capgemini-case-study-how-to-reduce-time-to-hire

How Capgemini saved 75% hiring time by using iMocha’s automated skills assessments to vet data scientists

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Brewing together with iMocha
Candidates assessed  
200+
Candidates shortlisted
80+
Hiring time reduced
60%
Selection time reduced
75%
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Capgemini at a glance

A global leader in consulting, technology services, and digital transformation, Capgemini is at the forefront of innovation to address the entire breadth of clients’ opportunities in the evolving world of cloud, digital, and platforms.

Headquarters: Paris, France

Global Presence: 50 countries

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Employees:

300,000+

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Established:

1967

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Industry:

Information Technology Services

iMocha products used:

Talent Acquisition

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the challenges
Capgemini wanted a solution that would help solve challenges with time spent by hiring managers on irrelevant candidates, over-dependence on resumes for screening, and a high time-to-hire ratio.
The challenge

Capgemini enables its customers to go digital through an array of services backed by AI, Analytics, and Platform. Under its Digital Services business unit, Insights & Data is responsible for creating solutions that drive impact with data. It would be fair to say that data science is a critical function and requires a niche skill set. With a growing demand from its customers for business intelligence and data science services, Capgemini looked to expand its team. The major hurdle it encountered was that its hiring managers, among the top-paid resources at Capgemini, spent most of their working hours vetting candidates. This hampered project deliverables a great deal. On average, it took Capgemini almost one week to screen, shortlist, and extend an offer letter. Data science is a niche skill, and there is intense competition to hire the best candidates. Moreover, in the absence of a skills assessment, their Hiring Managers spent almost 24 hours a month vetting candidates.

Capgemini was already using iMocha for university and entry-level hiring and decided to try the data science assessments as well. The data science assessments were available in 2 coding languages - R and Python. Each candidate was sent the assessment, and reports of the top-performing candidates were sent to hiring managers. Since there was no manual review involved, hiring managers could conduct the interviews and shortlist candidates for the HR round. Automated data science assessments meant that the time spent by hiring managers for the hiring process was reduced from 24 hours to just 6 hours in a month.

  • During one of the weekly calls with Capgemini, our customer success team dived into their University Hiring strategy.
  • During one of the weekly calls with Capgemini, our customer success team dived into their University Hiring strategy.
  • During one of the weekly calls with Capgemini, our customer success team dived into their University Hiring strategy.
  • During one of the weekly calls with Capgemini, our customer success team dived into their University Hiring strategy.

Step by step explanation of the workflow:

  • They did not have a large recruitment team that could reach out to these universities across the USA to participate in career fairs and interact with the students. This hampered their recruitment roadmap.
  • However, more important was the lack of technical resources to evaluate candidates who applied for this role.
  • They did not have a large recruitment team that could reach out to these universities across the USA to participate in career fairs and interact with the students. This hampered their recruitment roadmap.
The result
the result

Capgemini has managed to roll out offer letters within 4 days and hire the best data scientists. Hiring managers spend just 6 hours a month on interviews, focusing more on their primary job roles. Looking at the success of Insights & Data, other departments within Digital Services like AI Engineering, Data Trust, Data Foundation, and Project Management are looking to use iMocha for their hiring requirements.

Key highlights:

  • Data Science assessments in R & Python
  • Adding own questions
  • In-depth, skills-wise reports
  • Advanced proctoring and anti-cheating mechanisms
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