To support managers in conducting effective and well-prepared review conversations, Learned offers a smart feature that automatically analyses the review and generates a guide for the conversation. This helps structure the conversation, identify strengths and development areas and encourage open dialogue.
The feature offers managers:
A summary of the review: With an overview of trends, notable feedback and scores, including automatically recognised themes such as growth, cooperation or result orientation.
Insights by section: For example, ‘In the communication section, several colleagues mentioned that [employee] communicates clearly and proactively.’
Suggestions for conversation topics, Including open-ended questions that help make the conversation deeper and constructive, such as: ‘What have you yourself experienced as your most important development last period?’ ‘What support do you need to achieve the next goal?’
A draft conversation structure: For example: start with appreciation, discuss successes, then address development points and conclude with agreements for the future.
What data is used?
The analysis and guidance are based solely on data that:
Are entered within the platform,
Are located in the specific review,
And relate specifically to the employee in question.
It involves:
Completed feedback (from manager, colleagues, employee themselves) within this review
Scores per competency or objective within this review
Goals or progress linked to this employee in this review
No data is used on other employees or from external sources.
How is the data processed?
The AI in Learned analyses the above data to recognise themes, patterns and striking observations.
Based on these, a proposal is generated for conversation structure, points of interest and conversation questions.
The manager receives this as a non-binding guide. Everything remains editable and verifiable.