How Schneider Electric uses ‘predictive analytics’ in hiring


To control inappropriate hires, the company uses select norms to judge candidates.

As the economy scales up, people start looking for better jobs, which leads to an increase in the attrition rate. Suddenly, there could be calls from various department heads and managers to facilitate some urgent hiring. In such a scenario, it becomes a huge challenge for the HR manager to find the right fit for each role, forget about the best fit.

‘Predictive Analytics’ comes in handy during such situations, and Schneider Electric not only uses this quite often but most effectively.

For the uninitiated, predictive analytics is the practice of extracting information from existing data sets, which makes it possible to determine patterns and predict future outcomes and trends. It is a form of software-driven calculation that can anticipate the appearance of some patterns in hiring.

“It’s during these times that the chances of inappropriate hires can peak due to the paucity of time and other concomitant pressures in filling positions. If that’s the case, there can be higher turnover of employees within the first year – either voluntary or involuntary,” quips Rachna Mukherjee, chief, HR, Schneider Electric India.

To control such inappropriate hires, Schneider Electric India uses select norms to judge candidates.

In its assessments for hiring, the first thing that Schneider looks for is job fit —competencies and experiences required to deliver in the immediate role. Secondly, the company looks for leadership qualities and potential fit for the same — capacity and agility to grow as a leader in the organisation. The third most important aspect is the cultural fit — alignment with Schneider’s values and culture.

The company uses psychometric assessments in addition to behavioural event interviews to specifically predict the leadership and cultural fit.

The company has also used PAPI (Personality and Preference Inventory) along with Hogan assessments at different levels in the organisation.

However, all of these could be totally ineffective, if predictive analytics is not used as a tool.

Rachna Mukherjee

It helps companies recognise the type of people who could succeed in its environment, and the kind of sources that will help produce better hires.

Based upon this approach, a company can create an effective data-driven analytic agenda to rank the effectiveness of different hiring sources through employee roles. The resultant data and hiring profiles can help improve the effectiveness of future hires. It should be noted that even minor improvements in attrition rates can lead to significant financial benefits.

“In fact, the use of data and predictive analytics can impact the manner in which companies interact with customers, besides transforming how they search for, discover and retain promising talent,” quips Mukherjee.

She quotes a Gartner study, which has predicted that data usage will soar 800 per cent within five years, with 80 per cent of such data being unstructured— emails, social media posts, videos and CVs.

However, she puts in a word of caution, “while big data presents opportunities for HR teams, it also throws up its own challenges, given the proliferation of data. Nevertheless, astute use of data and PA can play a role in increasing the percentage of successful hires.”

Predictive analytics can be especially beneficial for recruiters who still rely primarily on gut feel to ensure appropriate hires. However, this can’t be the sole solution to all problems.

“Although predictive analytics may be helpful in improving hiring and retention rates, it should not be forgotten that there are various factors that could affect its results, including the employees’ performance and their retention, which may themselves have diverse drivers,” asserts Mukherjee.

Finally, improvement in retention rates is important not only from a company’s perspective, but also from that of the employees.

While it is well known that wrong hires can impact productivity, what is not so known is that this can affect the morale and engagement levels of other employees too, by upsetting the team spirit.

Keeping this in mind, Schneider undertakes all measures to ensure that its talent acquisition efforts are as efficient as possible.


  1. GE was practicing in India and globally for more 20 years in my knowledge
    I was one of the key recruitment service provider for them, I was trained by in this method of interviewing, I have very good success rate in hiring.with GE, across business.
    The probability of wrong hires is less in this method, I believe hiring is a solemn process, It is dilution of the basic and fundamental process is leading to artificial shortage of talent

  2. i would like to know the methodology we can adopt in Predictive Analysis, it there any specific formula used in this. or simply it is from past year trends of Attrition Rate etc.
    I would like to actually know how to do predictive analysis, some times in the situation of economic slowdown, stability will be much more higher, in this scenario it is really difficult to be predictive and sometime due to increase of demand in market, all your predictions may tends to false.
    Pl. guide me.

  3. Good article about use of technology in predicting outcomes in recruitment.However, technolgy cannot replace human intellect.

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Prajjal Saha is the editor and publisher of HRKatha, which he founded in 2015. With nearly 25 years of experience in business journalism, writing, and editing, he is a true industry veteran who possesses a deep understanding of all facets of business, from marketing and distribution to technology and human resources. Along with his work at HRKatha, he is also the author of the Marketing White Book. Thanks to his extensive experience and expertise, he has become a trusted source of insight and analysis for professionals across a wide range of industries.