Windward Insights

Four Reasons Why IT is Essential to Enterprise Analytics

Published Aug. 19, 2015
Written by Nick Wilkerson

Close up of businesswoman holding graphs in hand

As an IT executive, you’re likely all too familiar with the phrase “Big Data.”

Major departments of top companies and organizations across the globe are scrambling to surf this ever-growing ocean of information and insight-packed zeros and ones to potentially drive data-driven strategies for success.

One would logically assume IT Departments would lead this charge, but since IT’s traditionally been focused on strategies strictly related to data management and capture, they’re often left out of guiding efforts to actually use that data to achieve business outcomes.

It’s time for a change.

IT departments don’t just hold the keys to data; they turn those keys in a way that opens the door to useable, actionable,knowledge. It’s called Enterprise Analytics (EA)—and here are four reasons why it’s critical to the success of organizations that IT takes on a central role in guiding EA efforts.

Reason #1:Analytics done within line-of-business (LOB) analytical teams can’t keep pace with the growth of data and the demand for insight.

Many business units employ their own statisticians, data scientists, and analysts responsible for conducting reporting, data mining, and predictive analytics. While the analytical work done by these individuals undoubtedly provides tremendous insight and value, it’s too often done in an ad hoc fashion, designed to address specific research questions. IT can partner with LOB analytics teams by providing them with greater access to a larger variety of real-time data while augmenting their analytics and reporting efforts. In other words, IT can maximize the amount of data being put to work for the organization.

Reason #2:IT’s real-time access to machine-generated data across business units uniquely positions IT to quickly and efficiently convert data to insights.

IT has access to data relevant to various business units, including: marketing, sales, product management, HR, cybersecurity, and more. Moreover, much of this data is machine-generated and updated in real-time or near real-time.

Reason #3:Analytical software tools are more sophisticated, less expensive, and more accessible.

The growth in the demand for data insights has led to an ever-growing number of analytics software tools specifically designed to efficiently handle the volume, variety, and velocity of Big Data—and IT knows how to use them. IT can quickly and easily adopt such tools without having to worry about extensive and expensive deployment or ramp-up periods.

Reason #4:Collaboration with non-IT business units through analytics will position IT as a strategic partner with business units across the organization.

IT has always quite literally existed to serve the data needs of the company—analytics is a natural extension of that role. Expanding IT’s engagement in data analytics will empower IT to become a true strategic partner throughout the organization. Everyone wins when IT leads data.

It’s time for IT to open the door to strategic success through EA.

The bottom line is Big Data’s not getting any smaller. And the demand to extract the best information and insights to drive business success is more critical than ever before. IT can be the difference between massive amounts of dormant data simply taking up space, and massive amounts of data being converted into actionable insights for the organization in real time.

This is the first in a new series of blog posts Windward will be publishing on opportunities for IT to get involved in enterprise analytics. Future posts will provide some interesting applications and examples of the types of analytics IT can conduct.

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- Nick Wilkerson

  • Data Analytics
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