Application of Random Walk in Manpower Planning

TL;DR

This paper models employee career progression as a random walk with stochastic transitions, deriving explicit formulas for long-term distribution analysis in manpower planning.

Contribution

It introduces a novel application of random walk theory to model employee career paths and provides explicit formulas for their long-term distribution.

Findings

Explicit formulas for long-term employee distribution

Model captures various career transition scenarios

Provides analytical tools for manpower planning

Abstract

The career of an employee can be described (under certain circumstances) by a random walk, where the states of the random walk are determined by the level and position of an employee. At each decision moment the state of the employee is changed by four stochastic transformations: upgrading one position at the same level, upgrading one level, staying until the next decision moment in the current state and absorption in the current state. We obtain explicit formula for the long term behavior of the distribution of all employees using generating functions.