GSC Conference – Meeting Leading International Wholesale Players in Historic Windsor

I’m sitting in the Spring sunshine (it’s the UK so it’s cold) preparing my talk for the GSC conference in Windsor which starts tomorrow. This is a great venue as it gets representation from major carriers globally mostly concerned  with Trading international traffic and the subsequent business processes that support that seemingly simple activity. Few thoughts are paramount, one of them is that I’m presenting on Thursday so there will be a lot of information sharing by then so I hope I would manage to glue the audience to their seats.

The theme of my presentation is Evolution of Partner Settlement.   I think that the apparatus, systems, structures and know how which allows carriers to trade voice minutes will soon be in demand to negotiate, set prices and monitor a whole range of services and not just voice.

One particular area I’m interested in is content settlement. How does the carrier (or a cable company) set a fair price with a content creator?  How does the content owner verify the final payment?   If it’s all about supply and demand, how do providers gauge demand and look at product performance? Who could have predicted that a Danish sub-titled crime thriller, The Killer series, would take the world by storm? ( I guess the writer!)

What strikes me is that what Telcos sell changes, but not how successful business runs.  I once worked in a toy shop in a particularly posh part of London. Our buyer made the company a fortune from buying Japanese pencils ( a bit like Hello Kitty) – everyone thought she was nuts. She also ceremoniously dumped the then unfashionable Kermit the frog.  This released floor space, which she crammed with pencils  and she watched point of sales like a hawk. Nowadays we have sophisticated systems such as  ours to do this. But the core things that buyer spoke about, attractive stock, great presentation, customer experience are all key elements of product management and content distribution.  Managing the content catalogue and getting value for the content creative and the CSP are critical.

So I’m hoping to have a great discussion about Partner Settlement with people this week about all the hot topics  IPX, Content, M2M, Mobile Money – don’t ever let anyone tell you billing is boring.

Blog more later. Have a good week.

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).


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.


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.


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.


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 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.

A Thorn in the Side? – Handling Over-the-top Content Demands

As I interact with more and more service providers about their network capacity issues, I’ve become sure about one thing – what worked before, isn’t really working anymore.  The CapEx requirement for network equipment just to keep up with the exponential growth in data traffic (i.e., Data Tsunami) is still not getting them ahead of significant congestion issues and customer impacting events.  Why? Traditional capacity management paradigms are not working.

Essentially, feedback from carriers of all sizes and types has exposed one of the most significant shifts in thinking regarding how to go about managing and planning for network capacity.  They know that the rules are all changing and today’s content demands are outpacing the CSPs ability to keep pace.  The first key question is how to get back in front of the capacity demand (we’ll talk about monetization next…stay tuned).  So, why aren’t today’s processes scaling?

  • CSPs use a multitude of human resources and manual processes to manage network capacity.   This may have scaled under slower and more predictable capacity growth curves, but thanks to services like You-Tube & Netflix, entire network capacity is shifting in quantum leaps.
  • Solutions provided by equipment vendors are often platform specific, and reinforce a silo approach to Capacity Management when a holistic view is needed.  Service demand congestion is a network phenomenon which doesn’t care about individual equipment vendors or devices.
  • CSP planning groups leverage data and make decisions based on systems which have 20 – 40% inaccuracy in comparison to the actual capacity availability in the network.
  • Today’s CSP solution approach is often homegrown where 90% of the time is spent on acquiring and understanding raw data.  As a whole, everyone is trying to answer the question of how to proactively eliminate the possibility of congestion, but most are still focused on addressing the symptoms and not preventing the problem

It is surprising to note that even top tier/technology leaders cannot accurately predict where and when capacity issues will impact their networks.  This lack of visibility hurts CSPs considerably because as per our own studies, network events are behind can account for up to 50% of customer churn in high value mobile data services.

Flattening the CapEx curve

And the Capacity Management problem doesn’t really end there; in many ways it’s like a supply chain process. Marketing owns the function of forecasting where service uptake will drive capacity needs across the network. When Marketing underestimates service uptake, there is a real and significant impact to potential revenue: On average, it can take about 3 months from when capacity is fully tapped in a Central Office (CO) to when new capacity can be added to your network.  During that time, customers expecting service availability become hugely frustrated and begin to churn.  Engineering groups are pushed into panic-mode, trying to react as fast as possible – often putting capacity in the wrong places due to inaccurate data – resulting in further congestion, service degradation, an inefficient use of capital.

The message from CXO’s is crystal clear – there is an urgent and dire need to find new ways of monetizing the data crossing their networks. This need is exacerbated with OTT content and net-neutrality. SLA and authentication based revenue models are absolutely dependent on knowing what types of content/services are traversing your network, how much capacity they consume, and how utilization is driven by your consumer’s interests and activities.  This type of analysis requires a critical and intelligent binding of network and services data with business data to truly assess the financial impact to the CSP. Many Business Intelligence (BI) solution leaders will lay claim to abilities here, but actually fall very short of the mark.  Instead, real experience suggests that solutions in the marketplace today either:

  • Can handle the financial aspects of your business but have no understanding of today’s network dynamics in terms of capacity issues and services;
  • Can handle parts of your network very deeply, but do not correlate or provide a holistic view at the service level; or,
  • Can collect some network and service level information, but have no ability to incorporate business data to understand the impact to the business – i.e,. cost, subscriber behavior, propensities

All the above challenges bring us to the inevitable question – what kind of approach does one take in order to tackle capacity management issues? How does one stop chasing traffic and focus on flattening the CapEx curve instead? In order to attain ‘Capacity Management Nirvana‘, a proactive and scalable approach needs to be adopted by CSPs. An approach which not only intelligently binds network and business strategies based on the Data Tsunami realities but also brings proactive and predictive capacity management to the table. At the end of the day, a CSP should have access to all their capacity, the ability to leverage real and immediate feedback on the change in capacity as service uptake increases, and finally, the right tools and intelligence to get in front of what’s coming.

To know more about how a Capacity Management solution can help you address the above issues, download the whitepaper “Energizing Smart Growth with Network Intelligence

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