Mean time between failures (MTBF) is a key performance indicator (KPI) that measures the average time that a system or component operates without interruption or failure. MTBF is a common metric for reliability and availability of IT services. A higher MTBF indicates a lower frequency of failures and a higher ability to deliver uninterrupted IT services. According to the CRISC Review Manual 2022, MTBF is one of the KPIs for IT service delivery1. According to the CRISC Review Questions, Answers & Explanations Manual 2022, MTBF is the correct answer to this question2.
Mean time to recover (MTTR), planned downtime, and unplanned downtime are not the best KPIs to measure the ability to deliver uninterrupted IT services. MTTR measures the average time that it takes to restore a system or component to normal operation after a failure. Planned downtime measures the scheduled time that a system or component is not available for use due to maintenance or upgrades. Unplanned downtime measures the unscheduled time that a system or component is not available for use due to failures or incidents.
These KPIs are useful for measuring the impact and duration of service interruptions, but they do not directly reflect the ability to prevent or avoid service interruptions.

According to the CRISC Review Manual, a root cause analysis is a technique that identifies the underlying causes of an event or a problem. It helps to determine the most effective actions to prevent or mitigate the recurrence of the event or problem. A root cause analysis is the best approach for the risk practitioner to take in this scenario, because it will help to understand why the number of emergency changes has increased substantially and what can be done to address the issue. The other options are not the best approaches, because they do not address the underlying causes of the problem. Temporarily suspending emergency changes may disrupt the business operations and create more risks. Documenting the control deficiency in the risk register is a passive action that does not resolve the problem. Continuing monitoring change management metrics is an ongoing activity that does not provide any insight into the problem. References = CRISC Review Manual, 7th Edition, Chapter 3, Section 3.2.4, page 130.

Periodically reviewing big data strategies is the best option to minimize the risk of inaccurate data, because it allows the organization to assess the quality, validity, and reliability of the data sources and the analytics methods. It also enables the organization to identify and address any gaps, errors, or inconsistencies in the data and the results. By reviewing the big data strategies, the organization can ensure that the data analytics are aligned with the business objectives and the risk appetite.
Establishing an intellectual property agreement is not relevant to the risk of inaccurate data, as it is a legal measure to protect the ownership and use of the data, not its quality or accuracy.
Evaluating each of the data sources for vulnerabilities is a good practice, but it is not sufficient to minimize the risk of inaccurate data, as it only focuses on the security aspect of the data, not the validity or reliability of the data itself.
Benchmarking to industry best practice is a useful way to compare the performance and results of the data analytics, but it does not directly address the risk of inaccurate data, as it assumes that the data and the methods are already valid and reliable. References = Risk IT Framework, 2nd Edition, ISACA, 2019, page 62-
63.

The risk practitioner's most important responsibility in managing risk acceptance that exceeds risk tolerance is to verify authorization by senior management. Risk acceptance is a risk response strategy that involves acknowledging and agreeing to bear the risk and its potential consequences. Risk tolerance is the acceptable or allowable level of variation or deviation from the expected or desired outcomes or objectives. When the risk acceptance exceeds the risk tolerance, it means that the organization is taking on more risk than it can handle or afford. Therefore, the risk practitioner should verify that the risk acceptance is authorized by senior management, who have the authority and accountability for making risk management decisions and ensuring that they are aligned with the organizational strategy and objectives. The other options are not as important as verifying authorization by senior management, as they are related to the adjustments, conditions, or documentation of the risk acceptance, not the approval or validation of the risk acceptance. References = Risk and Information Systems Control Study Manual, Chapter 3: IT Risk Response, Section 3.2: IT Risk Response Options, page 133.

The percentage of system availability is the most important key performance indicator (KPI) to establish in the service level agreement (SLA) for an outsourced data center. This KPI measures the uptime or reliability of the systems hosted by the data center provider, and reflects the ability of the provider to meet the customer' s expectations and requirements for system performance and accessibility. A high percentage of system availability indicates that the provider is delivering consistent and quality service, while a low percentage of system availability indicates that the provider is experiencing frequent or prolonged system failures or disruptions, which can negatively affect the customer's business operations and reputation. Therefore, the percentage of system availability is a critical factor for evaluating the effectiveness and efficiency of the data center provider, and should be clearly defined and monitored in the SLA. The other options are not the most important KPIs to establish in the SLA for an outsourced data center, as they do not directly measure the quality or reliability of the service provided. The percentage of systems included in recovery processes is a measure of the scope or coverage of the disaster recovery plan (DRP) of the data center provider, but it does not indicate how well the provider can execute the DRP or restore the systems in the event of a disaster. The number of key systems hosted is a measure of the capacity or utilization of the data center provider, but it does not indicate how efficiently or securely the provider can manage the systems. The average response time to resolve system incidents is a measure of the responsiveness or agility of the data center provider, but it does not indicate how effectively or proactively the provider can prevent or mitigate system incidents. References = Risk and Information Systems Control Study Manual, 7th Edition, Chapter 3, Section
3.2.3.4, Page 140.