Improving Operational Efficiency Through Automation and Machine Learning

EasyChair Preprint 13532

Abstract

This abstract summarizes the concept of improving operational efficiency through automation and machine learning. Operational efficiency is a crucial aspect of business success, and organizations are increasingly turning to automation and machine learning to optimize their operations. This paper explores the benefits, challenges, implementation strategies, and best practices associated with leveraging automation and machine learning for operational efficiency improvement.

The abstract begins by defining operational efficiency and emphasizing its significance in business. It highlights the role of automation and machine learning as powerful tools for driving operational efficiency. The benefits of automation and machine learning are discussed, including the reduction of manual tasks, streamlined processes, enhanced accuracy, real-time data analysis, improved resource allocation, and scalability.

The abstract outlines the implementation process, covering aspects such as identifying automation opportunities, data collection and preprocessing, developing machine learning models, integration with existing systems, testing, and continuous monitoring. Case studies and examples from various industries, including manufacturing, supply chain management, customer service, and financial services, illustrate the practical applications of automation and machine learning.

Keyphrases: Automation, Chatbots, Customer Support, customer service, machine learning

@booklet{EasyChair:13532,
  author    = {Kayode Sheriffdeen},
  title     = {Improving Operational Efficiency Through Automation and Machine Learning},
  howpublished = {EasyChair Preprint 13532},
  year      = {EasyChair, 2024}}