Alex Leslie on Making Sense of Data

Look here for a great article from Alex Leslie on the relationship between revenue assurance and fraud management, and about how telcos struggle to make good use of their data.

I especially liked the anecdote about how T-Mobile UK put their RA and fraud teams in the same office so they would work efficiently together. The story ends:

Within six months they split them up.

Eric Priezkalns
Eric Priezkalns
Eric is the Editor of Commsrisk. Look here for more about the history of Commsrisk and the role played by Eric.

Eric is also the Chief Executive of the Risk & Assurance Group (RAG), a global association of professionals working in risk management and business assurance for communications providers.

Previously Eric was Director of Risk Management for Qatar Telecom and he has worked with Cable & Wireless, T‑Mobile, Sky, Worldcom and other telcos. He was lead author of Revenue Assurance: Expert Opinions for Communications Providers, published by CRC Press. He is a qualified chartered accountant, with degrees in information systems, and in mathematics and philosophy.

2 Comments on "Alex Leslie on Making Sense of Data"

  1. True – why?

    Same data, same ultimate goal, different types of people….

  2. Avatar Marcus Bryant | 27 Jul 2011 at 10:24 am |

    The question raised in the article:

    So why are operators so bad, so wretchedly awful, at using the data that washes through their systems on a daily basis?

    For me, this is pretty simple to answer.

    As an Industry we are so BAD at understanding it properly.

    As RA professionals we are all familiar with the typical lifecycle of this information, the systems and processes which enrich and transform it – from the basic ‘Switch to Bill Rec’, through Network, Mediation, Rating then Billing.

    It is rare to see these transformations documented in a coherent and intuitive manner:
    * We might see the system changes or data dictionary documenting the content of a given field in a given system and transformation performed upon it (if we are lucky this is accurate and up to date).
    * Additionally we may see for a given project or initiative (product/service implementation) a documentation of how the data to support the required functionality is transformed from end to end.

    What we don’t see, or typically have, is a proper metadata repository which is maintained and tracks our data from source at the network, through all its transformations to its end use, be it in a billing system, business intelligence repository or fraud/RA system.

    As a fairly extreme example of what I mean from one operator I worked with: In downstream systems, the reporting of customer handset use being based on the IMEI field in the rated CDRs. A reasonable assumption – the first digit sequence in the IMEI being the TAC FAC, used to uniquely identify the handset model. Not, however, if a rushed delivery to fulfil a marketing need caused the IT department to decide that overwriting the IMEI field with an IMSI was the least resistance route to rating certain SMS scenarios. A surprising number of those IMSIs matched to valid TAC FACs!

    If you cannot understand your data in the first instance, and its full end to end lifecycle, not just in general terms but at a detailed, field level from the Network to your downstream systems, it makes its use for Marketing Insight, Revenue Assurance or even Fraud so much more difficult and less reliable. We often talk about the CDR revenue stream as a company’s lifeblood – the reality is we often don’t know what our blood group is, or whether we have altered it at a genetic level as it pumps through the company’s veins.

    It is fine and admirable to use information to identify cross sell, upsell or even entirely new opportunities, as we often praise Tesco and its innovative use of Clubcards for doing within the BI world (ref. the dog food example in the article) but Telcos have a far more complicated relationship between the customer interaction with the service/product and the interpretation of that interaction from the data. In my experience, Telcos barely scratch the surface in terms of having a single resource (which should be system, rather than employee based) which can accurately perform that interpretation.

    Once Telcos genuinely understand their data, its complexity and lifecycle, not just scratching the surface with a general, high level, view then they will understand the true relationship between data and information. Only then can they usefully build the clever interpretative logic and algorithms to deliver true insight, value, security and most importantly; fully trust those insights.

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