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WiMax Operator's Manual

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182 CHAPTER 8 ■ NETWORK MANAGEMENT AND OSS<br />

provider for failing to meet the terms of the agreements—generally a reduction in the service<br />

fee. Incidentally, it is best to be scrupulous in such matters and to agree only to terms that can<br />

be met in normal circumstances. To be wildly overoptimistic regarding what the network can<br />

deliver is to verge upon fraud.<br />

Assurance<br />

Assurance OSS software refers to the management process of determining that changes in services<br />

and the corresponding changes in billing have in fact been carried out and, specifically,<br />

that stipulated service levels are being met.<br />

CRM<br />

Customer relations management (CRM) software as a product category encompasses a vast<br />

array of software offerings, by no means all of which are designed around the needs of telecommunications<br />

service providers.<br />

The term most commonly refers to software used in call centers by sales agents and<br />

telemarketers, though it can also include software for facilitating online transactions involving<br />

sales, modifications of services, and service requests.<br />

CRM will normally tie in with billing software and will also communicate with a central<br />

database of customer profiles and subscription information.<br />

Data Mining Software<br />

Data mining refers to a specialized type of analytical software that looks for patterns and relationships<br />

within the information contained in a comprehensive database, and it forms a class<br />

unto itself that is not directly connected with the larger customer relations division of OSS<br />

inasmuch as it does not involve flow-through procedures involving other software modules.<br />

In the case of telecommunications networks, data mining could be used for a number of<br />

purposes. The network operator may want to examine the demographic skew of certain service<br />

offerings as indicated by the existing customer base and then adjust marketing strategy<br />

accordingly. If, for instance, enterprises of a certain size or in a certain type of business tended<br />

to be frequent users of conferencing services, the network operator may want to construct a<br />

marketing campaign for acquainting similar types of subscribers with conferencing services on<br />

the theory that they will be apt to purchase such services. Or, if a certain demographic grouping<br />

tends to abuse flat-rate unlimited services, one may want to manage the network so as to<br />

throttle bandwidth to such users and put provisions for doing so in place before the commencement<br />

of service. Or, to cite yet another example, if a group defined by certain attributes<br />

recorded in the database is subject to unusually heavy churn (telecom jargon for customer<br />

turnover), one may decide to avoid active solicitation of individuals within that group or make<br />

special efforts to determine the source of the churn.<br />

Knowledge in the broadband access business is power, and data mining can provide network<br />

operators with the same kind of in-depth information of user preferences amassed by<br />

traditional market research companies. Even so, data mining has not been extensively used by<br />

independent operators and has remained largely the province of large incumbents (though it<br />

is by no means universal even there). Like all statistical techniques, data mining requires a reasonable<br />

sample to produce accurate results, so in a small network it is of dubious utility.

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