- مبلغ: ۸۶,۰۰۰ تومان
- مبلغ: ۹۱,۰۰۰ تومان
Continuous analyses of demanded services at the energy companies are the shortest path to recognize and anticipate customers' requests, reinforce and manage the communication and operational flows. Energy utilities need to increase their operational efficiency concerning costs and agility to improve useful media and evaluate customers' expectations and requirements. Operational effectiveness must pursue the demands, considering the amount of services that the companies provide at their relationship channels, the communication facilities and the systems' infrastructure. The companies need to organize a huge amount of historical and online data to represent and forecast customers' relationship scenarios. Resources evaluation ensure regional requirements and weather conditions best attendance response, adequately addressing faults at the energy distribution grid, motivate customers to use alternative media and improve relationship channels. Reaching this scenario, big data treatment techniques provide the necessary agility to achieve the monthly/hourly volume of data (millions of registers per month) and permit communication clusters' views.
This work provides a new process to recognize customers as decision makers, choosers and hirers of services, preparing paths to the new relationship now arising with energy companies' smart grid (0. The work retries products/new services management and differentiates communication with the buyers and their needs (Kotler et al., 2010). The paper attempts to restructure the model of service conditions care and provisioning which suites to (or points out) the customers' specific needs and regional characteristics. From the operational point of view, the recognition of the requested services in each attendance channel and improvement of knowledge of costumers/consumers expectations do, or will do, the differentiation to a better communication. The analyses performed additionally contribute to improve friendly systems, registering and accounting of the customer requests with greater accuracy.