progress toward their mission and vision. EBM addresses this by helping organizations set Strategic Goals (long-term objectives connected to mission), break them into nearer-term Intermediate Goals, and then into very short-term Immediate Goals that teams can act on now. Crucially, each goal should have measurable criteria so the organization can inspect whether changes are actually moving the needle. This keeps goals outcome-oriented (e.g. improving customer satisfaction) rather than activity-oriented, and it ensures every level of goal is aligned with delivering real value.
Key Value Areas (KVAs): A cornerstone of EBM is measuring value and capabilities in a balanced way. EBM defines four broad Key Value Areas which act as lenses on different aspects of organizational performance. These KVAs help teams and managers focus on what to improve and avoid blind spots.
The four KVAs are:
Current Value (CV): How much value the product or service delivers to customers today (e.g. customer satisfaction, revenue, market share).
Unrealized Value (UV): The potential future value that could be unlocked if the organization better met all possible customer or user needs – essentially the gap between current value and what could be achieved (e.g. untapped market segments, additional features that could attract new customers).
Ability to Innovate (A2I): How effectively the organization can deliver new capabilities or improvements (e.g. innovation rate, technical excellence, experiment frequency). This reflects the organization's capacity to adapt and innovate in response to market needs.
Time to Market (T2M): How quickly the organization can deliver a new idea or change and gather feedback on it (e.g. release frequency, lead time for changes).
Intended Application of EBM
EBM was initially formulated in the context of software and product delivery organizations adopting Scrum, but it is broadly applicable to any enterprise seeking to improve its results under uncertainty. It is especially useful when an organization has adopted Agile practices but wants to ensure those translate into real business value. For example, a company might use Scrum for development; EBM provides the management framework to measure whether Scrum is delivering the expected improvements in customer value, time to market, etc., and to guide further changes. Typical applications of EBM include setting organizational OKRs or targets in terms of KVAs, assessing the impact of transformations (e.g., “Are we actually reducing time-to-market with this new process?”), and steering investments toward initiatives with evidence of high impact. Because it is framework-agnostic, EBM can overlay any process or structure, providing a way to “measure, manage, and increase the value [an organization] derive[s] from their product delivery”. Ultimately, it helps organizations “improve outcomes, reduce risks, and optimize investments” by empirically guiding decisions at all levels.
How OT and EBM Complement and Contrast Each Other
Because Org Topologies and EBM operate in different yet related domains (structure vs. measurement), they can be used together in a complementary fashion.
Complementary Use Cases
In an organizational transformation, one can use Org Topologies to design the change and EBM to drive and verify the change. For example, if a company’s strategic goal is to improve innovation and adaptability, Org Topologies might suggest moving toward an Adaptive Topology – merging discovery and delivery functions into autonomous product units.
EBM would complement this by tracking Ability to Innovate and Unrealized Value metrics to see if the structural change actually increases innovation output or unlocks new market value. In fact, Scrum.org notes that their EBM framework is a good way to ensure “rigorous experimentation and a balance between value indicators” during change efforts.
Meanwhile, Org Topologies “offers a powerful tool for assessing the [current] situation and outlining the changes needed” to reach those objectives. Together, OT can tell you what to change in your org design, and EBM can tell you whether those changes are producing the desired results.
This closes the loop between design and outcome:
Strategy Alignment: Org Topologies helps translate strategic objectives into an appropriate organization design (e.g. choose a topology that fits a strategy of rapid delivery or one that fits a strategy of innovation). EBM ensures that those strategic objectives are clearly articulated as measurable goals and provides feedback on progress toward them. The two together ensure that structure and strategy are continually aligned and validated. If strategy shifts, EBM will catch changes in outcomes, and OT provides a mechanism to adjust structure accordingly.
Navigating Change Safely: Both frameworks stress incremental change, so used together they encourage a safe-to-fail approach. Org Topologies might implement a pilot re-organization in one product line (Elevate step with experiments), and EBM would measure the pilot’s impact in terms of value (did customer outcomes improve? did time to market improve?). If the metrics show positive evidence, the new design can be rolled out wider; if not, the organization can iterate on the design. This complementary approach reduces the risk of large-scale changes – you’re not “flying blind” with a new org structure because EBM is instrumenting the change with data.
Balancing People and Performance: Org Topologies brings in the human element – making sure people understand the why of changes, and that roles and team boundaries are set up for collaboration rather than confusion. EBM brings in the performance focus – making sure the changes actually deliver business results, not just feel good. In some transformations, there’s a risk of over-focusing on org charts and forgetting to measure outcomes (which EBM prevents), or conversely over-focusing on metrics and ignoring morale or clarity (which OT prevents by involving people in design). Together, they provide a more holistic transformation: structural, cultural, and outcome-based considerations are all addressed.
Contrasting Considerations
On the other hand, using both requires understanding their different mindsets. Org Topologies might identify a structural problem (say, too many narrow-component teams causing slow integration). EBM might identify a value problem (say, low customer satisfaction). These may or may not point to the same solution initially – it takes skilled interpretation to connect the two.
For instance, EBM could reveal a problem (low Current Value) that is due to factors outside org structure (maybe a poor product-market fit or outdated technology). Org Topologies might propose structural changes that need careful justification via evidence (to avoid reorgs that don’t pay off). In some cases, one framework might challenge the other: EBM’s data might suggest that a recent structural change (inspired by OT) is not yielding results, which could mean re-thinking the change or giving it more time.
Conversely, an OT practitioner might caution that certain performance drops are expected short-term during re-structuring and that patience is needed. Therefore, while they complement each other, it’s important to synchronize cadence and perspective – using EBM’s evidence to inform Org Topologies decisions, but also using Org Topologies wisdom to interpret EBM data in context.
Another contrast is in scope of impact: Org Topologies changes can have far-reaching consequences on people’s roles, team identity, and day-to-day work (which can be disruptive even if ultimately beneficial). EBM’s introduction (measuring things, setting new goals) is usually less structurally disruptive but can change mindsets and accountability. An organization needs to manage both the structural change management and the cultural shift to evidence-driven management. Leaders might choose to introduce EBM practices first (to identify where change is needed and build a culture of empiricism), or introduce Org Topologies first (to fix glaring structural bottlenecks), or do both in tandem. There’s no one right sequence, but it’s wise to communicate how they interrelate so teams don’t feel like “yet another initiative” piled on.
Elevating Kata: Measure and Improve Value with EBM for Enhanced Performance and Agility
When integrated thoughtfully, Org Topologies and Evidence-Based Management can reinforce each other to significantly enhance organizational performance and agility. Here are some ways an organization might combine the two frameworks:
Data-Driven Org Design: Use EBM metrics as diagnostics to drive Org Topologies interventions. For example, suppose EBM reveals that Time to Market is too slow and Current Value is stagnating. This quantitative evidence can trigger a closer look at org structure: perhaps teams are organized in a Resource Topology with many dependencies causing delays. Org Topologies would then provide a method to redesign toward a Delivery or Adaptive Topology (e.g. introduce more cross-functional teams, reduce hand-offs) to address the problem. After making structural changes, the organization continues to track the relevant KVA metrics. If Time to Market improves and Current Value starts rising, it validates the structural approach; if not, further adjustments are made. In this way, EBM identifies the symptoms, OT treats the root cause, and EBM then measures the treatment’s effectiveness.
Continuous Feedback into Structure: Apply an EBM loop within the OT “Elevate” phase. As Org Topologies changes are implemented incrementally, each change can be treated as an EBM experiment. Define an expected outcome (e.g. “by merging Team A and B into a single value-stream team, we expect deployment frequency to double in that product line”), implement the change, and measure the outcome (deployment frequency is a proxy for Time to Market KVI). This creates a tight feedback loop: structural change → metric outcome → learn → next structural change. It prevents the organization from over-correcting or making broad changes without evidence. Essentially, OT provides the actionable changes and EBM provides the measure of success, enabling a scientific approach to organizational evolution.
Strategic Goal Alignment Workshops: An integrated practice could be running a workshop where leadership uses EBM to set or refine strategic goals/KVAs, and simultaneously uses Org Topologies mapping to evaluate if the current org can meet those goals. For instance, leadership might set a goal to increase Unrealized Value (capturing a new market segment). In the same session, using Org Topologies maps, they might discover that the current structure has no dedicated product team exploring that new market (perhaps all teams are tied up delivering current features). This insight leads to an Org Topologies design solution (e.g. create a new “Explore” team archetype or reassign an existing team’s mandate to include the new segment). They would then implement that and use EBM to monitor if Unrealized Value (e.g. percentage of market captured or new customer adoption) starts to go down, indicating value is being realized. This illustrates how strategy → structure → metric integration can happen in a seamless flow.
Combining Language and Measures: Org Topologies provides a common language for org structure (with terms like CAPS, WHOLE, topologies, etc.), and EBM provides a common language for value and improvement (CV, UV, etc.). Together, they can help different parts of the organization communicate. For example, an agile coach might say “We need to elevate from a CAPS-1 to a CAPS-3 team to reduce dependencies,” and a product manager might add “Yes, that should improve our Time to Market.” When both the structural change and the expected outcome are clearly expressed, it creates alignment between organizational development efforts and business results. This integration of lexicon – structural terms coupled with value metrics – ensures everyone understands not just what change is happening, but why (what outcome is expected). It ties the abstract concepts of org design to concrete business metrics that people care about.
Ensuring Balanced Change: EBM’s four KVAs ensure that while pursuing one improvement, you don’t hurt another. An organization integrating OT and EBM will use those metrics to check that a structural change aimed at one dimension doesn’t inadvertently damage another. For example, moving to a Delivery Topology might speed up delivery (better T2M) but, if done in isolation, could lead to feature factory syndrome where lots of output doesn’t increase customer value (CV). By keeping an eye on Current Value and Unrealized Value, leaders can detect if they are churning out features with no outcome – and then course-correct by incorporating more “Adaptive” elements (e.g. ensure teams also have discovery capability, not just output focus). Thus, the EBM measures act as a compass ensuring Org Topologies changes truly lead to agility (ability to respond) and real value creation, not one without the other.
Scaling and Sustaining Gains: Over time, as an organization iterates between OT-driven changes and EBM-driven measurements, it can develop a capability for self-tuning. The structural changes (OT) solve immediate bottlenecks, and the measurement (EBM) ensures new bottlenecks or opportunities are quickly identified. This synergy can accelerate an agile transformation or any continuous improvement initiative. Org Topologies changes might happen at a slower cadence (since structural moves take planning), while EBM cycles can happen very frequently. An integrated approach might use EBM continuously (say, quarterly outcome reviews, monthly metric check-ups) and use Org Topologies periodically (say, an annual structural review or on-demand when EBM indicates a plateau). When both are embedded into the management practices, the organization is equipped to adapt both its strategy execution and its structure in concert. This leads to what we might call organizational agility in the truest sense: the organization can reconfigure itself (structure, teams, processes) and redirect itself (goals, investments) with relative ease, based on evidence, to seize opportunities or avoid threats.
Key Metrics Aligned to Organizational Topologies
The Evidence-Based Management (EBM) Guide (2024) Appendix provides example Key Value Measures (KVMs) that organizations can use to gauge value and improvements. Each organizational topology – Resource, Delivery, and Adaptive – emphasizes different goals, so certain metrics from the EBM examples will be more suited to each.
Below is a table of three exemplary key metrics fit for each topology, along with explanations of how each metric aligns with that topology’s characteristics and goals.
Resource Topology Org Goal: maximizing resource utilization and specialization
Metric (Key Value Area) | Alignment with Resource Topology |
Product Cost Ratio (Current Value) | Measures total product expenses relative to revenue. A lower cost-to-revenue ratio reflects greater efficiency in resource utilization, supporting a Resource-focused organization’s aim to optimize costs and maximize the output from each resource. |
Revenue per Employee (Current Value) | Indicates how efficiently each employee (resource) generates value. A higher revenue per employee means the organization gets more output per resource, aligning with the Resource Topology’s goal of maximizing resource use and efficiency. |
On-Product Index (Ability-to-Innovate) | The percentage of time teams spend working directly on product value (vs. overhead). A high on-product index means most of the workforce’s time is spent on productive, value-adding work, which aligns with maximizing resource productivity in a Resource Topology (minimizing idle time or context-switching). |
Delivery Topology
Org Goal: maximizing output and predictability of delivery
Metric (Key Value Area) | Alignment with Resource Topology |
Release Frequency (Time-to-Market) | Measures how often the product is released (e.g. daily, weekly, etc.). Frequent releases indicate a high throughput of features to customers, matching the Delivery Topology’s emphasis on steady output and regular delivery of value. This metric shows the capability to deliver predictably and often. |
Lead Time (to Value) (Time-to-Market) | The time from an idea or requirement being proposed to it being delivered and benefiting the customer. Short lead times demonstrate fast turn-around from concept to delivery, reflecting the Delivery Topology’s goal of rapid, predictable delivery of proven value. |
Change Failure Rate (Ability-to-Innovate) | The percentage of releases that result in failures (e.g. require hotfixes or rollbacks). A low change failure rate means releases are generally stable and successful, supporting the Delivery Topology’s focus on predictability and quality in output. This ensures that increasing release speed doesn’t come at the cost of reliability. |
Adaptive Topology
Org Goal: maximizing outcomes and innovation through fast adaptation
Metric (Key Value Area) | Alignment with Resource Topology |
Customer Satisfaction (Current Value) | Gauges how happy customers/users are with the product (e.g. via surveys or NPS). High customer satisfaction indicates the organization is delivering valuable outcomes, not just outputs. This aligns with the Adaptive Topology’s goal of maximizing customer-centric outcomes (delighting customers through continual learning and adaptation). |
Time To Pivot (Time-to-Market) | Measures how quickly the organization can change direction in response to feedback or market changes. A short time to pivot reflects true business agility – the hallmark of an Adaptive Topology – demonstrating easy, cheap change based on learning and a capacity to rapidly adapt strategy. |
Innovation Rate (Ability To Innovate) | The percentage of effort spent on developing new product capabilities (versus maintenance). A higher innovation rate means the organization dedicates more of its resources to creating new value. This supports the Adaptive Topology’s focus on innovation and exploration, ensuring the organization can continuously evolve and deliver novel solutions. |
Summary
In summary, Org Topologies and Evidence-Based Management are distinct but highly complementary frameworks. Org Topologies provides the “where and how to change” from a structural perspective, ensuring the organization’s form enables agility and aligns with its purpose. EBM provides the “whether and why to change” from a value perspective, ensuring the organization’s operations remain focused on delivering measurable value and that any change is justified by evidence.
Their key principles differ – one is about designing the system, the other about measuring and steering the system – yet they share a foundation in agile, empirical thinking and can mutually reinforce success. By integrating the two, organizations can avoid the pitfalls of structure-blind improvement or improvement-blind structure. Instead, they gain a powerful combined approach to become both well-organized and continuously learning – ultimately enhancing performance, adaptability, and agility in a sustainable way.
