Regardless of whether you are a small company or a much larger enterprise/organization, you are likely to encounter some amount of challenges when it comes to managing your people/employees. HR challenges emerge every year in response to changes.
The inspiration for this project came to us when we conducted a survey for HR consisting of different questions related to their work life. Here we came to know that HRs are actually facing difficulties when it comes to managing/inspecting the employees and their performances. In 2020 especially, Human Resource departments are facing even newer, and more unfamiliar challenges to tackle and manage. Hence we wanted to build a website/software/application that provides a system that will help HR to tackle the problems faced in daily life.
HRooze is a platform for performance insight. It gathers data from the employee's page for analytics. Allows HR, Department Head and Team Lead to use high-level overview and keep track of their employees. An employee can update his/her profile including the projects undertaken, Projects done, Working hours, Leaves and Personal Information, and the skill sets possessed by him/her. Also, it provides a HrBot that can solve employees' most frequent queries. We built the two Machine Learning models namely Employee Attrition and Employee Promotion.
In the allocated time, we were only able to build a mockup that aims to show what should be possible. Built and deployed Machine learning Models using Flask. Implementing the AI parts in the time was simply not possible. The following paragraphs describe the envisaged work rather than what we have built.
We've also built a web app using React and deployed it as a multi-page application which communicated with our MongoDB database. And Our web app will have authorization constraints which are done with the help of Google Oauth and Facebook Developers Tool.
HrBot is trained with different NLP libraries to demonstrate the intended functionality.
Despite a large number of solutions on the market, many of them do not meet important requirements from HRs, Managers, or Leadership, and, when analyzed in detail, many of them lack flexibility and scalability. However, some of their features are quite a in demand. So the main problem for us was the specification MVP scope in such conditions.
Real-Time data visualization. Collecting real-time data for our Machine Learning framework. Generating useful high-level metrics for the large amounts of data our platform collects.
We've built a mock bot to demonstrate. We have built Machine Learning Models which provide higher accuracy with lesser error rates.
On the engineering side, we had to learn how to develop an AI Bot, Perform Machine Learning.
In general, we've learned that there are not enough good tools that can automate HRs tasks. No high-level overview from various apps should provide analytics for improvement
Short term: Train Engines and develop custom AI framework. Add more AI tools. Add more applications to the platform
Long-term: Distribute the platform services globally keeping regulations in mind.