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July 2013

Radio Access Network Data: Why It’s Become An Immensely Useful Analytics Source

interview with Neil Coleman

Radio Access Network Data: Why It’s Become An Immensely Useful Analytics Source

What is the most valuable data in telecom?  You and I could probably argue about that for some time.

And my question is somewhat ludicrous when you consider that no data is valuable in isolation.  Data sources buttress each other: CDR usage data is great, but if you lack a CRM to find phone number and customer details, how can you do postpaid billing?

Fully cleansed data is better than dirty data, right?  Not always, says IBM Fellow, Jeff Jonas.  A customer’s first name, for instance, may vary across data sources due to input errors, so dirty data is handy for isolating the correct name.

The value of telecom data sets also changes over time.  When circuit-based telecom was in full swing, Telcordia’s LERG database  was the gold standard for IDing network facilities in North American, but now that number portability is rampant, the LERG is less valuable  than it once was.

So when you consider mobile’s significance to the telecom industry today, the importance of the Radio Access Network (RAN) should loom very large indeed.

But how so?  Why has it become more critical?  And how is RAN data -- which lives in the air interface between the base station and the handset -- turned into mobile analytics to deliver a business benefit?  All these questions are answered with a gusto by Neil Coleman, Director of Global Marketing at Actix in the UK.

Dan Baker: Neil, maybe the best way to begin is to briefly explain the Actix business.

Neil Coleman: Dan, what you call mobile analytics is what has long been known as mobile network optimization which is where Actix’s expertise lies.  Mobile telecoms make up the majority of our customers, but the wireless network equipment providers (NEPs) need the RAN data we provide too.

Over the years we’ve worked with over 300+ mobile operators and more significantly we have 55 deployments of ActixOne, our enterprise-grade mobile optimization platform, being deployed at telcos like AT&T, Verizon, Vodafone, Telefonica, Softbank, and Telstra.

Our whole business is to help mobile operators optimize their radio access networks.  And that also happens to be the most complicated part of a radio network because there are no physical connections there and so you face great variability.  That’s what causes dropped calls when you’re driving down the highway or poor voice quality indoors.

ActixOne Archtecture

How important is RAN network optimization in the bigger scheme of mobile service quality?

Our data and operator experience shows that about 80% of all problems that impact the customer experience come from the RAN.  Now you can discount that as a statistic we compiled, but anecdotally it feels right.  After all, the RAN is what distinguishes a mobile operator’s business and there’s not an awful lot that can go wrong with fixed cables.

How do you analyze the RAN data to deliver value?

What Actix allows you to do is build a 24x7 view of subscribers.  We provide a complete analytical view of the RAN: we geo-locate every single subscriber on the network.  Then we combine that with network performance data, data from the cells, as well as data from external systems and engineering.

We also produce geographic heat maps that show where subscriber demand is, sliced by high value vs. low value subscriber.  They also highlight where the operator suffers from capacity or coverage problems -- and basically how the network is impacting the subscriber.

When we correlate RAN data with business data such as churn, complaints, or social media it means we can say, “Coverage is lacking in many areas, but these are the places you could focus on fixing first because these are the places where VIPs or active social media people hang out.”  In that way, we give RAN data a business focus -- not just an engineering one.

In the old days, network optimization was accomplished through drive-testing, basically driving trucks out into the network to measure radio signals with portable antennas.  Is that activity still going on?

Very much so.  In fact, 10 years ago this was our primary business.  Drive testing still goes on, but that market will never get any bigger and operators generally hate the idea of paying people to drive around the neighborhoods.

That was the impetus for developing our ActixOne platform which collects live network data.  Today, only a third of our business comes from drive-testing, though it’s still highly useful to the operator.  For instance, before an LTE network is actually deployed it’s important to have the operator accept the network, to say, “Before I pay you the first $2 billion in LTE installments, Mr.  Network Equipment Provider, I’d like some assurance that the network is up and running properly.”  Another major use is in competitive benchmarking.  Market research firms like Nielsen will put 3 or 4 handsets in a van and drive the country to be able to say: “Verizon’s LTE network is better than AT&T’s in Chicago, but AT&T’s is better in New York.”

Do you have trouble accessing the data?  I imagine the Ericssons, Alcatel-Lucents and ZTEs of this world all have their own proprietary protocols.

In this space vendor interfaces are largely proprietary.  To avoid the need for special hardware to be deployed we take data directly from these interfaces.  Supporting proprietary interfaces provides us with our unique IPR and simplifies our entry points into operators.  We work closely with both operators and vendors to ensure that we obtain the rich data needed to geo-locate subscribers.

Here’s the surprising thing: the mobile operator really doesn‘t know where you are when you make a cellular call.  They know what cell tower you’re on, but they need the kind of analytics Actix provides to narrow down the location to within 15 or 20 meters.  And having that level of accuracy gives you a tremendous advantage in knowing where to put more capacity, target marketing campaigns, and plan for future growth.

RAN Intelligence Dashboards

Tell me more about using the RAN data for business or customer experience value?

When they make optimization decisions, the operators worry about VIPs and key segments.

Recently a European operator was using ActixOne to improve a high value corporate customer’s network experience.  And in doing that they deliberately sacrificed network quality for other subscribers to be sure the corporate customer was getting his needs fulfilled.  Now this trade-off was minor.  It’s not as if other subs suffered greatly, but that’s where optimization is going because network capital investments are huge and you can‘t afford to give a high quality service to everyone.

Small cells are where the market is heading.  It’s a customer intimacy thing -- bringing the network closer to the customer.  Small cells offer tremendous advantages in Gigabyte capacity delivered, but they also have a very limited range, so site placement is critical.  On the back end, we analyze the traffic loads on a street by street basis.  The operators are very eager to gain access to that data.

Here’s the funny thing.  While most of us complain that mobile service is pretty bad -- especially in the middle of the business day -- the irony is that difficulty in delivering a consistent customer experience coupled with the ability to serve some subscribers better than others is what keeps mobile operators in business.  When someone provisions a cable to your home, your service is either up or down.  But in the RAN, quality varies greatly by location.  And that power to influence the customer experience puts mobile operators in a special realm.  If they were a fixed line carrier, their business would be as commoditized as everybody else’s.

It’s a great perspective, Neil.  But tell me: how do you measure the customer experience (CE)?  And what sort of CE improvements do operators get when you optimize a location.

Mobile operators love these analytics.  When we first show them their data in our solution their eyes light up.  Then we show them how by using these insights to drive optimization they can reduce network management activities by 50% to 80%.

We tune to specific geo-located regions so they can improve the experience of certain customers.  Typical CE improvements are anywhere between 25% and 75% for those customers.  Now those numbers come from measuring the KPIs before and after they optimize.

Actually there are many CE KPIs in mobile, but monitoring voice calls is one of the best because voice service is highly personal and you know the user will be disappointed if the signal is bad or the call is dropped.  For that reason, a dropped-call-rate KPI is a very good indicator of CE.

Other popular measures are things like maximum data throughput or average throughput.  Now the improvements I’m touting here are not based on some fuzzy customer satisfaction KPI with touchy-feely measures: these are solid, hard data metrics that operators are familiar with and use all the time.

Wow, Neil, you’ve really made this RAN area exciting.  Thank you.  And what’s your take on the growth prospects for your sector?

Thanks, Dan.  We’ve certainly seen a shift over the past two years as monitoring the customer experience has risen in importance.  Our business is growing solidly as the broader market discovers the value in our specialized niche.  Before we operated behind closed doors, but today mobile operators realize RAN optimization and analytics is a big asset that they can gain greater and greater value from.

Copyright 2013 Black Swan Telecom Journal

 
Neil Coleman

Neil Coleman

Neil Coleman, Director of Global Marketing at Actix draws on over 15 years of industry experience in marketing, product management and R&D roles at Actix, Micromuse and IBM.  Over the last 6 years he has been responsible for bringing Actix’s suite of mobile analytics and optimization solutions to market.

At Micromuse Neil was instrumental in developing their service management product line.  Starting from scratch it grew to over 30% of revenue within 2 years.  Prior to this he led the creation of Micromuse’s traffic monitoring solution.  At IBM he managed IBM’s SLA management portfolio, helping position IBM in an emerging field.   Contact Neil via

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