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Big Data Analytics is a Useful Tool for Utilities
IVR Featured Article

Big Data Analytics is a Useful Tool for Utilities

 
October 10, 2014

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  By Joe Rizzo, TMCnet Contributing Writer
 


The electronic age that we now live in has given us access to a great deal of information. When you combine this with the ever-growing list of devices that are all interconnected leading us to the Internet of Things (IoT), you will see that data can be gathered from so many different sources. Big data is an all-encompassing term for any collection of data sets so large and complex that it becomes difficult to process using traditional data processing applications.


Big data analytics is the process of examining large amounts of data of a variety of types, or big data, to uncover hidden patterns, unknown correlations and other useful information. Big data analytics will not only help a company to understand the information contained within the data, it will also help identify the data that is most important to the business and future business decisions. Enterprises are increasingly looking to find actionable insights into their data.

Recently, ClickFox (News - Alert) had an opportunity to interview Michael Schneider, who is vice president of operations support for the San Diego Gas & Electric Utility (SDG&E) and SoCalGas. The question and answer session that was posted on Virtual-Strategy Magazine focused on what type of innovations big data analytics could bring and how it could impact the way utilities do business.

When you consider that just about every home is connected to a utility company, you can imagine the amount of information that is available. The best way to forge through all of this information is big data analytics. Schneider was looking for a way to better understand and find insights into the customer experience. Word of mouth travels fast and a bad customer experience is something that any company wants to avoid.

One customer experience that we have all gone through is following the automated voice telling us which number to click on to resolve our problems. Schneider said “We gained access to quantitative data that helped us understand how customers were interacting with us and how successful they were in completing a given transaction in their preferred channel.”

The information that was gained from looking at a wide variety of customer experiences gave SDG&E the insight they needed to make some major changes to how customers interacted with interactive voice response (IVR), better known as “that automated voice,” as well as live agents. This led to benefits for both ends. The simple process of changing a word or utility terminology to one that everyone can relate to resulted in a much better customer experience that saved time and energy.

On the flip side of the coin, the fact that customers were able to use the automated processes to get answers, pay their bills and essentially complete their transactions resulted in the utility cutting costs and thereby saving money. Schneider looks at this as a great return on investment when he said, “Our customer satisfaction scores rose as our costs dropped.”

Big data can have a huge impact that can lead to savings on a companywide level. The use of big data analytics allows the company to make informed decisions by actually understanding what the customers are experiencing and what they really want. This gives the company the ability to continue to add functionality in the self-service channels.

In closing, Schneider’s advice on using big data analytics is “Anchor your analytics to your business drivers and to make certain your planning is for the long term so that you don’t inadvertently create more data silos that have to be maintained.”

This is good advice. While it is true that the more information that you have, the better it can be used, the fact remains that it is too easy to be overwhelmed with too much data. Once you reach that point, the data tends to become irrelevant, which is why a good analytic strategy is very important.




Edited by Rory J. Thompson
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