EST. 2026

The Archive

Software Technology / IT · MSc · REF. TA-0732

A Natural Language Processing Approach to Improving Operational Efficiency in Enterprise Resource Planning (ERP) Systems

Abstract

This MSc study investigates the subject matter outlined in the title above through a structured research design appropriate to the MSc level. Using primary and/or secondary data collection methods, the research examines the underlying variables, tests relevant hypotheses, and presents findings with implications for practice and policy. This is placeholder abstract text generated for catalogue preview purposes; the full document contains a complete, topic-specific abstract, literature review, methodology, data analysis, and conclusion.

Chapter One — 1.1 Background to the Study

Organizations that depend on enterprise resource planning (ERP) systems are under increasing pressure to modernize, and Natural Language Processing has emerged as one of the more promising avenues for doing so, given its demonstrated impact in related domains.

In practice, however, adoption of natural language processing within enterprise resource planning (ERP) systems has been uneven, and its actual impact on process automation is not yet well understood in a rigorous, evaluable way — a gap this study is positioned to address.

1.2 Statement of the Problem

Existing approaches to process automation within enterprise resource planning (ERP) systems remain largely reactive and fragmented, with little systematic use of natural language processing despite its demonstrated value elsewhere. This study addresses the resulting gap by designing and evaluating a solution built specifically around natural language processing.

1.3 Objectives of the Study

  1. To design and implement a natural language processing-based approach to improving process automation in enterprise resource planning (ERP) systems.
  2. To evaluate the effectiveness of Natural Language Processing in enhancing process automation within enterprise resource planning (ERP) systems.
  3. To identify the key requirements and constraints relevant to deploying natural language processing in this context.
  4. To assess user and stakeholder perception of the resulting system.

1.4 Research Questions

  1. How can natural language processing be applied to improve process automation in enterprise resource planning (ERP) systems?
  2. How effective is Natural Language Processing at enhancing process automation within enterprise resource planning (ERP) systems?
  3. What requirements and constraints are relevant to deploying natural language processing in this context?
  4. How do users and stakeholders perceive the resulting system?

1.5 Significance of the Study

This study is significant to software developers and system architects seeking practical guidance on applying Natural Language Processing within enterprise resource planning (ERP) systems. It is equally relevant to organizations that rely on these systems, offering a reference point for evaluating whether such an investment is justified, and it adds to the growing body of work on natural language processing applications in software technology / IT.

1.6 Scope of the Study

As a MSc-level study, its scope is confined to designing and evaluating a natural language processing-based solution for enterprise resource planning (ERP) systems, focused specifically on process automation; broader deployment considerations fall outside this scope.

Chapters Two through Five, references and appendices are available for a one-time fee of ₦50,000.

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