As an IT executive, you’re likely all too familiar with the phrase “Big Data.” What you may not hear as often is the term, “enterprise analytics”.
Major departments of top companies and organizations across the globe are scrambling to surf this ocean of information and data. They want to potentially drive data-driven strategies for success. One would logically assume IT Departments would lead this charge, but surprisingly this isn’t the case. IT has traditionally been focused on strategies strictly related to data management and capture, rather than focusing on using data to achieve business outcomes.
This is where enterprise analytics comes into play.
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. This is Enterprise Analytics (EA)—and here are four reasons why it’s critical that IT takes on a central role in guiding EA efforts.
Reason #1: Analytics done within line-of-business (LOB) can’t keep pace with the growth of data and the demand for insight— an essential part of enterprise analytics.
Many business units employ their own statisticians, data scientists, and analysts responsible for conducting reporting, data mining, and predictive analytics. These individuals do analytical work that provides tremendous insight and value; however, it’s 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. Additionally, they can simultaneously augment their analytics and reporting efforts. In other words, IT can maximize the amount of data that can be put to work for the organization. In the end, they can use that to contribute to the success of enterprise analytics efforts.
Reason #2: IT’s real-time access to data across business units 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— meaning your enterprise monitoring will consistently be up to date.
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. These tools are 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: IT can be a as a strategic partner with business units across the organization using analytics.
IT has always quite literally existed to serve the data needs of the company—enterprise 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 Enterprise Analytics.
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 dormant data simply taking up space, and data being converted into actionable insights.
This is the first of many blog posts Windward will be publishing on opportunities for IT to get involved in EA. Future posts will provide some interesting applications real examples showing how IT is essential to enterprise analytics.
