Tag Archives: telco

Imagine A New Sheriff In Town

As we renew or reinvent ourselves for 2015, I wanted to share a case of “imagine if” with you and combine it with the narrative of an American frontier town out West, trying to find a new Sheriff – a Wyatt Earp.  In this case the town is a legacy European communications firm and Wyatt and his brothers are the new managers – the change agents.

management

Is your new management posse driving change?

Here is a positive word upfront.  This operator has had some success in rolling outs broadband internet and IPTV products to residential and business clients to replace its dwindling copper install base.  But they are behind the curve on the wireless penetration side due to the number of smaller, agile MVNOs and two other multi-national operators with a high density of brick-and-mortar stores, excellent brand recognition and support infrastructure.  Having more than a handful of brands certainly did not make this any easier for our CSP.   To make matters even more challenging, price pressure is increasingly squeezing all operators in this market.  The ones able to offset the high-cost Capex for spectrum acquisitions and upgrades with lower-cost Opex for running the network and maximizing subscriber profitability, will set themselves up for success (see one of my earlier posts around the same phenomenon in banking).

Not only did they run every single brand on a separate CRM and billing application (including all the various operational and analytical packages), they also ran nearly every customer-facing-service (CFS) within a brand the same dysfunctional way.  In the end, they had over 60 CRM and the same number of billing applications across all copper, fiber, IPTV, SIM-only, mobile residential and business brands.  Granted, this may be a quite excessive example; but nevertheless, it is relevant for many other legacy operators.

As a consequence, their projections indicate they incur over €600,000 annually in maintaining duplicate customer records (ignoring duplicate base product/offer records for now) due to excessive hardware, software and IT operations.  Moreover, they have to stomach about the same amount for ongoing data quality efforts in IT and the business areas across their broadband and multi-play service segments.

Here are some more consequences they projected:

  • €18.3 million in call center productivity improvement
  • €790,000 improvement in profit due to reduced churn
  • €2.3 million reduction in customer acquisition cost
  • And if you include the fixing of duplicate and conflicting product information, add another €7.3 million in profit via billing error and discount reduction (which is inline with our findings from a prior telco engagement)

Despite major business areas not having contributed to the investigation and improvements being often on the conservative side, they projected a 14:1 return ratio between overall benefit amount and total project cost.

Coming back to the “imagine if” aspect now, one would ask how this behemoth of an organization can be fixed.  Well, it will take years but without management (in this case new managers busting through the door), this organization has the chance to become the next Rocky Mountain mining ghost town.

Busting into the cafeteria with new ideas & looking good while doing it?

Busting into the cafeteria with new ideas & looking good while doing it?

The good news is that this operator is seeing some management changes now.  The new folks have a clear understanding that business-as-usual won’t do going forward and that centralization of customer insight (which includes some data elements) has its distinct advantages.  They will tackle new customer analytics, order management, operational data integration (network) and next-best-action use cases incrementally. They know they are in the data, not just the communication business.  They realize they have to show a rapid succession of quick wins rather than make the organization wait a year or more for first results.  They have fairly humble initial requirements to get going as a result.

You can equate this to the new Sheriff not going after the whole organization of the three, corrupt cattle barons, but just the foreman of one of them for starters.  With little cost involved, the Sheriff acquires some first-hand knowledge plus he sends a message, which will likely persuade others to be more cooperative going forward.

What do you think? Is new management the only way to implement drastic changes around customer experience, profitability or at least understanding?

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Posted in Big Data, Business Impact / Benefits, CIO, CMO, Customer Acquisition & Retention, Customer Services, Customers, Data Governance, Data Integration, Data Quality, Enterprise Data Management, Governance, Risk and Compliance, Master Data Management, Operational Efficiency, Product Information Management, Telecommunications, Vertical | Tagged , , , , , , , , , | Leave a comment

Understand Customer Intentions To Manage The Experience

I recently had a lengthy conversation with a business executive of a European telco.  His biggest concern was to not only understand the motivations and related characteristics of consumers but to accomplish this insight much faster than before.  Given available resources and current priorities this is something unattainable for many operators.

Unlike a few years ago – remember the time before iPad – his organization today is awash with data points from millions of devices, hundreds of device types and many applications.

What will he do next?

What will he do next?

One way for him to understand consumer motivation; and therefore intentions, is to get a better view of a user’s network and all related interactions and transactions.  This includes his family household, friends and business network (also a type of household).  The purpose of householding is to capture social and commercial relationships in a grouping of individuals (or businesses or both mixed together) in order to identify patterns (context), which can be exploited to better serve a customer a new individual product or bundle upsell, to push relevant apps, audio and video content.

Let’s add another layer of complexity by understanding not only who a subscriber is, who he knows and how often he interacts with these contacts and the services he has access to via one or more devices but also where he physically is at the moment he interacts.  You may also combine this with customer service and (summarized) network performance data to understand who is high-value, high-overhead and/or high in customer experience.  Most importantly, you will also be able to assess who will do what next and why.

Some of you may be thinking “Oh gosh, the next NSA program in the making”.   Well, it may sound like it but the reality is that this data is out there today, available and interpretable if cleaned up, structured and linked and served in real time.  Not only do data quality, ETL, analytical and master data systems provide the data backbone for this reality but process-based systems dealing with the systematic real-time engagement of consumers are the tool to make it actionable.  If you add some sort of privacy rules using database or application-level masking technologies, most of us would feel more comfortable about this proposition.

This may feel like a massive project but as many things in IT life; it depends on how you scope it.  I am a big fan of incremental mastering of increasingly more attributes of certain customer segments, business units, geographies, where lessons learnt can be replicated over and over to scale.  Moreover, I am a big fan of figuring out what you are trying to achieve before even attempting to tackle it.

The beauty behind a “small” data backbone – more about “small data” in a future post – is that if a certain concept does not pan out in terms of effort or result, you have just wasted a small pile of cash instead of the $2 million for a complete throw-away.  For example: if you initially decided that the central lynch pin in your household hub & spoke is the person, who owns the most contracts with you rather than the person who pays the bills every month or who has the largest average monthly bill, moving to an alternative perspective does not impact all services, all departments and all clients.  Nevertheless, the role of each user in the network must be defined over time to achieve context, i.e. who is a contract signee, who is a payer, who is a user, who is an influencer, who is an employer, etc.

Why is this important to a business? It is because without the knowledge of who consumes, who pays for and who influences the purchase/change of a service/product, how can one create the right offers and target them to the right individual.

However, in order to make this initial call about household definition and scope or look at the options available and sensible, you have to look at social and cultural conventions, what you are trying to accomplish commercially and your current data set’s ability to achieve anything without a massive enrichment program.  A couple of years ago, at a Middle Eastern operator, it was very clear that the local patriarchal society dictated that the center of this hub and spoke model was the oldest, non-retired male in the household, as all contracts down to children of cousins would typically run under his name.  The goal was to capture extended family relationships more accurately and completely in order to create and sell new family-type bundles for greater market penetration and maximize usage given new bandwidth capacity.

As a parallel track aside from further rollout to other departments, customer segments and geos, you may also want to start thinking like another European operator I engaged a couple of years ago.  They were trying to outsource some data validation and enrichment to their subscribers, which allowed for a more accurate and timely capture of changes, often life-style changes (moves, marriages, new job).  The operator could then offer new bundles and roaming upsells. As a side effect, it also created a sense of empowerment and engagement in the client base.

I see bits and pieces of some of this being used when I switch on my home communication systems running broadband signal through my X-Box or set-top box into my TV using Netflix and Hulu and gaming.  Moreover, a US cable operator actively promotes a “moving” package to help make sure you do not miss a single minute of entertainment when relocating.

Every time now I switch on my TV, I get content suggested to me.  If telecommunication services would now be a bit more competitive in the US (an odd thing to say in every respect) and prices would come down to European levels, I would actually take advantage of the offer.  And then there is the log-on pop up asking me to subscribe (or throubleshoot) a channel I have already subscribed to.  Wonder who or what automated process switched that flag.

Ultimately, there cannot be a good customer experience without understanding customer intentions.  I would love to hear stories from other practitioners on what they have seen in such respect

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Posted in Business Impact / Benefits, Complex Event Processing, Customer Acquisition & Retention, Customer Services, Customers, Data Integration, Data Quality, Master Data Management, Profiling, Real-Time, Telecommunications, Vertical | Tagged , , , , , , , , , | Leave a comment

The Future of Applications (4): Transforming to a Data-Centric Enterprise

This is my fourth blog in a series on the subject of “Informatica & Applications”.  You can read my previous blogs here:

In the era of big data we are seeing “big” changes in how customers are collaborating.  These changes are forcing enterprises to review how they interact with their customers and transform their business processes.

For too long we have built applications that treat human beings as impersonal entities – account numbers in banking; telephone numbers in telcos; and social security numbers in healthcare.  A big lesson that the social network is teaching us is that we all want to be treated as human beings.  We want to be appreciated for who we are, and that is not an asset on a balance sheet! (more…)

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Posted in Big Data, Master Data Management | Tagged , , , , , | Leave a comment