In the old days mobile network management was just about studying usage patterns and predicting peak hour traffic.
But that was back when voice calls and a few texts made up the bulk of the traffic.
With the rise of the mobile broadband dongle, networks that were designed for phones are now being used by PCs that can gobble data at a rate unimaginable on a handset.
Indeed, the load on some networks from the modest installed base of mobile dongles is said to exceed that of all the other phone based services put together, including voice.
The knock-on effect of this sudden surge in mobile data usage could have a far reaching impact on the way networks are managed and customers are charged.
To begin with, data traffic is more varied than voice, comprising text, images, streaming video and music as well as a rich mix of downloads. To help attract users and justify 3G investments, networks have offered a range of “all you can eat” data tariffs that at least promise a certainty of pricing for the user.
But how much longer can the “all you can eat” tariff be viable? Network capacity is a finite resource and without investment in greater bandwidth through 3G hotspots, such as home femtocells or public picocells, the macro networks will become congested, slow and unusable.
Increasing tariffs is one obvious way of managing and controlling capacity but risks simply stifling growth. An alternatives is more intelligent pricing plans - a good place to start is a far greater understanding of what mobile users are doing, when they are doing it and what the user experience is really like at the sharp end.
This information makes it possible to intelligently adjust tariffs and service levels themselves to better meet the needs of different customer groups. In other words, tariffs need to reflect what people do and should be presented in service terms rather than just (frankly unintelligible) data download limits.
Of course, acquiring such detailed knowledge remains a challenge. Simple user surveys don’t give enough detail and are expensive to deploy, so network operators need to look elsewhere. Two techniques are emerging – intelligent network monitoring and device level monitoring.
Network monitoring enables operators to understand the traffic on the network. Device-level monitoring allows them to understand the usage patterns of individual customers (anonymously) in order to categorise usage behaviours and spot patterns.
For example, if video and music are congesting the network at peak times operators can use this customer knowledge to design attractive new packages that encourage overnight downloads and so balance the load.
By using direct measurement to understand usage and customer needs, operators can combine tariff packages and investment decisions to optimise the service offering for their customers. And if you can do that, you have a better than average chance of running a successful and profitable network.
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