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People Analytics — Utilizing Human Resource Data —

Conventionally, the human resource (HR) administration has decided personnel measures and employee allocation, but now let us give employees choices for them.
A company where employees work positively and vigorously is attractive to anyone. On the contrary, a company with a low level of employees' happiness cannot satisfy the customer. It is time to take another look at HR strategies and measures by considering the level of well-being and engagement in rewarding work expressed as indexes.
NEC utilizes AI and data analytics to support innovation in the HR division with the aim of creating a society in which people live active and rich lives.

Use cases

New graduate recruiting analytics
The efficiency of recruiting employees is improved by predicting prospective employees based on data such as those entered in the employment application form. This allows limited recruitment resources to put more focus on candidates more likely to receive preliminary job offers. NEC's original deep learning technology enables characteristics of candidates who received unofficial job offers in the past, to be modeled accurately, leading to a highly efficient prediction.

Event and training analytics
The data obtained by analyzing participant emotions at in-house events or trainings can be used as an index for improving future events and trainings. This enables positive and negative responses to presentation contents to be clarified, leading to the improvement of future methods. NEC’s unique wearable devices allow four kinds of emotions of participants to be modeled, which are fed back to the organizers.

Organization engagement analytics
This analytics can be utilized for considering measures to improve employee engagement. The points strongly related to employee engagement are found to help review such measures. NEC’s original white-box AI visualizes influential factors.

Measure review support
Causal relationships to be derived from the questionnaires where only correlation was recognized. Visualizing a hidden context structure enables measures to be established with less-direct key factors included. Through this process, improved accuracy of measures and cost-effectiveness are expected.

Well-being analytics
When implementing a new way of working, the new normal, such as remote working, this analytics allows employees' well-being and work style to be measured. AI learns the work style of individuals with high levels of well-being and chatbots propose a work style to enhance well-being.

Personnel data analytics
The conventional manual analysis of personnel management data depended on the experiences and knowledge of superiors or veteran employees. The use of AI helps improve the efficiency of personnel management operations.
This analytics solution provides eight features including recruitment matching for new-graduates and mid-career applicants, retention support, determination of evaluation and remuneration, optimization of personnel allocation in organizations, and judgment on carrier plans and job category selection.

Risk cause analytics
Personnel data is analyzed easily/visually/on an ad hoc basis and a pattern or relation hidden in data is visually grasped, which in turn visualizes a risk to company management. By analyzing factors affecting business results from various perspectives, including individuals, teams, and organizations, better planning of policies and measures is supported.