Enterprise Systems Training Strategies: Knowledge Levels and User Understanding

Enterprise Systems Training Strategies: Knowledge Levels and User Understanding

Tony Coulson (California State University, San Bernardino, USA), Lorne Olfman (Claremont Graduate University, USA), Terry Ryan (Claremont Graduate University, USA) and Conrad Shayo (California State University, San Bernardino, USA)
Copyright: © 2010 |Pages: 18
DOI: 10.4018/joeuc.2010070102

Abstract

Enterprise systems (ESs) are customizable, integrated software applications designed to support core business processes. This paper reports research contrasting the relative effectiveness of two strategies for ES end-user training that differentially reflect the Sein, Bostrom, and Olfman (1999) hierarchical knowledge-level model. One strategy— procedural—involves training that targets the three lowest knowledge levels of the model (command-based, tool-procedural, and business-procedural); the other—tool-conceptual—involves training that also includes a higher knowledge level (tool-conceptual). A non-equivalent quasi-experimental design was used for groups of senior business students being trained to use an authentic ES. Performance measures were administered during training and ten days after training concluded. Both experiments demonstrated that training involving the tool-conceptual knowledge level leads to superior mental models, compared with training oriented toward lower knowledge levels, as expressed in the recollection and communication of ES concepts. Tool-conceptual knowledge-level training can be used to promote understanding and communication, and should be incorporated into training strategies for ES.
Article Preview

Introduction

Enterprise systems (ESs) are customizable, integrated software applications designed to support core business processes. Enterprise systems such as ERP, CRM and SCM often take years to implement, but unfortunately a significant number of ES implementations fail (Viehland & Shakir, 2005). Successful training strategies can help reduce failure (Wheatley, 2000). This study seeks to advance research in ES end-user training, examining strategies that could lead to more effective use of ESs and increase the chances of ES implementation success.

A large body of training research exists that relates to ES end-user training. From this literature, the Sein, Bostrom and Olfman (1999) hierarchical knowledge-level model (Figure 1) can serve as the basis for alternate ES training methods1. The model can be used to develop specific training approaches and methods across a wide variety of end-user training settings.

Figure 1.

Hierarchical knowledge-level model (adapted from Sein et al. 1999)

According to this model, training strategies should consider the types of trainees and IT tools on which they will be trained. The training methods should be designed using these inputs with the goal of achieving desired levels of knowledge, instead of focusing narrowly on skills and procedures (Sein et al., 1999). Table 1 characterizes ES end-user training outcomes in terms of knowledge levels.

Table 1.
Knowledge level outcomes for training (adapted from Sein et al. 1999)
          Knowledge Level          Focus          ES System Focus
          Command Based          Syntax and semantics          Learning the nuances of the system interface
          Tool Procedural          Combining commands to complete tasks          Learning the steps to enter and recall transaction data
          Bus. Procedural          Application of tool procedures to a task          Learning to complete and entire business process (i.e. procurement)
          Tool Conceptual          The big picture of what to do with the tool          Understanding workflow of the whole process and the organizational impacts
          Bus. Motivational          Reason to use          Business purpose of the system (e.g. integration, competitive necessity)
          Meta-Cognition          Learning to learn          Continuous learning cycle, ways to approach the learning system
Purchase this article to continue reading all 18 pages >

Complete Article List

Search this Journal:
Reset
Open Access Articles: Forthcoming
Volume 31: 4 Issues (2019): Forthcoming, Available for Pre-Order
Volume 30: 4 Issues (2018)
Volume 29: 4 Issues (2017)
Volume 28: 4 Issues (2016)
Volume 27: 4 Issues (2015)
Volume 26: 4 Issues (2014)
Volume 25: 4 Issues (2013)
Volume 24: 4 Issues (2012)
Volume 23: 4 Issues (2011)
Volume 22: 4 Issues (2010)
Volume 21: 4 Issues (2009)
Volume 20: 4 Issues (2008)
Volume 19: 4 Issues (2007)
Volume 18: 4 Issues (2006)
Volume 17: 4 Issues (2005)
Volume 16: 4 Issues (2004)
Volume 15: 4 Issues (2003)
Volume 14: 4 Issues (2002)
Volume 13: 4 Issues (2001)
Volume 12: 4 Issues (2000)
Volume 11: 4 Issues (1999)
Volume 10: 4 Issues (1998)
Volume 9: 4 Issues (1997)
Volume 8: 4 Issues (1996)
Volume 7: 4 Issues (1995)
Volume 6: 4 Issues (1994)
Volume 5: 4 Issues (1993)
Volume 4: 4 Issues (1992)
Volume 3: 4 Issues (1991)
Volume 2: 4 Issues (1990)
Volume 1: 3 Issues (1989)
View Complete Journal Contents Listing