Building a System That Learns – The Discipline of Continual Improvement – The Assurance in Action Series – Part 5

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Building a System That Learns – The Discipline of Continual Improvement – The Assurance in Action Series – Part 5

David Nichols – Co-Founder and Executive Director of the DVMS Institute

The Next Frontier of Assurance

Assurance is not a destination; it’s a discipline. Once boards and managers can demonstrate that intent has been translated into capability, that controls produce measurable evidence, and that culture reinforces resilience, the question then becomes: Can the organization learn faster than it changes?

In a digital economy characterized by volatility, uncertainty, complexity, and ambiguity, static resilience is an illusion. Technologies evolve, threats change, and customer expectations shift. What mattered last quarter might be irrelevant today. The real test of assurance is whether an organization’s system of governance, capabilities, and culture can continuously adapt to maintain stakeholder trust and business value under these conditions.

That is the essence of continual improvement.

Why Continual Improvement Matters

Frameworks like the NIST Cybersecurity Framework (NIST CSF) and ISO management systems have long recognized the importance of continuous improvement cycles. However, in many organizations, this idea remains abstract, functioning more as a clause at the end of a document rather than a central part of daily practice.

Managers know the cycle by heart: Plan, Do, Check, Action. Yet in practice, “Check” often means little more than a compliance review, and “Action” becomes another project or policy update. Improvement becomes episodic rather than systemic.

In the Digital Value Management System® (DVMS), ongoing improvement is fundamental. It serves as the core process that sustains the entire assurance system. It guarantees that the organization remains aligned with its governance goals and that each capability progresses in step with the environment in which it operates.

Ongoing improvement, when embedded into the DVMS, transforms governance from a reactive process into a dynamic, adaptive system—one that learns, adjusts, and improves in real time.

The Feedback Engine of DVMS

In Thriving on the Edge of Chaos: Managing at the Intersection of Value and Risk in the Digital Era, continual improvement is seen as a result of complexity—systems succeed not by being rigid but by being responsive. The DVMS incorporates this responsiveness into its design.

Every DVMS cycle—Create, Protect, Deliver (CPD)—relies on feedback loops. These loops ensure that assurance evidence, operational data, and cultural insights flow upward to governance, where they inform new strategic direction, resource allocation, and policy updates.

  1. Create: The organization builds capabilities designed to achieve specific outcomes.
  2. Protect: Those capabilities are tested, monitored, and refined to safeguard performance under stress.
  3. Deliver: Real-world results provide evidence that value is being sustained—and that evidence becomes input for the next iteration of “Create.”

 

It is a cycle, not a straight line. Every turn improves both performance and confidence. The DVMS transforms data into knowledge, and knowledge into confidence.

From Event-Driven Improvement to Systemic Learning

Most organizations tend to improve only after experiencing failure. An incident, outage, or audit finding prompts a brief increase in effort, but it typically reverts to previous levels. This type of improvement is event-driven—reactive, short-term, and crisis-dependent.

The DVMS model replaces this with systemic learning. Instead of reacting to disruptions, the organization uses assurance evidence to anticipate issues and continuously refine its approach.

For example:

  • If incident rehearsals reveal repeated delays in escalation, the DVMS identifies this as a systemic weakness in “Protect” and “Deliver,” not merely a performance gap. Managers modify roles, thresholds, or tools, and evaluate the improvement in later cycles.
  • If supplier continuity metrics indicate declining recovery performance, governance can act proactively, reviewing vendor assurance standards or allocating extra resources before a real incident happens.

 

Systemic learning is proactive assurance in action. It considers every data point an opportunity to strengthen resilience before disruption tests it.

QO–QM as the Engine of Continual Improvement

The Practitioner’s Guide to Building Cyber-Resilience (Second Edition) describes the QO–QM (Question Outcome–Question Metric) model as the mechanism that connects governance intent with measurable evidence.

In continual improvement, QO–QM becomes the engine that drives adaptive learning.

  • Question Outcome (QO): “Can we restore services within four hours of disruption?”
  • Question Metric (QM): “Our last three rehearsals achieved an average restoration time of 3.2 hours.”

 

The difference between these two measures, intent and evidence, is what drives continuous improvement. Managers use this gap to prioritize building skills, refining processes, or retraining teams. Over time, outcomes and metrics align.

Essentially, when the environment changes, such as with the introduction of new technologies, regulations, or threats, the QO–QM model enables the organization to adapt quickly. It prevents complacency by ensuring every metric remains relevant to the business context.

This is how assurance evolves from static reporting into dynamic governance.

The Cultural Prerequisite

Continuous improvement relies on culture. Without psychological safety, near misses go unreported. Without openness, feedback loops are incomplete. Without accountability, lessons are forgotten.

Part 4 of this series defined culture as a measurable skill. Here, culture becomes the foundation for continuous improvement. Managers must make review and adaptation a daily habit, something that occurs openly, without assigning blame.

When a culture values learning as much as success, improvement comes easily. When it doesn’t, confidence turns into ritual.

As Thriving on the Edge of Chaos reminds us, organizations that refuse to learn are not resilient; they are fragile, merely waiting for the next shock to come.

FastTrack: Making Improvement Achievable

For many managers, the concept of ongoing improvement across numerous capabilities can seem overwhelming. The DVMS FastTrack approach was designed to facilitate this transformation without chaos or burnout.

FastTrack structures continual improvement as a phased journey rather than a single leap. Managers begin by identifying critical Minimum Viable Capabilities (MVC) tied to governance outcomes. These form the initial focus of improvement cycles.

  1. Phase 1 – Establish Assurance Foundations: Align governance intent, define QO–QM pairs, and map current capabilities.
  2. Phase 2 – Surface Gaps and Prioritize Improvements: Use the MVC overlay to identify where resilience is weakest and where incremental gains have the highest value.
  3. Phase 3 – Build and Measure: Develop capabilities, capture assurance evidence, and feed results back into governance.
  4. Phase 4 – Institutionalize Learning: Embed improvement into regular operating rhythms, linking it with performance management, budgeting, and strategy.

 

The goal isn’t perfection; it’s velocity. Each iteration gathers evidence, enhances capability, and boosts confidence. FastTrack transforms ongoing improvement from a goal into a practical, measurable practice.

The Manager’s Role

Managers are the key to ongoing improvement. Boards set the vision, but managers maintain the momentum. Their roles go beyond just making changes—they need to make learning a routine. This involves creating teams that can analyze assurance data, conduct effective after-action reviews, and share lessons across departments.

Managers must also allocate time for reflection. In fast-paced digital environments, teams often move quickly from one project to the next without taking the time to review what they have learned. This “velocity trap” weakens resilience. DVMS disciplines—especially QO–QM reporting and CPD-based rehearsals—offer the structure to pause, assess, and adjust intentionally.

Managers who adopt this mindset become drivers of assurance maturity. They move beyond merely ticking compliance checkboxes and start building organizations that think, adapt, and continually improve.

The Executive Imperative

For executives and boards, continual improvement is the key to greater success. It shifts governance from just oversight to proactive foresight. Instead of waiting for quarterly reports, directors can identify trends—how resilience capabilities are developing, how gaps are closing, and where systemic risks are emerging.

This level of visibility raises the board’s role from just assessing performance to actively guiding development. The question is no longer “Are we compliant?” but “Are we learning quickly enough to remain resilient?”

In the DVMS model, continuous improvement is more than a management practice—it is a fiduciary duty. The capacity to learn under pressure now influences enterprise value.

Resilience Through Learning

Resilience isn’t built by just surviving disruption; it’s built by learning from it. Every incident, rehearsal, and near-miss offers data that enhances the organization’s ability to anticipate, respond, and adapt. In this way, continuous improvement isn’t just a management practice—it’s the process that makes resilience real.

The DVMS provides the architecture that turns learning into capability. Each cycle of Create, Protect, and Deliver transforms operational experience into evidence of assurance. That evidence, in turn, informs governance, guiding new policies, better priorities, and smarter investments. Over time, this feedback loop embeds learning into the structure of decision-making itself.

Thriving on the Edge of Chaos: Managing at the Intersection of Value and Risk in the Digital Era describes this as the hallmark of a learning organization, one that grows stronger not because disruption disappears, but because its systems are designed to evolve through adaptation. When organizations adopt the DVMS approach, they stop treating resilience as a goal to be achieved and begin managing it as a capability to be continually refined.

From Comfort to Confidence

Boards no longer need to depend on snapshots of compliance. They can observe resilience develop through evidence. Managers no longer need to justify why assurance is hard—they can demonstrate that it is ongoing.

The Assurance Mandate whitepaper argued for shifting from Governance, Risk, and Compliance (GRC) to Governance, Resilience, and Assurance (GRA). Parts 1 through 4 established the framework, encompassing intent, capability, evidence, and culture.

Part 5 closes the circle: assurance is not static. It learns. It evolves. It strengthens.

The first provides comfort. The second builds confidence. The fifth ensures that confidence lasts.

Looking Ahead

In the next article of the Assurance in Action Series, we will examine adaptive assurance—how real-time data, agentic AI systems, and predictive analytics are coming together to make dynamic assurance not only possible but also inevitable.

About the Author

Dave is the Executive Director of the DVMS Institute.

Dave spent his “formative years” on US Navy submarines. There, he learned complex systems, functioning in high-performance teams, and what it takes to be an exceptional leader. He took those skills into civilian life and built a successful career leading high-performance teams in software development and information service delivery.

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