Enhancing Field Employee Productivity and Performance with Android Software Solution and Machine Learning-based Predictive Analytic Model

Organizations with field employees face the challenge of maintaining high-quality standards while optimizing costs. Analyzing, Classifying, Predicting, and Monitoring the Field Employee's Regular Activities, Work Productivity and Performance is the challenging objective for Management in any Organization. Research study suggests using Android Application and machine learning predictive analytic model by using decision tree algorithm to analyze and classify field employee work productivity and performance. This aims to achieve a higher accuracy rate and better insights into employee performance. To track field employees, a GPS tracking app is used on mobile devices. As part of Mobile Computing implementation, Android Mobile device transfers the data in the form of text, voice and images to the web server and vice-versa. It generates location data with secured communication through cryptography techniques and stores captured data in a database server for further analysis. Furthermore, a web-based application is proposed for monitoring and generating reports for individuals and groups of field employees, including route maps and time sheets. This proposed solution is going to be a complete one-point automated software solution for any business organization for managing their field employees.