The Cusp of a New Phase For Mobile Network Operators

By | October 19, 2015

Data Analytics and SONThe wireless industry is rapidly entering a phase of reduced spending on infrastructure. This is evident from the many operator discussions on their future plans and is inline with analysts forecast of peaking infrastructure spending at $23 billion this year. Deployments in in the US, Japan and Korea have taken their course, but still some recently acquired bands are due to be built (e.g. AWS in the US and 3.5 GHz in Japan). China will continue with LTE deployments as will lagging European operators. With most LTE infrastructure in place, the move to LTE Advanced is not as capital intensive, and I don’t believe that we cannot count on densification to significantly increase spending. With 5G years away, where will operators focus and what will they increase spending on?

The answer to this question from a traditional operational perspective points to increased investment in self-organizing network solutions (SON) as operators rally to improve performance to support rising number of subscribers on LTE networks, especially as 2G or 3G spectrum is refarmed for LTE services. While SON adoption has lagged, the SON ecosystem has been the seen of much M&A activity (Nokia acquiring Eden Rock most recently), leaving only a few independent SON vendors on the scene (such as Reverb, PI Works, Cellwize and Amdocs, which itself has acquired other independent SON provides Celcite and Actix over the past couple of years.

SON features and functions

SON features and functions

Another area of expected operator investments in related to data analytics which has been subject to much hype in recent years but with limited inroads to date as many big data initiatives in the telecom sector stopped at the piloting and experimentation stage. There are many reasons that precluded wide scale adoption of big data techniques. Perhaps the most important one is that the complexity of big data requires well-working interfaces with the operator organization such as the marketing-engineering interface. The business case for big data is often not clear as well as the value of data. Regulatory restrictions and compliance with privacy rights also worked to limit applicability. Operators do have important data to leverage centering on the “where” of the subscribers (i.e. geolocation data), but they have limited information on the “what” and the “how” which remains the advantage of the OTTs. In this space, collaboration between operators and OTTs is feasible although it has been very limited to date with the two camps taking confrontational stance. Nevertheless, operators have much to gain in the coming phase from implementing data analytics to improve services, reduce churn and retain subscribers, and increase revenues.

Big Data Analytics in the Context of Mobile Network Operators

Big Data Analytics in the Context of Mobile Network Operators [Source: Ericsson]

In fact, increasing revenues is the major driver for operators in the next phase. With EBITDA margins dipping into the 30% range from the 50% range, operators will be hard-pressed to make significant new investments. Having built an all-IP wireless networks based on LTE, the focus will be on monetizing the networks by creating new revenues streams through optimization of services and operations by leveraging information to gain insights into subscriber behaviors, needs, and wants.

Contract churn vs EBITDA

Contract churn vs EBITDA [Source: TEfficient]