Deskless workers make up a substantial portion of the global workforce. These workers operate outside of traditional desk-based office settings and are found in various industries such as healthcare, agriculture, construction, retail, manufacturing, and transportation. Most of these workers lack connection to corporate IT networks, making communication and collaboration more challenging.
Most of these problems can be solved using already well known and user-proven technology — smartwatches. With appropriate software and connection to company systems, this solution is easily implementable. Smartwatches serve as powerful work assistants for deskless workers through three key features:
These features are essential because they allow deskless workers to keep both hands free while staying connected with their teams—all while tasks sync automatically with Microsoft Teams.
The solution is now available as a smartphone app for both Android and iPhone devices. It provides:
The ideal users of WrisPlanner are operational workers who often find themselves in environments where access to a computer is limited or non-existent. These workers typically engage in tasks that make the use of smartphones impractical, either due to the nature of their work or the need for hands-free operation. For these individuals, smartwatches offer an optimal solution, providing a convenient and efficient way to manage tasks and stay connected without the need for bulky or cumbersome devices. By leveraging the capabilities of smartwatches, WrisPlanner ensures that these workers can seamlessly integrate task management into their daily routines, enhancing productivity and reducing the reliance on traditional computing devices.
The technology integrates task management with smartwatch data and AI to enable automatic detection of tasks performed by users.
This data, which includes various activity metrics, is anonymized for privacy and securely stored.
Advanced algorithms analyze the data to identify patterns and correlations, developing a model to recognize and categorize tasks automatically.
Once refined, the model is deployed back to the devices. These devices can then autonomously detect and log tasks in the management system without manual input, leading to the automatic digitalization of work processes and enhancing efficiency and accuracy.