Mean Time to Respond (MTTR), often referred to as Mean Time to Resolution in Splunk Enterprise Security, measures the average time from when a notable event is created (detection) to when it is closed (remediated). Customizing dashboards to provide analysts with more relevant, contextual information streamlines their investigation and triage workflow. This allows them to understand and act on security events more quickly, directly reducing the time it takes to respond. Therefore, a decrease in MTTR is a primary indicator of improved analyst efficiency resulting from dashboard enhancements.

A. Mean Time to Detect: This metric measures the time it takes for the system to identify and generate an alert, which occurs before an analyst interacts with a dashboard for investigation.

C. Recovery Time: This is a component of the overall response process that focuses specifically on restoring systems to normal operation after containment, not the initial analyst investigation phase.

D. Dwell Time: This measures the duration an adversary is present in a network before being detected. It is a measure of detection capability, not post-detection analyst efficiency.

1. Splunk Enterprise Security Documentation

Use Splunk Enterprise Security

"Security Posture dashboard in Splunk Enterprise Security": The Security Posture dashboard provides Key Performance Indicators (KPIs) to measure the effectiveness of a security program. It includes metrics like "Mean time to triage" and "Mean time to resolution

" which are components of the overall MTTR. The documentation states

"Mean time to resolution is the average time between the creation of a notable event and its closure." This directly measures the full analyst workflow duration that dashboard customization aims to improve.

2. Splunk Enterprise Security Documentation

Administer Splunk Enterprise Security

"Key performance indicators in Splunk Enterprise Security": This section defines the core metrics used to evaluate SOC performance. It explicitly defines "Mean Time to Resolution" as a key metric for tracking the time it takes for analysts to handle notable events from creation to closure

making it the ideal measure for tracking efficiency gains from tooling improvements like dashboard customization.