AI Spotlight

USING AI TO OPTIMIZE FORECASTING IN WORKFORCE PLANNING

AI optimizes processes at a container terminal

Learn how Machine Learning (ML) improves the accuracy of staffing requirement predictions across various industries. By using AI applications, staff can be planned to match the target output even in the event of fluctuating and seasonal changes.

Key Benefits

  • Enhanced precision: Improvement in forecasting workforce demands based on historical data of shift schedules
  • Cost reduction: Less understaffing or overstaffing, but the right amount of staff for the desired output (e.g. delivery or production quantities)
  • Increase in efficiency in workforce planning: Less planning effort due to fewer staff cancellations at short notice

Use Case

Summary

  • In this use case we used Machine Learning to predict anonymously short-term sickness rates for a group of shift workers. By analyzing historical data on planned shifts and comparing them with actual shift schedules, the aim was to identify patterns of absenteeism, providing the visibility of the likelihood of employees calling in sick on a given day.
  • Displaying sickness rate predictions for upcoming shifts offered actionable insights for roster planners, enabling them to allocate resources more effectively.
  • Our software also provided recommendations for future development, including incorporating the model into automated roster creation. This improves employee satisfaction by ensuring that schedules are better aligned with their needs.

How It's Done

  • Machine Learning (ML) techniques analyze historical data and current trends to improve the accuracy of personnel demand planning.
  • Identified patterns are projected into the future. This leads to fewer under- or overstaffing and therefore to lower (personnel) costs and greater efficiency.
  • The application of ML in this context showed a significant improvement in personnel deployment plans for companies and their employees.

Did You Know?

  • It is estimated that the cost of staff shortages can account for up to 15-30% of potential turnover, while the cost of overstaffing can also amount to 10-20% of salary costs.
  • Predictable absences make it possible to distribute work pressure and contribute to more regulated working hours, leading to a better work-life balance and less stress.

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