Optimizing Office Automation Systems Using Mathematical Modeling: A Business Management Perspective

Abstract

The growing reliance on office automation systems (OAS) has transformed administrative and managerial operations, yet many organizations continue to experience inefficiencies arising from partial automation, uneven user proficiency, and suboptimal resource allocation. This study investigates the optimization of office automation systems through mathematical modelling to enhance workflow efficiency, task scheduling, and resource utilisation in contemporary office environments. Using survey data collected from over 100 respondents, the research evaluates awareness, usage, and performance of key automation tools and workflows, revealing moderate automation maturity, strong system reliability, but notable gaps in usability, performance, and integration. Building on these empirical insights, the study develops a unified analytical framework comprising a Workflow Efficiency Model (WEM), a Resource Allocation Model (RAM), and a Task Scheduling Algorithm (TSA). These models integrate automation levels, human proficiency, system performance, and task priorities using linear programming, queuing theory, and priority-based scheduling techniques. Simulation-based validation demonstrates that the proposed models effectively quantify workflow delays, identify bottlenecks in mixed human–machine processes, and optimize task assignments to reduce completion times and workload imbalance. The findings contribute to business management literature by offering a data-driven, scalable, and cost-effective approach to improving office automation without requiring major infrastructural changes. Practically, the study provides actionable guidance for managers seeking to enhance productivity, reduce operational costs, and improve decision-making through intelligent workflow design. The research underscores the strategic value of mathematical modeling as a managerial tool for achieving operational excellence in increasingly complex and digitally enabled office environments.