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Critical success factor based resource allocation in ERP implementation: A nonlinear programming model.

Ying Xie1, Colin Allen2, Mahmood Ali3

  • 1Faculty of Business and Law, Anglia Ruskin University, Bishop Hall Lane, Chelmsford, CM1 1SQ, UK.

Heliyon
|August 12, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces a Constrained Nonlinear programming model for Enterprise Resource Planning (ERP) implementation to help small and medium-sized enterprises (SMEs) manage resources effectively. The model optimizes investment in critical success factors (CSFs) for successful ERP deployment.

Keywords:
Critical success factorERP implementationNonlinear programmingResource allocationSMEs

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Area of Science:

  • Operations Research
  • Information Systems Management

Background:

  • Enterprise Resource Planning (ERP) implementation is crucial for SMEs but often faces challenges due to resource constraints.
  • Identifying and investing in Critical Success Factors (CSFs) is vital for successful ERP deployment.

Purpose of the Study:

  • To introduce a Constrained Nonlinear programming model for ERP implementation (CNL_ERP) tailored for SMEs.
  • To guide resource allocation towards CSFs during the pre-implementation and implementation phases.

Main Methods:

  • Development of the CNL_ERP model using the Generalised Reduced Gradient Method.
  • Application and validation of the model through three case studies in SMEs.
  • Strategy formulation for resource allocation to CSFs across project phases.

Main Results:

  • Case studies showed improved ERP implementation outcomes compared to observed results.
  • The CNL_ERP model provides a clear roadmap for resource concentration.
  • The model facilitates dynamic adjustment of resource allocation based on changing project conditions.

Conclusions:

  • The CNL_ERP model enhances SMEs' ability to strategically deploy resources for successful ERP implementation.
  • It offers a framework for understanding project progress and resource requirements.
  • The model supports adaptive management of CSFs and resources to maximize ERP project success.