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Future of Work · Behavioural Insight · Employee Experience

WorkWave — Exploring Sustainable Work Patterns

Context

Modern knowledge work generates signals around workload, meetings, focus and work rhythms, but those signals can easily become intrusive or difficult to interpret.

Scope

Exploratory behavioural-product concept using public illustrative data.

From Multi-source behavioral dataset

Problem

The design challenge was:

How might organisations understand team-level work patterns without turning behavioural analytics into employee surveillance or diagnostic scoring?

My Role

Behavioural analytics & UX-led concept design combining:

Behavioural insight · Human-centered UX · Information architecture · KPI framing · Ethical analytics

Key Decisions

Structured the concept around descriptive work patterns instead of individual assessment.


Explored relationships between meetings, focus time and workload patterns.


Positioned signals as information for exploration rather than deterministic predictions.

Outcome

Created an exploratory experience showing how team-level workload and focus information could be organised into clearer, more interpretable work-pattern views.

Decision Impact Summary

Key Insight

Behavioural information can support better conversations only when its limitations and context remain visible.


Decision Supported

Help teams identify workload and focus patterns worth discussing or investigating further.


Business Impact

Support more informed conversations around work rhythms and sustainable team practices.

UX Section

Work Pattern Experience & Information Architecture

WorkWave is structured into three executive-ready dashboard layers, each aligned with a specific organizational decision need.

Overview — Recognize

Workload
Focus patterns
Team-level trends

Workload & Focus — Understand

Meeting load
Focus time
Weekly patterns

Trends — Explore

Long-term patterns
Workload evolution
Recurring signals

Why it matters

Demonstrates how behavioural thinking and UX can make organisational information more understandable while preserving a people-first approach.

Applicable contexts

Future of Work · Employee Experience · HR Technology · Behavioural Products

Extended case details available upon request.

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© 2026 Maria Gioia Petrocchi
Digital Product Analyst

Product Analyst · Product Analytics · KPI Systems · Decision Support

Open to full-time, permanent roles (EU – on-site, hybrid, or remote)
Ethical, data-informed decision-making