A method for selecting processes for automation with AHP and TOPSIS

Organizations are more frequently turning towards robotic process automation (RPA) as a solution for employees to focus on higher complexity and more valuable tasks while delegating routine, monotonous and rule-based tasks to their digital colleagues. These software robots can handle various rule-based, digital, repetitive tasks. However, currently available process identification methods must be qualified to select suitable automation processes accurately. Wrong process selection and failed attempts are often the origin of process automation's bad reputation within organizations and often result in the avoidance of this technology. As a result, in this research, a method for selecting processes for automation combining two multi-criteria decision-making techniques, 'Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), will be proposed, demonstrated, and evaluated. This study follows the Design Science Research Methodology (DSRM) and applies the proposed method for selecting processes for automation to a real-life scenario. The result will be a method to support the proper selection of business processes for automation, increasing the success of implementing RPA tools in an organization.