Operators Struggle to Unlock Value in IoT-Driven Big Data

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Every Internet of Things (IoT) forecast predicts tens of billions of devices coming online over the next decade. With a lot of devices comes a lot of data, and if a recent survey is any indication, the telecom industry is struggling to figure out what to do with all of it.

Telecoms.com Intelligence polled more than 1,500 telecom professionals about big data. Seventy-one percent agreed that big data will be key for IoT’s success, an outlook that makes sense. After all, it’s tough to make or save money with IoT without having a way to analyze and act on the data those devices generate.

The telcos surveyed ranked customer analytics as the most important use of big data. IoT can provide those and other service providers with new insights into the myriad factors that affect the customer experience, so here big data creates opportunities to save and make money.

For example, if IoT nodes in the network, CPEs and elsewhere identify problems before they become noticeable to customers, then contact center staff levels can be lower because they won’t have to field as many complaints and questions. Ninety-seven percent of respondents cited proactive network maintenance and identifying network issues in real time is an important or very important feature of big
data.

Another 96 percent said the same thing when it comes to triggering proactive customer care based on network performance and customer experience. One wild card is how exactly those triggers are tripped. Some operators, such as AT&T, advocate closed-loop systems, where the network is intelligent enough to adjust itself based on big data. Others are uncomfortable with such high levels of automation and prefer to have staff analyze the data and then act on it. But manual intervention becomes less practical as volumes of big data soar because it’s not cost effective to have enough people analyzing it, especially in the kind of real-time scenarios that are key for fixing problems before they affect the customer experience.

Either way, by nipping problems in the bud, an operator can build a reputation as a provider of high-quality services. That helps it attract, retain and upsell enterprises and other customers that value reliability and performance, which in turn helps profit margins because the operator is less reliant on price as a market differentiator. Indeed, 48 percent of respondents agreed that “a good big data strategy would give my organization a competitive advantage,” while another 28 percent agreed that “correct use of data is critical to the success of my organization.”

Lack of Skills and Business Cases Often Limits Implementation

So it’s surprising how many respondents aren’t following through. More than half said they don’t believe they’re making good use of big data. Why? A quarter blamed “a lack of required skill sets in organization,” while another 21 percent said there’s “not enough clear business cases to warrant investment.” The latter is a surprise, given the aforementioned widely held perceptions about big data’s competitive value.

For big data and IoT vendors, these responses highlight opportunities. For example, the lack of required skills indicates a market for professional services to help operators make and save money with IoT-driven big data. But to maximize sales of those services, those vendors also will have to educate the significant amount of operators that are skeptical about IoT big data’s business cases.

Besides improving the customer experience, another potential business case is selling big data to third parties, with customer-specific details stripped out to avoid concerns about privacy. But many survey respondents are skeptical about whether such sales will drive much revenue. Twenty-four percent
said that 1 percent or less of operator revenue will come from sales of anonymized customer data. Another 30 percent see it driving up to 4 percent of revenue. Only 12 percent see revenue as high as 8 percent.

Even so, respondents are bullish about using big data to drive personalized marketing and content, with 87 percent citing those applications as important. Another 78 percent see big data as another tool for enabling Wi-Fi offload, which is yet another example of how big data can save money for operators.

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Mr. Fellah, is a Senior Analyst and founder of Maravedis with 20-year experience in the wireless industry. He authored various landmark reports on Wi-Fi, LTE, 4G and technology trends in various industries including retail, restaurant and hospitality. He is regularly asked to speak at leading wireless and marketing events and to contribute to various influential portals and magazines such as RCR Wireless, 4G 360, Rethink Wireless, The Mobile Network, Telecom Reseller to name a few. He is a Certified Wireless Network Administrator (CWNA) and Certified Wireless Technology Specialist (CWTS).

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