Why High Employee Turnover Hurts Profitability — A Python Simulation

TL;DR: High turnover is expensive. We built a Python simulation to show how frequent employee replacement drains productivity and profits.

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💼 The Real-World Problem

Hiring and training new employees takes time and money. But how much does frequent employee turnover actually affect a company’s bottom line?

We often assume it's "bad," but let's model it in code to see how bad—and why.

In this article, I use Python to simulate a company with:

• A fixed number of employees
• A monthly turnover rate
• A realistic learning curve for productivity
• Associated hiring/training costs

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🧪 Simulation Design

Assumptions:

• New employees are less productive and need time to ramp up.
• Monthly turnover is either low (2%) or high (20%).
• Training a new employee costs $500.
• Employees can produce up to $500/month at peak performance.
• Experience grows linearly, but productivity grows sigmoidally (i.e., quickly at first, then plateaus).

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📊 Python Code: Turnover Simulation

import numpy as np
import matplotlib.pyplot as plt

class Employee:
    def __init__(self):
        self.experience = 0  # in months
        self.training_cost = 500  # cost to hire/train

    def productivity(self):
        return 1 / (1 + np.exp(-0.3 * (self.experience - 6)))  # sigmoid curve

    def monthly_revenue(self):
        return self.productivity() * 500  # peak revenue = $500/month

def simulate_company(months, num_employees, turnover_rate):
    employees = [Employee() for _ in range(num_employees)]
    total_revenue = []
    total_cost = 0

    for month in range(months):
        # Replace a portion of the workforce each month
        num_to_replace = int(num_employees * turnover_rate)
        for _ in range(num_to_replace):
            employees.pop(0)
            employees.append(Employee())
            total_cost += 500  # training cost

        monthly_rev = 0
        for emp in employees:
            monthly_rev += emp.monthly_revenue()
            emp.experience += 1

        total_revenue.append(monthly_rev)

    cumulative_revenue = sum(total_revenue)
    net_profit = cumulative_revenue - total_cost
    return total_revenue, net_profit

# Simulation parameters
months = 60
num_employees = 100
low_turnover = 0.02
high_turnover = 0.20

# Run simulations
low_rev, low_net = simulate_company(months, num_employees, low_turnover)
high_rev, high_net = simulate_company(months, num_employees, high_turnover)

# Plot the results
plt.plot(low_rev, label=f"Low Turnover (Net Profit: ${low_net:,.0f})")
plt.plot(high_rev, label=f"High Turnover (Net Profit: ${high_net:,.0f})")
plt.title("Impact of Employee Turnover on Company Profitability")
plt.xlabel("Month")
plt.ylabel("Monthly Revenue ($)")
plt.legend()
plt.grid(True)
plt.tight_layout()
plt.show()

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📈 Results

Running this simulation gives us two curves:

• Low turnover companies have employees who gain experience and hit peak productivity.
• High turnover companies continuously lose experienced workers and spend heavily on training.

Despite having the same headcount, the high-turnover company earns much less over time and incurs more cost.

For example, your output may look something like:

Low Turnover (Net Profit: $2,110,000)
High Turnover (Net Profit: $1,350,000)

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🔍 Takeaways

• Employee experience compounds value—it’s like investing in human capital.
• High turnover kills momentum. You lose productivity and pay more in onboarding.
• Retaining staff isn't just HR fluff—it's a clear business decision.