Strategic modeling to improve services and operation to energy industries' customers

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• 作者：Carlos Alberto Fró ; es Lima^a ; ^b ; ^{froes@knbs.com.br" class="auth_mail" title="E-mail the corresponding author} ; Bernardo Marega Luz^a ; Sí ; lvia Tamada Takemoto^a ; Paulo Barisson Jr.^c ; Roberto Antô ; nio Terencio Tezzin^c ; ^{tezzin@cpfl.com.br" class="auth_mail" title="E-mail the corresponding author} ; Luciano E.A. Peres^c ; Tales Neves Anarelli^c ; Andrea Florencio da Silva^c
• 关键词：Customers' attendance ; Operational improvement ; Customers' demands anticipation ; Relationship ; Attendance strategies
• 刊名：Journal of Business Research
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：69
• 期：11
• 页码：4862-4869
• 全文大小：912 K

文摘

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.