Task analysis of groups
The artificial intelligence of the Yva platorm uses NLP (Natural Language Processing) to recognize the presence of tasks, positive, negative or conflicts in communications between employees.
The information contained in text messages is extremely sensitive to the business of our customers. With this awareness, we deliberately designed Yva in such a way that all text analytics are implemented as a classification. The system has a task: to understand whether the text contains a set of high-level features that can give useful information about the performance of individual employee of the company, about their contribution to a healthy atmosphere in the team, about the actual (not nominal) place of the employee in the business processes of the enterprise.
Yva is designed in such a way that text messages are not stored in the platform, so they cannot be read or stolen, they only exist in the information systems of the customer's company. It is absolutely safe to trust Yva to “read” the text.
We have developed and patented a two-step procedure for working with text. Thanks to it, we can use already trained classifiers or train new ones even without the text itself.
Yva platform understands a task as the presence of instructions for a specific person or group of employees in the message's informative part.
Examples of tasks:
Print out, sign and send the courier with the documents to the address below.
Schedule a meeting, discuss my proposal and inform me about the result.
John, choose an acceptable option and give appropriate instructions.
Metrics of an employee communication with tasks are divided into three blocks:
Metrics for all contacts, that is, any communication of an employee,
Metrics for internal contacts, that is, communication within the organization,
Metrics for external contacts, that is, communication with people outside the organization.
For each block of metrics Yva calculates: