Cutting Hiring Time by 30%

The platform is a national government service for companies that hire a large number of foreign workers. It already handled many of their business operations. Our job was to add a hiring service where companies could find employees and candidates could find jobs, all online.

Before this, much of the hiring happened offline and took a long time. The goal was to make it faster for recruiters and easier for job seekers.

Recruiters needed a faster way to find the right people, and candidates needed an easier way to find relevant jobs. The main problems were:

• Offline hiring processes that were slow and hard to track.
• Hiring large numbers of people quickly.
• No analytics to help recruiters make decisions.

Key Objectives

• Move the hiring process online.
• Automate candidate screening with a recommendation system.
• Give recruiters analytics to support their decisions.

The platform had two main user groups: recruiters, who often had to hire in large numbers, and job seekers looking for work.

User Personas

I built personas from interviews with five recruiters who had used the previous system. The interviews showed what slowed them down, what they wanted to achieve and what they expected from a new tool.

Pain Points & Solutions

• Slow hiring: online interviews instead of in-person meetings.
• Hiring at high volume: a talent pool and a recommendation system with match scores.
• Reviewing applications by hand: automatic match scoring based on candidate data.
• No analytics: decision-support tools inside the platform.

Ideation

The key idea that came out of research was a match score. The platform rates each candidate on experience, skills and availability. Recruiters set a minimum score, and the platform recommends candidates who pass it.

Prototyping

I started with low-fidelity wireframes in Figma and moved to a clickable prototype. Each version was reviewed with users and stakeholders and updated after their feedback.

I ran usability tests with five participants. They showed where the main flows were confusing, and after the fixes task completion went up by 15%.

I also worked with a UX writer on the interface copy, FAQs and tutorials, and reviewed every text to keep it clear and consistent.

Key Features

• Hiring process: applying is simple, and every application gets a match score.
• Talent pool: one place to manage candidates and see recommendations.
• Analytics: tools to track and improve hiring performance.
• Responsive design: a mobile version alongside the desktop one.

Design System

The platform already had a design system, and I used it so the hiring service looked and worked like the rest of the platform’s services.

I kept a screen inventory table to track which screens were approved and ready for development. During the build I worked with developers on technical issues and fixed design problems as they came up.

Analytics

We used Hotjar to watch how people used the platform, find bugs and create Jira tasks to fix them.

UX Audit

We regularly checked the built product against the design to keep quality up.

• Speed: hiring time dropped by 30% in the first month after launch.
• Adoption: 1,496 new user profiles were created in the first month.
• User education: articles and FAQs helped people get started and made them more satisfied with the service.

Achievements

Iterative testing with real users turned a slow, mostly offline process into a working online service.

Learnings

Next, I’d focus on:

• Making the platform more accessible for users with different needs.
• Adding quantitative research alongside interviews.
• Expanding the analytics tools.