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Category Archives: Revenue Assurance

Does a Digital Lifestyle offer Operators opportunities, or is the path more ominous?

It stands to reason that the Digital lifestyle of consumers will dramatically impact how operators generate revenues over the next 10-15 years. Transformations are taking place that will move activities, entertainment, commerce, healthcare, transportation, and most other aspects of our lives into Digital modalities. This has invited thousands of micro-providers of applications and networks into the mix, quickly marginalizing the value of the operator to merely an “enabling pipe.” This puts the operator into a competitive situation, ultimately impacting margins. But that’s only on the revenue side of the equation… the story could become far more complex.

For an operator, the days of 25%-40% EBIDTA are waning, if not almost gone (in many regions). Pressures on pricing remain downward, with new product offers being the primary method to sustain acceptable revenues and margins. This has opened the door for some impressive creativity by many operators, especially in developing markets. In many cases no market appears off limits, as seen by the offerings by progressive organizations like MTN in Africa: Who would have anticipated an operator would offer personal transportation services rivaling Uber?

These seemingly odd moves are, in fact, brilliant moves by operators to seek new sources of revenues as their businesses are being redefined by the digital services we are quickly becoming reliant on. The impacts on revenue models due to this change in the business are stunning: Traditional billed services like voice, and even data, are fading in importance. Revenue models are instead focusing more on casual services, pay-per-use services, marketplace services, etc. Put more simply, the “pipe” is no longer where the earning potential lies for the operator.

So now a previously non-agile, large operator business is finding itself competing with, and in many cases partnering with, literally thousands of aggressive, hungry micro-entities that provide products and services accessed by the networks. There is less reliance on monthly guaranteed revenue; the battle for revenue very often resides in millions of micro-transactions.

All of the discussion cannot focus entirely on revenues, however. Margins are also sustained by costs. Agility, therefore, must exist on the cost side of the operator business. In the old world of monthly recurring and predictable revenues, costs could be managed and allocated more confidently. Opex and Capex planning and forecasting practices were based on budgeting with a high degree of certainty. But as revenues models are changing, so must cost models. Where possible, operators will need to employ similar creativity to curbing costs, as they are with earning revenues.

How can operators, therefore, modify cost models in the business to be as aggressive and variable as the revenue models they rely upon? This is where the opportunities for SDN/NFV networks can shave significant costs, while changing operator cost models in ways that were not previously achievable.

Software-Defined Networks (SDN) and Network Function Virtualization (NFV) will allow operators to provide Network-on-Demand and Service-on-Demand models to consumers, while effectively minimizing, if not eliminating the need for human intervention. The costs associated with truck rolls, call centers, and expensive specialized network equipment will be dramatically reduced, resulting in decreased Opex and Capex burdens on the business. The savings need to expand further, however.

In current cost models, operators must deploy and maintain network services around the clock, which consumes significant and ongoing expenses. However, if a network is based on SDN/NFV architectures, the deployed services are no longer in a fixed position in the network, simply because they are now software-defined and/or virtualized. This means an intelligent network can move assets where needed, and when needed. These assets are capitalized as licensed instances; so now an operator can have a pool of 1,000 licenses for a virtual service, and deploy them only as necessary.

This type of dynamic deployment model should allow operators to negotiate dynamic cost models as well; imagine only paying for a license when you have it deployed (and it is generating revenue). While this idea may seem far-fetched, consider that now the network functions we are discussing are no longer controlled by a few network equipment and function providers; micro-entities (application developers) can now produce those functions, often at far less expensive price points.

The business transformations taking place in operators globally are forcing entirely new ways of addressing margin pressures, as the revenue and cost variables operators have historically used are no longer the same. Looking beyond margins in consumer-facing products and services, new network cost models must be explored, especially since those models were based on what is now an outdated means to earn revenues.

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:

World

 

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.

Factors Complicating Assurance in 4G Environments

GSMA has a vision for 2020 for Telecommunications Industry around connected living which focuses on main pillars which are expected to drive the industry forward, namely – Network 2020, Personal Data, Internet of Things and Digital Commerce.

As per my view, the single most important take away from that vision is the rise of Telco 2.0.

Telco 2.0 are those telecom operators which are expected to expand transformationally by taking risks to chase higher rewards in both known and as yet unknown new parts of the value chain. These are expected to be the most advanced & disruptive Telecom Operators.

1

The most important enabler of these, so called, Telco 2.0 operators would be the ‘platform’ which would allow them to explore & experiment with those unknowns and expand services while ensuring higher customer experience which will help them achieve that visionary status.

One of such platforms is 4G, which riding on the inability of 3G-3.5G networks in delivering the required quality of service, has shown tremendous adoption rate within operators over the years.

What has made 4G enabled networks so popular is its proven capability as an ideal platform for cross domain services convergence & all access technologies.

A comparison between 4G LTE & HSPA (~3G) based network and service delivery capabilities can be seen below:

2

The bitmap above also provides a crude reasoning around lower adoption rate of certain services which were also rolled out over 3G enabled networks, but did not meet the consumer expectations around quality, reliability and price.

4G based networks provide the ability to the operators to become the ‘Real’ converged service providers, which until 3G was more theory than practicality. Operators are now becoming OTT service providers including communication, social media, social network, content, advertisement etc., connected living enablers, enterprise enablers etc. which was, until now, being offered mostly by 3rd parties.

With operator owning the converged service offerings (or at-least controlling some part of the service delivery like quality etc.), the increase in traffic over its pipes has shown potential of increase in direct revenues, that too proportionately.

Factors influencing complexity in 4G environment

Yes. 4G is great! But, not without the share of complexities it injects in the area of assurance (RA & Fraud) operations.

The following variables are identified to be the main influencers with respect to complexity and uncertainty in 4G environments:

New Network Elements

4G introduces new set of network elements and O/BSS systems generally being customized in terms of design or implementation as per the operator raising concerns around interfacing, data availability or quality. This also points to increase in complexity & volume of RA & FM activities to be performed due to increased data sources and controls.

Also, a lot of components in 4G implementations are still not COTS and provide different logging & access levels which raising concerns around capability around identification of internal frauds and external access attempts/brute force attacks.

Parallel Networks

Traditional networks including certain components adopted from 2G, 3G environment and running in parallel to enable backward compatibility and interconnection leads to further increase in risk, complexity and number of controls to be managed.

Non Standard Implementations

Some areas of 4G network, O/BSS systems and interface partnerships (operator, content providers etc.) are being implemented in customized non-standard fashion to enable interconnections (including roaming approach) and support complex products and service offerings (like VoLTE or VoLTE roaming etc.). The situation is more of an experiment and working towards developing a standard rather than following one.

Lack of reference 4G RA & FM practices combined with custom implementations, RA & FM activities are expected to be driven by non standard data sets and frequencies until stability/maturity.

Initially in 4G space, RA & FM practices may be exposed to the scenario of ‘Incident induced learning’ or ‘reactive RA & FM’.

Higher Convergence

Higher convergence of ‘core’ telecom operator provided services introduces more ‘direct’ risks to the operator and an increased need to manage RA & fraud risks introduced by the new services, which in an earlier setting, was a headache of the third party service provider.

New Pricing Models

Conversion to charging policies from minutes to bytes (sessions) and bytes to service subscription & access mixed with complex bundling packs & rate plans is expected to change the traditional mindset of conducting RA & FM, especially around charging, discounting, billing & invoicing.

Disruptive roaming charging policies are also expected to be introduced which will change the perspective further.

For session based charging policy, verification of policy implementation is also expected to impose its own set of challenges.

Complex service offerings

Telecom operators are going beyond their traditional service offerings (Apart from voice and data – TV / content / cloud etc.) and venturing into the modern areas revenue generation such as content, advertisements, connected living etc.

Rich content (VoD, music, messgaging, magazines etc.) management & delivery to become the fulcrum 4G revenues. Also, with various channels of content delivery at hand, advertisement revenues will also play an important role for mature 4G operators

But, service based subscriptions, validity & dynamic delivery along with innovative & complex content and partner agreements are expected to complicate the RA & FM activities like never before.

Increase in transaction volumes

4G subscriptions is expected to increase 3.5 folds to 1.3 billion and data traffic by 6 folds to 17 Exabytes by Dec 2018. Operators will be dealing with many fold increase in data per unit of earned Revenue.

Considering revenues are tied to data sessions, transaction volume mgmt. for the purpose of RA & FM is expected to introduce a big challenges and would require advance data treatment, management & analysis techniques (e.g. Big data).

Responsiveness & Scalability is expected to be one of the main talking points with respect to volume management

Rapid Product & Services Launch

New product, package and service launch across the breath of 4G enabled service platforms are expected to see a considerable rise in throughput due to shortened development, delivery & release cycle.

The agility of RA & FM departments in terms of proactive assessment and risk readiness is expected to keep pace with the higher number of products, services and packages being launched at the breakneck speed across the breath of business offerings

Margin Management & Revenue Enhancement

With increased competition, Revenues are expected to be driven by high volumes and low margins and not high margins. Product performance measurement in terms of adoption and revenue generation against target will have to be carried out at much higher frequency.

With RA having and access to all cost items, charging, payins/payouts, usage records, quality parameters and first visibility to trends and anomalies, margin management and revenue enhancement activities are expected to take center stage

Skill set and technology within the team will have to be enhanced or absorbed to enable and handle increased cross functional interfacing , analytics and product management

Lack of Skill Set

Lack of mature reference 4G implementations is also expected to lead to lack of required skill set which is needed to manage and continuously improve the RA & FM operations. There will be focus on more laborious, reactive & risk prone approach of skill ‘creation’ rather than ‘absorption’

Updated Network Access Authentication Methods

Operators need risk readiness against newer authentication methods which are different for different services – ISIM, USIM, Single Sign On etc. Considering device authentication & security is in the hands of the manufacturer or the OS provider,  any security flaw is a direct risk to the subscriber base of the operator

Also, 3rd party firmwares & apps are readily available for the assistance of hackers. This situation increases the device or OS takeover further.

Increased UE & CPE Types

Exponential increase in multi vendor UE & CPE types has increased user exposure to IP frauds like takeovers (Accounts or UE) enhanced by ‘easy’ service access methods such as ‘single sign on’ for single or multiple services.

While user equipments are highly exposed to malicious Apps, URLs, Malwares etc., readily available custom firmware for Customer Premise Equipment are found to expose them to the same level of risks.

To top it off, high profile sensitive customer information hacking cases by external sources are on the rise both against individual subscriber and enterprise networks, calling for much more robust, secure and continuously improving infrastructure and detection capabilities.

Power user exploits

Power users or technology aware users are expected to exploit any loopholes in the implementation of service access, newer pricing models etc. through the use of various complex techniques such as URL masking etc. to bypass charging and gain free access to services

Spoofing or device configuration updates like MAC Address may also gain popularity to help divert charging to someone else in absence of adequate authentication and multi level device binding mechanisms

 

Movement to 4G or a higher capability environment is inevitable.

I believe, if traditional approach to manage RA & FM operations is continued as it is even for 4G environments, these functions are expected to attract steep investments to manage complexity factors mentioned above (including increase in network elements & O/BSS systems, data streams, data loads, controls, resourcing, technology requirements etc.).

There is an immediate need of shifting from current mindset and adopting “Smart” & “Agile” RA & FM practices across the operational spectrum (of people, process, measurement, organization & technology) to contain costs and risks much more efficiently.

Taking a cue from Game of Thrones – “Winter is coming! and this one will be long. God help us all if we’re not ready!”

BSS/OSS Transformation – An Assailable Phase for Telcos

“Rapid” is an understatement to describe the pace at which the telecommunications industry is evolving. A vicious circle formed between the advancement of hardware capabilities and services offered to utilize these capabilities is probably what is causing this constant evolution. With such augmentation in the services offered, migrating to next-generation operations and billing systems is inevitable to operators. While the change is definitely a thumbs-up for telcos, the flip side is the challenges inherent to the transition phase itself.

Consider an expert chef in a successful restaurant offering a variety of dishes to customers. Quite obviously, his menu changes periodically to ensure that he caters to the constantly changing customers’ taste. While a changing menu keeps the restaurant and the chef in good business, it also brings in a big risk of cooking something unsavory in the process of creating something new. Though the chef is dexterous at what he does, it would always be a possibility that he would add that extra pinch of salt or sugar while trying out a new dish. Does this mean that the chef is not competent enough? Or should it stop the chef and the restaurant from offering newer dishes? The answer is “No”. It only goes to indicate that the transformation phase is highly vulnerable and needs to be dealt with extra caution to ensure continued success in the business.

Equating the above analogy to the telecom sector, one would understand that the chef is the telco and the new dishes are the variety of services offered to customers. The extra pinch of salt/sugar that we spoke about is the possible leakage or frauds that can hit telcos during the phase of BSS/OSS transformation.

A recent survey by KPMG indicates that 49% of the teclos undergoing transformation projects saw a significant increase in revenue leakage and threat of fraud while another 45% indicated a partial increase in revenue leakage and threat of fraud. Put together, a whopping 94% of operators have encountered some kind of increase in revenue leakages during the transformation phase.

Reasons for this vulnerability are quite straight forward. The controls that existed with a set process get disrupted and start to diminish once the transformation begins, thus leaving the operators in a bit of a handicap. Another main reason would be the significant loss of data that is an innate characteristic of transformation projects. This causes blind spots in the revenue chain and keeps telcos in the dark about the leakages occurring. To add to the telcos’ woes, transformation projects are not completed in a day’s work. They may stretch to anywhere between 2-10 years depending upon the size and type of operations.

All this points to one thing – with the breathtaking speed of change in the telecom sector,  telcos have to adapt quickly and decisively or else risk even greater leakage. Revenue Assurance processes need “greater than ever” emphasis during the transformation phase. After all, no one likes extra salt in their dishes; not even a pinch of it.

5 Questions to consider before starting RA activities

In my last post, I tried to highlight the “revenue” aspect for RA and the way KRA’s should be worked on. In continuation to that post, here are 5 questions that should be considered before starting of the RA activities:

  1. Who is responsible for RA?  It has to be a collective responsibility across the organization where every team/department has their role to play. Being in the Revenue Assurance department, is almost as good as being a Product Manager- where the individuals do not have a lot of control on the rest of the organization, yet they are suppose to own and be “solely responsible” for the role/product in the company. Hence, aiding in RA activities is as much a responsibility of Marketing and Network departments as it is for the core RA team.

  1. What should be viewed as the tactical task for the RA department?  All actions/activities that has the ability to allow the operator to generate revenue needs to be monitored to make sure there are no leakages.

  1. What is the ideal number of controls that should be worked on by the RA teams? This depends on the maturity of the organization in terms of organization, influence, people, process and tools. Hence it is always preferable to perform a quick maturity analysis, based on which primary focus areas would be identified and controls created. Not all controls would necessarily impact revenue. Understanding the maturity enables the creation of a roadmap for improvement across the organization. Typically there is NO need to have hundreds of KPIs to monitor each segment or process. This is because of the 80-20 rule. 80% leakages can be found by 20% of appropriate controls. Hence it is essential to work on controls/KPis that have maximum impact, rather than trying to monitor hundreds of them.

 

  1. 4.       Is Cost Management a part of RA activities? Only when the RA team is capable enough to secure the top-line for the organization, should they focus their activities on more strategic objectives like cost and margin assurance and management. Revenue maximization should ideally not be a part of RA department activities.  Most RA teams should venture into this area solely to ensure they provide ample Business Intelligence for marketing and sales departments to take the information to the market to generate more revenues.

 

  1. 5.       What are the most important parameters to report on?  RA departments should look to quantify the findings from data analysis to provide view of
    1. a.       leakage detected
    2. b.      leakage corrected and recovered
    3. c.       leakage corrected and recovered as percentage of detected
    4. d.      leakage detected as percentage of revenue
    5. e.      leakage detected as percentage of EBIDTA
    6. f.        time to recover from detection of leakage.

In a nutshell, RA is not rocket science, but it is an extremely important and challenging aspect of business- not only telecoms but across other industry verticals as well. The effect in telecoms is much more because of the complexity of operations.

In following articles, we would talk more on RA, scope, new horizons and verticals for RA. Stay tuned.

The “Revenue” of Revenue Assurance

What is the scope of Revenue Assurance? Honestly, this is a vendor / RA team/ consultant capability dependant age old myth, leading to the term being a misfit for the purpose. There are always things that one can debate on such as what is in scope and what is out of scope? However, if one takes the terms “revenue” and “assurance” at the face value what would be defined as the scope of work? It would simply mean any activity/event that has the ability to generate revenue should be monitored to ensure that the associated ‘revenue’ is generated; and if it is not, ensure steps are taken to fix it. Sounds fair? But then, this brings in another primary question: “What is “revenue”?

Ask personnel from finance and they would give you the most appropriate and correct answer. Now if you ask the same question to an RA professional, the response would not be encouraging. It is not to say that such individuals don’t know anything- but it is a matter of knowledge w.r.t the financial context. Typically, the individuals working in the RA department have sound knowledge of KPIs, data analysis and such items that are monitored as part of RA activities.  However, often the large part of data analysis related to finding leakage is not translated in the correct/appropriate terms for business benefit.  The net effect of this at times, results in inappropriate KRAs for the RA department. I remember hearing somewhere, the KRA for the RA department for an operator was to detect x% more leakage from the previous year!  I don’t think that is a valid KRA.

The solution therefore is to establish the following two things:

  1. KRA’s for the RA department need to be worked backwards: The KRA’s of the department need to be defined keeping in mind the core business objective of the operator.  In this aspect, one would have to determine, how to map the organization KRA’s to that of the RA department? This would definitely vary across operators. Example, if the organization’s focus is to improve profitability of services, one would have to determine the impact of the same in cases of leakage.  Hence, the KRA for RA department would have to be worked backwards to ensure that the efforts put in by the RA department are aimed at fixing leakages around activities that would improve profitability.

  1. Accounting of detected leakages in a manner that makes sense:  The “revenue” calculations should be used only for quantification and gauging the leakage potential and recovery. This may or may not be the most accurate revenue calculation because RA is not accountable for revenue generation. However, there are a few methods  which use the following of revenue calculation
    1. ARPU
    2. “best fit rating” of usage xDRs
    3. Effective rate of XDRs
    4. Effective rate of files

NOTE: A revenue assurance department should ideally NOT even attempt to calculate Revenue per Stream/Service/Business Unit, ARPU, AMPU and other revenue figures. These should be obtained from the financial systems for quantification of the leakage detected and to understand the potential impact of leakage on the top line of the company.

Besides “revenue” there are multiple other aspects of RA that should be addressed and answered much before the start of RA activities. In the next post I would try to address the following 5 questions that should be looked at, as the business aspect around RA:

  1. Who is responsible for RA?
  2. What should be viewed as the tactical task for the RA department?
  3. What is the ideal number of controls that should be worked on by the RA teams?
  4. What are the most important parameters to report on?
  5. Is Cost Management a part of RA activities?

Zen and the art of Root Cause Analysis

Our story begins with Farmer Joe who has a beautiful daughter Janet. Farmer Joe decides to bequeath the family decorative pin to Janet on her 20th birthday. Now Janet, in a fit of unbridled joy decides to run around a haystack holding the pin towards the heavens. Suddenly,in a scene far too clichéd to be coincidence, she trips and the pin falls into the haystack…

Now begins the daunting task of “finding the pin in the haystack”. Janet is faced with a dilemma which would be quite familiar to RA analysts the world over – how do we find the pattern which highlights the root cause (or the pin, if you are a farmer’s daughter who goes by the name of Janet) within a world of millions of CDRs.

Of course, the solution is to cut the haystack into smaller cubes and search smaller segments for the pin. Does this sound familiar to you, my RA analyst friend? It should – because this is the way we attempt to find the root cause today. When your system presents you with millions of CDRs (or, God forbid, meaningless summaries), we tend to break them into smaller sets which have seemingly similar patterns. Then begins the back-breaking task of finding the elusive pattern that indicates the root cause – an endeavor that involves quite a few cups of strong coffee, pointless mails and shattered dreams regarding deadlines and analyst efficiencies.

But hey, this is how we do Root Cause Analysis the world over right? We would reduce our effort by managing the problem size right? Well, it gives me great pleasure to say that the winds of change are blowing. Today, I would like to introduce to you to a fundamental paradigm shift in Root Cause analysis which would effectively transform the way we do RA.

Let’s imagine for a second that Janet decides to find the pin by placing a powerful magnet over the haystack. Consider how much time and effort she saves, as compared to breaking the large haystack into smaller stacks. Consider how sure this solution is, as compared to the possibility of not finding the pin even after breaking the haystack into smaller segments.

Now imagine such a magnet for RA. A magnet that presents the analyst with all the hidden patterns in a problem set (discrepant CDRs). Imagine how this would change your day in terms of boosting analyst efficiency, achieving cost efficiencies as a department, being prepared to handle new and upcoming technologies and always staying one step ahead of the curve.

That magnet has a name, and its name is “Zen”. Subex recently launched ROC Revenue Assurance 5, and along-with RevenuePad (which my colleague Moinak would write about), Zen is one of the fundamental pillars of this ground-breaking solution.

Zen is an automated Root Cause Advisory engine which provides, for the first time ever, machine intelligence for pattern identification and presentment. What makes it revolutionary is that the engine is programmed to sniff out patterns with minimal involvement from the analyst. Give Zen two data sets, and it will tell you exactly why some CDRs in data set 1 are not present in data set 2. This also involves telling the analyst what percentage of the total data set can be linked to any particular pattern. Since pictures speak louder than words, here is a sample illustration:

The future of Root Cause Analysis

Zen is essentially a data analytics engine for ROC Revenue Assurance 5. Based on the discrepant sets identified as the result of an audit, Zen automatically fires up the pattern analytics engine. As Zen works on identifying the patterns, it also works on linking the patterns to specific CDRs (to ensure that an audit trail would be maintained). Finally, Zen presents the analyst with a comprehensive view of:

  • All identified patterns in the discrepant data set
  • Distribution of how many CDRs are linked to which pattern
  • Historic event indicators to further guide the analyst towards the root cause

Zen is keyed towards two “Intelligent” actions:

  • Pattern Analytics
  • Analyst Feedback integration

We refer to Patterns as “Areas” and the learning from past investigations as “Reasons”. Why do we need both, you ask? The answer is fairly simple – the same pattern (or Area) might have presented itself for very different “Reasons”. A simple example of Subscriber profile between HLR and Billing might clarify this point.

An analyst, on performing the HLR vs Billing subscriber reconciliation, finds that 20 subscribers on the HLR are not present on the Billing platform. Now, in the absence of provisioning logs, he/she might surmise that this is a simple case of provisioning error and forward the information to the relevant teams.

However, if the same discrepancy is seen next week for the same set of subscribers, it might be prudent to address the possibility of internal fraud as well. Here we see an example where the same pattern (20 subscribers are missing repeatedly in billing but are provisioned on the network) might be due to two distinct “Reasons” – Provisioning Error or Internal Fraud.

Zen helps you tie it together. Reasons are incorporated into the Zen engine based on “Acknowledgments” received from various teams. This helps to ensure that “False Reasons” are minimized. In this manner, Zen becomes a repository of Analyst intelligence to address the world-over issue of Knowledge Management in RA.

Zen is a virtual analyst who never sleeps, eats or goes on vacations. For sure he will never leave the team (taking his accumulated knowledge with him).

In conclusion, I want all of us to take a moment to step into Janet’s shoes. The pin is in the haystack, and the stack is getting bigger and bigger all the time (due to burgeoning volumes and technology/product complexity). The timelines to find that pin are ever-shrinking, and cost reduction is the call of the hour globally.

How is your team planning on finding that pin?

Black Swan Ahoy!!!

Whoever thought that the above picture would give flutters of fear to senior management one day?

But thanks to Mr. Nassim Taleb who brought the concept of the “Black Swan” event to the forefront, it’s what sleepless nights are born of. Of course, the Natalie Portman movie comes a close second…

Let’s start off with what Enterprise Risk Management is all about. As per Wikipedia:

Enterprise risk management (ERM) in business includes the methods and processes used by organizations to manage risks and seize opportunities related to the achievement of their objectives.”

I came across another definition by Jim Deloach, which I felt was equally (if not more) clear:

Enterprise Risk Management is the discipline, culture and control structure an organization has in place to continuously improve its risk management capabilities in a changing business environment.”

Essentially, my distillation of ERM is a framework which helps an organization to manage risk. Now, in a similar manner, I’m going to try and distill the Who, What, Where, When and Why of ERM. Please feel free to correct me, as I think I’m going to be a student of ERM till my dying day (not because of any misplaced sense of passion, but because ERM is an ocean).

Who

ERM is a complex, complex bit. Let’s begin by trying to understand who is the owner of the ERM framework.

ERM is kind of like voting – it’s everyone’s responsibility, but ultimately tends to get forgotten in a world of everyday complexities. However the buck should and will stop at the CEO. Under the CEO, we might see specialist roles like the Chief Risk Officer or Risk Managers or Auditors.

What

Hmmm…didn’t we define what ERM is? If we assume we know ERM because we know it’s definition, I would say that we are making the same mistake as the crew of the Titanic – what you see is a small part of a large thing.

ERM incorporates, as per COSO, 8 odd elements from Internal Environment to Monitoring. If I attempt to simplify, ERM constitutes all the elements of Universe measurement, Goal alignment, Risk & Mitigation and Measured Monitoring.

Where

Okay – so there’s  a huge laundry list of ERM related activities. Now where do we apply these…

As with everything else about ERM, my answer would be everywhere. ERM figures in all your day-to-day operational activities all the way to your 10 year strategic goal. In my experience, the space where ERM is given due importance today is primarily in Compliance. It’s been pointed out in various findings that ERM, as a complete practice, is quite immature.

When

Ah, this question. To be honest, I do not have a complete and convincing answer for this one. I would encourage you, the reader of this post, to provide your perspective.

In my view, the earlier the better. ERM is a vast area. It would be useful to start your ERM practice when the internal processes and universe is still manageable.

Why

Why you ask? In the words of George Mallory, when asked why he wanted to climb Mount Everest – Because it’s there.

To expand on this, ERM enables the business to safeguard itself against a potential cascade of risks which would threaten its existence. ERM enables large organization to be nimble and respond to opportunity. ERM aligns the organizational goal across all its functions not only from an operations perspective, but all the way into the strategic horizon. ERM would, though indirectly, improve customer and share-holder perception of the organization. I would say that the real question here is, why wouldn’t you implement an ERM framework. Here again, I invite the reader to give your perspective.

After reading this post, the obvious question you might have on your mind is – where do the swans come in. I think I’ll leave that for another post for now. The intent of this post was to provide a base on which we can build.

Authors note: I wish I knew who to credit for the wonderful picture I have used in this post.

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