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 support this vision, we introduce a data mining technique called recursive partitioning. We illustrate how it can be applied to a large customer costing and profit dataset to identify the characteristics that differentiate more and less profitable customers. We discuss how the output of the recursive partitioning algorithm (a binary decision tree) can be used to increase customer profitability and identify future profitable customers. We conclude by suggesting and discussing some of the obstacles and research opportunities that this vision presents to the accounting field.