SEARCH

Today, I want to share a framework that has transformed how organizations approach compliance measurement Here's the thing: We often get caught up in measuring everything we can, but what truly matters are the They measure how well you're meeting your rule-based obligations—think regulatory requirements, internal if we're delivering on our promises. 📈 Effectiveness Metrics: These are the "so what" metrics—they measure It's not about drowning in data—it's about measuring the right things that keep you: ✅ True to your mission

Compliance is an end, a means, a measure, and a value. ➡️ As an “end” it is the outcome of meeting all stakeholder trust. ➡️ As a “means” it is the activity of aligning the means toward that end. ➡️ As a “measure

Contextual Factors: external factors beyond a company’s control, typically measured or tracked through Making systems changes relies on knowledge of what measures of effectiveness, performance, conformance (A shby’s Cybernetics Law of Ethical Inadequacy ) When a measure becomes a target, it ceases to be a good measure. What measures will be used to define success?

This is not unlike the practice of risk management where measures are used to interfere with the natural At a quantum level, the act of measuring affects what we observe. It's only when we take the measurement that one is made more certain and the other less so. We don’t want the measurement of what “is” to affect what “will be.” To limit the effect we isolate the measurement from the reality we are observing.

Meeting all these obligations requires measures of conformance, measures of performance, measures of effectiveness, and measures of assurance.

QC: The Reactive Measures At its core, QC is a set of activities focused on identifying and addressing QC involves inspections, testing, and other validation measures to catch errors or problems before a QA: The Proactive Measures In contrast, QA takes a more proactive and holistic approach to quality. activities such as: Establishing clear quality standards and processes Implementing quality control measures QA as the Measure of Assurance As the role of QA has evolved, it has become the primary measure of an

Consistency is a critical measure of performance and passing an audit is the measure of success.   Risk controls (measures) are put in place to ensure that objectives are achieved, and outputs are evaluated Meeting objectives is a critical measure of performance, and making progress is the measure of success

In fact, even when considering qualitative characteristics they are often mapped to quantitative measures Quantitative measurements are considered by many as better than qualitative measurements. One of the reasons given for this is that the former are objective whereas qualitative measurements are indicators are measured and monitored. That is a qualitative measure which requires a value judgment.

This provides a measure of conformance at least at some level. This systems-first approach emphasizes system interactions so that a measure of effectiveness is achieved Not only is the system operational it is already demonstrating a measure of effectiveness.

additional uncertainty surrounding specific requirements that necessitate structured assurance and risk measures distinction is crucial for implementing effective management processes, technical controls, and risk measures specific assurance protocols for these requirements, and Implement appropriate risk controls and measures

Governance in the AI era requires more than traditional oversight; it requires proactive measures like incorporate guardrails (e.g., safety and security protocols) and lampposts (e.g., transparency and fairness measures AI Safety Policies: Measures to prevent harm and ensure robust testing and monitoring of AI systems.

Many organizations try to use measures of conformance to predict and possibly prevent future occurrences Lagging Indicators and Actions Lagging indicators measure what has already happened specifically after Leading indicators include measures of effectiveness of the preventive controls which are predictive Bottom Line Lagging indicators can never be leading as they measure things after the risk event. They may have utility to predict future risk events but this is limited as they often measure things