Improving Purchase to Pay Process Efficiency with RPA using Fuzzy Miner Algorithm in Process Mining

Robotic process automation is a solution for automating human digital interactions to increase efficiency and reduce costs. We analyze the possible solutions of Robotic Process Automation (RPA) in the purchase to pay process dataset to measuring efficiency using process mining methods. We investigate 10% of 1,595,923 event logs and found that there was still a lack of automation in the purchase to pay process. Process mining will examine repetitive activities in purchase to pay process and discover analysis of vendors in a month, it was found that the use of automation was 4.5%, 3.72% and even 0% which should have been a repetitive process that could have been replaced with robots. The author analyzes purchase to pay data from the large multinational coating and paint companies in the Netherlands from BPIC 2019. The main motivation is to make the purchase to pay process more efficient so as to improve company performance by utilizing the application of RPA in terms of productivity, cost, speeds and error reduction.