[HR/WFM/Tech] Inovium's Mario Da Roza Presents: How Companies Leverage Machine Learning, Artificial Intelligence, and Analytics in Workforce Management
As organizations strive to maintain efficiency and accuracy in managing their workforce, the integration of Machine Learning (ML) and Artificial Intelligence (AI) into Workforce Management (WFM) solutions is becoming increasingly critical. This presentation will explore how businesses can leverage ML and advanced analytics to optimize their WFM strategies, ensuring policy consistency, detecting anomalies in payroll, and maximizing the effectiveness of their application usage.
We will begin by discussing the importance of policy consistency and how ML can automate the monitoring process to ensure compliance across various teams and locations. By identifying deviations in real-time, organizations can mitigate risks and uphold fair treatment of employees.
Next, we’ll delve into anomaly detection with a focus on payroll tolerance. Using sophisticated algorithms, companies can quickly identify errors or inconsistencies in payroll data, allowing for swift corrections and minimizing financial discrepancies.
The presentation will also cover how businesses can optimize their application usage. Many organizations utilize WFM systems but fail to harness their full potential. We’ll explore how data analytics can reveal inefficiencies and guide process improvements, ensuring that your WFM solution works as effectively as possible.Beyond these points, we will examine how WFM data can be a crucial contributor to monitoring employee well-being. By analyzing data such as scheduled hours, actual work hours, and attrition rates, organizations can detect early signs of employee burnout or risk of attrition. Furthermore, behavioral data can highlight inconsistencies in policy application, helping to close gaps that lead to unfair treatment, legal challenges, or even severe consequences like loss of life.
