Spotlight on Big Data & Telecoms

How CSPs can generateprofits from their data

Should CSPs simplifytheir obbjectives?

Why CSPs should lose their fearand embrace the potential

Big data defined

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CONTENTS

21VANILLAPLUS

AUGUST/SEPTEMBER 2012

Well, yes they have, in the sense thatthey store, analyse and react to millionsof call detail records and have done fordecades. But no, in the sense thatthey're new to analysing unstructureddata. The more complex datasurrounding communications sessionsand in particular mobile datatransactions is unfamiliar, and they'relearning how to extract intelligence fromthe vast and valuable data they collectand store.

In addition, they’re wrestling withunderstanding the business case for bigdata investments and it is now clear thattwo stage approach will happen. To startwith CSPs will use big data internally toimprove their efficiency and theexperience they provide to theircustomers. That’s hard to define in cold,hard cash terms, although some havebeen brave enough to present anestimate: low single digit percentagerevenue increases are expected fromthese types of initiative. Remember, thatrepresents a huge amount of money inthe CSP sector.

Later things will get more interesting –and more complex. CSPs will use the

data they collect and analyse to sell onto others. Their data is of evident use butthere are substantial hurdles for them toovercome in order to do this in ways thathave a positive outcome. There are twomain barriers here: CSPs do not want todo anything that will alienate theirsubscribers. If data is sold on in a heavy-handed way to non-relevant companies,users will be angry and the attempt togain revenue could have the oppositeeffect as they leave. The second barrieris in what operators are legally allowedto do with this data. In Europe inparticular, CSPs are heavily regulatedand data protection initiatives areexpected to increase this burden ratherthan lessen.

Even though few have concrete ideasabout what big data will achieve forCSPs, it’s clear from the content of thisVanillaPlus Spotlight that there is enoughto justify investing in big datatechnologies and expertise right now.Latecomers may miss the boat whenthe wider revenue opportunities becomeapparent.

We hope you find the Spotlightinformative

21Introduction and contents

22Show me the moneyGeorge Malim goes in search of therevenues CSPs hope to gain frombig data deployments

24Who’s afraid of that big,bad data?Monica Ricci argues that it’s time forCSPs to lose their fear and embracethe potential of big data

26How big is big data?Carlos Pinto explains why now is thetime for big data

28Time for CSPs to take ownershipAmdocs explains why CSPs areuniquely postioned for big datasuccess

30Data can be big as well as cleverNick Booth says the big dataopportunity will only succeed if CSPssimplify their objectives

31Velocity, volume and varietyRani Goel explains what big datameans for CSPs

33Make sense – and cents– out of big dataMatrixx Software explains why real-time technology can provide theinsights CSPs need

Big data is approaching the peak of its hype cycle in the ITworld. The evidence is plain to see; big data is emblazonedin big letters on taxis in London, in airports across the worldand even in television advertising. But what does it mean forCSPs? Surely they've been handling big data for decades?

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VANILLAPLUS AUGUST/SEPTEMBER 201222

It’s easy to get carried away amid the hypesurrounding big data but in the end it only hasvalue to CSPs if it creates revenue for them.There’s certainly a groundswell of belief that this willbe the case but few are brave enough to putforward what effective usage of big data couldmean for CSPs’ finances.

One of the few prepared to venture a view is RanAchituv, head of the CTO office, product businessat Amdocs, who estimates that big data andanalytics could generate an incremental 3 to 5%increase in revenue over the next five years. Achituvthinks the strongest returns on big data investmentwill be in customer experience management. Hehighlights the opportunities that will come from

real-time decision making to optimise careoperations and deliver return on investment interms of deflecting and reducing call volumes.

“Although it’s right to pull out the need to put abusiness case together because investment isneeded here, it’s hard to give a generic figure,”acknowledges, Adrian Simpson, CIO at SAP UKand Ireland. “Big data is faster but so what? Thevalue comes from what you couldn’t do before andwhat new things that exist that didn’t previously.”

“There’s lots of data and people are scrambling totake advantage,” says Igor Sarenac, vice presidentof customer management at Convergys. “There areclearly areas where you can go. People get excited

Big data is being marketed on the promise that the insights it can providewill enable operators to generate both hard and soft revenues. They’ll beable to reduce churn and improve the customer experience fairly easily butcashing in on selling data to third parties presents more of a challenge,finds George Malim.

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23VANILLAPLUS AUGUST/SEPTEMBER 2012

about there being lots of data in CSPs but in reality,there was always lots available – not as much or asquickly as there is now. People have changed andnow are aiming at the right target but they have tofigure out how to do segmentation and howsuccess is measured here.”

Martin Wachutka, group director of operations atTelekom Austria Group, also thinks those softrevenue benefits are the immediate big dataopportunity for operators. “There are two mainrequirements that have to be fulfilled before youcan use big data within CSPs,” he explains. “Thefirst involves the whole ecosystem you have withinthe company to use and gain this data. Lots ofdata is available but the linkage of the different bitsand pieces is key and the knowhow for that israrely available. The second aspect is the mindset,the challenge of how we prepare the ground togain hard money. Big data in the past has been justfor internal purposes – we had no clue how tomake money out of it. To do so you have to thinkabout your business model.”

The first opportunity is relatively straightforward:“We can gain a lot internally with big data,” headds. “Money is coming from not losing customersso you save on customer retention and activationcosts but selling off data [to third parties] is notreally a big case yet – internal use for improving thecustomer experience is the case.”

Monica Ricci, director of product marketing at CSGInternational, agrees: “It is primarily about getting abetter understanding of customer behaviours butalso your own operational behaviours and areaswhere you can generate efficiencies,” she says. “Alot of those generate soft returns but the hardreturns come down to an opportunity to betteroptimise your offers. They will be more about thepackage of offers you can provide. Users will seethe value in there being one player in the entireecosystem that understands the sum of thepackage. This is where CSPs have the best chanceto get real and hard revenues from big data byfinding a way to be that provider.”

The hard case, of reselling insights from big data,hasn’t really emerged or crystallised yet. “I see theopportunities but I don’t think the market is matureenough,” adds Sarenac. “I see handset makersand MVNOs being interested but I don’t consider itthe mainstream of [big data] revenue.”

Wachutka points out that operators are limited bythe regulatory and legal situation in regard to their

data. They also won’t want to alienate theircustomers. “CSPs are really heavily regulatedunlike OTTs which are rarely regulated,” he says.“OTTs can do almost anything without fear but wewon’t get any relief on the legal aspect as Europe,in particular, moves even more towards dataprotection. The legal situation will become moreintensive and restrictive towards us than it has inthe past and that is destroying the case for sellingdata. On the other hand, we’re used to this – notmis-using data is in the genes of CSPs.”

Others think that as CSPs do more in M2M, smartcities and cloud services, big data requirementsbecome unavoidable and opportunities to monetiseemerge. “M2M, smart cities and cloud are threevery important opportunities for us and they arealmost indistinguishable in terms of how theyoverlap with big data,” says Gareth, head of newbusiness strategy at NEC Europe. “There is aprimary and secondary market for data, the endstep is the secondary market which involvesidentifying organisations that are really interested inthe data.”

Ken King, director of telco and media convergenceat SAS, identifies the hard and soft revenueopportunities. “Primarily it’s the better satisfactionof the digital consumer as their needs change andbecome specific to the individual user,” he says.“There are spreadsheets being developed withinCSPs where the soft revenue is being identified buta leap of faith needs to be taken that the consumerwill respond positively to initiatives in this area by aquantifiable amount. The new businessopportunites are on the other side of the ledgerwhere operators are trying to find new businessmodels to compensate for the loss of traditionalrevenues.”

Sarenac thinks there’s a case for big data andoperators don’t need to leap blindly into developingtheir capabilities. “Today CSPs already spendheavily on improvements to a system withoutknowing what that impact will be – that can becounter-productive,” he says. “Big data canprovide much more value.”

Ricci agrees that the case exists but thinks it needstime to mature: “Overall the investment in the pieceparts that go into big data is potentially larger soI’m leaning towards thinking the immediate revenueopportunity will not be that large,” she says. “It willbe more about the soft opportunities than the hardones. The benefits are real but it may not result in alarge step change.”

The hard case,

of reselling

insights from big

data, hasn’t

really emerged or

crystallised yet

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Big data is the natural consequence of the exponentialgrowth in communications-enabled devicesinterconnecting across ever-more powerful andubiquitous data networks. With Ericsson and othernetwork equipment manufacturers predicting manybillions devices of devices connecting with the networkover coming years, generating more frequent and morecomplex interactions, the number of anticipated datatransactions is truly staggering.

It is only natural that when Communications ServiceProviders (CSPs) think about big data, their firstthoughts, stemming from a traditionally network-centricviewpoint, are of the network. They see a need tomanage extreme growth in subscriber data usage,carefully manage investments in capacity, and processnetwork records more efficiently to ensure that revenueleaks are plugged and profits maximised.

But it’s not all about threats and challenges, and it’s notall about network management. Big data is a topic thatapplies to many industries, including manufacturing,utilities, retail and healthcare; verticals that are seeinggreat opportunity in the increasing capability to sharedata across advanced networks.

Industry analysts, trade and general media have madebig data a topic of the day, and not without cause;CSPs are facing strategic decisions concerning themanagement both of data volumes and of theopportunities and insights that may derive fromadvanced data analysis.

How big is big data?To get a feel for the ballooning growth of big datachallenges – and solutions – it may be helpful to try to putsome definitions and metrics around the phenomenon.

Starting with what big actually means, the frameworkused by many analysts, including Forrester and Frost &Sullivan, seems to work well. This describes data as big

if it demonstrates exceptional growth in dimensionsreferred to as the ‘Three Vs’ of big data – data recordvolumes must be growing rapidly, they need to becollected and processed with increasing speed (orvelocity), and they often represent a rapidly growingnumber (variety) of transaction types.

In reality, most big data scenarios are large in morethan one dimension. So broadly, big data is aboutmanaging rapidly growing volumes of increasinglycomplex transactions at accelerating speeds. And whilethere is no specific benchmark that determines whetherdata should be considered big, it seems to be widelyaccepted that big data sets are those that are growingat a rate of at least 40-60% annually.

Taking a more general view, McKinsey Global Institutedescribed big data in mid-2011 as “anything that isoutside of the operating parameters of the typicaldataset”.

Think about any data sets or operational processesthat are well managed in your business today. Projectyour data volumes doubling year on year, andcomplexity increasing substantially due to additionalservice information, location data or customerparameters. Imagine processes need to be executed inhalf the time, just to get through the volumes oftransactions. If this vision of the future highlights a pointwhere your systems, your operations or your ability touse customer data starts to buckle, then you’veidentified a big data challenge.

Importantly for the software industry, and anotherindicator of growth in interest, IDC predicts that themarket for big data solutions – which includes servers,storage, systems and services – across all globalindustries is growing at almost 40% annually. Theyforecast this market to reach nearly US$17 billion inspend by the year 2015, at a growth rate seven timesthat of the overall IT industry.

When CSPs think of big data their first thoughts are of the network and thechallenges associated with managing it. However, big data isn’t just aboutCSPs’ network management issues, it provides an opportunity to redefinehow they interact with customers, partners and across internaldepartments. Here, Monica Ricci argues that CSPs should lose their fearand embrace the potential of big data.

Monica Ricci:Volumes, velocity and

variety are the three

Vs at the heart of

big data


How big are the benefits?We know that big data is a processing challenge, butCSPs can gain encouragement from the way thattransmission and analysis of large amounts of serviceand customer data has greatly benefited otherindustries.

In the healthcare industry, the term big data isassociated with the growing digitisation of medicalrecords, x-rays and scans that can now be easilytransported and shared among networks of providers,practitioners, insurance carriers and patients. The endresult everywhere is faster and better-informeddecisions about treatment, resulting in better qualityhealthcare for the individual at lower cost.

In utilities, big data is largely associated with the rolloutof smart grid infrastructure that enables detailed meterdata to be constantly polled, providing insight intoenergy utilisation, and enhanced monitoring andcontrol, ultimately down to the appliance level.

CSPs across the globe have long been grappling withburgeoning network traffic, and the issues andimplications are well understood, if not necessarily wellmanaged. But the opportunities that extend from bigdata reach well beyond efficient management ofnetwork traffic. Analysys Mason recently commentedthat mobile operators stand to gain particularadvantage from the size of their subscriber base, theamount of data that they hold about their subscribersand the diversity of that data, including usage records,financial history, payment options and preferences,mobile commerce activity, and location-based datafrom their movements throughout the network.

Service providers can derive considerable actionableintelligence from these sources. In particular,aggregating raw data into comprehensive customerrecords, and applying sophisticated analytical tools, willempower CSPs to tailor content and services muchmore closely to customer preferences and improve theiroverall service experience.

What’s big for the CSP?Within a CSP environment, there are numerousprocesses that are both critical to, and derive benefitfrom, better data analysis. Improved understanding ofoperational processes related to customer service andfinancial management – including aged debt and churn

– help the CSP to further automate and driveefficiencies out of common tasks. But big data is alsoabout better understanding how and when a customeruses which services, enabling the CSP to better servethe customer and gain greater value from anecosystem where more and more content and servicesare coming from third parties. Customer records, usagerecords and billing records are now used not only bythe CSP, but are often by external parties and partners– generally in aggregate fashion. Data-driven insightscan lead to value-based price plans, high-performingadvertising models, an enhanced customer experience,and data-driven decisions that improve operationsacross the board in a CSP environment.

Just as we struggle to quantify how big is big, thepotential benefits of deploying a big data strategy arenot always easy to define. To take one example,however, McKinsey Global Institute, in that same 2011report, estimates that the application of location-baseddata alone will generate US$100bn of value to CSPs inthe next ten years. Such location data-driven servicesalready exist today, of course, but will greatly improve inthe future as the data that fuels them is betterprocessed, better analysed and better understood.

Head in the right big directionThe good news is that CSPs are already moving.Judging by the increasing frequency and urgency ofplanning sessions and project launches by our CSPcustomers, CSG has observed big data strategiesbecoming a greater priority for every service provider.But don’t feel alone if you don’t think your organisationhas taken steps to manage big, or even growing, data;many discussions are exploratory, looking for bestpractice examples from industry peers and vendors –these still feel like early days.

Ultimately, while processing and management of verylarge volumes of data is a technical challenge, theinsights that stand to be derived from that data offergreat potential to increase a CSP’s knowledge of itsbusiness, enabling the CSP to better direct its networkinvestment, improve the efficiency and lower the cost ofoperational processes, deepen its knowledge ofcustomers’ behaviours and needs and enhance thecustomer experience, increasing both loyalty andlifetime value.

The author, Monica Ricci, is director of product

marketing at CSG International


CSPs across theglobe have longbeen grapplingwith burgeoningnetwork traffic,and the issuesand implicationsare wellunderstood, ifnot necessarilywell managed


A N A L Y S T V I E W

Picture the scene: It’s 1956 and a 5MB hard drive isbeing loaded onto a plane – with a forklift truck. Thiswas the year that Doris Day was in the music chartswith her famous song ‘Que Sera, Sera (Whatever WillBe, Will Be)’. At that time, Doris Day did not have toworry about digitalised songs being distributed illegally:you would have needed an entire cargo plane full ofhard drives to transport the digital version of just one ofher albums, and a dozen men working for the wholeday just to copy it. Today, it only costs US$600 to buy adevice capable of storing all the music albums in theworld, and you can easily copy anything on it with theclick of a mouse.

This massive advance in device storage capacity andcomputing technology benefits many more peopleother than just the music pirates. The large-scaleutilisation of internal data is becoming critical tosuccessfully competing in many industries: the era ofbig data has begun. We believe that, of all industries,mobile telecoms has the most to gain from thisevolution, because of three assets: 1) the quantity ofcustomers it has access to 2) the amount of dataavailable and 3) the diversity of that data.

Firstly, the mobile market has very high levels ofpenetration, even emerging economies havepenetration rates of around 100%. Further, mobile is anoligopolistic industry, with typically just three or fourmobile operators in each country. This means that mostoperators have access to data from a large number ofcustomers, and multinational operator groups haveaccess to customers’ data from several countries.

Secondly, mobile operators have access to a largeamount of data per customer. Data is generated everytime a customer makes a call, navigates the web oracquires a product using their phone. Simply by havingthe phone connected to the operator’s network data isbeing generated, such as location, speed of movementand even biometric data.

Lastly, the diversity of data availability allows mobileoperators to achieve a depth of customer profilingbeyond that of other industries. Operators have thepotential to know a customer’s whereabouts, their

network of contacts, content preferences, wealth andproduct preferences.

In the not-so-distant future, mobile operators will alsobe able to generate revenues from the packaging andselling of this data. With traditional revenues such asvoice and SMS under pressure from web-basedservices and over-the-top (OTT) providers, and withmobile broadband now reaching its peak of profitabilityin developed economies, we expect big data to be thenext source of enhanced profitability. But in order tomove on to this stage, operators need to set up the basicprocesses, frameworks and technical infrastructuresneeded to capture and manipulate big data.

Before considering big data sales as a source ofrevenue, operators could use their data access toenhance internal processes, such as knowingcustomers’ value, what type of content they prefer andthe type of device they carry. Similarly, decisions on therolling out of networks and sales channels shouldconsider the location and demographic data ofpotential customers. Customer care departmentsshould use data to predict when a customer is at risk ofchurn and act upon it. Customer data will also allowoperators to reduce their losses from customer ordealer commission fraud.

Large European operators, such as Orange, Vodafoneand Telefónica have, for several years, used the powerof data analysis to improve their managementdecisions. In general, Middle East and Africanoperators are still in the early stages of theseprocesses. There is therefore enormous potential toincrease revenues and margins by enhancing thecustomer experience using data analysis to improveinternal processes.

The capacity for data capture, storage and analysis hasincreased significantly in the last decade, and themobile industry has a significant opportunity to evolveprocesses and methodologies to take advantage.‘Whatever will be, will be’ might have been anapproach in 1956, but we now have the data andtechnology to plan and impact customer value withmuch more direction.

Concepts of big data have evolved as what constitutes big has developed.Big data is applicable to many industries but mobile CSPs could have thegreatest opportunity, explains Carlos Pinto a manager with analyst firmAnalysys Mason.

Carlos Pinto:Enormous potential

to increase revenue

and margins

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About


Take a look at any statistic today in thecommunication industry and you’ll soon find yourselfswamped by some really big numbers. IDC predictsthat worldwide smartphone sales will total over 680million units in 2012. Cisco reported that global mobiledata traffic grew 2.3-fold in 2011, more than doublingfor the fourth year in a row at 597 petabytes a month.In addition, average smartphone usage nearly tripledin 2011 while mobile video traffic exceeded 50% oftotal traffic for the first time. And it’s not just traditionalcommunication players that are reporting suchnumbers. Skype reported that 300 million minutes ofSkype video calls are made every day while WhatsApprecently reported a new daily record of 10 billionmessages.

Our ability to consume services shows no sign ofslowing down and the services offered bycommunication companies have never been in higherdemand. This immense growth means dealing withunprecedented quantities and types of data, whethera call, text message or data session. On the onehand, this data needs to be processed, monetisedand managed in the most cost efficient way possible.Large service providers are already persisting severalbillion usage records per day making it the mostexpensive component in the storage and databasedomain. On the other hand, big data represents agreat opportunity for service providers to learn morethan ever about the ways their customers use theirdevices and services, and put this knowledge to workcreating personalised, differentiated services.

Big data, big opportunitiesWith the exponential growth of smart connecteddevices, ubiquitous broadband and advanced

applications, it’s not just the quantity of data that haschanged but also the nature of the data. Most if not allusage data in the telecoms industry has traditionallybeen structured, transactional data. This type of datais also not necessarily real-time and could be hours,weeks or in some cases months old. Today’stransactional data has been supplemented with real-time data fed from a variety of sources such as thesocial networks, location based services, deviceapplications and even unmanned devices.

The constant influx of rich, real-time data means thatservice providers are uniquely positioned to learn more than ever about how, when and why customersuse network services. Over the top (OTT) players likeAmazon, Facebook and Google have long understoodthe power of consumer data and have used it tointroduce contextualised, personalised services intothe market place. Service providers are now alsorealizing the power of big data to transform theircustomer experiences and the need to manage,analyse and act on data in real-time. More focused,contextualised offers will allow service providers tocombat churn, drive satisfaction and potentially slowthe erosion of core network services to non-traditional players.

But big data comes at a price. Service providers facea growing challenge in cost-efficiently scaling up ITinfrastructure and operations to cope with big data.Despite falling IT infrastructure costs, the sheer paceof today’s growth is threatening to push costs higherand margins lower, creating an ever widening gapbetween the two. Service providers also need a moreefficient and scalable reference architecture thatmakes it simpler, quicker and less expensive to scaletheir capacity to meet demand.

Although much of their data has been structured and gatheredretrospectively, CSPs’ transactional data has now been supplementedwith real-time data fed from a variety of sources such as the socialnetworks, location based services, device applications and evenunmanned devices. The constant influx of rich, real-time data means thatthey are uniquely positioned to learn more than ever about how theircustomers use their services, writes Jonathan Shmukler.

Jonathan Shmukler,Product marketing

director in Amdocs

revenue management


Big data, big implicationsDealing with big data has several significantimplications for service providers. One of the most pressing issues is the massiveincrease in event inflow which is being driven byincreased data service usage as well the move to real-time charging across all customer types – prepaid andpostpaid. Service providers must find ways to costefficiently rate, store and manage the billions of networkevents that they receive on a daily basis.

While traditional approaches to IT infrastructurescalability are making inroads into reducing costs andoperational efficiencies, the sheer pace of growth iscreating an ever widening gap threatening to pushcosts higher and margins lower. The near exponentialgrowth means that service providers need to adoptnew technologies as well as a more efficient andscalable reference architecture that makes it simpler,quicker and less expensive to scale capacity to meetdemand.

The communication industry is actively researching andadopting several new solutions that enable a paradigmshift in scalability such as the use of open sourcedatabases running on small, commodity servers withdirectly attached storage capable of almost unlimitedscalability. Examples include the use of HBase and theApache Hadoop Big Data Platform.

In addition, service providers must look towards leanoperations that do not increase with system footprint.Many of the new technologies that aim to addressscalability and hardware/software cost reduction arebuilt on virtualised machine architecture. It is crucial tohave an operational layer that is agnostic to the numberof machines ‒ zero or marginal increase in operationswhen the number of machines grows. As such, theoperational layer requires tools, processes andautomation to handle any number of hosts efficientlyand, from a central administrative viewpoint, with little orno increase in spending when adding additional hosts.

The second implication is how service providers use bigdata in order to create a new generation of products,services and customer interactions. According toGartner, big data requires “new forms of processing toenable enhanced decision making, insight discoveryand process optimisation." CSPs are realizing that they

still have a lot to learn about managing, analysing andacting on an ever growing set of structured andunstructured data.

In terms of truly owning big data, service providersneed to take a holistic approach to businessintelligence and analytics moving all the way fromdescription to prescription. In other words, whenprocessing data service providers should be striving toanswer four key questions:• What happened on the network?• Why did it happen?• What is likely to happen next?• What should we do about it?

Providing these answers will require a combination ofnext generation analytic and decision makingcapabilities coupled with expertise and businessprocesses. Rather than shying away from thecomplexities of big data, service providers need toembrace the wealth of new information that hasbecome available and learn how to act on it – in real-time. By combining transactional, historical informationwith real-time unstructured data service providers canlook to deliver instant, contextualised offers andservices across devices and networks.

Take for example the ability to suggest a specificservice to a customer based on their location andpropensity to use a specific service. Perhaps a user islooking up information on a music concerts in their areaand they regularly listen to a specific jazz radio stationonline. A service provider could then alert them to thefact that a jazz band is performing in the area and offerthem a preview of the bands music in addition to theability to purchase tickets.

Another example could be advising a user who usesdata intensive applications such as Instagram orPandora to switch to Wi-Fi to avoid data overagecharges. The notification could be sent if the user is inthe vicinity of an available Wi-Fi connection or if theirdata plan is about to expire, or a combination of both. While big data still presents several challenges it is clearthat the potential value to service providers isenormous. By adopting a holistic strategy to big datatechnology as well as next generation intelligence andanalytics tools service providers can become moreproactive in addressing their customers’ needs as wellas guaranteeing the highest levels of network service.

Compare today's CSPs with the airline industry,where competition for customers and the cost ofinfrastructure have both been so high that everyunit of capacity is catered for. That's why no twoairline customers ever seem to pay the same priceand empty seats are minimised. They have useddata to evolve flexible pricing schemes and created

an elasticity of supply that manipulates a demandresponse for every plane seat.

To be fair, CSPs have never really had to bother.The incentive to mine data in order to fine tuneservice was never there. There was a vastaddressable market of subscribers who pretty

CSPs have always had silos of information on their customers and their assets – somemight think it's a shame they never did anything with it. Big data provides thatopportunity but it will only work if CSPs simplify their objectives, writes Nick Booth.

BIG DATA INTELLIGENCE

Gordon Rawling:Big data needs

algorithms to

optimise supply and

demand


Continued on page 32

Sponsored by

B I G D A T A


What is big data? There are many definitions andopinions, but most agree that it has three maincharacteristics, namely volume, velocity and variety. Arecently published Gartner research report offers thefollowing definition: Big data is high-volume, high-velocity and high-variety information assets thatdemand cost-effective, innovative forms of informationprocessing for enhanced insight and decision making”.

Communication service providers (CSPs) have allthree attributes in plenty, and they’ve been investing inmanaging, safeguarding, and storing this data. Theopportunity, however, lies in getting this data in thehands of the users who can analyse it easily andmake better-informed decisions. While a day oldsummarised data in a warehouse may be efficient andacceptable for managed reporting on routineinformation, it’s not suitable for fast-changing andunanticipated management information needs.

We are seeing a fundamental shift in a new analyticsinfrastructure paradigm that enables real-time visualdiscovery of large amounts of data enabling businessusers to find critical information in a timely manner.

CSP traditional revenues are declining, they arelooking to fill this gap with new sources of revenue.Leading providers are moving to a model to: Createthousands of offers for very targeted marketsegments, Analyse data in hours, and Innovate andincrease campaign yield by making changes to theoffers quickly and effectively.

CSPs generate massive amounts of data every day.

Now, with machine-to-machine (M2M)communications, this volume is ready to growexponentiall y. CSPs need to analyse this big dataquickly and effectively and are turning to the newanalytics infrastructure with in-memory computing tocrunch the data in seconds rather than days. As a result,they can do what-if? analysis, model data and runsophisticated data mining and forecasting algorithms.

Hear directly from T-Mobile how analysing very largeamounts of data in near real time enables them toinnovate quickly and develop entirely new businessmodels.

Research by Aberdeen Group into BusinessIntelligence (BI) found that 65% of business decisionmakers face a shrinking decision window, making itimperative that business users have self-serviceaccess to the data they need to make decisions.

If a picture is worth a thousand words, then why notmake data discovery visual? Visualisation providesrapid access to data in a format that’s easy forbusiness users to digest and use. According toAberdeen’s research, managers that make use ofvisual discovery tools are 10% more likely than theirpeers to access information they need in time toimpact decision making.

The value for CSPs lies not in big data itself but theinsights they can get about their subscribers,operations and partners with the right visualisationand data discovery tools that allow decision makers tomake fact-based decisions. The ability to analyse verylarge amounts of data at line item detail, quickly andeffectively is driving innovation in terms of businessmodels not possible before and that’s why there is somuch excitement surrounding big data.

Big data is going through a hype cycle in which many definitions and opinions haveemerged regarding what it constitutes. Here, Rani Goel defines big data and explainsthe business drivers it presents for CSPs

The author,

is global seniordirector oftelecomsindustrymarketing forbusinessanalytics at SAP.

3) Business-user access to data.

1) Real-time information access.

2) Ability to analyse large amounts of data.

Rani Goel


much took what was offered to them. Why spendmoney on systems you don't need? That's allchanging now, says Bob Machin, director ofproduct marketing at CSG International, but it'staking time for the CSPs to get used to. “Thisindustry is still getting accustomed to the idea ofsaturated markets, downward pressure onrevenues and margins and the other unpleasantfacts of life in a mature industry,” says Machin.

The new market conditions have reallyconcentrated the mind on revenue maximisation,he argues. The onset of 4G and the change it willcatalyse in supply and demand, will only make itmore imperative to emulate the airlines's skills incapacity management.

As CSPs launch their mobile IP networks, these4G offerings will only spoil subscribers. Instead ofbeing grateful for all the bandwidth and the raft ofnew services, they are likely to get greedy anddemand even more. Pretty soon they'll becomplaining about the lack of coverage and theslow speeds and threatening to jump ship for thecompetition. Big data could be used to help CSPscompete – if not on pricing, on the allocation ofresources.

“Capacity will always be a chasing game in termsof demand,” says Gordon Rawling, OracleCommunications' marketing director. “CSPscan't tie up capital in advance, until they know thepatterns of usage, so big data needs algorithmsthat can optimise the supply and demand ofcapacity and automatically fine tune the network.”

In theory, big data can act as a sort of automatedtraffic manager, the better to maximise the qualityof network service. If, say, an end user brings aparticularly popular cell to a standstill, bydownloading a film onto his iPad, the network canrespond with a surprisingly subtle piece ofcustomer relations management. The machinery ofthe network will send a message, acknowledgingthat the subscriber is downloading a film, and strikea bargain with them: get a higher quality version ofthe film, if they download at a quieter time.

That is the theory, but whether CSPs can pull thisoff is another matter. The problem with workingwith big data – as in unstructured information thatcomes in the form of social media, images,

messaging and video – is that it is vast and vague.Analysing sentiment, in real time, is incrediblyambitious, and probably too much to ask of analgorithm writer at this time.

“For data to have meaning, it is vital to findrelevance and make sense of it,” says Mike Foster,senior director of infrastructure services atQlikView. “CSPs don't have the platforms ortechnology to analyse it, so they ignore it.” But, heargues, partners can offer flexible, associative, self-service analysis at the speed-of-thought. Well hewould.

Social media plays an increasingly important role ina CSP's complex big data sets, insists AdrianSimpson, chief innovation officer at SAP.“Customers turn to their platform of choice to shareinformation about themselves and opinions ofproducts and services. Sentiment analysis makesvendors respond to customers quickly,” saysSimpson.

Big data seems to offer so many possibilities andthere's such a myriad of technologies, it could beone of those technologies that promises everythingand delivers nothing. Unless its users are veryfocused, argues CSG International’s Machin. Whatinsights are we missing out on? “The truth is wedon't really know. We've been here before withdata mining and warehousing techniques,” he says.

The lesson is to reign in your ambition and makethe most of what's already available. “We’ve beendetecting an aversion to open cast data mining,”adds Machin. Trawling trillions of gigs of data fornon-specific patterns leading to possiblecompetitive advantage hasn't worked in the past.

There's more interest among CSPs in appliedanalytics – taking existing business functions andasking the question ‘what more could theoperational data tell us?’

So, initially, big data service suppliers can runmediation principally to feed billing and revenuecapture. That's a start. Building on that, given whatthose transactions represent, CSPs could learnmore about customers’ patterns of usage.

It's a long learning curve.

Adrian Simpson:Customers will turn

to their platform of

choice

Bob Machin:Industry has an

aversion to open cast

data mining

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Historically, Call Detail Records (CDRs) were used in theoffline environment as a source for analytics. MostCDRs contained information about one subscribercalling another with basic information such as Anumber, B number, length of call, and so forth. CDRswere stored in a data warehouse where analysis couldbe done to generate models about network traffic andsubscriber usage patterns.

Today, with smartphones and tablets, subscribersspend the majority of their time using data services –not voice. The amount of event detail records (EDRs)this produces not only far exceeds CDRs, but thecharacteristics of data sessions and the informationcontained within them has also changed dramatically.This creates a new set of challenges for operators topull meaningful insight and analytics out of traditionaldata warehouses.

Smart devices are creating a vast amount of small datasessions, in fact more than half of all data sessions areless than 1 MB. There is a tremendous amount of valuelocked up in this data which is not being realized. Butwith the right tools in place, operators can get insightinto network usage data before the EDRs even hit thedata warehouse.

MATRIXX Insight provides real-time event processingtogether with an Algebraic Decision Engine to processall network traffic while tracking and aggregatingsession information. Examples include understandinghow much network capacity is consumed by specificOTT traffic, application usage trends by device type,average data consumed per tariff plan, or droppedsessions per region.

The concept is simple. Meter and track any type ofinformation available from EDRs or network probes,and aggregate this data instantly as it comes off thenetwork. Organise, evaluate, aggregate and transformdata into a manageable set of information in real-time.Track information in configurable slices of time and byconfigurable parameters such as subscriber segment.

Combining this ability with high performance, efficientreal-time processing allows operators to turn rawnetwork event data into meaningful, aggregatedinformation as soon as it happens. Parallel-MATRIXXTechnology provides the most efficient real-timeprocessing available, processing billions of events aday on a small set of commodity blade servers.

Quickly gaining this type of insight about how thenetwork is being used gives CSPs more leverage withOTT players to negotiate partnerships. CSPs can alsooptimise network operations by understandingsubscriber usage trends and proactively planning forthem. Most importantly, CSPs can create new pricingstrategies by understanding subscriber usage patterns.The drive to capitalise on big data will be achieved bythe use of real-time technology which is scalableenough to handle exploding session data, aggregate itand add intelligence in a cost-efficient manner. MATRIXXSoftware reduces the traditional cost barrier for CSPsto manage all this data in real-time, making the analysisof big data affordable, implementable and profitable.

Mobile operators are suffocating under a wave of big data created bysmartphone traffic and chatty applications. But new real-time technologycan provide just the oxygen they need to thrive in this environment.

A D V E R T I S E M E N T F E A T U R E

What operatorswill see usingMATRIXXSoftware’sapproach tooperatorbalances

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