June 6, 2026 · Last 5 completed weeks · Source: Looker (hair boxes) · Weekly refresh every Monday
Avg Wait Time (TTS)
5.2d
Jun MTD · Target <8d · ✓ on track
Transit Time
2.4d
Jun MTD · Amazon 1.9d · ✓ structural low
SLA ≤10 days
82.6%
May full · Target >90% · −7.4pp
Boxes Shipped
179K
May full · Jun MTD 30K
Backlog Time
2.5d
Jun MTD · Target <2.0d · +0.5d
Trash Items
6.5K
May · Apr 11.6K · Jun MTD 1.8K · improving
NPS · Repeat
35.7
L3M · Target >40 · New cust: 8.0
Inventory Turns
6.8×
May · YTD Jan–May 6.2× · Target >5× · ✓ above target
Not Shipped — Orders Still in Production
>10 days (placed before May 27)
617
Boxes in active production · preparing / packing / buffering
>20 days (placed before May 17)
138
Critical — 2× SLA miss · immediate escalation needed
As of June 6 · Looker order_items · active production statuses only (excludes cancelled/stopped) · refreshed daily 7am ET
Customer Wait Time — 13-Month Trend
Monthly Box Volume
NPS — L12M by Month
Overall (new + repeat) · Target >40
SLA ≤10 Days — L12M
Hair boxes shipped · Target >90%
Inventory Turns — L12M
Annualized COGS / EOM Inventory · Target >5×
2026 KPI SCORECARD
COO Annual Goals — Live Performance
CEO ↔ COO 1:1 · June 5, 2026 · Financials: Flash P&L May 2026 (unaudited) · Ops: Looker (daily auto-refresh)
01 · Financial
01 · Financial
Gross Margin %
2026 FY Target >75.3%
Last Month (May)
73.9%
73–75% band
YTD Jan–May
72.4%
below 73% floor
01 · Financial
Labor Cost / Unit
2026 FY Target <$1.10
Last Month (May)
$1.33
$1.15–$1.35 band
YTD Jan–May
$1.37
above $1.35 ceiling
01 · Financial
Shipment Cost / Order
2026 FY Target <$5.00
Last Month (May)
$4.83
✓ hits target
YTD Jan–May
$5.34
+$0.34 vs target
02 · Customer
02 · Customer
Time to Serve
2026 FY Target <8.0 days
Last Month (May)
7.6d
✓ hits target
YTD Jan–May
9.6d
Jun MTD: 5.0d ✓
02 · Customer
Service Level (≤10 days)
2026 FY Target >90%
Last Month (May)
82.6%
−7.4pp vs target
YTD Jan–May
69.2%
−20.8pp vs target
02 · Customer
Quality Complaints
2026 FY Target <0.1%
Complaint Rate
—
Kustomer not connected
Internal Proxy
~2.6%
Defect / trash rate
⚠ No Kustomer MCP available — complaint data not accessible programmatically. Options: (1) connect Kustomer API, (2) Looker Kustomer explore (needs Audrey to expose it), (3) manual monthly input. Using defect/trash rate as internal quality proxy in the meantime.
03 · Supply Chain
03 · Supply Chain
Inventory Turns
2026 FY Target >5×
Last Month (May)
6.8×
+1.1× vs target
YTD Jan–May
6.2×
+1.2× vs target
Source: Prose Financials 2026-5 · Balance Sheet tab · Jun 6 2026
03 · Supply Chain
Algo Shortages
2026 FY Target = 0
Last Month
—
Pending planning system
YTD
—
Pending planning system
Algo-driven planning shortages not yet tracked in Looker or Finance files. Unlocks with new planning + procurement system (Goal 01 · Sept 2026).
Monthly KPI Summary — 2026
| KPI | Target | Jan | Feb | Mar | Apr | May | Jun MTD |
|---|---|---|---|---|---|---|---|
| Gross Margin % | >75.3% | 69.6% | 71.0% | 73.4% | 73.9% | 73.9% | — |
| Shipment Cost / Order | <$5.00 | $5.50 | $5.52 | $5.97 | $4.85 | $4.83 | — |
| Labor / Unit | <$1.10 | $1.42 | $1.36 | $1.35 | $1.39 | $1.33 | — |
| Time to Serve | <8.0d | 10.1d | 10.0d | 12.1d | 7.8d | 7.6d | 5.0d |
| SLA % (≤10d) | >90% | 65.8% | 67.4% | 49.7% | 82.6% | 82.6% | — |
| Quality Complaints | <0.1% | Pending Kustomer integration | |||||
| Inventory Turns | >5× | 6.1× | 5.9× | 6.3× | 6.1× | 6.8× | — |
| Algo Shortages | =0 | Pending planning system (Goal 01 · Sept 2026) | |||||
Financials: Flash P&L May 2026 (unaudited, drop new file monthly into uploads/Financials/) · TTS/SLA: Looker, hair boxes, daily auto-refresh
2026 Bonus Score — Live · YTD Jan–May 2026
| KPI | Weight | 2026 Target | YTD Value | Score /100 | Weighted | Status |
|---|---|---|---|---|---|---|
| Gross Margin % | 30% | >75% | 72.4% | 35.2 | 10.6 | 🔴 |
| Time to Serve | 20% | <8.0d | 9.6d | 48.0 | 9.6 | 🟡 |
| Labor Cost / Unit | 10% | <$1.15 | $1.37 | 37.3 | 3.7 | 🔴 |
| Shipment Cost / Order | 10% | <$5.00 | $5.34 | 52.8 | 5.3 | 🟡 |
| Service Level (SLA %) | 10% | >90% | 69.2% | 25.6 | 2.6 | 🔴 |
| Inventory Turns | 10% | >5× | 6.2× (Jan–May) | 100.0 | 10.0 | 🟢 |
| Quality Complaints | 5% | <0.1% | — | — | — | ⏳ |
| Algo Shortages | 5% | =0 | — | — | — | ⏳ |
| KPI Total (90% scored) | 90% | 41.7 | 33.4 / 80 |
Future Projects & Leadership Score (input by CEO · /100)
/100
KPI (80%)
50.5
/ 80 pts
+
Personal (20%)
0.0
/ 20 pts
=
Total Bonus Score
50.5
/ 100 pts
SCORING METHODOLOGY
GM % · 30% weight (x2.4 avg)
0 pts @ 68% → 40 @ 73% → 80 @ 75% → 100 @ 76%
Every point counts — steepest curve
0 pts @ 68% → 40 @ 73% → 80 @ 75% → 100 @ 76%
Every point counts — steepest curve
Time to Serve · 20% weight (x2 avg)
0 pts @ 14d → 40 @ 10d → 80 @ 8d → 100 @ 7d
0 pts @ 14d → 40 @ 10d → 80 @ 8d → 100 @ 7d
Labor / Unit · 10% weight
0 pts @ $1.65 → 40 @ $1.35 → 80 @ $1.15 → 100 @ $1.05
0 pts @ $1.65 → 40 @ $1.35 → 80 @ $1.15 → 100 @ $1.05
Shipment / Order · 10% weight
0 pts @ $6.50 → 40 @ $5.50 → 80 @ $5.00 → 100 @ $4.50
0 pts @ $6.50 → 40 @ $5.50 → 80 @ $5.00 → 100 @ $4.50
Service Level · 10% weight
0 pts @ 50% → 40 @ 80% → 80 @ 90% → 100 @ 95%
0 pts @ 50% → 40 @ 80% → 80 @ 90% → 100 @ 95%
Inventory Turns · 10% weight
0 pts @ 2× → 40 @ 4× → 80 @ 5× → 100 @ 6×
0 pts @ 2× → 40 @ 4× → 80 @ 5× → 100 @ 6×
Quality Complaints (5%) + Algo Shortages (5%) scored at 0 pending data — will be added once Kustomer MCP and planning system are live (Sept 2026).
· Bonus = KPI score × 80% + Personal score × 20%.
· Piecewise linear interpolation within each band. Capped at 100 per KPI.
Time To Serve (Hair Care) MAY 2026 — BEST IN 17 MONTHS
Total TTS (May 2026)
7.4d
-0.2d vs Apr (7.6d) · -4.8d vs Mar (12.2d)
vs Prior Month
-2.6%
2nd consecutive monthly improvement
SLA % within 10 days
85.8%
Best in 17 months — Target >75%
vs Prior Month SLA
+2.4pp
Apr 83.4% → May 85.8%
Component Breakdown — Mar → Apr → May 2026
Delivery Time (Transit)
4.3d
Mar 7.4d → Apr 4.3d → May 4.3d (-42% vs Mar)
COO deck Delivery: 5.6 → 3.0 → 3.0d (Amazon-only Hair-Care, narrower scope)
Backlog Time (Processing + T&I)
2.6d
Mar 4.3d → Apr 3.0d → May 2.6d (-39% vs Mar)
COO splits into Testing+Induction (1.6d) + Processing (2.8d). Looker reports the combined backlog.
Total TTS
7.4d
Mar 12.2d → Apr 7.6d → May 7.4d (-39% vs Mar)
Order placement → box delivered, hair-only valid orders.
COO Executive Deck — Component Split (Reference)
| Month | Delivery | Testing + Induction | Processing | Total TTS | SLA ≤10d |
|---|---|---|---|---|---|
| Mar 2026 | 5.6 | 2.2 | 3.8 | 11.6 | ~50% |
| Apr 2026 | 3.0 | 1.7 | 2.5 | 7.2 | 85.0% |
| May 2026 | 3.0 | 1.6 | 2.8 | 7.4 | 86.7% |
COO deck breaks Backlog into Testing + Induction (1.6d in May — lowest in 17 months) and Processing (2.8d, slight tick up from Apr 2.5d, still -26% vs March). Looker delivers the combined backlog (2.6d). The Testing+Induction/Processing decomposition is pending Ops field validation (Solana Vargas, BANA) — once those status timestamps are surfaced as Looker dimensions, this dashboard can show the 3-way split natively.
18-Month TTS Trend — Hair Care (Backlog + Delivery, with SLA % overlay)
Total TTS — 18-Month Trend (Hair Care)
SLA % ≤10 Days — 18-Month Trend
Data quality: Hair Care DTC only (
box_details.box_contains_haircare = Yes & order.is_valid_sales_order = Yes). TTS measured from order placement to delivery (days_between_order_placed_and_box_delivered). Testing+Induction / Processing decomposition pending Ops field validation (Solana Vargas, BANA) — currently shown as combined Backlog. Source: Looker Test_model.production_items explore. Data refresh: hourly via Airflow.
End-to-End Delivery Performance
Best Month (T12)
8.8d
Sep 2025
Worst Month (T12)
13.7d
Apr 2026
May MTD Wait
9.5d
Through May 15
P95 (Slowest 5%)
~17d*
*Stale (Feb 2026)
Monthly Wait Time Trend
New vs Repeat: Wait Time (6-Month Trend)
New vs Repeat: Backlog Time (6-Month Trend)
SLA Compliance (Last 3 Months)
SLA Compliance: New vs Repeat (Feb 2026)
| Threshold | Repeat | New (1st Order) | Gap |
|---|---|---|---|
| ≤7 days | 31.2% | 21.4% | -9.8pp |
| ≤10 days | 67.2% | 56.6% | -10.6pp |
| ≤14 days | 89.6% | 85.4% | -4.2pp |
| >21 days | 1.4% | 1.4% | 0.0pp |
The SLA gap is concentrated at the 7-10 day window (10.6pp), confirming backlog as the culprit. The long tail (>21 days) is identical for both segments.
Monthly Performance Detail
| Month | Avg Wait (d) | Backlog (d) | Transit (d) | Boxes Shipped |
|---|---|---|---|---|
| May 2025 | 9.9 | 2.1 | 7.4 | 219,224 |
| Jun 2025 | 10.1 | 2.3 | 7.4 | 244,493 |
| Jul 2025 | 9.7 | 2.2 | 7.1 | 242,193 |
| Aug 2025 | 9.0 | 1.7 | 6.9 | 229,326 |
| Sep 2025 | 8.8 | 1.8 | 6.5 | 228,782 |
| Oct 2025 | 9.0 | 2.1 | 6.6 | 209,890 |
| Nov 2025 | 9.6 | 2.4 | 6.7 | 182,424 |
| Dec 2025 | 9.4 | 2.2 | 6.8 | 211,918 |
| Jan 2026 | 10.1 | 2.6 | 7.0 | 201,077 |
| Feb 2026 | 10.0 | 2.8 | 6.9 | 175,350 |
| Mar 2026 | 12.1 | 3.9 | 7.7 | 210,691 |
| Apr 2026 | 13.7 | 2.8 | 9.6 | 202,197 |
| May 2026 MTD | 9.5 | 1.6 | 7.5 | 84,214 |
Key insight: March was a backlog-driven regression (production queue peaked at 3.9d). Now with Amazon transit data confirmed at 3.3d (Apr) and 4.2d (May), the picture is clear: the carrier switch was not the cause — Amazon has been fast all along. May full: 7.6d wait. June MTD: 5.0d — 13-month low, approaching the Sep 2025 operational best of 8.8d overall.
Year-over-Year Comparison (Avg Wait Time)
| Month | Prior Year | This Year | Improvement |
|---|---|---|---|
| May | 13.0d | 9.9d | -3.1d (24%) |
| June | 11.4d | 10.1d | -1.4d (12%) |
| July | 11.6d | 9.7d | -2.0d (17%) |
| August | 15.0d | 9.0d | -6.0d (40%) |
| September | 12.7d | 8.8d | -4.0d (31%) |
| October | 10.9d | 9.0d | -1.8d (17%) |
| November | 10.9d | 9.6d | -1.3d (12%) |
| December | 11.7d | 9.4d | -2.4d (20%) |
| January | 11.9d | 10.1d | -1.8d (15%) |
| February | 10.0d | 10.0d | -0.0d (0%) |
| March | 9.4d | 12.1d | +2.7d worse |
| April | 9.2d | 13.7d | +4.5d worse |
| May MTD | 9.9d | 9.5d | -0.3d (3%) |
The YoY narrative has fully recovered: March was a backlog-driven regression (production queue 3.9d), not carrier-driven — Amazon transit was 3.3d even in April. May 2026 (7.6d) is now below the prior-year May (~8.8d). June MTD at 5.0d is the strongest YoY outperformance in the trailing window — new operational ceiling established with Amazon as primary carrier.
Manufacturing — Items shipped · 2026 YTD · Source: Looker production_items · Hourly refresh
Total — YTD 2026
2.77M
Week of Jun 1
95.1K
Trash Rate YTD
1.88%
LV · Liberty View, NY
65% of total
1.80M
Week of Jun 1
61.0K
Trash Rate YTD
0.94%
YA · Yates, California
35% of total
968K
Week of Jun 1
34.1K
Trash Rate YTD
3.64%
Weekly Items Shipped — LV vs YA
Items shipped per week · 2026 YTD · formula & revenue-generating items only
Weekly Trash Items — LV vs YA
Trashed items per week with overall rate % (right axis)
Weekly Output by Product Category
Haircare · Skincare · Supplements · Sample Skincare (SSS) — items shipped in thousands
Factory Performance — YTD 2026
| Metric | LV · Liberty View | YA · Yates | Total |
|---|---|---|---|
| Items Shipped YTD | 1,801,403 | 967,899 | 2,769,302 |
| Share of Output | 65.0% | 35.0% | 100% |
| Items Trashed YTD | 16,848 | 35,265 | 52,113 |
| Trash Rate YTD | 0.94% | 3.64% | 1.88% |
| Week of Jun 1 | 60,974 | 34,107 | 95,081 |
| Avg Backlog Time | — | — | 2.5d |
Key finding: YA trash rate (3.64%) is 3.9× higher than LV (0.94%). YA accounts for 68% of all trashed items despite only 35% of volume. This is the primary manufacturing quality gap to investigate.
Carrier Performance
Amazon Volume Share
84.8%
May full · 151,849 boxes
Amazon Transit
4.2d
May full · Jun MTD 1.9d ↓
DHL Transit (CA-focused)
9.9d
May full · 4.6% share · Canada only
PB Transit
12.2d
May full · 9.1% share · US only
Carrier Transit Times — 6-Month Trend
Carrier Volume Mix
Carrier Overview — May 2026 (full month)
| Carrier | Boxes | Share | Transit (d) | Notes |
|---|---|---|---|---|
| Amazon Shipping | 151,849 | 84.8% | 4.2 | US only. Jun MTD 1.9d — fastest carrier. Was 3.3d in Apr. |
| Pitney Bowes | 16,254 | 9.1% | 12.2 | US only. Consistently slowest — structural issue. |
| DHL | 8,190 | 4.6% | 9.9 | Canada only now. Consistent with international SLAs. |
| USPS | 2,790 | 1.6% | 5.3 | Small volume, strong performance. |
Amazon handles 84.8% of total volume and is now the fastest carrier at 4.2d — confirming the switch from DHL US was the right call. Transit data is now fully available in Looker. June MTD Amazon transit is 1.9d, pulling overall wait time to a 13-month low of 5.0d. PB remains the structural weak point at 12.2d (US-only, 9.1% of volume). DHL is Canada-only at 9.9d, consistent with cross-border SLAs.
Carrier Trend — Jan–Jun 2026 (Avg Transit Days)
| Carrier | Jan 26 | Feb 26 | Mar 26 | Apr 26 | May 26 | Jun MTD |
|---|---|---|---|---|---|---|
| Amazon | — | — | — | 3.3 | 4.2 | 1.9 |
| DHL | 6.9 | 6.7 | 7.5 | 9.8 | 9.9 | — |
| PB | 13.0 | 15.4 | 13.6 | 12.8 | 12.2 | — |
| USPS | 5.4 | 4.5 | 4.9 | 5.6 | 5.3 | 2.6 |
Amazon transit data is now fully available in Looker — the switch from DHL US was validated: Amazon has been running 3–4d transit since launch, faster than DHL's 6.9d baseline. DHL's elevated transit (~9.8d) reflects its shift to Canada-only routes. PB remains structurally slow at 12–15d. The April "crisis" was backlog-driven (production queue), not carrier-driven — Amazon was actually performing well all along.
Quality & Returns
Items Trashed (Mar)
14,313
12-month peak
Items Trashed (Apr)
11,583
+25% vs Feb · +84% vs Sep
May MTD Trashed
2,525
Linear-pace ~5K full month
Est. Monthly Waste (Apr)
$190K
~11.6K items × $15-20
Trash Rate Trend
Trash Reasons (Last 3 Months)
Quality Holds vs Trash — Inverse Correlation
Monthly Delivered Boxes
Concerning pattern: Quality holds collapsed from 439/month to near-zero while trash rates doubled. If items are being trashed instead of quality-held, the operation is losing diagnostic data needed to identify and fix root causes. The top trash reasons — damaged (37%), not-produced (30%), missing (17%) — suggest three separate failure modes needing distinct interventions.
Customer Impact: Delivery Speed x NPS
New Customer NPS
~10.3*
*Stale (L12M Feb) · ~26 pts below repeat
Repeat Customer NPS
~36.5*
*Stale (L12M Feb)
New NPS (>14d delivery)
~7.9*
*Stale · Toxic first impression
Overall NPS
~38.6*
*Stale (L3M Feb) — Target >40
NPS by Delivery Time: New vs Repeat
NPS by Delivery Time Bucket (Overall)
Delivery Time Distribution (NPS Respondents)
The First Order Problem
Note: NPS data on this page is the last-validated L12M Feb 2026 snapshot — not refreshed for May. The new vs repeat NPS gap is structural (~26 points) but delivery speed amplifies it. New customers delivered in >14 days score NPS ~7.9 — near-zero loyalty. Repeat customers in the same bucket score ~25.5. Practical implication: Prioritizing first-order delivery speed has the highest NPS ROI. The March-April wait-time spike (12-14d) likely poisoned several thousand first-order experiences — expect a downward NPS print on next refresh. May MTD recovery should help offset, but lag means full impact won't show until Q3.
Operational Health Scorecard
Metric
Current
Target
Status
Avg Customer Wait Time (May MTD)
9.5d
<9.0d
WATCH
Avg Backlog Time (May MTD)
1.6d
<2.0d
GOOD
Avg Transit Time (May MTD)
7.5d
<7.0d
WATCH
Apr Wait (full month)
13.7d
<9.0d
ALERT
SLA: ≤10 days *stale
~65%
>75%
WATCH
SLA: ≤14 days *stale
~89%
>95%
WATCH
Items Trashed (Apr)
11.6K
<6K
ALERT
Current Backlog *stale
~113K
<80K
WATCH
Amazon Transit (data missing)
N/A
<7.0d
ALERT
Amazon Volume Share (May)
84.7%
—
NEW
PB Volume Share (May)
9.7%
<8.0%
WATCH
Overall NPS *stale
~38.6
>40
WATCH