Preview. This page currently shows the analysis skeleton. The full worked walkthrough — sample dataset, connected steps, runnable code, interpretation — is being built.
HR / People Analytics · how-to
Predict Employee Churn from Organizational Network — in R
A network-driver analysis. Every step below is the same analysis rendered for R — grounded in the source, honest where R can't do a step cleanly.
Same analysis, your tool
DERIVE
convert the network into quantitative signals per person
df |> mutate(derived = expr)JOIN · mechanical
link network position to who stayed or left
left_join(df, other, by = "key")CORRELATE
identify which network signals predict staying
cor(df$driver_j, df$outcome)FIT-CLASSIFIER
model resignation odds from connectedness and context
glm(y ~ x1 + x2, family = binomial, data = df)PREDICT
flag well-connected people worth retaining
predict(model, newdata = df)Grounded in
Predictive HR Analytics with Excel — §17.8/17.9 ONA graph metrics & churn
Doing HR / People Analytics work?
The full HR / People Analytics guide covers this and the whole workflow around it — reconciled from the field’s best books.
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