Statistical Model to Find Whether Employee will Back to Office or Not at the End of WFH

Abstract

Introduction

Problem Statement:

As companies reduce or eliminate work-from-home policies, managers need a way to predict whether an employee will return to the office. The challenge lies in identifying factors that influence this decision.

Solution: Logistic Regression Model

A logistic regression model using the sigmoid function has been developed to predict the probability (p) that an employee will come to the office (where p is between 0 and 1).

Model Details:

• Sigmoid Function:

  p=11+e−zp = \frac{1}{1 + e^{-z}}p=1+e−z1?

• Input Variables (10 independent features):

  • A = Age

  • E = Experience

  • NTS = Native town same as work location

  • HA = Has ailment

  • MYK = Mother with young kids

  • SAP = Stays with ailing parents

  • HLH = Has litigation in hometown

  • HHL = Has high loan

  • EXPM = Experience level: mid

  • EXPS = Experience level: senior

  • RT = Role is technical

• Logistic regression equation (z):

  z=3.3382−0.1043A+0.1111E+0.1583NTS−3.1658HA−1.9852MYK−1.6115SAP−1.3185HLH+3.5049HHL−0.0300EXPM+0.5758EXPS−1.2013RTz = 3.3382 - 0.1043A + 0.1111E + 0.1583NTS - 3.1658HA - 1.9852MYK - 1.6115SAP - 1.3185HLH + 3.5049HHL - 0.0300EXPM + 0.5758EXPS - 1.2013RTz=3.3382−0.1043A+0.1111E+0.1583NTS−3.1658HA−1.9852MYK−1.6115SAP−1.3185HLH+3.5049HHL−0.0300EXPM+0.5758EXPS−1.2013RT

Application:

By inputting the values for these 10 variables, HR or a manager can determine the likelihood (p) that a particular employee will attend office.

• p ≈ 1 → Employee likely to come to office

• p ≈ 0 → Employee likely to prefer remote work

Copyright

Copyright © 2025 Joy Kumar Roy. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.