EST. 2026

The Archive

Software Technology / IT · MSc · REF. TA-0652

The Application of Predictive Analytics in Enhancing Process Automation in Point of Sale 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

Predictive Analytics has become one of the more actively explored innovations in the design of modern point of sale systems, promising gains in efficiency and reliability that legacy, largely manual approaches have struggled to deliver.

In practice, however, adoption of predictive analytics within point of sale 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 point of sale systems remain largely reactive and fragmented, with little systematic use of predictive analytics despite its demonstrated value elsewhere. This study addresses the resulting gap by designing and evaluating a solution built specifically around predictive analytics.

1.3 Objectives of the Study

  1. To design and implement a predictive analytics-based approach to improving process automation in point of sale systems.
  2. To evaluate the effectiveness of Predictive Analytics in enhancing process automation within point of sale systems.
  3. To identify the key requirements and constraints relevant to deploying predictive analytics in this context.
  4. To assess user and stakeholder perception of the resulting system.

1.4 Research Questions

  1. How can predictive analytics be applied to improve process automation in point of sale systems?
  2. How effective is Predictive Analytics at enhancing process automation within point of sale systems?
  3. What requirements and constraints are relevant to deploying predictive analytics in this context?
  4. How do users and stakeholders perceive the resulting system?

1.5 Significance of the Study

Beyond its immediate technical contribution, this study offers value to organizations evaluating whether to invest in predictive analytics for their own point of sale systems, and contributes to the broader literature on applied software technology / IT by documenting a concrete implementation and evaluation case.

1.6 Scope of the Study

As a MSc-level study, its scope is confined to designing and evaluating a predictive analytics-based solution for point of sale 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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