JLL is recognized as the global leader in real estate services across hospitality properties of all shapes and sizes.
JLL buys, builds, occupies, and invests in various assets, including industrial, commercial, retail, residential, and hotel real estate.
.avif)
.webp)
JLL’s India office was looking to hire candidates for analyst roles for their Technology, Data, and Information Management (TDIM) global center.
The recruitment team was looking to hire entry-level candidates from top universities and colleges. Before using iMocha, JLL had the traditional method of pen-and-paper assessments, which was tedious, time–consuming and unsuitable for campus hiring. Campus hiring generally involves visiting the campuses, pre-placement talks, assessments, and interviews, and then releasing the list of shortlisted candidates for further interviews or rolling out offer letters.
Campus hiring usually involves around 200+ students attending, but having traditional methods of assessment was not viable. Another huge problem of campus hiring is mass cheating. With a large number of students, it becomes impossible to prevent cheating.
JLL’s team realized that to hire top talents, they would need to revamp their hiring strategy and switch to an automated process.
JLL's team created the assessment with the help of iMocha’s customer success manager.
The assessment was a combination of Aptitude, Tech, Programming, and Writing skills. They created one assessment with multiple links for various campuses. This enabled them to conduct simultaneous assessments on 3 campuses. Since it was a totally automated process, they did not require huge teams to be present for the campus, as normally is the case.
iMocha’s image proctoring, window violation, and question randomization features ensured cheating prevention. The assessments were conducted within the hour, and the results were generated instantly. The students who performed well were shortlisted for face-to-face interviews.
The recruitment team was able to transform the campus hiring process to shortlist the best talents in a quick time.
.webp)
