Episode 60 — Improve governance processes using evidence, feedback loops, and root causes (3A6)

In this episode, we bring the entire governance journey to a practical question that separates a living governance system from a frozen one: how does governance get better over time instead of repeating the same problems with new names. Beginners often assume that once governance processes are designed and approved, they should stay stable, and if something goes wrong, the solution is simply to write a stricter rule. In reality, governance exists inside changing enterprises, where priorities shift, technology evolves, staff turn over, and risk environments change. That means governance processes must improve continuously, not by adding random complexity, but by learning from evidence, listening to feedback, and addressing root causes rather than symptoms. This approach keeps governance practical because it reduces frustration, prevents recurring failures, and builds confidence that controls are real and effective. The goal is to understand how evidence, feedback loops, and root cause thinking work together to strengthen governance processes without turning them into bureaucracy.

Before we continue, a quick note: this audio course is a companion to our course companion books. The first book is about the exam and provides detailed information on how to pass it best. The second book is a Kindle-only eBook that contains 1,000 flashcards that can be used on your mobile device or Kindle. Check them both out at Cyber Author dot me, in the Bare Metal Study Guides Series.

A useful first step is recognizing that governance processes can fail in predictable ways, and those failures are often signals that the process design does not match operational reality. A process can be too slow, causing teams to bypass it. A process can be unclear, causing inconsistent decisions and frequent rework. A process can be too strict, causing workarounds that increase risk. A process can be too loose, causing drift until an incident or audit finding reveals the weakness. Beginners sometimes see these problems as people problems, like teams being careless or resistant, but governance improvement starts by assuming the system needs adjustment rather than assuming the people are the main issue. That mindset is important because it leads to better fixes; if you blame people, you often add training and enforcement, while if you analyze the system, you may discover capacity constraints, confusing criteria, or missing tools that make compliance difficult. Improving governance is therefore an engineering activity in the broad sense, where you observe system behavior, diagnose why it behaves that way, and adjust design to produce better outcomes. This does not mean changing processes constantly, because constant change creates confusion, but it does mean refining them deliberately when evidence shows they are not performing. When improvement is disciplined, governance becomes more reliable because problems are addressed at their source. This is how governance matures rather than oscillates between strictness and neglect.

Evidence is the foundation of improvement because evidence tells you what is actually happening, not what people believe is happening. Evidence can include performance indicators, audit findings, incident trends, exception volumes, review cycle times, and outcome measures like delivery reliability and risk exposure. Beginners often think evidence means numeric metrics only, but evidence can also include decision records, process artifacts, and patterns of recurring questions that reveal confusion. For example, if multiple teams repeatedly ask the same question about a standard, that is evidence that the standard is unclear. If change approval processes are repeatedly bypassed through emergency changes, that is evidence that planning and sequencing are failing or that the process is too slow for reality. Evidence helps distinguish between isolated mistakes and systemic issues, which is critical because systemic issues require process redesign, not individual correction. Evidence also protects governance credibility because improvements are justified by observed patterns rather than by personal opinions or political pressure. When leaders see evidence-based improvement, they trust governance more because it looks like a managed system. This trust is important because governance often requires investment and time, and evidence shows why that investment matters.

Feedback loops add another dimension because evidence alone can miss the lived experience of people who use governance processes daily. A process might look fine in metrics but still create frustration because it adds unclear steps, forces redundant reviews, or requires information that teams do not have early enough. Feedback loops provide qualitative insight into where friction exists and why teams might be bypassing governance or treating it as a checkbox. Beginners sometimes assume feedback is complaining, but in governance improvement, feedback is data about usability. If a process is not usable, it will not be consistently executed, and inconsistency is how risk grows. Feedback loops can include structured opportunities for teams to report confusion, delays, and unintended consequences, and they should encourage honesty by focusing on improvement rather than blame. Feedback also helps governance identify where controls can be simplified without sacrificing protection, such as combining redundant approvals or clarifying criteria so fewer meetings are needed. When feedback is treated seriously, teams become more willing to engage with governance because they see their input can lead to practical improvement. This reduces bypass behavior and increases adoption of controls.

A mature feedback loop is not a one-way suggestion box; it is a cycle where input leads to analysis, decisions, changes, and then confirmation that the change helped. Many organizations collect feedback but do not close the loop, which causes people to stop participating because they assume nothing will happen. Closing the loop means communicating what was heard, what will be changed, what will not be changed and why, and what evidence will be used to evaluate the change. Beginners might think this is excessive, but without closure, feedback becomes noise and trust erodes. Closure also supports accountability because governance teams must justify decisions and must track whether the change improved outcomes. It is especially important to be transparent when a requested change cannot be made, because otherwise people interpret silence as disregard. When feedback loops are closed, they become a governance strength because they help the organization adapt controls to reality without losing purpose. Feedback loops also prevent overcorrection because they provide more nuanced understanding than metrics alone. In this way, feedback and evidence complement each other, producing a more accurate picture of what the governance system is doing.

Root cause analysis is what prevents governance improvement from becoming a cycle of treating symptoms. Symptoms are the visible problems, like delayed approvals, repeated exceptions, or recurring audit findings, while root causes are the underlying reasons those symptoms keep returning. Beginners often assume the root cause is human behavior, like people not following the process, but root cause analysis asks why people are not following the process, which can reveal systemic causes. For example, the root cause of bypassing architecture review might be that the review process is too slow for delivery cadence, or that standards are unclear, or that approved patterns are not easily available. The root cause of repeated data handling mistakes might be that classification rules are confusing or that safe storage options are inconvenient. The root cause of frequent emergency changes might be that planning cadence is weak or that incident-driven work is consuming capacity. Root cause analysis therefore connects governance problems to broader system factors like capacity, incentives, tooling, and clarity. When governance improvement targets root causes, the fixes are more durable because they change the conditions that produce failure. This is the difference between repeatedly reminding people and actually making the right behavior easier.

A practical root cause mindset also recognizes that governance issues often have multiple contributing causes, not one single reason. A delayed risk review might be caused by a bottleneck team being overloaded, but also by unclear submission requirements that force rework, and also by a lack of standardized templates that would speed evaluation. Fixing only one cause might improve the situation slightly, but the symptom could still persist. Root cause analysis encourages looking at the entire pathway, from demand creation to review execution to decision follow-through, and identifying where friction accumulates. Beginners might expect root cause analysis to be highly technical, but in governance it can be conducted through careful questioning and evidence review, focusing on process flow and decision points. It also requires distinguishing between special causes, like a one-time disruption, and common causes, like persistent overload or unclear criteria. Governance improvement should focus on common causes because they create repeated failures. When common causes are addressed, metrics improve and frustration declines, and the process becomes easier to execute consistently. This is how governance moves from reactive correction to proactive design improvement.

Evidence, feedback, and root causes are most powerful when they are integrated into a regular improvement cadence, because improvement that happens only after crises is usually rushed and tends to create overcorrection. A regular cadence might include periodic review of governance performance indicators, review of quality assurance findings, and structured collection of stakeholder feedback. The purpose is to create predictable moments where the organization asks whether governance is still fit for purpose and what should be adjusted. Beginners sometimes assume improvement cadence means constant change, but a mature cadence includes prioritization, meaning only the most impactful improvements are implemented at a time, while other ideas are queued. This prevents governance from becoming unstable. A cadence also supports experimentation, where the organization can implement a limited process adjustment, observe results, and then decide whether to scale it. This is a safer way to improve than making broad changes based on assumptions. Regular improvement cadence also supports transparency because stakeholders know when improvements will be considered and how decisions will be made. When cadence is predictable, governance feels like a managed system rather than a set of unpredictable rules.

Improving governance processes also requires careful attention to unintended consequences, because solving one problem can create another if the change is not tested against real behavior. For example, tightening a review requirement might reduce certain risks but increase bypass behavior if the process becomes too slow. Simplifying a process might increase speed but reduce evidence quality if the simplification removes necessary decision documentation. Beginners might assume improvement is always positive, but governance improvements must be evaluated as tradeoffs. This is why evidence must be monitored after changes, and why feedback loops must remain open, because they reveal whether the improvement made the process more usable and whether outcomes actually improved. Unintended consequences can also show up as measurement distortion, where teams adjust behavior to meet the metric rather than to meet the goal. A mature governance improvement approach monitors for these effects and adjusts measures or processes when needed. This iterative approach is how governance becomes refined over time. It also helps maintain trust because stakeholders see that governance changes are made thoughtfully and corrected when they create new problems.

Another essential improvement practice is standardizing what works, because improvements that remain localized do not strengthen enterprise governance as a whole. If one team develops a better way to document decisions, or a better way to handle exceptions, governance should capture that practice and make it available across the enterprise. Standardization does not mean forcing identical processes everywhere, but it does mean ensuring that core governance expectations are consistent and that successful patterns are shared. Beginners might assume standardization is restrictive, but sharing successful patterns can actually increase autonomy because teams can move faster when they have proven approaches. Standardization also improves auditability because evidence becomes more consistent and easier to review. When improvements are standardized, the enterprise reduces duplication of effort, because teams do not have to invent solutions independently. Governance becomes more efficient and more coherent. This is how improvement becomes enterprise learning rather than isolated optimization.

Governance process improvement must also include communication, because changes to governance processes affect how people work, and confusion about new expectations can create temporary risk and friction. Communication should be clear about what changed, why it changed, how teams should comply, and how success will be measured. Beginners often underestimate how much confusion comes from small process changes, especially when multiple processes intersect. Clear communication reduces that confusion and helps people adopt the improvement without resorting to old habits. Communication is also part of closing the feedback loop, because it shows stakeholders that their input and the evidence were used thoughtfully. It is equally important to communicate what did not change, because stability matters and people need to know what remains consistent. A governance improvement that is not communicated well can create new bypass behavior because people will follow the old path out of habit. Therefore, governance must treat communication as part of the improvement process, not as a separate announcement. When communication is consistent, adoption improves and the organization stabilizes faster.

A final improvement principle is maintaining balance between control and speed, because governance exists to support enterprise outcomes, not to slow progress until nothing moves. Evidence and feedback should be interpreted with this balance in mind, ensuring that governance controls protect what matters without creating unnecessary friction. Root cause analysis helps here because it reveals when a control is failing not because it is conceptually wrong, but because it is impractical under current constraints. In those cases, improving the process may mean making the safe path easier, such as clarifying criteria, reducing rework, or providing standard patterns that teams can use quickly. It may also mean investing in capacity, such as strengthening review teams or improving tooling, so controls can be executed without delays. Beginners sometimes think the only way to improve governance is to tighten rules, but mature improvement often involves simplification and enablement, not just enforcement. The ultimate test is whether governance improves the enterprise’s ability to deliver value safely and reliably over time. When improvement maintains this balance, governance becomes an enabler of sustainable speed and controlled innovation. That is the outcome governance should aim for.

As we close, improving governance processes using evidence, feedback loops, and root causes means treating governance as a living system that learns and adapts without losing coherence. Evidence reveals what is actually happening, including performance trends, process drift, and recurring weaknesses that threaten value and risk control. Feedback loops reveal usability issues and operational reality, and closing those loops builds trust that governance is responsive rather than detached. Root cause analysis prevents superficial fixes by identifying the underlying conditions that produce recurring problems, such as capacity constraints, unclear criteria, or incentives that encourage bypass behavior. When these elements are integrated into a regular improvement cadence, governance becomes more reliable, more auditable, and more practical because processes are refined based on reality rather than on assumptions. For brand-new learners, the key takeaway is that governance maturity is not achieved by creating perfect rules once; it is achieved by continuously improving how decisions are made and executed so the enterprise can deliver outcomes with confidence. This is the final step that makes governance sustainable, because it ensures the system does not stagnate, and it ensures that G E I T remains aligned to enterprise priorities as the world changes.

Episode 60 — Improve governance processes using evidence, feedback loops, and root causes (3A6)
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