The Beaconforce mobile app continually records employee responses to questions that are personalized and specifically directed to employees based on their previously established attitudes, preferences, sentiments and mental states. Where possible, other diverse metrics including IOT data, individual performance data, and biometrics are recorded to assist in generating recommendations.

The employee state engine infers each employee’s perceptions of skills, challenges, communications, feedback, sense of improvement, risk tolerance, sense of autonomy, mastery, purpose, and control, sense of belonging, team interactions, goal clarity, and other factors. These inferences become the basis for adaptive branching of question streams, recommendations, tips, and suggestions for the development of skills and proficiencies.

Inferences derived from analysis of assessment data drive the creation of recommendations and suggestions for micro-actions – nudges to improve performance. Recommendations and related materials are delivered to employees and managers via the mobile app.

Employees and managers act on suggestions directed at specific competencies and areas of performance. Later, their self-assessment of performance and effectiveness of micro-actions is recorded along with other measurements in future assessments. Through this interactive process, sustainable change can truly happen from within.