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DISHA 4.0 HCOS

ENGAGEMENT INTELLIGENCE

Don't Just Measure Engagement. Understand What Shapes It.

Combine structured feedback, pulse signals and authorized organizational context to understand where experience is strengthening or weakening.

What is happening to employee experience, what signals explain it — and what can the organization responsibly improve?

This page owns experience understandingEmployee profilingPerformance evaluationAttrition prediction

The Engagement Pulse Lab

Create a fictional team, select a topic, adjust the response pattern — and watch the system generate an evidence-aware picture.

Fictional team: Platform (12 people)

Signal picture: Workload

Declining

  • Open-text: 6 of 9 responses mention sustained overload
  • Workload pattern: after-hours activity up
Sample: 9 of 12 respondedConfidence: Medium-high

Signals, not verdicts — investigate before acting

Illustrative team — synthetic feedback, fictional people.

Engagement Dimensions

PurposeManager relationshipRecognitionGrowthWorkload sustainabilityAutonomyBelongingPsychological safetyConfidence in direction

Configurable per organization — never imposed.

Purposeful Pulses

Every pulse exists to trigger an action — someone owns the follow-up.

Question ownershipFrequencyAudienceResponse rateAction owner

Five Concepts, Kept Separate

Sentiment

How people feel in the moment.

Engagement

Connection to work over time.

Satisfaction

Judgement of conditions.

Participation

Showing up and contributing.

Commitment

Intention to stay and invest.

They correlate sometimes. They are not the same thing.

Signal Fusion

Combine feedback with authorized contextual signals: team changes, workload patterns, development activity, organizational events.

Do not infer sensitive personal states — ever.

Theme Intelligence

AI groups open-text feedback into themes and emerging issues.

Sustained overloadRepresentative responses: 6 · Confidence: medium-high
Recognition unevennessRepresentative responses: 4 · Confidence: medium
Restructure uncertaintyRepresentative responses: 3 · Confidence: low-medium

Every theme links back to representative source responses — and its confidence.

The Listening Map

Visualize themes by team, function and geography.

Only where privacy and sample-size rules permit.

Driver Exploration

  • What changed?
  • Where?
  • Which themes recur?
  • What organizational event coincided?
  • What evidence supports the interpretation?

The Action Studio

Convert a validated issue into an intervention — then measure whether the signal actually moved.

Workload reviewManager conversationRecognition actionDevelopment action
Record ownerTarget populationExpected effectFollow-up measurementCheck the signal changed

The Manager Cockpit

Team themesResponse contextWhat changedCommitmentsConversation prompts

The Employee Voice

Employees see how feedback is aggregated, what action resulted and when re-measurement will occur.

From Signal to Action

Illustrative demo — fictional team, synthetic feedback

A workload decline, honest themes, two interventions — and the follow-up plans compared side by side.

Engagement AI Agents

Listening Analyst

Designs purposeful pulses.

Theme Analyst

Groups text into honest themes.

Driver Explorer

Investigates what changed.

Action Planner

Structures interventions.

Manager Coach

Prepares manager conversations.

Follow-up Analyst

Checks whether signals moved.

Trend Intelligence

Show movement over time and annotate organizational events.

Avoid causal claims without supporting evidence.

Privacy Safeguards

Minimum sample thresholdsAggregationSuppressionAccess controls

Designed to prevent re-identification.

SEE THE SYSTEM

Listening Is Not the Same as Measuring.

A pulse goes outThemes surface with sourcesAn intervention is plannedThe action runsThe follow-up measures the change

Listen, act, re-measure.

From Listening to Understanding to Acting.

Engagement Intelligence turns feedback into evidence-aware understanding — and every validated issue into an intervention that gets re-measured.

Build a Listening-to-Action System →