3 Key Pillars of IT Analytic Applications

As a long time analytics professional and enthusiast, I have seen organizations leverage domain and role-specific analytic solutions for improving sales, marketing, supply chain, production, and many other functions. One notable exception has been the IT organization. This is particularly ironic considering IT has typically been responsible for building and/or delivering analytic solutions to other areas of the business.

This is not to say that IT has not leveraged analytics. Technology companies have certainly offered log file and system level analytics to IT for server optimization, uptime monitoring, and event log analysis.

However, while many tools have emerged to provide greater oversight of their systems, there has been a dearth of solutions that provided strategic insights for the Business of IT. By that, I refer to analyses of the people, processes, and finances of the IT organization. Given the increasingly critical role of technology in modern business, it is vital that IT adopt analytics on par with the rest of the organization.

The benefits of a robust analytic application are many. Increased visibility and accountability across teams, transparency into IT inner workings to the larger organization, outstanding customer service, and resource optimization are among the many benefits to be seen. Collectively, these benefits can help IT leaders more effectively achieve business goals. In my experience though, such benefits cannot be delivered by sets of disparate tools and metrics. They can only truly be realized through a comprehensive analytic application.

What are the characteristics of such an application? Here are three essential pillars of IT analytic applications that distinguish themselves as business management solutions rather than operational tools.

  1. Many islands, one paradise: Most business areas have multiple operational applications that have specialized roles in automating processes. For example, an ITSM system would focus on IT Services desk, whereas the call center would run on CTI and ACD systems that record call volumes. Combining data from these related, but disparate system is critical to providing users full visibility. Data integration is one of the hardest tasks of providing insightful analytics to end users.
  2. Different strokes for different folks: Everyone needs analytics, but the type and manner in which they consume those analytics will vary. Whereas an IT executive might want to review highlights of their operations, a service desk manager may wish to explore the details of their backlog queue and identify the outlier incidents that get reassigned too often. Moreover, the service level manager of one application should only be seeing her group’s total work and not that of any other group. Applications must provide role-based views of the data based on the needs of each business user.
  3. I don’t know what I don’t know: Unlike operational applications that automate repetitive processes, analytic applications are meant for exploration, hunting data and finding new insights. Thus, an application should provide an inquisitive user all the capabilities that allow them to chart unknown territories with a rich set of metrics and related fields.

There are of course many other characteristics of a good application, which we will discuss in future posts, but these 3 key features are vital for IT Leaders to manage their business.

What other key capabilities and proficiencies do you expect from analytic applications?

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