The full case study
AI-powered human capital management, step by step
On this page · 9 sections
About the business
Our client from the US oil and energy company “Quantum Energy” with 10K employees wanted to build a custom human capital management solution. His company required that solution to:
- encourage employees develop new skills
- motivate them to achieve career goals
- reward them for reaching set goals.
- help HR managers track core metrics
- let HR managers focus on areas of improvement.
The AI-powered HR solution should include a set of features for 2 user roles – HR managers and regular employees. Our client also wanted to implement a gamification and achievements feature with IoT tracking and different surveys.
The project was complex. So our goal was to start with MVP, test it with employees and HR managers. And then improve and scale solution according to their feedback.
Project tasks
- Complete a discovery to define product vision and objectives, prepare requirements, create a roadmap with prioritized features.
- Develop an MVP of HR platform with core AI-powered features, release it, and gather feedback of employees and managers.
- Keep scaling MVP and improving its functionality based on collected feedback.
Project team
- Project Manager
- Business Analyst
- 3 UX/UI designers
- 4 Front-end developers
- 4 Back-end developers
- Software Architect
- 4 QA engineers
- DevOps specialist
6 month for Discovery & Design
9 months for development and testing
Features for HR managers
AI-powered KPI analysis
AI collects and aggregates employee performance metrics, predicts performance trends, and detects employees with lowest KPIs.
Meeting scheduler
HR managers can use AI scheduler that is integrated with employees calendars. It suggests available time slots and sends automated reminders.
Progress tracking
There is a set of tools allowing to set goals, track KPIs, collect 360-degree feedback, and get a holistic view of each employee performance.
AI-powered analysis
An AI algorithm helps HR managers to automatically analyze all performance results, define employees qualification, and initiate rewarding.
Features for employees
AI-powered onboarding
Employees receive the link and proceed with onboarding. AI helps them to verify all documentation and perform training.
Development program
Employees can choose one development program or course, complete it, and track the progress.
Set of surveys
The platform has a set of surveys that help employees asses their knowledge, satisfaction and engagement.
Rewarding system
While passing development program and surveys, employees earn points that can be exchanged for rewards.
Gamification
Our client wanted to create custom rewarding system for employees. They should be able to earn points and then exchange them for real benefits like additional day-offs, new courses, etc.
To make this rewarding system engaging and fun, we decided to implement gamification elements:
- tasks with progress trackers
- market of rewards
- employees’ wish lists
- rewards counter
Employees can earn points in several different categories – sport, health, career, and peers. To earn points they should complete certain tasks and the app will track the progress. Then they can go to the market of rewards and exchange their points.
Employee achievements
One of the main goals of this HR platform was to encourage employees to develop their skills and increase motivation. So the platform should help employees set clear goals and complete various courses.
To make learning experience more engaging, we implemented achievements feature with IoT tracking. The app is compatible with smart watches and bracelets. It helps employees easily track their goals completion.
Once employees completed a course, the app offers them to take the survey to measure level of engagement, motivation, and self-confidence. The data is collected and then used by management to find new talent retention and growth opportunities.
Development approach
- Back-end: We selected microservices architecture to optimize app performance, maintenance and costs. Most of the services were built on Node.js/Nest.js, and for AI-related ones we selected Python as the most powerful and robust stack. We also used cloud services like AWS Lambda, AWS S3, and AWS Elemental MediaConvert, and we selected Amazon RDS and Amazon MQ for data storage.
- Web Apps: The platform has a public web UI for those who haven’t installed mobile app, and a web-based content management tool for the back office. We selected React for these web apps with Next.js server-side rendering for SEO-friendly public content. This combination ensures the development of stable, swift, and captivating web apps.
Outcome
It took us 10 months to build a solid MVP of an HR platform for our client. As of now, it is being tested by thousands of employees within the “Quantum Energy”.
We have received only positive feedback from the users and our client. He is planning to scale MVP into a fully-fledged product and implement even more AI-powered features in 2024. So our cooperation continues.
