Email a colleague    

May 2013

Leveraging the RA/FM Platform to Deliver Business Insights to Finance & Marketing

Leveraging the RA/FM Platform to Deliver Business Insights to Finance & Marketing

You can never rest on your laurels in this business.  People in revenue assurance, fraud management, and similar staff roles know full well they exist to support the business.

And while the business may be quite pleased with the revenue leaks you found yesterday, yesterday was yesterday.  So if you expect those same internal business customers to remain happy, you must listen to their current needs, then deliver accordingly.

For example, many of the professionals using our RA and fraud management tools have told us their internal customers are making urgent requests for up-to-date analytics data to help them grow the business, not just protect revenue streams.

Why are they turning to RA/FM?  And why are they doing so when those operators already have a data warehouse (DW)?  Two reasons: faster response and superior integration.

Faster response is not simply a function of processing speed, but also platform flexibility.  Being an IT-controlled platform, data warehouses are constrained by lots of factors: IT’s priorities, IT’s workload/ internal processes — even the data sources IT loads.  By contrast, an RA/FM platform can be tuned to the needs of a small user group and quickly support new data sources.  This greater flexibility often translates to a faster overall response — a key factor in dynamic markets like mobile where time equals money.

Now ideally a DW provides a fully integrated set of enterprise data for analysis -- the so-called “single version of the truth”.  However, in practice, most service providers have multiple DWs and data marts each using different keys, making it hard to achieve that integrated view.  An RA and FM implementation, though, already has a unified view of relevant data in a platform already paid for.  So adding the ability to do real-time analysis makes expanding the role of an RA/FM a compelling choice.

Now you can bet that we at cVidya were excited to hear that our customers wanted us expanding the uses of our software platform.  Yet we knew that if we expanded the product suite we needed to be very careful.  We did not want to simply bolt on a generic business intelligence (BI) tool that requires the customer to figure out what data sources, reports, dashboards, and KPIs to pull together.

Our strong suit over the years at cVidya has been to simplify the analysis problem for our customers by embedding intelligence in our products.  So the approach we settled on does exactly that -- it delivers use case-specific functionality in a new cross-product layer that cuts across all our software applications.

A Cross-Product, Value Enhancement Layer for Finance & Marketing

We think this cross-product layer approach greatly enhances the value of the existing RA/FM platform by allowing it to serve many other use cases.

Our layer is called cVidya Insight™ and it resides in each of our products.  Our Revenue Assurance solution, MoneyMap has its own analytical tools and so is our Fraud Management solution, FraudView.  In addition, for customers who have multiple product offering we can offer a cross product analytical view that utilizes views and insights from different sources and products.

Cross-Product Layer Architecture
in RA/FM Platform

Cross-Product Layer Architecture
Source: cVidya

The beauty of layering is that the extensive extracting, loading, normalizing and enrichment of data required for RA/FM doesn‘t have to be repeated.  It’s ready to immediately serve up additional insights to the CFO (in uses such as profit/ margin assurance) or to equip marketing with the vital info it needs.

And because the dashboards, reports and KPIs are productized to support particular lines of business, the operator doesn‘t have to figure out what analysis and insights he needs because they are built in.  This pre-configuration is what separates this approach from that of a general purpose BI tool.  We need to stress here, that customers can still customize and create new ones per their specific demands.

Monitoring and Growing LTE Service

Perhaps the best way to illustrate how a cross-product intelligent layer delivers value is to explain how we are using it in the new service area of LTE.

Monitoring and actions in LTE begin on the risk side.  The CFO is alerted to problems over margins, exposure to revenue risks, etc.  And since LTE is a relatively new line of business, the exposure and risks can be high as revenues are ramping up.  The margins too will not be high in the beginning so all of these things must be continuously monitored.

Dashboard for Cross-Product Layer
in RA/FM Platform

Dashboard for Cross-Product Layer Architecture
Click here to see more dashboard examples.

Now it’s here where a fraud management platform comes in particularly handy in identifying customers who are taking unfair advantage of their price plans.

Once the fraud management team identifies the users abusing their data price plan, then they can use this info to define next steps with these customers such as getting those customers on alternative price plans/offering.  Rather than cut service off or limit their quality of service, the remedy here is often to make an offer an increase bandwidth in return for agreeing to move to a more profitable arrangement.

At the same time, the revenue assurance team is analyzing different aspects of LTE services not only for the purpose of identifying revenue leakages but also in terms of profitability for different categories, such as price plans, sub services and 3rd parties costs and revenues, resulting in flagging certain LTE services for low margins.  A thorough segment analysis is performed to understand how customers are consuming data traffic, monitoring the usage of OTT applications as well as verifying bills and checking settlement processes.

Delivering Greater Value to Marketing

The marketing department seems to be especially keen on exploiting the RA/FM’s data gold mine, so we had several great discussions with marketing teams to understand their needs.

In fact, we developed a couple of different products for marketing.  One of those integrate 3 pre-defined use cases in the areas of retention, price plans, and LTE/3G data, each with its own clear set of drills downs and dashboards.

So on the LTE dashboard; marketing can view the actual usage of customers -- how much data they are using per month, from which locations, what types of OTT and other content they are using — and also how much money they are generating.

This view was created by combining demographic and financial information so marketing can understand customer patterns and behavior.  The marketing offer model goes one step further to calculate the next best offer/action for the individual customer, which can get complicated especially when the customer is using various devices or is billed off a shared data price plans where the usage or minutes of family members are aggregated.

Conclusion

We are certainly in the early stages of this market trend calling for a much wider use of the revenue analytics platforms designed primarily to protect revenues.

The good news is that our layering strategy will allow RA and FM departments to better utilize their current deployment and maximize the potential of their RA and FM systems as well as serve their demanding internal clients in marketing and finance.

It’s about combining applications and data sources from many directions.  And in many cases, I’m sure, the layers will need to communicate across applications developed by other solution vendors and internal shops.

In the last 12 years our customers have enabled us to accumulate significant domain expertise on the business protection side of analytics.  Yet going forward, we realize that success also hinges on our ability to blend both business protection and business growth analytics in ways that take our customers in whatever direction they need to go.

Copyright 2013 Black Swan Telecom Journal

 

About the Expert

Amit Daniel

Amit Daniel

Amit Daniel is Executive Vice President of Marketing and Business Development at cVidya.  Prior to joining cVidya, Amit worked in Starhome for the last 12 years as VP Marketing & Business Development and prior to that as Director of Product Management in which she was responsible for various product offerings and roadmap throughout the product lifecycle.

Ms.  Daniel brings to cVidya rich market and product experience from Golden Lines, an international telecommunication provider, where she served as Director for International Carrier Relations for America, Asia and Western Europe.  She holds a B.A and an MBA in International marketing and finance.   Contact Amit via

Related Stories

  • Bogus to Delete interview with Tom Erskine
  • Leveraging the RA/FM Platform to Deliver Business Insights to Finance & Marketing by Amit Daniel — Carrier professionals using RA and fraud management tools are getting requests from internal customers who want the role of RA/FM platforms expanded to deliver up-to-date analytics data for finance and marketing purposes.  This article advocates a cross-product layer to serve such broader use cases.  The effect would be to transform the existing RA/FM platform into a combined business protection and business growth analytics engine.

Related Articles

  • Will Real-Time Decisioning Save Big Data Analytics from Overblown Hype? interview with Tom Erskine — Telecom analytics is more than just collecting and analyzing data.  It’s also about taking action — correct action — often in real-time and across a complex provisioning environment.  In this interview you’ll hear how next best actions are creating value in retention and upselling through a more flexible, business-process driven approach.
  • A Big Data Starter Kit in the Cloud: How Smaller Operators Can Get Rolling with Advanced Analytics interview with Ryan Guthrie — Medium to small operators know “big data” is out there alright, but technical staffing and cost issues have held them back from implementing it.  This interview discusses the advantages of moving advanced analytics to the cloud where operators can get up and running faster and at lower cost.
  • The Customer Engagement Era: How Personalization & Backend Integration Leads to a Richer Mobile Biz interview with Rita Tochner — How does a mobile operator move its subscribers to higher levels of spending and profit?  Fierce competition, social media scrutiny, and the high cost of new networks all conspire against these goals.  In this interview, however, you’ll learn how engaging better with customers, getting more personal, and being more sensitive to their individual needs is the path forward.
  • Telecoms Failing Badly in CAPEX: The Desperate Need for Asset Management & Financial Visibility interview with Ashwin Chalapathy — A 2012 PwC report put the telecom industry on the operating table, opened the patient up, and discovered a malignant cancer: poor network CAPEX management, a problem that puts telecoms in grave financial risk.  In this interview, a supplier of network analytics solutions provides greater detail on the problem and lays out its prescription for deeper asset management, capacity planning and data integrity checks.
  • Batting for More Churn Reduction and Revenue Assurance Home Runs interview with Peter Mueller — What’s it like to transform an IT shop to big data and cloud?  In this interview, the CTO of a boutique revenue assurance explains how his firm made the leap.  He shows how project-oriented programs and working with carrier customers to explore RA and churn reduction “hunches” is where much of the action is.
  • History Repeats: The Big Data Revolution in Telecom Service Assurance interview with Olav Tjelflaat — The lessons of telecom software history teach that new networks and unforeseen industry developments have an uncanny knack for disrupting business plans.  A service assurance incumbent reveals its strategy for becoming a leader in the emerging network analytics and assurance market.
  • From Alarms to Analytics: The Paradigm Shift in Service Assurance interview with Kelvin Hall — In a telecom world with millions of smart devices, the service assurance solutions of yesteryear are not getting the job done.  So alarm-heavy assurance is now shifting to big data solutions that deliver visual, multi-layered, and fine-grained views of network issues.  A data architect who works at large carriers provides an inside view of the key service provider problems driving this analytics shift.
  • The Shrink-Wrapped Search Engine: Why It’s Becoming a Vital Tool in Telecom Analytics interview with Tapan Bhatt — Google invented low cost, big data computing with its distributed search engine that lives in mammoth data centers populated with thousands of commodity CPUs and disks.  Now search engine technology is available as “shrink wrapped” enterprise software.  This article explains how this new technology is solving telecom analytics problems large and small.
  • Sharing Intelligence, Services, and Infrastructure across the Telecom Galaxy interview with Gary Zimmerman — The telecom industry is an industry of sharing.  In fact, the rise of mobile broadband is driving a greater reliance on real-time intelligence, services trading, and infrastructure exchange.  In this article, a leading info exchange provider explains the value of its services portfolio and points to other interoperability and sharing ideas under development.
  • Data Monetization: Why Selling Intelligence is a Hot New Revenue Stream for Mobile Carriers interview with Joe Levy — Data monetization is a revenue dream come true for mobile carriers: a highly profitable sideshow where the carrier analyzes and sells data it already collects for other purposes.  In this article you’ll learn how operators monetize their data through use cases in corporate advertising and media branding.
  • Harvesting Big Data Riches in Retailer Partnering, Actionable CEM & Network Optimization interview with Oded Ringer — In the analytics market there’s plenty of room for small solution firms to add value through a turnkey service or cloud/licensed solution.  But what about large services firms: where do they play?  In this article you’ll learn how a global services giant leverages data of different types to help telcos: monetize retail partnerships, optimize networks, and make CEM actionable.
  • Raising a Telco’s Value in the Digital Ecosystem: One Use Case at a Time interview with Jonathon Gordon — The speed of telecom innovation is forcing software vendors to radically adapt and transform their business models.  This article shows how a deep packet inspection company has  expanded into revenue generation, particularly  for mobile operators.  It offers a broad palette of value-adding use cases from video caching and parental controls to application-charging and DDoS security protection.
  • Radio Access Network Data: Why It’s Become An Immensely Useful Analytics Source interview with Neil Coleman — It’s hard to overstate the importance of Radio Access Network (RAN) analytics to a mobile operator’s business these days.  This article explains why the RAN data, which lives in the air interface between the base station and the handset --  can be used for a business benefit in network optimization and customer experience.
  • Back Office Streamlining to Enterprise Support: The Many Flavors of Wireline Analytics interview with Tom Nolting — Mobile analytics gets plenty of press coverage, but analytics is just as crucial for wireline operators.  In this article, a billing VP at a leading wireline operator discusses several diverse uses of analytics in billing, enterprise sales/retention, and network partner margin assurance.
  • Analytics Biology: The Power of Evolving to New Data Sources and Intelligence Gathering Methods interview with Paul Morrissey — Data warehouses create great value, yet it’s now time to let loose non-traditional big data platforms that create value in countless pockets of operational efficiency that have yet to be fully explored.  This article explains why telecoms must expand their analytics horizons and bring on all sorts of new data sources and novel intelligence gathering techniques.
  • B/OSS Mathematics: The Quest to Analyze Business Problems & Drive Operating Decisions interview with Matti Aksela — Analytics is the glory of mathematics brought to practical use.  And in telecom, analytics has merely stratched the surface of its full potential.  In this article, you’ll learn how machine learning is being combined with the power of CDR number crunching to optimize mobile top-ups, control churn — and in the future, help telecoms make critical network and operating decisions.
  • Leveraging the RA/FM Platform to Deliver Business Insights to Finance & Marketing by Amit Daniel — Carrier professionals using RA and fraud management tools are getting requests from internal customers who want the role of RA/FM platforms expanded to deliver up-to-date analytics data for finance and marketing purposes.  This article advocates a cross-product layer to serve such broader use cases.  The effect would be to transform the existing RA/FM platform into a combined business protection and business growth analytics engine.
  • A Mobile Marketer Service: Bridging Personalization & B/OSS Flowthrough interview with Efrat Nakibly — Marketing analytics is a prescriptive program for driving  actions such as sending a timely promotion to a mobile subscriber.  But completeness demands that you also be able to provision that treatment, qualify the promotion, and keep billing fully in the loop.  This article shows how a managed services program can deliver such an end-to-end process and manage customer life cycles on a one-to-one basis.
  • Science of Analytics: Bringing Prepaid Top Ups & Revenue Maximization under the Microscope interview with Derek Edwards — Prepaid subscribers are the customers that carriers know the least about.  The operator is not interacting with prepaid customers on a monthly basis.  You’re not sending a bill, nor do you have detailed profiles on these customers, especially in the developing world where customers are buying SIMs at a grocery store.  This interview explains how contextual marketing meets the unique analytics challenge of prepaid customers.
  • Connecting B/OSS Silos and Linking Revenue Analytics with the Customer Experience by Anssi Tauriainen — Customer experience analytics is a complex task that flexes B/OSS data to link the customer’s network experience and actions to improve it and drive greater revenue.  In this article, you’ll gain an understanding of how anayltics data needs to be managed across various customer life cycle stages and why it’s tailored for six specific user groups at the operator.
  • Profitable 3G: China’s Mobile Operators Monetize Networks with Retailers & Partners interview with Kevin Xu — Mobile operators are at the center of explosive growth in wireless services.  But to exploit this opportunity requires IT ingenuity and a broader view on how the mobile user can be served.  In this article you’ll learn the innovative techniques Chinese operators use to monetize 3G networks via analytics and partnerships with retailers, social networks, and advertisers.
  • Customer Analytics: Making the Strategic Leap From Hindsight to Foresight interview with Frank Bernhard — Are your company’s analytics programs scattered?  Is there a strategy in place for customer analytics?  This interview with a leading telecom analytics consultant explains why strategy and planning around the analytics function is crucial to getting your money’s worth.  Topics discussed include: hindsight vs. foresight; an advanced analytics program; and the interface sophistication required to support high end vs. low end analytics users.
  • Meeting the OTT Video Challenge: Real-Time, Fine-Grain Bandwidth Monitoring for Cable Operators interview with Mark Trudeau — Cable operators in North America are being overwhelmed by the surge in video and audio traffic.  In this article you’ll learn how Multi Service Operators (MSOs) are now monitoring their traffic to make critical decisions to protect QoS service and monetize bandwidth.  Also featured is expert perspective on trends in: network policy; bandwidth caps; and  customer care issues.
  • Analytics Meditations: The Power of Low-Cost Hardware and the Social Network Within interview with Ken King — Analytics didn‘t arrive yesterday.  Data warehousing and BI have been in the telecom vocabulary for twenty-five or more years.  In this interview, you’ll gain a perspective on why “big data” changes the game and why social network (or social circles) analysis promises the next level of insights.  Other interesting topics include: segmenting the analytics market, engaging with carrier clients, and upgrading from older- to newer-style methodologies.
  • LTE Analytics:  Learning New Rules in Real-Time Network Intelligence, Roaming and Customer Assurance interview with Martin Guilfoyle — LTE is telecom’s latest technology darling, and this article goes beyond the network jargon, to explain the momentous changes LTE brings.  The interview delves into the marriage of IMS, high QoS service delivery via IPX, real-time intelligence and roaming services, plus the new customer assurance hooks that LTE enables.
  • Shared Data Plans: The Challenge of Managing a Family of Pricing, Revenue Assurance, Fraud, and Network Policy Issues by Amit Daniel — Verizon Wireless‘ recent announcement of its move to shared data plans for families shook the mobile industry.  In this column, cVidya’s Amit Daniel shines a spotlight on the knowhow and analytics tools that operators now deperately need to offer the right  shared data price plans, ensure bandwidth throttling is handled correctly, and address new fraud concerns.
  • Analytics Guru: Are Telecoms Ready for the Biz Intelligence Explosion? interview with John Meyers — Business intelligence is evolving from the creation of dashboards and reports to taking action based on a deep knowledge of the environmental context.  The article explores the implications of “big data” in terms of IPTV, storage requirements, hardware, event collection, and deep packet inspection.
  • Social Networking for Telecoms: How To Enlist Friends and Family as Mobile Marketers interview with Simon Rees — Social Network Analysis (SNA) is about exploiting data on “friends and family” connections to combat churn and win new CSP business.  The article explores how an analysis of the ebb and flow of CDRs, phone calls, and messages, can identify key influencers and drive powerful marketing campaigns.
  • Making the Strategic Leap From Billing to Merchandising interview with Humera Malik — Today billing/charging technology has progressed to the point where the usage intelligence, the charges, the user behaviors, and the analytics can all come together in near real-time.  This article discusses the organizational and marketing strategies that enable a operator to create a true “merchandising” system that can revolutionize a CSP’s business.