The role of business analytics in the controllers and management accountants' competence profiles An exploratory study on individual-level data

Abstract

Purpose In recent years, the rise of big data has led to an obvious shift in the competence profile expected from the controller and management accountant (MA). Among others, business analytics competences and information technology skills are considered a ``must have'' capability for the controlling and MA profession. As it still remains unclear if these requirements can be fulfilled by today's employees, the purpose of this study is to examine the supply of business analytics competences in the current competence profiles of controlling professionals in an attempt to answer the question whether or not a skills gap exists. Design/methodology/approach Based on a set of 2,331 member profiles of German controlling professionals extracted from the business social network XING, a text analytics approach is conducted to discover patterns out of the semi-structured data. In doing so, the second purpose of this study is to encourage researchers and practitioners to integrate and advance big data analytics as a method of inquiry into their research process. Findings Apart from the mediating role of gender, company size and other variables, the results indicate that the current competence profiles of the controller do not comply with the recent requirements towards business analytics competences. However, the answer to the question whether a skills gap exist must be made cautiously by taking into account the specific organizational context such as level of IT adoption or the degree of job specialization. Originality/value The insights provided in this study extend the ongoing debate in accounting literature and business media on the skills changes of the controlling and MA profession in the big data era. The originality of this study lies in its explicit attempt to integrate recent advances in data analytics to explore the self-reported competence supplies of controlling professionals based on a comprehensive set of semi-structured data. A theoretically founded explanatory model is proposed that integrates empirically validated findings from extant research across various disciplines.