Etch Media — Staff Tracking & Performance

Powered by Etch Media AI • Real-time Workforce Intelligence

Today: 25 Mar 2026

Executive Overview

Real-time staff performance metrics powered by AI-driven camera network analysis

Active Staff On Floor
24/28
85.7% present
+2.1%vs last week
Staff Floor Coverage
87.3%
% of hours with adequate zone staffing
+3.2%vs last week
Break Compliance
94.2%
Exit camera: left & returned on time
+2.1%vs last week
Customer Happiness Score
7.8/10
Facial emotion AI detection
+0.4vs last week

Staff Activity Breakdown

Staff Activity Breakdown

Camera AI classifies staff into 4 observable states:
• With Customer — staff detected within proximity of a customer (serving/assisting)
• On Floor (Available) — present in store zones, no customer nearby, no phone
• On Phone — personal phone detected in hand during shift
• On Break — exited store via exit camera

These are the only states the camera can reliably distinguish.

Insight: 45% of shift time spent with customers is strong. 8% phone usage (mostly 2–4PM) is above the 5% target. 15% on break is within policy. Consider phone policy reminder to reduce non-break phone time.

Weekly Trend — Camera Observables

Weekly Camera-Observable Metrics

All metrics are directly observed by camera AI:
• Customer Interactions (bars) — count of staff-customer proximity events per day
• Phone Violations (red line) — phone usage incidents detected during shift hours
• Floor Presence % (green line) — % of shift time staff are visible on floor cameras

No manual input required. Fully automated.

Insight: Saturday peaks at 248 interactions with 92% floor presence. Phone violations lowest on Sat (2) and highest on Wed (8) — mid-week slump pattern. Floor presence dips to 84% on Wednesday, correlating with higher phone use.

Attendance Trend This Week

Attendance Trend

Stacked bar showing Present, Absent, and Late staff by day. Helps identify attendance patterns and potential scheduling issues. Auto-logged from AI camera network and badge readers.

Insight: Monday shows 3 lates (higher than avg). Consider earlier briefings on Mondays or revisit shift start times. Attendance otherwise stable—no absence spike detected.

Real-Time Location & Activity

AI camera network tracks staff location and activity classification across zones

Staff in Zone A (Sales Floor)
12
Primary selling area
Staff in Zone B (Checkout)
5
Payment processing
Staff in Zone C (Stock Room)
4
Replenishment & prep
Staff on Break
3
Currently off-duty

Hourly Zone Distribution (8AM–9PM)

Zone Distribution Over Day

Stacked area chart showing how staff spread across three zones throughout the day. Zone A (Sales Floor) should peak during customer hours. Reveals staffing imbalances and opportunity to shift resources.

Insight: Zone A peaks at 2PM (14 staff) then drops to 8 at 5PM, despite 6–7PM being peak customer hours. Recommend shifting lunch breaks to 5–6PM to maximize floor presence during high-traffic periods.

Activity Classification Timeline

Activity by Hour (Camera-Observable)

Hourly stacked bar showing 4 camera-detectable states:
• With Customer — staff in proximity to customer
• On Floor (Available) — visible on floor, no customer or phone
• On Phone — phone detected in hand during shift
• On Break — exited via exit camera

Helps identify when phone usage spikes and when staff are most customer-engaged.

Insight: 6–7PM shows highest "With Customer" rate (15 of 24 staff). Phone usage spikes at 2–3PM (4 staff on phone simultaneously). Break times cluster at 12–1PM as expected. Floor availability dips at 4PM — consider staggering breaks to maintain coverage.

Zone Coverage Heatmap

Coverage by Zone

Horizontal bar chart showing ideal vs actual coverage % for each zone. Green = well-staffed, Orange/Red = under-covered. Under-coverage can lead to missed customer interactions and longer queues.

Insight: Zone B (Checkout) at 71% coverage during peak hours is below target (80–85%). Adding 1–2 staff or cross-training would reduce queue times from current 3.2 min to target <2 min.

Staff Movement Between Zones

Zone Transitions

Shows frequency of staff movement between zones. High movement suggests staff are responding to needs dynamically. Excessive movement may indicate inefficient task allocation or unclear zone ownership.

Insight: 156 transitions between A↔B and 142 between A↔C is healthy. 64 transitions C↔B suggests stock room staff are helping with checkout overflow—consider dedicated checkout cross-training.

Store Performance Comparison

Aggregate floor metrics compared across branches — camera-observable, no individual identification on floor

Best Performing Store
KLCC
Store Score: 88/100
Avg Interactions/hr (All Stores)
8.2
Aggregate proximity events
+1.3vs last week
Avg Floor Coverage (All Stores)
87.3%
% hours with adequate zone staffing
+3.2%vs last week
Customer Happiness (All Stores)
7.8/10
Exit camera emotion detection
+0.4vs last week

Store Performance Ranking

Store Score — Camera-Observable Formula

Store Score = (Floor Coverage % × 25%) + (Interaction Rate × 25%) + (Break Compliance × 20%) + (Customer Happiness × 20%) + (Phone Discipline × 10%)

All inputs are aggregate camera metrics per store:
• Floor Coverage % — % of operating hours with adequate staff in each zone
• Interaction Rate — staff-customer proximity events per hour
• Break Compliance — % of staff who returned from break on time (exit camera)
• Customer Happiness — exit camera facial emotion (% positive)
• Phone Discipline — inverse of phone violations per shift-hour

Compared across all branches for fair benchmarking.

Insight: KLCC (88) leads — highest floor coverage (94%) and lowest phone violations. Bangsar (84) close behind. Sunway (76) lags due to higher phone usage and low floor coverage during peak hours. Recommend Sunway manager review staffing during 5–7PM rush.

Interaction Rate by Hour (Store Comparison)

Hourly Interaction Rate per Store

Camera counts staff-customer proximity events per hour at each store. Comparing across stores reveals which locations handle peak hours better and which need staffing adjustments.

Insight: KLCC peaks at 14.2 interactions/hr at 6PM vs Sunway's 9.6. Bangsar maintains the most consistent rate throughout the day. Mont Kiara shows sharp drop at 2–4PM — correlates with floor presence dip.

Floor Coverage by Store

Zone Staff Coverage per Store

Grouped bar showing floor coverage % and phone violation rate per store. Higher coverage = more hours with adequate staff in zones. Lower phone rate = better discipline. Both are directly measured by floor cameras.

Insight: Pavilion has lowest floor coverage (78%) despite high foot traffic — likely understaffed during peaks. KLCC leads at 94% coverage. Sunway has highest phone violation rate (5.8/hr), dragging its coverage down to 80%. Recommend staffing review for Pavilion and phone policy enforcement at Sunway.

Customer Happiness by Store (Exit Camera)

Facial Emotion at Exit

Exit cameras (eye-level) detect customer facial expressions as they leave. Happiness Score = (% Positive × 10) + (% Neutral × 5) + (% Negative × 0), normalised to 0–10.

This is the most reliable emotion metric — captured at controlled eye-level angle as customers exit. Compare across stores to identify service quality differences.

Insight: Bangsar leads happiness (8.2/10) — 74% positive exits. Sunway lowest (7.1/10) — 18% negative exits, correlating with lower floor coverage (80%). Improving Sunway's staffing during peak hours could raise happiness score by 0.5–0.8 points.

Attendance & Compliance

Automated attendance tracking and break/policy compliance metrics

On-Time Rate
96.4%
This month
+1.8%vs last month
Est. Avg Clock-In Time
~8:52 AM
Estimated — first camera detection
-4 minvs last week
Break Policy Compliance
94.2%
Took scheduled breaks
+2.1%vs last week
Avg Hours on Floor
7.2 hrs
Detected by floor cameras

Weekly Attendance (Stacked)

Weekly Attendance

Stacked bar showing On-Time (green), Late (orange), and Absent (red) staff by day. Auto-logged from entrance/exit face recognition cameras, eliminating manual tracking errors.

Insight: Monday shows 3 lates (above typical 1–2). Tuesday–Friday stable. Thursday 1 absence (illness called in). Track Monday lates for pattern—may need shift time adjustment or manager reminder.

Break Duration Distribution

Break Length Patterns

Bar chart showing breakdown of break durations. Most staff take 15–30 min breaks as scheduled. Staff exceeding limits may need reminders. Too-short breaks (under 10 min) reduce rest quality.

Insight: 72% of breaks are 15–30 min (policy-compliant). 18% exceed 30 min (only 2–3 staff repeat offenders). Brief reminder on clock discipline could tighten compliance to 96%+.

Clock-In Time Distribution

Clock-In Times

Distribution of staff clock-in times in 15-minute intervals. Shows how many staff arrive early vs late relative to shift start (9:00 AM). On-time is 9:00–9:15 AM; early (<9:00) is proactive; late is after 9:15.

Insight: 18 staff clock in early (before 9:00)—sign of engagement. 24 on-time, 3 late. No staff are more than 10 min late. Overall punctuality is strong. Monitor the 3 late staff for patterns.

Late Arrivals This Week (Individual)

Late Arrivals — Face Recognition

Staff identified arriving after shift start via entrance camera face recognition. Shows how many minutes late each person was detected. Note: times are estimated based on first camera detection — actual arrival may be slightly earlier.

Insight: Mark T. late 3 times this week (avg 12 min) — emerging pattern. John M. late twice but only 3–5 min. All others on time. Consider a Monday reminder for Mark T. since 2 of 3 lates were on Monday.

Behavior & Phone Analysis

Floor camera AI detects phone usage, staff-customer proximity, and activity states (aggregate — no individual identification)

With Customer %
45%
Staff in proximity to customers
+3.2%vs last week
Floor Presence %
87%
Staff detected on floor cameras
+4.1%vs last week
Phone Violations Today
24
Aggregate across all staff
Peak Phone Hour
2–3 PM
4 simultaneous detections

Floor Presence vs Phone Usage Trend

Hourly Floor Activity

Line chart showing two camera-observable metrics by hour:
• Floor Presence % — % of scheduled staff detected on floor cameras
• Phone Detection % — % of floor staff with phone-in-hand detected

When floor presence dips and phone detection rises, it signals an attention problem. Both are aggregate — no individual identification.

Insight: Floor presence peaks at 9AM (94%) and 6PM (89%), dips to 78% at 4PM. Phone detection inversely spikes at 2–3PM (22%). The afternoon dip correlates with both lower floor presence and higher phone use. Consider staggering breaks or a brief team huddle at 3:30PM.

Activity Level by Zone

Zone Activity

Bar chart showing average activity level (0–100) per zone, based on:
• Staff-customer proximity events
• Movement frequency
• Staff count vs target

Sales Floor expected highest (customer interaction). Stock Room lower but should be 70+. All aggregate, no individual identification.

Insight: Zone A (Sales Floor) shows 86 activity level — high customer-facing interaction. Zone C (Stock Room) at 74 — expected lower due to fewer customers. Zone B (Checkout) at 82 — consistent with transaction volume.

Staff Activity Breakdown (Aggregate)

Behavior Tracking (Aggregate)

AI classifies aggregate staff behavior on the floor (no individual identification):
• With Customer — in proximity to customer
• Available — on floor, no customer nearby
• Phone Use — phone detected in hand
• On Break — exited via exit camera

Phone usage is tracked as total incidents per store. Individual identity is NOT known from floor cameras.

Insight: 42% with customer and 28% available is healthy. Phone usage detected 24 times today (aggregate — individual identity unknown from floor cameras). Highest phone concentration during 2–4PM. Recommend store-wide phone policy reminder during afternoon briefing.

Phone Violations by Store

Phone Violations — Store Comparison

Aggregate phone violations detected per store today. Camera detects phone-in-hand during shift hours (excludes break areas). Individual identity is NOT tracked — only total count per store. Compare across branches to identify stores needing policy reinforcement.

Insight: Sunway leads with 38 phone violations (highest per-staff-hour rate). KLCC lowest at 12 violations. Sunway's phone violations correlate with its lower Store Performance Score (76) — phone discipline accounts for 10% of the score formula. Recommend Sunway-specific phone policy enforcement.