Navigating the Maze of IT Complexity with Analytics

In Analytics

Perhaps no single word better describes IT today than the word “complex.” In a recent survey conducted by Ipswitch, 66% of more than 1,300 IT professionals worldwide agreed that increasing IT complexity makes it more difficult for them to do their jobs successfully.

Thanks to the variety of technologies available, technology’s role as a core business enabler, and the accumulation of legacy systems, IT staff are faced with an often messy amalgamation of systems and applications spanning business units, processes, regions, and so on. This leaves IT with the challenging task of simplifying the IT environment in order to better service customers.

Applying the Rules of Manufacturing

The key to simplified IT lies in the principles of manufacturing. You may already be familiar with the idea that the IT organization is like a manufacturing environment with multiple processes, dependencies, and queues, as well as bottlenecks, resource contention, and utilization rates.
This isn’t a new concept. In the book The Phoenix Project, Gene Kim makes this comparison and says that if you make a change on one side of the floor, something goes awry on the opposite side. Therefore, if you want to fix a problem downstream, you should look upstream to find the cause. But how do you go about optimizing the environment?

Using Measurements to Address Complexity

At Numerify, we have our own take on this concept. If you think about the IT organization in terms of manufacturing, complexity is an operations optimization problem. The best way to simplify is to measure every metric, identify the dependencies between them, and determine the root cause of every problem and resource contention. You can then simplify your processes accordingly.

For example, say you have a high mean time to resolve (MTTR) for specific types of incident resolution issues. The root cause of this problem may be mismatched IT skills, or there could be a process issue where incidents are being routed to the wrong person. Analytics will enable you to slice and dice the data to determine that the exact cause of delay and what you need to do to fix it.

Let’s look at another example: The business requests a change to the way pricing is calculated in the CRM system. The application developer writes and adds in the code, resulting in a change. That change causes an issue with the quote generation process in the CRM system. Upon discovering that their quotes are wrong, salespeople call the IT service desk, which logs the incidents. In order to find the root cause, somebody needs to correlate the incidents with the change —that’s what analytics does. Analytics enable IT to see that when a particular change was introduced, it resulted in 53 specific incidents that came in from sales, store operations, and customer service.

Without this visibility, IT’s only option is a whack-a-mole approach that involves addressing each incident rather than the underlying root cause. As a result, the problem becomes worse and IT is no closer to simplifying the environment or optimizing operations.

The Impact on ROI

Finally, IT analytics can help you prove return on investment (ROI). Take, for instance, a new firewall that is easier to use and manage. By quantifying the number of incidents and requests related to the old firewall and analyzing the reduction in incidents after installing the new firewall, you’ve not only improved security but reduced the time and trouble connected with supporting the old firewall. This correlation helps you prove the ROI of your investment to your business leaders.

[Photo courtesy of Flickr.]
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