Return on Investment (roi) for Multi-Technology son juan Ramiro, Mark Austin and Khalid Hamied

7.4. Case Study: ROI for Self-Optimization

7.4.1. Self-Optimization and ROI Components

The kind of Self-Optimization covered in this chapter is conceived as an online, adaptive process that runs continuously and autonomously, i.e. with no human intervention at all. With this scheme, inputs are gathered from several sources (performance counters, current p arameter settings, alarms, call traces, etc.) and qualified decisions on how to modify the key parameter settings on a per network element (or even adjacency) basis are automatically made and implemented in order to adapt those settings to the varying environmental and traffic conditions, ensuring optimum performance. Manual execution of such process is typically u nfeasible due to the unrealistic engineering bandwidth requirements associated with it. Therefore, even though it is a fully autonomous process, there are no OPEX savings directly linked to automation, since these tasks are not typically carried out in the absence of SON.
Moreover, the presence of active Self-Optimization processes results in measurable quality improvements, which are translated to additional revenue and cash flow through reduced churn, which will be taken into account in this analysis. Apart from quality enhancement, the discussion of the benefits associated with Self-Optimization is going to be focused around the fact that a properly optimized network experiences a noticeable capacity increase (mainly on the radio side, but also in the transmission domain through increased trunking efficiency by means of load balancing techniques), which means that more traffic can be served with the same amount of HW. This capacity increase lowers the need for future HW and transmission expansions due to capacity reasons and therefore has a strong influence on the CAPEX and OPEX contributions to the different cash flows.
Although both Self-Planning and Self-Optimization reduce the CAPEX related to HW expansions, they do it by exploiting different mechanisms. Whereas Self-Optimization increases the amount of traffic that can be served with each radio equipment unit, Self-Planning avoids unnecessary investments by accurately calculating where and when additional capacity is going to be required.