Look carefully at the latest press release from Subex and you will find it raises some intriguing questions about the purpose of revenue assurance. On the surface of it, we hear a typical good news story: ‘leading SE Asian operator’, ‘successful implementation’, ‘now processing over 100 million CDRs a day’, ‘provides unprecedented automated correction capabilities’. But hold on… how do we feel about those last two statements when read together? There is nothing wrong with processing lots of data – well done to everyone involved. Unprecedented automated correction sounds good too, but what does it mean? The meaning is not obvious because, after all, this is unprecedented. One likely meaning, if this is applied to 100 million CDRs per day, is that data is being manipulated without human oversight. On the one hand, this can be a good thing. If there is something wrong with the data, then fix it as quickly and cheaply as possible. On the other hand, it begs a question about the role of RA, especially if we believe that RA has something to do with better operational efficiency. If it is efficient to automatically correct the errors in data, then why is it not more efficient to change systems so they produce the correct data in the first place?
100M CDRs per day + Auto Correction = ?
Look carefully at the latest press release from Subex and you will find it raises some intriguing questions about the purpose of revenue assurance. On the surface of it, we hear a typical good news story: 'leading SE Asian operator', 'successful implementation', 'now processing over 100 million CDRs a day', 'provides unprecedented automated correction capabilities'. But hold on... how do we feel about those last two statements when read together? There is nothing wrong with processing lots of data - well done to everyone involved. Unprecedented automated correction sounds good too, but what does it mean? The meaning is not obvious because, after all, this is unprecedented. One likely meaning, if this is applied to 100 million CDRs per day, is that data is being manipulated without human oversight. On the one hand, this can be a good thing. If there is something wrong with the data, then fix it as quickly and cheaply as possible. On the other hand, it begs a question about the role of RA, especially if we believe that RA has something to do with better operational efficiency. If it is efficient to automatically...
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I am pondering organisations’ capacity and capability to correct root cause issues. We are all familiar with the project office process to follow for system changes. These get prioritised and allocated to resources, which often don’t exist. Me thinketh that if a tool such as Subex’ can auto correct a known glitch, the CSP would opt to make use of that until they have time and resources to allocate to the proper correction.
The down side, and we all know this too, is that we never get around to doing those root cause fixes. Why? Because there is a working workaround, so let’s spend our persistent shortage of resources on something for which there is no workaround.
This sounds a bit like the unintended fruits of RA tools. Perhaps vendors should use that as a selling point :-D I know. This is fundamentally wrong, but it is also real life.
You’re right about real life getting in the way of our ideals, even when it comes to ideals about how to run a business. The point I keep returning too – perhaps with boring regularity – is whether RA has a tendency to turn itself into part of the problem, not part of the solution. I see error as being driven by complexity. That means any philosophy which is designed to counter error and improve efficiency must also address the root cause of error, which is complexity. So RA, if it is to have a coherent philosophy, and not just pay lip service to addressing root causes, must look to find long-term solutions that reduce complexity, instead of adding to it. The danger with the formulation you have identified is that RA becomes part of the complex processing chain – so who is assuring the part that RA now plays in this processing chain?
100 million is not a lot,
its not even tier one