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Intelligence & Analytics

Heavy Lifting Analyst Notes
Heavy Lifting Analyst Notes
Heavy Lifting Analyst Notes
8/6/2010
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Business intelligence (BI) will play a pivotal role in the success of telecom operators. Integrated BI solutions will not only provide operators with real-time intelligence, but also help them to maximize their revenue potential from a short window of opportunity.

Integrated BI solutions can potentially help operators to address some of their most pressing issues, such as:

  • Providing customer profitability analysis and end-to-end visibility for new product rollouts
  • Providing deep analysis of a customer's information and needs – even in real time, if it's important to the operator – creating greater service value and preventing churn
  • Helping operators minimize fraud and revenue leakage by integrating closely with billing, revenue assurance, mediation, etc., platforms
  • Helping operators provide real-time customer assistance
  • Providing tools for operators to optimize network resources and offload traffic
  • Improving customer experience by reducing network outages, allowing operators to keep customers happy with fewer outages and keep opex down by reducing network repairs
  • Working closely with BSS platforms to provide a 360-degree view of subscribers and their services
  • Providing better forecasting for new product rollouts


Let's look at couple of very popular applications of BI that can provide significant help in meeting operators' goals around opex/capex reduction and churn avoidance.

In the context of fulfillment of NGN services, accurate network capacity planning and trending is becoming critical. On-demand, bandwidth-intensive service requires dynamic, real-time allocation of network resources across the end-to-end network infrastructure. During network infrastructure expansion, the planning organization should be able to carefully target capacity growth to ensure it appropriately addresses current and developing shortfalls.

It helps in justifying the need for a less physical build, which directly helps in capex savings, reducing overhead, and saving time on field service, planning, and project management. Real-time BI solutions can play a central role in accurate, realistic, and proactive network capacity planning and trending capabilities, which will not only enable correct sizing of the future network, but also help service providers reduce capacity shortfalls, minimize order fallout, and increase efficiency by identifying underutilized network resources.

One other important BI use case revolves around the ability to deal with unstructured data. The ability to correlate unstructured responses to questions – as well as analyze call-center interactions and other input sources, such as blogs, forums, email, social networking sites, chat, call center transcripts, and customer feedback forums – helps operators to enrich their understanding of their customers' perception of their services. BI solutions based on various inputs work through pattern recognition, extraction, and various other techniques, adding value to the carrier's BI strategy.

Social network analysis (SNA) is becoming extremely popular among wireless operators. Although many operators are wary of coming out to openly discuss how they are using this technique because of potential backlash over subscriber privacy issues, this remains one of the popular uses of BI. SNA is a type of analytical scoring system that enables service providers to perform CDR, IPDR, etc., analysis to identify social calling circles among friends and families.

Such analysis will have both defensive and offensive implications: From an offensive perspective, this analysis can help operators target or up-sell offers based on customer preferences and what games or applications are popular among the subscriber's circle of trust. From a defensive perspective, SNA allows operators to identify calling patterns and the influencer in a specific social group, and develop algorithms to help them calculate how that influencer churning would affect the rest of the social circle.

They next step for operators is to determine which customers they actively want to keep, and hence execute compelling marketing campaigns and offers to communicate with and deter potential churners. The churn event for the rest of the social circle typically occurs within four to seven days after an influencer leaves for another provider, so time is of the essence when providing retention offers or general communications to potential churners.

SNA certainly raises important questions regarding whether it borders on an invasion of subscribers' privacy. Without trying to get into that debate, it should suffice to say that we always knew Big Brother was watching!

— Ari Banerjee, Senior Analyst, Heavy Reading

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User Rank: Light Beer
12/5/2012 | 4:27:41 PM
re: Intelligence & Analytics


In theory, a slam dunk. But how to achieve the end goal?


I'm sure the operators will spend 6 months trying to figure whether they can achieve these aims by tweaking the in-house systems they already have. once they realize they can't, or that Bob who did the code retired 5 years ago.


Then they go to the vendors, who tell them the only way to achieve this is a massive install and replace operation that will cost tens of millions. Or, if the vendor doesn't have a large professional services team, a bolt-on that can be integrated over the course of nine months that requires 20 people to live on the premises as they suck data out of old systems and try to feed it into the new ones...


Is there a SPIT vendor called Rock'n'Hardplace Ltd., by any chance? 

abanerjee
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abanerjee,
User Rank: Moderator
12/5/2012 | 4:27:29 PM
re: Intelligence & Analytics


Agreed, it is easier said than done. However to tame the elusive cstomer experience beast these concepts will become table stakes. Without a doubt operator's success will be based upon intelligent decision making capability using already existing data. Smart algorithms using laws of probability will act as crucial underpinning. Top line BI vendors like SAS, SAP (Business Oblects), IBM, Microstrategy, Ventraq, Oracle, HP etc need to work with operators and provide cost effective data rationalizing mechanisms with embedded intelligence to impart this competitive intelligence.

digits
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digits,
User Rank: Light Beer
12/5/2012 | 4:27:26 PM
re: Intelligence & Analytics


Totally. The first vendor/integrator to show it can REALLY deliver against promises and make a REAL difference to opex and customer experience strategy without forcing a carrier into a proprietary dead end will clean up. It's all about who can figure out the implementation model first. (I know that every service provider is different, but there is also a lot of commonality.)

shygye75
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shygye75,
User Rank: Light Sabre
12/5/2012 | 4:27:24 PM
re: Intelligence & Analytics


Clearly there's much to be gained from BI initiatives. The big issue is whether a set of new processes can have a positive effect on organizational efficiency without creating a new set of problems. Network operators have been slow to adopt BI in part because they don't know what those side-effects are. This opens the door to the era of the "hollow operator" -- the outsourcing of many or most network operations to trusted partners from the telecom and IT supplier sectors.

jtrembley
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jtrembley,
User Rank: Light Beer
12/5/2012 | 4:27:03 PM
re: Intelligence & Analytics


Many BI projects have failed miserably. The focus has been on storing and managing the data and not how insights gained from BI drive actions. The move to more real-time BI is needed as relying purely on historical reporting does not always accurately reflect what is happening right now. That said, how mining data for insights triggers human or automated actions is what will lead CSPs to find it invaluable. This presumes BI solutions get smarter over time and detect patterns and anomalies to drive actions against them.


Most vendors today focus on selling a platform and rely on the tried and true model of garbage in/garbage out which does not deliver actionable results. The trend towards real-time BI can exacerbate the problem. For any BI to become meaningful it has to help CSPs dynamically make decisions that are both timely (when they need to make it) and accurate (based on complete and current data).

jasffox
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jasffox,
User Rank: Light Beer
12/5/2012 | 4:26:07 PM
re: Intelligence & Analytics


We saw this issue again and again and three years ago took the leap to boot-strap a solution that addresses big data, gloabal data and real-time data holisitically.  The result was DataRoket (www.dataroket.com). 


Many thought that we would have no chance and that no one cared about integrated global views (everyone has a data warehouse) or real-time (who needs real-time sounds like a small market). We launched 6 months ago, with no marketing or even much of a sales team and our first customers are our biggest fans.


Glad to see others feel that the time for such a solution is now.

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