Analytics/Big Data

Big Data, Sans Hype

Big data, as a term, often gets over-hyped and over-used. But, as a practice, strategies are already being put to use at network operators as they wade through the challenges to make it an every day part of how they do business.

On a recent live chat on the site, Light Reading editors were joined by TM Forum executives, Heavy Reading analyst Ari Banerjee, and nearly 60 other participants to discuss how big data is actually being used today and what the roadblocks to more extensive usage include. We had an enlightening, hour-long discussion that managed to stay hype free.

So how are operators using big data today? The consensus was that it was a priority for them, but not on its own. Operators are undertaking big data initiatives to inform and improve such network transformations (and acronyms) as SDN, NFV, LTE, and CEM.

Banerjee noted that Heavy Reading has consistently seen operators undergoing initiatives related to call centers or customer care to reduce churn, as well as network resource management-centric initiatives around capacity management, planning, WiFi offload, and small cell placement. Big data applied to SDN isn't here yet, but give it 18 to 24 months, he said.

"I've seen live implementations of analytics tools running in major operators that allow them to pinpoint the experience of their highest value customers, and that data is driving scarce capital investment in the right directions," added Nik Willetts, CSO at the TM Forum. "There is also a lot of real progress and programs underway in data monetization."

Big data challenges
That's all great news, especially for the plethora of vendors looking to help operators flesh out these strategies. But, there's also no shortage of challenges that is still irking the market. Here's a few that came up on the chat:

  • Peter Crayfourd, head of customer engagement programs, TM Forum: "One of the main challenges in telcos, today they look at most of their data from a snap shot point of view thus missing the end to end customer experience per user. This creates quite a big hit on the storage and processing of big data as it needs to be viewed in a customer not business technology way."

  • Banerjee: "Silos, silos and more silos…Also sanity of data is a big issue. Data discovery, expensive integration efforts, as well as expensive professional services effort are roadblocks."

  • Willetts: "You have two simultaneous pressures on operators -- capital crunch because of the investment needed to sustain the demand due to growth in mobile data, and saturated markets with falling margins driving the need to hang on to the customers you have and increase the services they buy from you."

  • Crayfourd: "I would have to say they have quite a long way to go before they make customer centric improvements, as all the networks I know process their KPIs every 15 minutes! Which means, as a customer, if you are on a conference call for one hour and you drop a call every 16 minutes, the network KPI is GREEN although the customer has had a very poor experience. This has to change if we want to become customer centered and start building that trust and loyalty."

  • Banerjee: "Key challenge in many case for operators is where to start. Tools are available but top management commitment and organizational siloes and cost all prove to be bottlenecks."

  • Steve Cotton, director of business assurance programs, TM Forum: "The key challenge, in my opinion, is to find the bold CxO leader to launch such a sea change approach to doing business."

Carol Wilson and I are headed to San Jose, Calif., next week for the TM Forum's Digital Disruption conference where big data, alongside a range of other Service Provider IT (SPIT) topics are on the agenda. Check back for our ongoing coverage of the show, and let us know if you have any questions in the comments section below.

— Sarah Reedy, Senior Editor, Light Reading

Sarah Thomas 10/28/2013 | 10:14:48 AM
Re: Any evidence of impact on top or bottom lines? Thanks to you and AVacek for sharing some examples. It's always good to see real-world use cases with named operators, especially for an area like big-data that needs concrete ROI to prove its worth right now.
Larrinaga 10/28/2013 | 7:44:29 AM
Re: Any evidence of impact on top or bottom lines? Hi Ray, 

We have many examples of companies that have implemented our solution and are ready to share very specific ROI data.

In particular one of the largest telecommunication provider in Europe is using Sinequa to provide its call center agents with an instant 360° view of customer calling in, dramatically reducing the time previously needed to open all the enterprise applications containing customer data. By reducing the average time of calls, the have acheived savings of up to 60M  €.

If you want more informations, let me know. I would be happy to share more about it with you. 


kaop 10/26/2013 | 5:27:10 PM
Re: Any evidence of impact on top or bottom lines? One of the biggest advantage of Analytics is ability to scale unlimited data.  More data give the self-service users more access and control of their accounts.  They do not have to contact customer service; saving companies money.
DOShea 10/25/2013 | 9:40:24 PM
Capacity management Even if it is a couple years away, looking forward to seeing how big data is applied to capacity management issues, and how it really matches up with SDN.
AVacek 10/25/2013 | 1:15:08 PM
Re: Any evidence of impact on top or bottom lines? I work with big data company Newfield Wireless. I wasn't able to join the chat, but in response to your question, I can show you two case studies we've done with customers who reported very specific returns on investment.

MetroPCS reported significant savings and said using our TrueCall platform helped increase engineering efficiency by more than 30% when used to resolve trouble tickets. Another customer, nTelos, reported a 40% savins in antenna modification. You can view the case studies at http://www.newfieldwireless.com/about-us/success-stories.


Sounds like it was a great conversation; sorry I missed it.
[email protected] 10/25/2013 | 9:22:12 AM
Any evidence of impact on top or bottom lines? Does anyone know if there is any evidence of a direct impact on revenues/margins of the inmplementation of big data/analytics strategies/technologies.


I know that Verizon is quite bullish about how much money it is saving in handset returns as a result of an implmentation in the US but do such instances ever get reported internally and externally (to investors) with a return-on-investment case?


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