Using Advanced Analytics to Redefine IT Service Excellence

Enabling profitable revenue growth, business scalability, operational efficiencies and increased customer satisfaction by using rapid innovation has now become the prime focus for any CIO office. Modern IT organizations have positioned themselves to be in-charge of setting up the big data foundation for enabling business teams across engineering, manufacturing, sales, marketing, operations and finance to rev up the growth engines, become more agile and reduce business risk.

While doing so, many IT organizations don’t have the time or the resources to effectively manage their own backyards e.g. end-user productivity infrastructures, service desks etc. While there are some tools like Zendesk and ServiceNow to manage the IT service delivery and performance, these, however, generally lack good analytical reporting capabilities. Therefore, many IT organizations have still relied on spreadsheet-based reporting.

It not only takes long time to generate IT service performance reports, it is also very difficult to get any insights into the service performance. As these reports provide no predictive capabilities, it is very difficult to plan intelligently for future service improvements. The overall usability of these reports is generally very poor.

There are tons of 3rd party analytical solutions that integrate with these service management platforms. However, most of these cannot be efficiently used by the end users. These tools force the users to have a pre-understanding of the semantics and grammar, and require a lot of training. They still expect an IT engineer to write the logic for answering any typical reporting request. This is equivalent to buying a car body, instead of a ready-to-drive car, that works only on a particular type of road. The driver is expected to fit appropriate parts depending on the type of road, weather conditions, and everything else about the route… Imagine having to do that day in and day out, and for every possible route… with business teams waiting in line for IT to help with the car assembly! I am not kidding!

At PMC Sierra, as part of our digital transformation, we encouraged end user adoption of analytical products that freed up the IT bandwidth and saved costs on training. Drastin is one such solution that showed potential to increase analytics usage across the enterprise. With its “Google-like” search interface and rich visualizations, anyone could start using it without much training.

Drastin is a natural language-based platform that learns from the historical data and helps predict future performance. With its great visualization dashboards, it helps provide easy slicing and dicing and drill down into the data (diagnostic analytics), and hence improves the overall user adoption.  Also, since it is a cloud-based “Analytics as a service” tool, one doesn’t have to tie down the precious IT resources to the management of this tool. Drastin’s search functionality is natural and allows business users to make better decisions while removing the linear dependency on IT engineers. Within a few days after initial setups and with some data learning by the tool, one could ask their business queries in English (for example, “Monthly MTTR last year for network team”) and get an instantaneous response.

Good advanced analytics tools can remove the painful reporting process and allow stakeholders easy access to KPIs, metrics, actionable insights, without much training. CIO office can get deeper insights into IT Service Delivery across teams, drive the IT organization to effectively track performance for service improvements and encourage data-driven decisions.

Advanced analytics tools can help redefine IT Service Excellence.

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About adhirmattu

A Senior Information Technology Executive with expertise in building world class global IT organizations to improve company profitability and growth. Experienced in supporting multiple large scale acquisitions & global system implementations with consistent track record of reducing cost of IT service delivery.
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