Shift Management Using Artificial Intelligence

Managing shifts in labor-intensive companies is a significant challenge, especially with real-time schedule changes. However, with Mehr's AI tools and algorithms, you can improve discipline, reduce delays, and accurately calculate payroll factors.

Challenges of Shift Management in Labor-Intensive Companies:

  • Real-time changes to shift schedules.
  • Difficulty in regulating attendance and departure times according to new shift rules.
  • The need for shift planning to ensure maximum employee and worker discipline.

Analysis of Shift Management Issues:

  • These issues are present in almost all labor-intensive companies and organizations dealing with shifts, meaning they are not a flaw in the administrative system itself but rather an inherent reality.
  • It is challenging to address this issue by assuming a supervisor can manually input required shift adjustments in real time. Therefore, relying on human intervention to fix the shift system is not feasible.
  • There must be an intelligent automated system capable of predicting and correcting required shift adjustments independently, without relying on human intervention to manage this task.

Mohr Intelligence Solutions:

  • The research and development team at Mohr has built three tools that regulate the process of shift changes and assign each worker or employee to their correct shift after it has been changed, without the need for human intervention.
AI Shift Management
Movement Nature Prediction Tool

Attendance and departure movements (in case each movement is not certainly defined) are entered into this tool to predict whether this movement is an attendance or a departure.

Shift Planning Tool

Maher’s algorithm for employee shift planning can be used as a proactive intervention tool to improve the accuracy of shift schedules. It can also be used to optimize workforce allocation to shifts.

Shift Prediction Tool

This algorithm examines the employee’s attendance and departure movements and predicts whether the worker has changed their shift or simply arrived or left early or late. If the shift was changed, alerts are handled accordingly.

Movement Nature Prediction Tool

Attendance and departure movements (in case each movement is not certainly defined) are entered into this tool to predict whether this movement is an attendance or a departure.

First card image
Shift Planning Tool

Maher’s algorithm for employee shift planning can be used as a proactive intervention tool to improve the accuracy of shift schedules. It can also be used to optimize workforce allocation to shifts.

Shift planning tool
Shift Prediction Tool

This algorithm examines the employee’s attendance and departure movements and predicts whether the worker has changed their shift or simply arrived or left early or late. If the shift was changed, alerts are handled accordingly.

Attendance prediction tool
AI Shift Management

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