Improve Mean Time to Happiness
by Christine Cignoli on

Modern IT metrics encompass a lot of measurements, from throughput and latency to capacity and error rates. In a complicated technology world, the question of which metrics to track has gotten more complicated too. It’s just one more challenge in a challenging IT environment. And businesses and their IT teams can’t spend all their time tracking every metric. A simplified view of the most important metrics is what’s really needed. That’s especially true when you’re trying to get an accurate, reasonably up-to-date look at how your overall infrastructure is performing, and how users are experiencing applications and getting work done (or not).

When IT teams are using performance monitoring software, reduced mean time to resolution (MTTR) is one way to confirm its importance and value to business team leaders. (MTTR can also refer to mean time to repair.) Either way, “mean” is an average of the time it takes from a problem being reported to the time when that problem is fixed.

The road to a short, continually improving MTTR is paved with details that can derail the whole thing. The path starts with notification of the problem and continues through diagnosing the problem (ideally with little or no finger-pointing between IT teams), then time to fix, test and fully resolve the problem. That’s assuming that resolving the problem doesn’t take more than one attempt or any guesswork about what the problem is. Improving MTTR also includes a big human element, with various people potentially involved in finding, prioritizing and fixing the problem.

Monitor for Better MTTR

Reducing overall MTTR for users comes with details and dependencies that can easily trip up the various IT teams that might be involved. When performance monitoring enters the equation, though, it gets easier. We helped one of our customers improve a scenario we’ve likely all been on the user side of—that of a hotel guest wrestling with slow WiFi.

The slow guest WiFi network at a large multinational hotel chain was causing problems for users, and costing some hotel managers their bonuses. The hotel chain used AppNeta to reduce mean time to resolution on issues to just hours, rather than days as it had been before. Managers can log in to the AppView portal to run individual reports on how bandwidth is performing at their location. All sites are monitoring to Google, so there’s one web service with global visibility.

The MTTR improvements at that company affect a lot of end users, whose experience with hotel WiFi just got a lot better. That’s a positive outcome all around, especially considering how much slow WiFi can negatively affect guests and their corresponding customer satisfaction. Reducing mean time to resolution is obviously excellent for users, but it’s a metric that can also help IT and business leaders choose strategy and technology that adds efficiency to their work. That fast MTTR cuts time spent on helpdesk ticket wrangling and other reactive tasks. 

Performance monitoring adds an element of proactivity to the quick remediation process that users today demand. Preventing problems is ideal, but solving them quickly is nearly as good when they do happen.

Filed Under: Industry Insights

Tags: APM , metrics , monitoring technology