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Managing Product Performance Using Advanced Analytics

It seems there is an endless array of products being offered to mobile customers every day. Prepaid plans, postpaid plans, new bundles, new handsets, movement to services on tablets, increase bandwidth offers for data streaming, etc. As operators load the consumers up with more and more choices, understanding what is being bought, who is buying it, is the product making money, when does it start making money, will a new plan rob my bottom line accidentally, etc, are all questions operators must be able to answer, and on an almost daily basis.

As an operator, you should be asking a series of daily questions that need to be answered to protect your business and identify significant revenue opportunities and risks:

1. What are your product margins today? Which products are generating positive returns? Which programs are missing their business plan? By how much?

2. When a new product is proposed, do we understand what the impact will be from our existing customers that migrate from their current product to this new product?

3. When a competitor responds to your new offer with a comparable offer, how fast can you see that impact to your market?

4. What is the right product offer, the right price, for the right customer segment, in the right section of the network that we should be focusing our marketing resources around?

Many of these questions require much, much more than simple metrics and reports generated by mining activities. They require advanced analytics that allow operators to predict behaviors and successes (and failures) before those events come to pass, and most importantly, before budget and resources are focused in the wrong areas! Advanced analytics offer predictive, detailed analysis about what an operator should do, why they should do it, when they should do it, and what the expected outcome should be. Unlike simple forecasting, analytics is based on science, and offers a proven methodolgy for establishing successful strageties in the business in a near real time environment.

ROCware Product Performance Management (PPM) addresses these (and many other) issues, in a near-real time, high performance analytics environment. Using ROCware’s advanced analytics technology, PPM is able to provide operators with a full view of their products, margins, and a highly robust future-view into margins, customer and product behaviors, and many other factors that are crucial to properly track and manage your product portfolio.

It is very common today for an operator to have access to limited product data. Looking more closely at what the operator actually does have access to, it is really often based on excel spreadsheets, with limited information around sales metrics, with some segmentation. This is not set up as a repeatable process, and thus the requests are completed manually, and most commonly with 4-6 week latency. This doesn’t help an organization understand margin and profitability; it doesn’t help an organization understand competitive impacts, or the impact of a proposed plan on your existing market. ROCware PPM does all of this automatically, every day.

There was a time when a monthly performance report was adequate. That was before products became far more complex, and competitive pressures were measured in days (sometimes hours). An operator without daily views into their product health and threats is vulnerable to risks that could cost the business millions of dollars in just a single month. ROCware PPM, along with the other ROCware suite of advanced analytics solutions, takes this worry off the table, allowing operators to quickly and confidently mange changes in their business.

July 9, 2012
Traditional Capacity Management is doomed to fail and cost CSPs millions in unnecessary CapEx!

Most CSPs today adopt a traditional capacity management approach that consists of planning their network resource requirements over the next 12 months based on past consumer trends.

Reality check! In today’s fast paced end-user consumption and service demand, trying to predict resource needs 12 months out based on past end-user behavior is like playing a lottery based on past outcomes in hopes to hit it big – More often than not you will lose big time.

The reality is that the past doesn’t predict the future anymore and that end-users are causing unpredictable shifts in resource consumption in the network as they tune into major events and build their life around real-time communications. Oh sure, many CSPs will read this and think, we have the latest probes in the network giving us loads of real-time data and complex flows where we know if packets are traveling left or right in the network. And yet with all this information CSP still can’t keep ahead of today’s data tsunami, without being concurrently choked by escalating CapEx. Having loads of low-level information more often than not causes data overload: You have so much raw data that you don’t know what it means from an overall congestion perspective without weeks or months of analysis. Or even worse, you may interpret trends differently depending on the data sample you examine, making it virtually impossible to project congestion and business impacts. Many CSPs with whom I have spoken face the same problem: When in doubt, pour more CapEx into the network, in the hope of adding the right resources to alleviate congestion.

What if there is a way to more precisely target the CapEx spend needed in the network, to deliver the services the CSPs need to thrive? In fact, there is, and it’s called “Real-time Capacity Analytics”!

Real-time Capacity Analytics is about understanding all capacity-related data rather than looking at it on a per attribute or device perspective – which provides little more clarity than just a blip in an ocean of traffic – instead looking at capacity consumption as it relates to end-to-end path and services to end-users. It is amazing how CSPs are concerned about how capacity congestion affects their subscribers and yet most solutions today fail to look at capacity from an end-to-end end-user perspective. Without an end-to-end view and understanding of how different segments of the network path and services affect congestion, CSPs may be spending CapEx in portions of the network that may temporarily relieve the symptoms of congestion rather than resolving the root cause.

So as a CSP, the next time you face customer impact based on congestion, ask yourself: Did I see it coming? Did I get the right warning signs that congestion was building up over time? Did I get a read of time to exhaustion that could have helped me plan added capacity before impacting my customers? Is my solution pinpointing where to target my Cap Ex? And finally, do I have a solution that can tell me if my network can accommodate new subscribers or services, and, if not, where will the congestion hot-spots occur and how much Cap Ex is needed?

If your current solution isn’t helping you answer any of the above questions, it is time to consider Real-Time Analytics for Capacity Management before your business gets swept away by the tides of capacity congestion.

June 22, 2012
Mobile Money – Are your customers secure?

KARIBU !!!

‘ M-Pesa’ has been leading the revolution of mobile wallets across the globe. Over 50% of the adult population in Kenya today use M-Pesa service to send money to far-flung relatives, to pay for shopping, utility bills or taxi ride home. While East Africa has been dominating the numbers in the past few years other regions including APAC, EMEA, Europe and Americas are about to explode sooner or later with their own models – NFC, Google Wallets, Mwallets, Apple Passbook,etc

More operators are walking down the path of offering Mobile Banking services in some form or the other every year. These players might get caught off-guard & face what a leading operator in Uganda recent got hit with– a million dollar mobile money fraud loss !! News articles indicate that a recent internal fraud in a leading operator in Uganda lead to 3.5 Million Dollar loss, Mobile Money boss losing his job & 8 other employees getting fired. Operator also received reprimands from the regulator and had significant dent to its brand image. This mess also opened up competition for other players in the country. Regaining confidence of customers and regulators will not be an easy job for such operators. They will be looking to enhance security within their mobile money offerings. It might be a differentiator and lead to uplift in adoption.

This incedence clearly presents a learning for other operators about to offer Mobile Money services. Moving forward, one of the key areas of focus for operators will be to provide a secure mobile money platform to users and manage frauds beyond the traditional regulatory requirements. Below infographic highlights some variants of Mobile Money frauds already rampant within operations and potential damage they might cause.

June 20, 2012
Fraud has the potential to affect entire business adversely !!!

Here’s a recent incident with one of FM head in SE Asia. The FM head said, as an organization, the focus last financial year (FY) was on acquiring subscribers. The situation however when the annual report was published was :

(a) High growth in subscriber numbers
(b) Significant drop in revenues
(c) Drop in ARPU & AMPU

So, what had not gone according to the plan? Marketing had come up with “jazzy plans” to attract new subscribers. This was an avenue for dealers to inflate sales and earn commissions, as they realised the controls were not stringent (falsified subscriptions, dummy subscribers etc). Hence a significant portion of the new customers were taken on-board, but not generating revenue. This not only affected the top-line growth and in turn impacted the health indicators (ARPU and AMPU), but had a snow balling effect on investor confidence. The stocks have since then taken a beating.

This year the Telco is focusing on cleaning the subscriber base and finding ways to have the others generate more revenue. The FM head said, had we been vigilant while growing, we could have avoided a lot of negative consequences. The learning is fraud not only impacts small pockets of revenue streams. It could potentially impact the business at large. Hence it is imperative to consider fraud aspects as part of the proactive controls when launching new products and services.

June 19, 2012
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?
June 19, 2012
Should the government be in the business of running a business? – Subex Limited
Could privatization of Air India have saved this day? Should the government be running a business? Should it have left the business to people with the necessary skills and expertise? It is argued that privatization, which is a part of disinvestment process, results in better use of resources and efficient allocation. Around the world, many instances of businesses that have thrived after government relinquishing control are common place (there is also the other side that have not taken off well due to various other critical success factors not being met).Nevertheless, increasingly, governments are taking the role of regulators and not producers.

Is it not a similar situation being observed in Telecom industry? From a situation where the Telco’s produced (or managed) everything themselves, they are shifting their focus to building brand equity, customer satisfaction and user experience. Thus, telco’s are deciding how their eco-system needs to shape and work to achieve their goals (regulators), while a partner is delivering the required results (producers). Some of the strategic outsourcing engagements in India (Bharti and IBM for example) are very good examples of a thriving partnership. What was common place for networks is now spreading its tentacles to B/OSS.

Of course, many Telco’s are in a quandary on where to fit in functions like Revenue Assurance & Fraud Management – firstly, does it come under tactical operations or strategic business? One RA business head that I know of in the region has been tasked, by the CFO, with a specific KRA of increasing revenue by “x%” from the existing customer base in the current FY. Many more are likely to follow suit in the coming years (refer to KPMG Global RA survey 2012). The profile of RA/FM is changing – in addition to protecting revenues; they are involved in the areas of enhancement & managing revenues. Hence, the answer to the question above – RA/FM are both tactical (producing the desired results) and strategic (supporting the strategic initiatives of the organization).

Now what would be the right strategy – should I outsource or not? There is no one answer that is right. The only right answer is “what suits you”, depending on the organizational social & cultural makeup, risk appetite and the scale of economic issues. When I meet my customers, we work with multiple options and eventually decide on the best fit. Here are a few possibilities that could be looked at:
- Pilot program (minimal scope, few people, short duration etc) for the risk averse
- Bonus / Gain share to ensure accountability from vendors
- Part outsourcing the tactical part and retaining strategic initiatives (remember one main challenge is to retain resources for career progression reasons. This would be an opportunity to give them the much needed upward movement into a new area)
No matter what the option chosen, it is important that it works for both the partners in meeting the common goals.

And, I hope Air India takes off well again – they have better leg-room and delicious food compared to other airlines in the sector.
June 14, 2012
An economical approach to Mobile Money?

It’s clear to all that the advance of mobile money and NFC services has become an unstoppable force, with the latest estimates putting global NFC m-payment transactions at US$50 billion by 2014. For the Fraud & Security teams in mobile operators this heralds arguably the single biggest change in the risk landscape since the original proliferation of mobile services back in the late 90s and early 00s.

Where there is money, there is fraud. It was therefore inevitable that when mobile phones became a financial instrument, they would immediately become a target for fraud. Mobile phones were already a very popular target for fraudsters and the combining of the 2 is simply irresistible. This has presented Fraud & Security teams with a fresh sets of challenges and opportunities, the first of which is how they are going to monitor the new services.

Many operators are looking to the financial services industry for best practice and whilst this certainly makes sense, I’m not so sure that the purchase of monitoring tools from the financial services environment is as wise. By buying in such systems, mobile operators run the risk of creating a siloed view of their customers, with one system looking at mobile money usage and others looking at calls, SMS etc. Surely the most effective way forward is to have a single view of every customer, assessing risk across all services.

Almost all operators have some form of Fraud Management System (FMS), monitoring their customers’ calls, SMS and data traffic. Mobile money services are relatively simple when compared to those offered by banks and insurers and the same is true of the data that they produce. It is therefore well within the capability of an FMS to take in mobile money and NFC transaction data and present it alongside the calls, SMS and data usage.

To avoid unnecessary expenditure and inefficient use of resource, my advice to mobile operators is to challenge your FMS supplier to provide you with a solution for monitoring your mobile money services. Only if their answer is ‘no can do’ should you be looking elsewhere!!

June 12, 2012
Understanding customers is really a two way street…

Organizations are racing to understand customers for a variety of reasons, but the most prevalent is that their markets are increasingly saturated, and they need to protect their base. Concurrently, there is a big push to go “steal” customers from their competitors, but let’s not focus on that for the moment…let’s talk about understanding customers.

As an organization that provides both services and products, a typical telecom operator has really keyed in on “understanding their customers” and “customer experience management” as buzz words and phrases that have led to initiatives that include developing 360 degree views of those customers. This has created focus on things like demographics, segmentation, billing history, purchase history, contact history, service usage analysis, etc. These are certainly important factors, and they do help paint a picture of that customer to the operator. But the perspective is often skewed, in that the operator is looking at the customer from the operator’s point of view. Instead, to better understand the customer and their experience, the operator needs to adapt their approach to the customer’s point of view.

While this customer point of view strikes many as common sense, it still remains an elusive paradigm. Quite simply put, the operator needs to understand how the customer perceives the operator has treated them. How has the network quality been for that customer? How many unfavorable events has that customer had to experience (dropped calls, failed downloads, etc.)? On top of the number of times the customer has contacted, how many times did they contact before an issue was resolved (not to mention hold times in the queue with each episode)? These and other factors contribute to truly understanding how the operator has treated the customer, which then helps better explain why a customer may be considered a promoter or detractor.

Why is understanding customers a two-way street? It is because two components make up that understanding: The behavior of the customer, and the behavior of the service provider. Two points of view that often result in entirely different outcomes than predicted by looking through a single lens.

May 29, 2012
Would Product upgrade alone solve the problem?

During one of my business travels recently, I met the Revenue Assurance & Fraud Management heads of few telco’s. There was one meeting in particular that struck me – let me call him Jack, the AVP of FM. Jack has been using a Fraud Management System(FMS) for close to 4 years & has certain business challenges to address. Jack was exploring the option of upgrading the FMS to tackle the challenges and needs.

Jacks’ primary challenge was to build a business case justification for FM upgrade to show the elusive RoI. Apparently, there have been challenges of his team detecting fraud, and he was of the belief that an upgrade will help address the fraud in new generation of services (which the current system is not capable of) and thus contribute to the RoI.

On probing further it was clear that he’s been under tremendous pressure from the higher-ups to showcase RoI, especially in the recent past due to tough macro-economic conditions. Some more questioning and discussions with his team members revealed that there have been (and are) many hurdles in performing their tasks –

a)      IT issues pertaining to system availability, performance, processing & tuning

b)      Knowledge issues in fine-tuning the rules and thresholds periodically

c)      People issues in understanding the domain and carrying out effective and smart investigations

While the operator is on a drive to introduce Next Generation services, more than 88% of the revenue still comes from traditional services – Voice, SMS/MMS, Roaming, Interconnect and GPRS. The top frauds also happen in these areas – https://www.cfca.org/fraudlosssurvey/

It was a revelation for Jack when the data was put up for discussion. It was also evident that an upgrade alone is not going to solve his problem. The need of the hour was an overhaul of the entire eco-system (address the 88%), along with the upgrade (to address the remaining 12%).

During the course of the discussion, I suggested a few best practices based on prior experience through the Managed Services engagements.

a)      Conduct an assessment to baseline the performance of the current function, including a SWOT analysis and detailing a roadmap for growth

b)      Basis assessment, build a business case for justification for skills/efficiency improvement and required technological upgrades

c)      As next step, strengthen the foundation of fraud prevention by improving on people, process by leveraging on best practices and experience from vendors and partners if needed

d)     Once the basics are addressed, mature to the next level by incorporating technological, process, procedures & skill upgrades

I also quoted one such Subex Managed Services engagement in India, where the operator was on an older version of the Fraud Management when the engagement started and has seen more than 2 times RoI within a year, followed by an upgrade to latest version. This helped them in the following ways:

a)      Optimize the resources as a first step and improve on fraud operations through skilled workforce, leveraging on existing technology and automation of repeatable tasks

b)      This resulted in significant financial savings, lowered operational and workforce risks, improved knowledge and enhanced business agility

c)      The highly scalable model for future growth also meant they were able to choose specific fraud related services and technological upgrades depending on its strategic objectives and business priorities

Jack, being the positive person, was able to appreciate a new perspective on his challenges and is looking forward to a detailed assessment to build a case for strengthening the FM team.

After this incident, I wonder are there more Jack’s out there with the right intention but not necessarily armed with the right tools?

April 25, 2012
Data Discrepancies Don’t Matter
Now, referring to the title, you may be thinking: That’s a rather cheeky thing to say given the high direct and indirect costs of errant data incurred by virtually all operators. You might cite the significant Opex penalty related to reworking designs and to service activation fallout. I get that. What about the millions of USD in stranded Capex most operators have in their networks? Check. My personal favorite comes from Larry English, a leading expert on information quality, who has ranked poor quality information as the second biggest threat to mankind after global warming. And here I was worried about a looming global economic collapse!

My point is actually that the discrepancies themselves have no business value. They are simply an indicator of things gone bad. The canary in the coal mine. These “things” are likely some combination of people, processes and system transactions, of course. Yet many operators make finding and reporting discrepancies the primary focus of their data quality efforts. Let’s face it, anyone with modest Excel skills can bash two data sets together with MATCH and VLOOKUP functions and bask in the glow of everything that doesn’t line up. Sound familiar?

For context, I am mostly referring to mismatches between the network and how the network is represented in back-office systems like Inventory—but the observations I will share can be applied to other domains. Data anomalies, for example, are all too common when attempting to align subscriber orders and billing records in the Revenue Assurance domain.

Too often, Data Integrity Management (DIM) programs start with gusto and end with a fizzle, placed on a shelf so that shinier (and easier!) objects can be chased. Why is this? Understanding that I am now on the spot to answer my own rhetorical question, let me give it a go.
- The scourge of false positives: There are few things as frustrating as chasing one’s tail. Yet that is the feeling when you find that a high percentage of your “discrepancies” are not material discrepancies (i.e. an object in the Network but not in Inventory) but simply mismatches in naming conventions. A DIM solution must profile and normalize the data that are compared so as not to spew out a lot of noise.
- The allure of objects in the mirror that are closer than they appear: OK, not sure this aphorism works but I trust you to hang with me. I am referring to misplaced priorities— paying attention to one (closer, easier) set of discrepancies while ignoring another set that might yield a bigger business impact once corrected. Data quality issues must be prioritized, with priorities established based upon clear and measurable KPI targets. If you wish to move the needle on service activation fallout rates, for example, you need to understand the underlying root causes and be deliberate about going after those for correction. Clearly, you should not place as much value on finding ‘stranded” common equipment cards as on recovering high-value optics that can be provisioned for new services.
- The tyranny of haphazard correction: I’m alluding here to the process and discipline of DIM. Filtered and prioritized discrepancies should be wrapped with workflow and case management in a repeatable and efficient manner. The goals are to reduce the cost and time related to correction of data quality issues. If data cleanse activities are unstructured and not monitored by rigorous reporting, the business targets for your DIM program are unlikely to be met.
- The failure to toot one’s own horn: Let’s say that your data integrity efforts have met with some success. Do you have precise measurements of that success? What is the value of recovered assets? How many hours have been saved in reduced truck rolls related to on-demand audits? Have order cycle times improved? By how much? Ideally, can you show how your DIM program has improved metrics that appear on the enterprise scorecard? It is critical that the business stakeholders and the executive team have visibility to the value returned by the DIM program. Not only does this enable continued funding but it could set the stage for “self-funding” using a portion of the cost savings.
- The bane of “one and done”: For a DIM program to succeed in the long run, I suggest drawing from forensic science and tracing bad data to underlying pathologies… i.e. people, process and/or system breakdowns. A formal data governance program that harnesses analytics to spotlight these breakdowns and foster preventive measures is highly recommended. The true power of DIM is in prevention of future data issues so that the current efforts to cleanse data will not simply be erased by the passage of time.
Identifying data discrepancies is a good first step. Correcting and preventing them is even better. Institutionalizing DIM via continuously measuring and reporting your successes… well, you get the idea.
April 18, 2012