machine learning and workforce
data visualisation

Partnering with a large bank, this visualisation explores how people are flowing through their job families and considering the effect of machine learning and workforce automation.

The purpose of this project was to identify the impact of promotion systems and automation. As a separate step, finer-grained analysis measures and explains variance among departments on key measures such as average direct reports per manager and total number of managers. As machine learning applications and increasingly automate knowledge work, observing changes in key organisational ratios reveals cases to learn from and replicate as well as cases where interventions and change are called for.

Key facts

  • Impact of promotion systems and automation
  • Biweekly observations of 100,000 employees
  • Across 12 business platforms in 48 countries
  • 5-year period