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Revenue assurance maturity: perhaps it’s time for that concept to mature as well.
talkRA’s Eric Priezkalns and the TM Forum have both developed models for assessing the maturity of RA organizations. Independently, colleague David Sherick and I came up with our own Five Dimensional Model of Revenue Assurance -- yet another maturity guide.
But our conception of what the RA practice is about moves on. And that’s a healthy change that advances our art. As for myself, I find the more client engagements I have, the more insights I gain, and a few contracts later certain RA problems or functions loom much larger and more significant than I formerly thought.
One area I think we maturity modelers have failed to shine enough light on is corrections. Finding revenue leaks is wonderful stuff, but we also need to implement fixes to correct the historical issue and reduce the chance of further errors.
So in this column, I’d like to examine this area of RA corrections a bit.
RA problem identification and corrections are really two sides of the same coin.
On the mobile side, one of the standard reconciliations is between the HLR, the contract and the billing system. Over the years, RA departments have gotten pretty efficient at identifying the discrepancies, but the manual fixes to these problems are another story. Wouldn‘t it be handy to have an automated tool that could accurately make changes to the CRM, HLR / IN and Sales Order Systems?
On the fixed side, with leased circuits, one of the standard leakage measurement points is ensuring that network inventory matches what was ordered by customers. And finding mismatches leads to many areas of potential correction: fixing incorrect invoices; modifying facility orders, and making changes to recover stranded assets.
These mobile and fixed examples actually share much in common. Both situations call for comparing two different data sets and correcting one or another without introducing any further errors.
So what is the most likely source of correction those errors? You guessed it: the manual entry phase, whether it’s the classic mistyping of numbers, lack of training, people being hurried, or users just getting bored or distracted.
For years, we’ve recognized that manual systems are the source of so many data integrity problems, but our industry never seems to tackle this problem.
Walk through your various business processes, Prospect to Cash, Network Management, and so on, and see many local databases and spreadsheets in use. Why? Well, mainly because people do not consider the original source data to be accurate or fit for their purpose. At this point, you can begin to see one of the new challenges for RA: identifying sources of accurate data and ensuring that their accuracy is maintained.
Be honest — how many of you are seeing new manual billing processes sprouting up in your organisation? Quite a few of you, I suspect. When an innovative product or service is produced, marketing exerts pressure to get the product launched, and they are simply not going to let billing automation delay their time table. The result? Manual billing becomes an ugly, but necessary expedient.
This was certainly the case during the early days of GPRS — which is why the service was often given away for free. It was also the case for MMS back in the dark days, and I suspect that today’s advanced LTE services are also getting deployed faster because the invoicing is being handled manually.
Yet, as we all know, manual invoicing is manageable when you have only 10 subscribers, but as soon as the subscriber count mushrooms into the hundreds or thousands, it becomes unwieldy. Unfortunately, management usually finds more pressing things to spend its budget on than billing automation.
On the RA side, there is always the requirement to recalculate the bill. Sure, the tariffs need to be checked. But there other reasons, too. The Sales department wants to show the savings that would have been earned by a potential client. Sometimes the customer is on the wrong bundle so Customer Services needs to recalculate the bill with the correct bundle to calculate the credit. This simple kind of automation would benefit any number of departments.
Ah, but there’s a catch: the problem is usually not considered of sufficient weight or priority to warrant a project And since it was not part of the initial planning process, there’s no budget for it anyway. The other stumbling block is IT. Automated -- or even semi-automated -- interfaces into mission critical BSS and OSS systems raise a red flag. What if they should cause a system crash? Effectively, this means IT will never give you free reign in the design. Oh, and IT has neither the time nor budget to work on your project. In other words, good luck.
I have no simple solution for the problems I’ve just described. And since I’m not a software developer, I can only point to the usefulness of such a solution, but cannot build it on my own.
Yet from an RA Consultant’s perspective, wouldn‘t it be cool if you could walk into an organisation, look at any one of their problems, and deliver a solution within the normal timeframe of your contract? And wouldn’t it be nice if that solution was affordable and versatile enough that you could apply it to other areas as well?
Hence we arrive at the notion of a “Swiss Army Knife” RA solution. For those of you who don‘t know the name, the Swiss Army Knife is a portable all-purpose gadget made by Victorinox that comes with a wide range of tools folded into the body. There is a knife, but you can also get a pair of scissors, a file, a screwdriver — the high tech version even comes with an USB drive. In short, it’s a device to tackle many small jobs and that anyone can use.
So what would this RA Swiss Army Knife look like? Well, here’s a quick list of the functionality I’m looking for:
So, where do I get one of these tools? I wish I knew. The elements of such a multi-purpose tool are certainly available from the many software vendors serving our market, but pulling together a unified tool is probably a long ways off.
Yet the benefits are tantalizing. It could dramatically reduce the number of unrecognized errors and substantially lower an organization’s revenue risks.
NOTE: For further reading here, I suggest an excellent free book excerpt entitled, “Thirteen causes of enterprise data quality problems” by Arkady Maydanchik.
Copyright 2012 Black Swan Telecom Journal