Mobile data services are growing up spectacularly all over the world. Users have at hand more and more sophisticated devices every day, demanding progressively higher amount of data, higher speed and lower access time. Operators are forced to invest heavily to attend this demand. Achieving profitability on these investments is vital for Operator´s survival and development. For that achievement, two issues are of utmost importance: demand predictability and network performance planning. The first is roughly under operator´s control as mobile data demand is mostly driven by applications and devices capabilities. The later is – or should be – entirely under operator´s control.
This paper refers to network performance planning, meaning a two-dimensional feature composed by capacity (the amount of data that each individual network cell allows to transport) and quality for the user (a combination of speed and delay which drivers customer experience). The rationale behind Telconomics approach to solve this issue relies on the fact that mobile data technologies are far from being deterministic in its performance. More specifically, Telconomics states this is not possible to plan in advance the radio access network performance offered to its users but it is to determine it by empirical statistical processes which, in turn, allows for elaboration of what if scenarios, so network performance can be continuously improved to match real demand and eventually to anticipate to expected or desired demand.
That´s what we call real time intelligence applied to the mobile data access network. It is the basis for achieving one of the most important targets for Operators all over the world: “Obtain as much return as possible from investment in the network and focus it on real quality to the customer.”