Elsevier

Information & Management

Volume 44, Issue 7, October 2007, Pages 626-634
Information & Management

Rethinking ERP success: A new perspective from knowledge management and continuous improvement

https://doi.org/10.1016/j.im.2007.05.006Get rights and content

Abstract

Most IS research about ERP implementation stops short at system start-up and seldom addresses post-implementation issues. However, ERP implementation is a continuous improvement effort and continued efforts after system start-up will influence the ultimate success of an ERP implemented system. We defined a four-phase ERP refinement model that incorporated knowledge management (KM) into each major implementation phase. This knowledge-enhanced ERP implementation model adds insights when used to investigate ERP success. It also provides practitioners with a guideline for incorporation of KM into their ERP strategy to improve success rates of ERP systems.

Introduction

A great deal of time, efforts, and costs has been directed toward the implementation of enterprise resource planning (ERP) systems. Such systems are beginning to be adopted by many medium to large businesses. Over 60% of the U.S Fortune 500 had adopted ERP systems by 2000 [7], [19] and projected spending on ERP adoption was an estimated $72.63 billion [1]. ERP projects are a large investment and commitment by an organization. Their inherent size and scope has often lead to complexities. Research of ERP implementation has mainly focused on their initial start-up [4], [8], [10]. There has been little research effort in the area of post-implementation support [20]. Many organizations see the start-up of an ERP system as the final goal instead of a milestone, but many ERP systems have been discontinued 3 months to a year after they were “successfully” completed [17], which shows that a static view of ERP implementation is inaccurate, not strategic, and potentially costly.

ERP implementation projects rarely have a static ending point. Consequently, continuous improvement activities are generally required to lengthen the life of these expensive systems. A critical process inherent to the lifecycle is knowledge management (KM) [5].

The knowledge created during ERP implementation and management is a significant resource for an organization and it should be properly managed [2] and the knowledge needs to be created and shared in each phase of ERP implementation, as well as post-ERP projects. Due to the size and scope of an ERP system, it therefore becomes a strategic asset of the organization.

To understand the process of integrating KM into ERP lifecycle, a model is needed for assessing and validating an organizations’ efforts. As stressed by Nonaka and Konno [11], a knowledge forum, “Ba”, is an important platform where knowledge can be shared and new knowledge created. Our research model focused on an organization's KM execution structure – the “Ba” of ERP KM – and how this knowledge structure helps manage knowledge throughout the ERP implementation phases. It addresses both the processes used during the initial creation of knowledge and those processes used to maintain it. Although organizations are becoming more knowledge-focused, fundamental project management methodologies are still needed to embrace KM properly [6]. Systematic incorporation of KM into ERP project management is strategic and critical [16].

We therefore believed that ERP implementation was an enterprise-wide continuous improvement effort which consisted of initial ERP implementation plus a series of post-implementation projects and that to make enterprise systems successful, KM must be incorporated into each implementation phase of ERP implemented projects strategically and systematically. The model was established by consolidating knowledge theory [12] with fundamental ERP implementation methodology.

Section snippets

ERP implementation methodologies

Traditional system implementation methodologies provided practitioners with guidance of managing the tasks in a software implementation project. Progressively, these methodologies evolved into a set of “recommended collection of phases, procedures, rules, techniques, tools, documentation, management and training used to develop a system” [3]. The traditional linear (waterfall) approach assumed that systems would typically be superseded by newer systems. However, as IT systems become more

Knowledge management

Sarvary provided an appropriate definition of knowledge and KM: “Knowledge is information plus the causal links that help to make sense of this information. KM might be seen as a process that establishes and clearly articulates such links”. Knowledge management includes knowledge capture, documentation, and sharing within a project team or organization. It has increasingly become a business process, supported by database technologies and activities aimed at the creation and sharing of knowledge.

Incorporating KM into ERP implementation

Our contention is that for each phase (Analysis, Design, Construction and Deployment) of any IT project, knowledge will cycle through the four quadrants of the SECI model. The transitions within a phase can be considered knowledge steps. Thus, four knowledge steps make up a phase, four phases become a project, and multiple projects constitute the life of the ERP implemented system.

By explicitly identifying the KM steps within each project phase, we can improve an organization's ability to

KM caveats

Our knowledge-enhanced ERP implementation model was based on certain assumptions about organizations, stakeholders, and knowledge. First, we assumed that different stakeholders involved in ERP projects share the same basic goals and objectives about KM. For example, ERP owners should purposefully manage the knowledge created during project implementation and other stakeholders (such as ERP vendors, consultants, and support team members) should have a positive attitude toward KM and be willing

Relative returns

The ultimate success of ERP implementation depends on how well an organization manages the knowledge created during the implementation process. It is important to measure returns from using this knowledge approach in managing ERP implementation. Though knowledge cannot easily be measured, the degree of knowledge gain can be estimated and predicted. Fig. 6 shows how each of the four steps provides relative value in terms of the knowledge gain due to the project and thus to the organization. The

Methodology illustration

For illustration purposes, a high-level review was made of our methodology against a practical methodology. Several commercial ERP implementation methodologies exist; some of these have been provided by ERP vendors. We decided to compare our ideas with those of ValueSAP® from SAP® AG [15]. This methodology is provided for use in projects implementing the SAP software suite. Although it shares many of the same methodological constructs as other methodologies, SAP uses a slightly different

Conclusion and implications

IS research for ERP projects generally analyzes critical success factors for new systems implementations. Seldom does it address perpetual support for the final success of ERP systems; in fact, many ERP systems fail shortly after they are completed. Techniques to capitalize on the knowledge created during the development process are not widely in use. Many organizations do not manage any of the knowledge they are creating.

Giving the organization a knowledge-sharing community – established

Thomas McGinnis is a doctoral student at the University of North Texas. He holds an MS degree in MIS from Central Michigan University and a BS in CIS from Bentley College. Before pursuing his doctoral studies in Information Systems, he spent 16 years in the chemical industry focusing on Enterprise Information Systems, and Business Process Reengineering. More recently, he was a consultant for a leading IT consulting firm. His research interests include Enterprise Resource Planning, Enterprise

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    Thomas McGinnis is a doctoral student at the University of North Texas. He holds an MS degree in MIS from Central Michigan University and a BS in CIS from Bentley College. Before pursuing his doctoral studies in Information Systems, he spent 16 years in the chemical industry focusing on Enterprise Information Systems, and Business Process Reengineering. More recently, he was a consultant for a leading IT consulting firm. His research interests include Enterprise Resource Planning, Enterprise Architecture and Knowledge Management.

    Zhenyu Huang is an assistant professor in the Business Information Systems department at Central Michigan University. He received his Ph.D. degree in Management Information Systems from the University of Memphis in 2003. His research interests include Data Visualization, E-government, Knowledge Management, ERP, Interoragnizational Information Systems, and Gaming for Learning. His research results have appeared in MIS journals and conference proceedings.

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