Incorporate all data

Valuable data streams are coming from all directions, and CSPs need to incorporate this disparate data in order to gain pervasive visibility into the customer experience, network performance, and the performance of their business. CSPs can adopt BI (business intelligence) solutions that address the multitude of available data. According to recent research from Ovum, IBM, Oracle, SAP, and SAS are the frontrunners in this area. According to Ovum, nearly half of BI and analytic applications built and run in 2014 will integrate text and data analysis and modeling, complex business rules, and predictive analytics. This will only increase the demand for processing power, however, as enterprises seek to extract value from this data quickly. 

“BI vendors today cannot be choosy about the data they analyze. Unstructured and semi-structured data is more relevant for BI today than ever before, and so is invaluable customer and pipeline data sitting idle in CRM systems. Vendors that fail to see the forest for the trees (curated data) will lose business and hinder growth for their customers,” says Surya Mukherjee, Senior Analyst at Ovum.

Visual discovery tools--tools that enable users to visualize and mash-up data from many sources--are coming onto the market, and represent a significant development in BI. They are significant because they package up big data in an easily digestible, dynamic, and infinitely configurable visual interfaces without the need for extensive programming or development work from IT teams. In many ways, this represents the future of analytics.

"Enterprises today need BI that is smarter and faster, but invisible. User interfaces and experiences that are reminiscent of the enterprise resource planning era will not survive the next five years,” said Mukherjee.

Ask the right questions

Can’t figure out which question to ask of your data? Don’t worry, there are tools that can help. SAP, for example, has a new solution that helps service providers understand the key drivers that relate to a specific question. To help analyze and target relevant customers, SAP InfiniteInsight automates the building of sophisticated predictive models and helps users quickly get to the right algorithm for their business problem with a model built for accuracy and optimal results. Customers can then access all available variables in SAP Customer Engagement Intelligence and stack them against one another in order to identify the predictive ones, allowing the user to better understand the key drivers of each model within minutes. 

“SAP Customer Engagement Intelligence is a first step toward making predictive analytics available to everyone,” said Shekhar Iyer, global Vice President, Business Intelligence and Predictive Analytics, SAP. “The integrated solution puts the power of predictive analytics into the hands of the business user, enabling more effective targeting and faster time to value by integrating business intelligence, agile visualization and advanced analytics into standard business processes.” Cox Communications used SAP's solution to personalize product recommendations in an effort to boost acquisition and retention rates. 

“Through SAP InfiniteInsight, Cox has been able to quickly poll through massive amounts of data to generate custom models for various regions and products,” said Parimala Narasimha, Director, Marketing Analytics, Cox Communications. “With SAP, we are able to derive insights in an automated way and provide customized recommendations.” 

Analysis done right beats big data hype

CSPs that embrace Big Data solutions will have a significant competitive advantage in the years to come. These solutions lower costs, improve efficiencies, boost average revenue per user (ARPU), and open new revenue streams while guiding business strategy in the right direction. Just as important as the hardware capabilities of a big data solution are its analytical strengths, and greater focus must be given to these attributes. No one wants to be standing around in "lucky underwear" wondering what happened. Done right, big data is bigger than the hype, and certainly better than spurious correlations.