Bibliographic citations
Rodriguez, A., Cieza, M. (2023). Modelo para seleccionar procesos financieros a automatizar con RPA a través de técnicas de process mining en una empresa de consumo masivo [Tesis, Universidad Peruana de Ciencias Aplicadas (UPC)]. http://hdl.handle.net/10757/669017
Rodriguez, A., Cieza, M. Modelo para seleccionar procesos financieros a automatizar con RPA a través de técnicas de process mining en una empresa de consumo masivo [Tesis]. PE: Universidad Peruana de Ciencias Aplicadas (UPC); 2023. http://hdl.handle.net/10757/669017
@misc{sunedu/3472875,
title = "Modelo para seleccionar procesos financieros a automatizar con RPA a través de técnicas de process mining en una empresa de consumo masivo",
author = "Cieza Anchahua, Maritza Lorena",
publisher = "Universidad Peruana de Ciencias Aplicadas (UPC)",
year = "2023"
}
This project aims to satisfy the need to integrate the disciplines of Process mining and Robotic Process Automation (RPA) to identify criteria for selecting suitable processes to automate. Currently, companies are trying to optimise their financial fronts with RPA; however, the selection of processes to automate does not consider the maturity and standardisation of their processes, specifically with process mining tools. This means that the results expected by the business in economic terms are not achieved. To carry out this project, different models for processes selection to automate were analysed. From this point, the strengths and points of improvement of each model were identified to make a proposal that encompasses good practices and meets the needs of the business. The proposed solution consists of 3 processes: process mining, selection and prioritisation, RPA. Each process has different sub-processes with deliverables, tools to be used and participants. The added value of this model is the value dimension sub-process that helps to monetise the automation initiatives through the efficiency matrix. The model was validated by 6 experts in process automation projects in different areas and the economic feasibility of 2 processes was also carried out, giving a payback period less than 2 years.
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