How to Connect Data to Meaningful and Measurable Results - Slide 4

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One of the most powerful elements of a correlation model is that it is self-correcting. Because you are using the correlation model to answer the “whys” when you observe an unfavorable trend, a deficiency in the model becomes readily apparent.

Let’s use MTRS as our example. You might define that MTRS should be driven by two correlated metric indicators:

  • The number of Incidents in which the initial response target was breached
  • The average number of Incidents per day

The logic would read that MTRS will move in correlation to these two indicators. If your teams are not responding according to the agreed upon response timelines, there’s a strong likelihood that it’s going to take them longer to restore service. And if there are simply too many incidents occurring, it is likely to stress your organization’s capacity to respond and thus increase the average restoration time.

But what if MTRS is rising, yet response targets are being met and the average number of incidents is low? In this case, the model will have demonstrated to you that there is a correlation between MTRS and something that you have not yet identified. That means that you are not yet measuring or managing all of the things necessary to effectively manage MTRS.

According to Charles Araujo, president and managing consultant of CastlePointe, your IT organization has a problem, and you don't even know it.

He explains that you're collecting data and probably think that you have everything you need. But you likely have trouble connecting that data with any action that had a meaningful and measurable impact on the results your organization delivers. That's because what you have is data. But what you really need is information that enables action.

The primary focus of any IT service management or IT transformation effort is to improve service delivery and operational efficiency in order to deliver the appropriate level of service in the most cost-effective manner possible. To do that, you must be able to measure your performance in a way that enables you to monitor your effectiveness and take the corrective actions necessary to move you toward your goal.

The problem is that most IT organizations collect reams of technical data, but have trouble converting that data into meaningful, results-driven action. The primary flaw is in the data itself. In most cases, how it's collected and reported makes it almost impossible to take action.

In this slideshow, Araujo highlights the benefits of building an IT Metrics Correlation Model to gain the full value of the data being collected.

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