The More You Use Shiftlyx, the Better It Gets. Here's How

The More You Use Shiftlyx, the Better It Gets — Here's How

Preference learning is not magic. Here is exactly how Shiftlyx learns what matters to you, shift by shift.

The Four Affinity Scores

Shiftlyx tracks four dimensions of your preferences, each building a profile over time.

**Income affinity:** Do you consistently choose shifts with higher pay? Night enhancements, weekend premiums, bank shifts? The income score increases when your pattern favours earnings over other factors.

**Recovery affinity:** Do you prioritise rest? Consecutive days off, limited night clusters, adequate turnaround gaps? The recovery score climbs when your pattern aligns with optimal recovery.

**Continuity affinity:** Do you prefer the same shift type consistently? Sticking to days or nights rather than flipping? Continuity affinity rises when your pattern shows minimal circadian disruption.

**Social affinity:** Do you avoid weekends or target specific days? The social score reflects how well your pattern matches your stated off-day priorities.

How Learning Works

Every shift you enter, every adjustment you make, and every strategy you use feeds into the model. Shiftlyx uses a weighted moving average: recent patterns matter more than old ones.

**After 5 shifts:** Basic profile. The system knows whether you tend toward days or nights.

**After 15 shifts:** Reliable predictions. The system can suggest optimal shift patterns with confidence.

**After 30 shifts:** Deep understanding. The system's recommendations align with your actual preferences, not just your stated ones.

The Key Insight: Stated vs Revealed Preferences

What you say you want and what your pattern reveals are often different. You might say "I want to work fewer nights" but your actual shift choices show you consistently picking up night bank shifts because they pay more. Shiftlyx tracks both. Your stated preferences from the onboarding questionnaire set the initial profile. Your revealed preferences from actual behaviour refine it.

What This Means for Planning

The planner does not ask you to rank priorities every time. It uses your affinity scores to generate ranked candidates that match your actual preferences. As the scores stabilise, the green checkmark on recommended shifts becomes more reliable. The strategies learn which trade-offs you actually make.

**Privacy note:** All preference data stays on your device. Shiftlyx uses local processing for learning. No preferences are sent to a server or shared with your employer.

**References:** Shiftlyx Preference Learning Technical Documentation.