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 a variety of assets including industrial, commercial, retail, residential, and hotel real estate.
JLL’s India office was looking to hire candidates for analyst role for their Technology, Data and Information Management (TDIM) global centre. The recruitment team were looking to hire entry-level candidates from top universities and colleges. Before using Interview Mocha, JLL had the traditional method of pen and paper assessments. This was tedious, time – consuming and not at all suitable for campus hiring. Campus hiring generally involves visiting the campuses, pre-placement talks, assessments, 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 and having traditional methods of assessment were 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 created the assessment with help from Interview Mocha’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 in 3 campuses. Since it was a totally automated process, they did not require huge teams to be present for campus as normally is the case.
Mocha’s image proctoring, window violation, and question randomization feature 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 were able to transform the campus hiring process to shortlist the best talents in quick time.