AI and performance measurement

Published on 25/03/2024

AI and performance measurement

Published on 25/03/2024
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AI and performance measurement

In the realm of talent management, a tangible transformation is underway: the era of traditional performance measurement methods, characterized by their rigidity and retrospective outlook, is giving way to a new, dynamic, and proactive vision driven by artificial intelligence (AI).

For years, HR departments have relied on subjective evaluations and self-assessment forms to chart their teams’ performance. Although reliable, these methods have led to biases, offering a view of work performance that often seems more a fragmented reflection than a clear and complete picture.

The introduction of AI in this field overcomes these limitations, heralding a new era in performance measurement. By integrating intelligent systems, organizations are adopting a more dynamic, proactive, and objective approach.

AI not only facilitates real-time data collection and analysis but also introduces a degree of customization and foresight previously unattainable. This shift is not only reforming measurement methods but is also recalibrating expectations and outcomes in the realm of Human Resources.

There are several ways in which artificial intelligence is used to assess staff performance compared to more traditional methods.

Productivity and efficiency tracking

Traditionally, HR has used manual methods to track tasks and evaluate productivity. These methods can lead to human errors and consume a significant amount of time within department functions. Moreover, they can be intrusive and generate distrust, negatively affecting workers’ morale and productivity.

Therefore, with the digitalization of companies and the incorporation of Artificial Intelligence tools, employees’ activities and work patterns can be analyzed automatically and efficiently.

There are advanced performance management systems, such as the one developed by WorkMeter, that facilitate measuring and evaluating employees’ productivity, achieving:

  • Real-time activity tracking. It allows identifying when employees are most active or detecting decreasing productivity peaks.
  • Detailed reports on application usage. Know which applications are most used in each department and if their use affects an increase or decrease in productivity.
  • Tracking time spent on websites. Details the times spent on productive websites according to the nature of the job.
  • Drawing conclusions from a large volume of data. Productivity and performance data are presented in interactive dashboards where managers and employees can clearly view the information.
  • Assisting in decision-making and feedback meetings. HR managers can obtain objective results in which positive or negative productivity deviations are detected as arguments during periodic performance evaluations.
  • Offering personalized and self-consumable data. Employees can optimize their performance without feeling intrusively supervised by accessing their performance results.

These solutions revolutionize how organizations monitor, evaluate, and improve their operations. By incorporating AI, an era is marked were the search for precision, customization, and foresight is paramount.

Performance measurement in telework with AI

As organizations adopt remote work models, AI offers innovative solutions to overcome the unique challenges posed by performance supervision and management at a distance.

In 2023, WorkMeter published a report on the main telework metrics, supported by more than 46,000 records collected automatically. This study not only makes a deep comparison between in-person and remote work but also details a variety of key indicators such as productivity, activity, and focus.

Furthermore, the report examines how these indicators vary between different roles within the organization, specifically contrasting differences between managers and employees; it also contrasts these results between the different work models, in-person, hybrid, and remote work.

The following are ways AI can enhance productivity and employee performance tracking in telework:

  • PC activity tracking. As mentioned, keeping a record of workers’ activities at their workplaces can allow tracking their productivity level in telework.
  • Automatically detecting telework. Through behavioral studies, there are systems that can tell if a user is working from home or the office.
  • Automatically keeping track of absences. Incorporate tools that detect unauthorized absences on telework days when the employee is expected to be at their workplace.
  • Streamlining communication without affecting productivity. Knowing which workers are available throughout the workday to not interrupt productive tasks that make them lose their thread of tasks.
  • Through virtual assistants. Providing employees with real-time chat that resolves doubts related to organizational topics can save time for other departments.

This leads to a deeper and more detailed understanding of productivity, focus, and employee engagement in both remote and in-person environments. Moreover, it gives organizations the ability to anticipate and adapt to emerging remote work challenges, thus promoting a more efficient and satisfied workforce.

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