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All posts by Srikanth Vasudevan

The changing business model of Assurance

It’s been more than a year since I have even looked at my phone bill, lying in my inbox, marked as read, never to be opened. Bundle of services packaged under a single price, only to change by a small margin when India moved to a single Goods & Services Tax framework.

This is the new world of telecommunication. Select services of your liking, planned well like mine is, you would rarely be looking into your bills, scrutinizing itemized lines and stressing about your usage with  customer care.

In a recent survey of complaints received at the CCTS (Commission for Complaints about Telecom-Television Services, Canada) while incorrect charging complaints increased by 71% Y/Y, complaints on changes to contracts increased by over 200% Y/Y.

This trend is one of the key indicators of the change that is emerging in the space of assurance. The others being the steady and continuous interest in mitigation of risks within the partner ecosystem primarily related to contracts, margin, partner invoices, and inventory.

What’s Changing?

Today with telcos moving into the domain of content providers with offerings of entertainment streaming, current affairs consumption, shopping, and many more options. All these services are bundled into a highly configurable plan that has an “all you can eat” approach as long as it is within the “Fair usage policy” means for a telco subscription, services, on-boarding, customer intelligence, and QoS are the critical assurance parameters from a retail point of view.

However, the change being addressed has a pivotal impact from a B2B perspective from the massive complexity of the partner ecosystem.

partner ecosystem

Today for a partner ecosystem the risk universe includes devices, direct carrier billing, partner credibility, partner & product margins, pay-in & pay-outs, revenue sharing, contract alignment and many more which needs to be monitored & actioned on at near real time.

Furthermore, we are not talking just about revenues but also costs and liabilities. So, the new business model of assurance, which we are referring to as “Business Assurance.”

“Assurance is becoming a source of competitive advantage.”

Business Assurance is not just a methodology but a major transformation in practice & technology. The new Business Assurance solution will need to:

  • Own and maintain the system that measures data quality
  • Own and maintain the business anomaly detection engines
  • Manage & drive business intelligence & insights
  • Measure and anticipate the impact of changes or offerings on customers
  • Monitor the content & partner environment for business feasibility and continuance
  • Gain a comprehensive understanding of revenue & cost breakdown in the organization
  • Help in assuring the “business model” itself, as opposed to a line of business

In short Business Assurance is the new Revenue Assurance. It is not a question of if this transformation will happen but when will it happen? If it hasn’t yet started, it will.

Reporting “The Smart Way” in RA

“As is”
Read the news using your favorite news app on your smart phone or device? Notice how the app renders news items that are important to you or of interest to you and stacks them together with short headlines followed by a short summary thereby making sure that one wouldn’t need to feel short of time finding what really needs to be read.

Is this done in your RA department?

The below diagram illustrates how majority of the RA departments report the necessary information to all concerned departments and how the subsequent action items are publicized and owned by various departments.

Reporting2

In majority of RA functions the following gaps exist in the reporting of findings and their subsequent action points:

• Reports rarely designed with specific information that is immediately consumable by target audience
• Reports rarely designed with specific requirements to the target audience than can be easily converted to action items
• Majority of the RA operations use one reporting template for all business functions

“Smart Reporting”
The below figure illustrates the ideal modus operandi that requires to be followed in a RA reporting structure.

Reporting1

Key improvements in the model are as follows:
• Reports specifically designed to target audience. For example: Reports to CxO will address revenue & cost savings, key mitigation measures taken, not exceed a time length of 5 minutes and requiring specific actions / escalations
• All reports to address specific actions required from various business functions and will be time bound
• Organizational news feeds will be made part of RA reporting

Here the emphasis is on smart reporting, which can be quickly consumed and acted upon.

Revenue Assurance and LTE

Emergence of LTE

Through the last one decade when telecommunication globally evolved from 2.5G to 3.5G taking along the subscribers from a mere 56 Kbps to streaming of HD videos & music on your handset, data and content has evolved by giant leaps far faster than anyone predicted. The evolution not only provided a broad variety of services to the end users but also magnified the economics of content provision, VoIP services and eCommerce by leaps and bounds.

A far cry from just using you mobile phone for voice and SMS, the thirst for data from the end users of today sends out a clear message that even the speeds offered by 3G networks fall short of the requirement. So much so that this evolution is slowly but steadily diminishing the traditional circuit switched voice traffic.

The below stats geographically indicated illustrates the current data evolution:

 

Risk Profiling

The evolution of LTE differs not only from an end user product offer perspective but also from the point of network architecture. This makes LTE evolution very different from the 3G evolution wherein only a few components changed along with minor adjustments in xDR formats. These minor changes resulted in majority of the core RA practices to accommodate a 3G risk mitigating process with minor adjustments to already existing controls.

However this would not be the case when it comes to LTE wherein majority of the network components are different with layers of complexity that originates from the perspective of how products are designed and offered.

  • Product Design

When it comes to how RA facilitates product design in an LTE network we must take note of the fact that very few RA practices today have a functioning RA process that contributes to marketing campaign, product offer development and change management in a 2G / 3G / fixed line / broadband environment. The primary reason being that majority of the RA operations still concentrate towards leakage detection and not revenue enhancement.

However in the case of LTE where subscribers have access to multitude of content and eCommerce in a market which is growing at a rate of 30% – 55% at any given geographical market coupled with thinning bottom lines, here RA processes for product design becomes far more important in the insights that can be generated through various multi-dimensional usage modeling.

  •  Order Management & Provisioning

Unlike a 2G & 3G environment wherein the subscriber service configuration is spread across the order management system, HLR, IN and billing in an LTE scenario the scope of risk is drastically amplified due to the dynamic allotment of service elements in the PCRF as per a designated service plan.

Herein any risk mitigation process begins with the analysis of services allocated at order management, subscriber’s historical usage and the subsequent policies that are dynamically enforced by the PCRF.

  • Rating and Billing

LTE brings in complexities within each service plan wherein the rating differs across each and every data session initiated by a subscriber. For instance, if a subscriber is streaming a video / music and simultaneously texting through a popular messaging service the corresponding rating will also differ specific to the plan associated to a session; in this case video stream will be rated differently from the messaging service. Here again to add another layer of complexity, rating can also differ on the QoS guaranteed to an end user.

Evolution of RA

It becomes fairly clear that majority of the traditional controls that has been used for a 2G & 3G scenario cannot be reused for RA in LTE thereby paving the way for RA evolution along with the corresponding LTE evolution.

One of the important takeaways in the evolution of RA is the importance of analytics for revenue reporting / projections through multi-dimensional data modelling which is a must in a LTE environment which thereby provides a multitude of insights on subscribers, products, network utilization and revenue generation.

Mobile data offloading & Revenue Assurance

Emergence of mobile data offloading

Though mobile data offloading is not new to the industry it is catching steam off late and that has made operators around the world take notice. The factors that are driving mobile data offloading is the ever growing smart phone market giving people the option of streaming any content of the internet right on to the palm of their hands.

Surprisingly it is not “work on the move” that is making a large percentage of the populace download content through their smart phones extensively but the driving factor happens to be  streaming of video content from sites such as YouTube that ranks at the top of data usage .

Key industries can’t afford to ignore the trend especially when recent industry research predicts that nearly 50-60% of the data would be offloaded by the year 2017 by either WiFi, WiMax or Small cells with WiFi being a major player over the latter two.

Why offload with begin with?

At a time when cellular operator costs are going up due to investments in 3G and 4G network evolution, WiFi still ranks at the top for data offloading primarily due to 3G/4G pricing, poor signal reception indoors and WiFi’s higher bandwidths offerings with little or no interference.

The three factors put together are the leading cause for smart phone / tablet data usage being offloaded to a WiFi network.

A simple iPad sales figures of 2012 provides a interesting insight into the fact that 9 out of 10 iPads are only WiFi show casing a interesting find that cellular data services has been given a miss at the highly sought iPad retail market itself

“A little known fact is that contrary to popular belief a smart phone / tablet also uses lesser battery when connected to a WiFi network accounted due to the lower signal strength requirement.”

The benefactors

Apart from the end users who get excellent bandwidth, speed and zero interference reception; the businesses which provide broadband services to end users cash in by filling in the gaps between the cell towers, literally.

A few OPCOs in the wireless business who also double up by providing broadband services in the form of ADSL or FOC loop back their users into their network business.

How can RA help?

Analytics, analytics, analytics!!!

“The true potential of analytics is only limited by ones own imagination of what can be done with an array of data at your disposal”

Here RA’s primary role comes in as a revenue enhancer or opportunity loss identifier and not as the more commonly known roles of “leakage identification”.

From an RA perspective looping in key information of users such as the data usage pattern over cellular and WiFi and overlaying them over various dimensions of demographics, content, customer categorization and lifestyle components will provide an insight on potential cellular onload or offload opportunities which can be monetized by provision value add or add on services to potential users.

From an operators perspective this insight can increase revenues especially in regions where a good smart phone markets show below par cellular data usage therein operators can increasing their service offerings to targeted localities and users in the form small cells, WiFi, or  WiMax.

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