Human-computer interaction and role allocation in information-intensive work processes: Robotic process automation in financial administration work

Abstract

The aim of this study is to provide a more detailed view into how the interplay between human and computer manifests itself in contemporary information-intensive work processes, specifically in financial administration work.

Literature about information-intensive work, distributed cognition, mindful and mindless action, and epistemic and pragmatic action are reviewed to provide a thorough understanding about the cognitive processes, physical actions, and data processing activities required to carry out work tasks and processes.

This study follows qualitative case study and grounded theory methods for inductive theory-building, and uses semi-structured interviews and direct user observation as research data collection techniques. One of the Case Company X’s business units is examined in the empirical part of the study, which provides a view into information-intensive tasks and processes in financial administration shared service centre. Financial administration with its various rule-based tasks and processes is an ideal field of work to study, as new technologies such as robotic process automation and machine learning can be implemented effectively to the tasks and processes that follow to large extent certain step-by-step procedures.

By analysing the gathered data, it made possible to characterise many common financial administration tasks with certain characteristic profiles. This allowed to identify in which tasks human labour can be augmented or substituted with automation, but also what are human agents’ areas of strength.

As this study shows, automation tools can be best applied to tasks that involve mindless, rule-based processing of data and information. If such task is also considered to be in a support role and requiring merely pragmatic actions to carry out the tasks, it is even more potential candidate for automation. However, if a task calls for applying judgment mindfully, and also requires epistemic actions to perform it, then a human agent should carry out such task.

Based on the existing literature and empirical findings, a framework is formed that illustrates contemporary information-intensive operations on a general level. These insights and findings provide a new theoretical base to expand on, and clarify for managers what is the best course of action to take when automating information-intensive tasks and processes.