2015
DOI: 10.2308/isys-51180
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From Bean Counters to Bean Growers: Accountants as Data Analysts—A Customer Profitability Example

Abstract: Extensive data mining and analytics (DM&A) are increasingly requisite for companies to be competitive in this age of information. This demand, combined with (1) accountants' reputation for understanding and generating quality data, and (2) the increased accessibility of DM&A tools, has created a unique opportunity for accountants to play a larger strategic role in their organization. We argue that accountants should own and drive a larger part of the DM&A that occurs in their organization. To suppo… Show more

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Cited by 17 publications
(15 citation statements)
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“…For example, Krahel and Titera (2015, 411) describe the technological advances that can “enable faster and more articulate data collection and transmission” and can improve costing, present value calculations, and estimates. Brown‐Liburd et al (2015) acknowledge that it is necessary to use new tools to harness these large quantities of data, and Gray and Debreceny (2014) provide an example by explaining how data mining can facilitate auditors' work when clients have large quantities of electronic data (also see Pickard and Cokins 2015 and Perols et al 2017). Schmidt et al (2020) investigate the reluctance of some accountants to adopt data analytics in spite of these benefits.…”
Section: Theoretical Underpinningsmentioning
confidence: 99%
“…For example, Krahel and Titera (2015, 411) describe the technological advances that can “enable faster and more articulate data collection and transmission” and can improve costing, present value calculations, and estimates. Brown‐Liburd et al (2015) acknowledge that it is necessary to use new tools to harness these large quantities of data, and Gray and Debreceny (2014) provide an example by explaining how data mining can facilitate auditors' work when clients have large quantities of electronic data (also see Pickard and Cokins 2015 and Perols et al 2017). Schmidt et al (2020) investigate the reluctance of some accountants to adopt data analytics in spite of these benefits.…”
Section: Theoretical Underpinningsmentioning
confidence: 99%
“…through simulations of the planning phases, but also encourage themselves to accompany them critically, in order to distinguish themselves from the newly professional area "Data Scientist" [6]. Pickard down strategic relationships from the self-generated data [38]. Technological progress with new tools would make it possible to prepare better decisionmaking bases [39].…”
Section: Literature Reviewmentioning
confidence: 99%
“…However, this leads to a need of methodological and professional competences as well as a thorough understanding of the relationships. Especially the article of Pickard and Cokins resulted in the thesis, that MAs have so far barely developed competences to track down strategic relationships from the self-generated data [38]. Gaensslen explicitly points to emerging knowledge in the areas of statistics and information technology [42].…”
Section: Proposition 3: Current It Competencies Of Mas Do Not Meet Thmentioning
confidence: 99%
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“…Mastering Predictive Analytics, MAs have the opportunity to own, analyze and drive a larger part of an organization's data, using procedures arraying from simple financial ratios to more forward-thinking techniques such as regression, clustering and factor analysis (Cokins 2014;Pickard and Cokins 2017). Thus, Prescriptive Analytics goes beyond the Predictive Analytics by endorsing one or more recommendation and solution and displaying the potential outcome (Appelbaum et al 2017).…”
Section: Challenges To Adapt the Ma's Skills To The New Tasks And Responsibilities Regarding Bd And Damentioning
confidence: 99%