Lernen Visualizing Workforce Trends | Analyzing Workforce Trends

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Visualizing workforce trends is essential for strategic HR planning because it turns complex data into clear, actionable insights. When you translate hiring, attrition, or promotion data into visual formats, you can quickly spot patterns, seasonality, or sudden changes that might be missed in raw tables. This empowers HR leaders to make informed decisions about recruiting, retention, and talent management, ensuring the organization remains agile and competitive.


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import matplotlib.pyplot as plt
import pandas as pd

# Sample data: monthly headcount
data = {
    "Month": ["Jan", "Feb", "Mar", "Apr", "May", "Jun"],
    "Headcount": [120, 125, 130, 128, 132, 135]
}
df = pd.DataFrame(data)

plt.figure(figsize=(8, 5))
plt.plot(df["Month"], df["Headcount"], marker="o", color="blue")
plt.title("Monthly Headcount Over Time")
plt.xlabel("Month")
plt.ylabel("Headcount")
plt.grid(True)
plt.tight_layout()
plt.show()

Line charts like the one above are especially useful for workforce planning because they make trends in headcount easy to interpret. If you see a steady increase, it may indicate successful hiring or business growth; a sudden drop could signal higher attrition or layoffs. By monitoring these patterns, you can anticipate staffing needs, budget for recruitment, or address emerging retention problems before they escalate.


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import numpy as np
import matplotlib.pyplot as plt

# Sample data: hires and attrition by month
months = ["Jan", "Feb", "Mar", "Apr", "May", "Jun"]
hires = [10, 8, 12, 9, 11, 7]
attrition = [5, 7, 6, 10, 8, 6]

ind = np.arange(len(months))
width = 0.6

plt.figure(figsize=(8, 5))
plt.bar(ind, hires, width, label="Hires", color="green", bottom=attrition)
plt.bar(ind, attrition, width, label="Attrition", color="red")
plt.xlabel("Month")
plt.ylabel("Number of Employees")
plt.title("Hires vs. Attrition by Month")
plt.xticks(ind, months)
plt.legend()
plt.tight_layout()
plt.show()

1. What does a line chart of headcount over time help HR understand?

2. Fill in the blank: A stacked bar chart can show multiple ____ in one visualization.

3. How can visualizing promotions help identify talent pipeline issues?

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Abschnitt 2. Kapitel 4