Key Performance Indicators (KPIs) and Key Risk Indicators (KRIs) have a mixed reputation. They are widely accepted as necessary, rarely considered exciting, and often confined to dashboards that attract scrutiny only when problems occur. At the same time, Identity and Access Management (IAM) is one of the most critical control domains in modern enterprises, combining significant investment, operational dependency, and direct security risk. Without meaningful measurement, organizations cannot determine whether IAM improves security, enables the business, or merely sustains complex processes.
From KuppingerCole’s expert perspective, the challenge is not a lack of metrics. The challenge is translating IAM measurements into outcomes that are relevant beyond the technical domain. The right context is crucial.
Significant Investment, Limited Visibility
IAM is rarely a small undertaking. It spans directories, authentication, access governance, provisioning, and privileged access, to name a few capabilities, and increasingly developer platforms and cloud-native architectures. In regulated industries, measurement practices are well established, driven by compliance, audits, and regulatory scrutiny. Metrics exist because they must exist.
In less regulated sectors, IAM measurement is often weaker, despite growing pressure from cybersecurity threats, digital transformation initiatives, and user experience expectations. The result is frequently a reactive posture. Visibility increases only after incidents, audit findings, or failed projects.
A proactive approach requires visibility by design. Effective KPIs and KRIs provide insight into answering the following questions:
- How strong is the security posture really?
- How much of the attack surface can actually be seen?
- Where are IAM operations efficient, and where they are not?
- Whether users and teams can do their jobs without fighting controls
Outcome-driven metrics, Zero Trust, and similar terms are useful only if they help translate technical signals into business value. Otherwise, they amount to little more than new terminology applied to old metrics.
Performance is not the Same as Risk Avoidance
KPIs and KRIs are often used interchangeably, and that is where confusion starts.
KPIs measure performance. They assess how effectively IAM processes operate by measuring adoption rates, coverage, throughput, and efficiency. They answer whether defined objectives are being achieved.
KRIs focus on risk. They act as early warning signals, indicating when control weaknesses increase the likelihood of incidents. Typical examples include Segregation of Duties (SoD) violations, orphaned accounts, unauthorized access, or excessive privileges.
In practice, KRIs can be expressed as KPIs, and many organizations integrate them into a unified measurement framework. However, the underlying perspective remains critical.
- KPIs justify investment and operational improvement
- KRIs justify attention and intervention before incidents happen
Treating them as interchangeable without this distinction risks overlooking growing exposure while reporting strong “performance”.
Make IAM Outcomes Visible
IAM teams often operate largely out of sight. Their work becomes visible primarily when access fails or security incidents occur. Well designed KPIs and KRIs change this dynamic by enabling transparency around improvement and control effectiveness.
Reducing the number of orphaned accounts is a typical example. On its own, this appears as a technical hygiene metric. Translated into business terms, it demonstrates reduced attack surface, improved security posture, and lower likelihood of abuse. Transparency is not about marketing IAM activities; it is about making outcomes understandable and defensible to stakeholders. It is also a governance requirement. Without it, IAM can be evaluated primarily on cost and disruption rather than on risk reduction and enablement.
Measurement Requires Foundations
A KPI- and KRI-driven IAM approach cannot succeed without basic prerequisites. Experience across many organizations shows recurring patterns:
- Strategic alignment is essential. IAM objectives must be explicitly linked to business and risk objectives. Technically grown IAM functions often struggle here, as metrics evolve organically without a business context.
- Clear accountability and governance are equally important. Without defined ownership, metrics lack authority and interpretation. In addition, They are also not resilient as owners adapt these metrics to change. IAM governance boards, especially when closely connected to security and Information Security Management System (ISMS) functions, provide an effective structure.
- Communication channels determine whether metrics lead to action. Reporting without established collaboration between IAM, security, IT operations, HR, and business units limits impact.
- Baseline IAM maturity is a prerequisite. Standardized joiner, mover, and leaver processes, authentication controls, and basic governance must be in place before metrics become meaningful.
- Reliable identity and asset data underpin every metric. Weak data inputs stemming from poor data quality, gaps in context-aware data, broken or incomplete linkages, and a lack of data comparability inevitably lead to misleading KPIs and KRIs.
- Finally, alignment with a risk and control framework ensures consistency. Highly regulated industries benefit from established frameworks, while other sectors often need to formalize them before meaningful risk indicators emerge.
Once organizational and data related prerequisites are established, the question is no longer about measurement capability, but about relevance. Not all IAM metrics carry the same weight, and those that connect directly to everyday operational experience tend to achieve far greater acceptance outside the security domain.
Onboarding and offboarding metrics are a prime example. Delayed onboarding directly affects productivity and user experience. Delayed offboarding increases attack surface and insider threat exposure. Measuring average onboarding and offboarding times creates a direct link between operational efficiency and security risk.
Helpdesk metrics offer another high impact perspective. Ticket volumes related to authentication or Multi Factor Authentication (MFA) often reveal usability issues, weakness in processes, adoption gaps, or insecure workarounds. These indicators connect user experience, productivity, and security in a way that is immediately understandable. They also enable communication back to employees, reinforcing trust in IAM improvements. Once these organizational and data related foundations are in place, the discussion shifts from whether IAM can be measured to which metrics actually matter. At this point, relevance becomes the differentiating factor, particularly for stakeholders outside the security function.
Developers are the New Frontline Users of IAM
There is another stakeholder group that often gets forgotten in traditional IAM measurement: developers.
If IAM is hard to integrate, developers bypass the associated procedures and process overhead Not because they intentionally neglect the associated risk, but because they want to meet their business and product delivery goals. That results in shadow IT, inconsistent identity handling, and security gaps that show up later as unpleasant architecture debt, caused by risk being deprioritized under pressure
Business enablement metrics can be very concrete by answering the following:
- How quickly are IAM Application Programming Interface (apis) adopted?
- How much time does it take to integrate IAM into a new application?
- How easy is it to embed IAM-related policies into infrastructure and pipelines?
If those numbers improve, IAM stops being perceived as a gatekeeper and starts acting as a platform. That is where IAM becomes a business enabler. Secure by design becomes the default, not an afterthought.
Metrics must evolve with the identity landscape
IAM environments are changing. Non-human identities, service accounts, and workload identities are now integral to enterprise architectures. While terminology evolves, the underlying challenge remains. These identities require ownership, governance, and risk visibility.
KPIs and KRIs that do not adapt to this reality lose relevance. Effective IAM measurement must extend to non-human identities and answer the following questions:
- Where are they?
- Who owns them?
- How are they governed?
- Are they under control, or quietly expanding into an unmanaged population?
If the IAM architecture is updated without updating KPIs and KRIs, then the ability to tell the right story to the right stakeholders is lost, making related risk management more reactive than proactive.
Final thoughts
KPIs and KRIs do not make IAM exciting. But they determine whether IAM is steerable, explainable, and defensible. Organizations that want to use them more effectively should start by reassessing what is being measured today, why those metrics exist, and who actually uses them. Metrics that cannot be clearly linked to business objectives, risk decisions, or operational improvement should be challenged or retired.
To move from measurement as reporting to measurement as a management tool, organizations can benefit from a number of concrete actions:
- Review existing IAM KPIs and KRIs and explicitly map them to business objectives, risk scenarios, and decision points.
- Establish clear ownership for each KPI and KRI, including responsibility for interpretation, thresholds, and follow-up actions.
- Validate the quality, completeness, and comparability of underlying identity and asset data used for measurement.
- Focus on KPIs that directly affect user experience, such as onboarding and offboarding performance, helpdesk signals, and developer enablement, rather than abstract control states alone.
- Integrate IAM metrics with existing risk and control frameworks to ensure consistency and avoid parallel reporting structures.
- Regularly review and adapt KPIs and KRIs as identity architectures evolve, particularly in areas such as non-human identities and automated workloads.
Used in this way, KPIs and KRIs become more than dashboards or compliance artifacts. They provide a shared language for IAM teams, security, and business stakeholders, support informed decision-making, and enable continuous improvement. In increasingly complex identity environments, this ability to steer and explain IAM effectiveness is no longer optional. It is a prerequisite for sustainable risk management and business enablement.
For those seeking to move beyond theory, Events such as EIC 2026 in Berlin provide a space to compare IAM measurement approaches, discuss what works in practice, and understand how others adapt KPIs and KRIs to changing identity landscapes.
