|© 2016 Black Swan Telecom Journal||•||protecting and growing a robust communications business||• a service of|
|Email a colleague|
You can never rest on your laurels in this business. People in revenue assurance, fraud management, and similar staff roles know full well they exist to support the business.
And while the business may be quite pleased with the revenue leaks you found yesterday, yesterday was yesterday. So if you expect those same internal business customers to remain happy, you must listen to their current needs, then deliver accordingly.
For example, many of the professionals using our RA and fraud management tools have told us their internal customers are making urgent requests for up-to-date analytics data to help them grow the business, not just protect revenue streams.
Why are they turning to RA/FM? And why are they doing so when those operators already have a data warehouse (DW)? Two reasons: faster response and superior integration.
Faster response is not simply a function of processing speed, but also platform flexibility. Being an IT-controlled platform, data warehouses are constrained by lots of factors: IT’s priorities, IT’s workload/ internal processes — even the data sources IT loads. By contrast, an RA/FM platform can be tuned to the needs of a small user group and quickly support new data sources. This greater flexibility often translates to a faster overall response — a key factor in dynamic markets like mobile where time equals money.
Now ideally a DW provides a fully integrated set of enterprise data for analysis -- the so-called “single version of the truth”. However, in practice, most service providers have multiple DWs and data marts each using different keys, making it hard to achieve that integrated view. An RA and FM implementation, though, already has a unified view of relevant data in a platform already paid for. So adding the ability to do real-time analysis makes expanding the role of an RA/FM a compelling choice.
Now you can bet that we at cVidya were excited to hear that our customers wanted us expanding the uses of our software platform. Yet we knew that if we expanded the product suite we needed to be very careful. We did not want to simply bolt on a generic business intelligence (BI) tool that requires the customer to figure out what data sources, reports, dashboards, and KPIs to pull together.
Our strong suit over the years at cVidya has been to simplify the analysis problem for our customers by embedding intelligence in our products. So the approach we settled on does exactly that -- it delivers use case-specific functionality in a new cross-product layer that cuts across all our software applications.
We think this cross-product layer approach greatly enhances the value of the existing RA/FM platform by allowing it to serve many other use cases.
Our layer is called cVidya Insight™ and it resides in each of our products. Our Revenue Assurance solution, MoneyMap has its own analytical tools and so is our Fraud Management solution, FraudView. In addition, for customers who have multiple product offering we can offer a cross product analytical view that utilizes views and insights from different sources and products.
The beauty of layering is that the extensive extracting, loading, normalizing and enrichment of data required for RA/FM doesn‘t have to be repeated. It’s ready to immediately serve up additional insights to the CFO (in uses such as profit/ margin assurance) or to equip marketing with the vital info it needs.
And because the dashboards, reports and KPIs are productized to support particular lines of business, the operator doesn‘t have to figure out what analysis and insights he needs because they are built in. This pre-configuration is what separates this approach from that of a general purpose BI tool. We need to stress here, that customers can still customize and create new ones per their specific demands.
Perhaps the best way to illustrate how a cross-product intelligent layer delivers value is to explain how we are using it in the new service area of LTE.
Monitoring and actions in LTE begin on the risk side. The CFO is alerted to problems over margins, exposure to revenue risks, etc. And since LTE is a relatively new line of business, the exposure and risks can be high as revenues are ramping up. The margins too will not be high in the beginning so all of these things must be continuously monitored.
Now it’s here where a fraud management platform comes in particularly handy in identifying customers who are taking unfair advantage of their price plans.
Once the fraud management team identifies the users abusing their data price plan, then they can use this info to define next steps with these customers such as getting those customers on alternative price plans/offering. Rather than cut service off or limit their quality of service, the remedy here is often to make an offer an increase bandwidth in return for agreeing to move to a more profitable arrangement.
At the same time, the revenue assurance team is analyzing different aspects of LTE services not only for the purpose of identifying revenue leakages but also in terms of profitability for different categories, such as price plans, sub services and 3rd parties costs and revenues, resulting in flagging certain LTE services for low margins. A thorough segment analysis is performed to understand how customers are consuming data traffic, monitoring the usage of OTT applications as well as verifying bills and checking settlement processes.
The marketing department seems to be especially keen on exploiting the RA/FM’s data gold mine, so we had several great discussions with marketing teams to understand their needs.
In fact, we developed a couple of different products for marketing. One of those integrate 3 pre-defined use cases in the areas of retention, price plans, and LTE/3G data, each with its own clear set of drills downs and dashboards.
So on the LTE dashboard; marketing can view the actual usage of customers -- how much data they are using per month, from which locations, what types of OTT and other content they are using — and also how much money they are generating.
This view was created by combining demographic and financial information so marketing can understand customer patterns and behavior. The marketing offer model goes one step further to calculate the next best offer/action for the individual customer, which can get complicated especially when the customer is using various devices or is billed off a shared data price plans where the usage or minutes of family members are aggregated.
We are certainly in the early stages of this market trend calling for a much wider use of the revenue analytics platforms designed primarily to protect revenues.
The good news is that our layering strategy will allow RA and FM departments to better utilize their current deployment and maximize the potential of their RA and FM systems as well as serve their demanding internal clients in marketing and finance.
It’s about combining applications and data sources from many directions. And in many cases, I’m sure, the layers will need to communicate across applications developed by other solution vendors and internal shops.
In the last 12 years our customers have enabled us to accumulate significant domain expertise on the business protection side of analytics. Yet going forward, we realize that success also hinges on our ability to blend both business protection and business growth analytics in ways that take our customers in whatever direction they need to go.
Copyright 2013 Black Swan Telecom Journal