Dutton Brown · Production · 2026

Production KPI Map

The 4 Tier 1 KPIs that drive the monthly review, and the Tier 2 metrics that support them

4 Tier 1 KPIs drive the monthly production review — one per operational lens: Output, Efficiency, Quality, and Fulfillment. Unlike Marketing's externally-sourced KPIs, Production's are almost entirely generated from Catherine's own operational logs and Dutton Brown's internal systems: Weekly Shipping Data, Assembly Log, Rework Log, Repaint Log, and Parts Request Log. The data is already being collected. This map connects it to decisions.

Tier 2 KPIs do one of two jobs — they either explain a Tier 1 movement after it happens (diagnostic) or signal a future Tier 1 movement before it shows up (pipeline).

Report everything, discuss selectively. Every Tier 2 is pulled monthly alongside its Tier 1 and sits on the review page. The owner walks through the Tier 1s in the meeting and highlights whichever Tier 2s are worth the room's attention. The time-consuming part isn't gathering the numbers — it's deciding what to do when they move.

Diagnostic — explains a Tier 1 shift after it happens
Pipeline — signals a future Tier 1 shift before it happens
Tier 1 KPIs and their supporting Tier 2s
4 Tier 1 · 13 Tier 2 supporters
Tier 1 · Output · Floor
Value Shipped
Sum of $ Shipped for weeks ending in the reporting month, net of returns. Pulled from Catherine's Weekly Shipping Data in Notion — 14 weeks already tracked. The single money-out number for the floor: everything that left the building with a price tag attached.
Source: Notion Weekly Shipping DataMonthly
Supporting Tier 2
  • Value Shipped - Items Built
    Total items assembled in the month (Assembly Log Qty). Catherine's throughput target is 519 items/week (up from 432 avg in 2025). Differs from Items Shipped — built items may sit in backstock before shipping.
  • Value Shipped - Items Shipped
    Count of items shipped in the month. Pairs with Value Shipped to detect mix shifts: same $ at fewer items = higher-value orders; same $ at more items = pure volume growth.
  • Value Shipped - Capacity Gap
    Orders Received minus Orders Shipped. When positive (received > shipped), backlog is accumulating. The floor's leading indicator — when this goes positive for 2+ weeks, fulfillment pressure is building.
  • Output - Powder Booth Utilization
    % of scheduled production hours the powder booth is actively running. Catherine tracks this — currently at 58%, indicating meaningful headroom before a capacity ceiling. Key input for Operations when evaluating ad spend and quoting lead times.
Tier 1 · Efficiency · Labor
Labor Cost % of Shipped Value
Total production labor cost (QuickBooks) ÷ Value Shipped × 100. The margin-efficiency signal for the floor. Sept 2025 baseline: 11.21%. In 2025: revenue +2.6%, payroll +5.7%, NOI −$61K. This is the metric that tells that story every month.
Source: QuickBooks · Notion Weekly Shipping DataMonthly
Supporting Tier 2
  • Labor - Items Shipped per FTE
    Items Shipped ÷ production FTE count. Individual productivity proxy — Catherine weights this at 25% in performance reviews. Moves with headcount changes and product mix shifts.
  • Labor - FTE Utilization %
    Actual hours worked ÷ scheduled hours. Sept 2025 baseline: 89.13%. Low utilization reveals workflow gaps — waiting for parts, idle between stations. High utilization with growing backlog signals a capacity ceiling.
Tier 1 · Quality · Build
Total Yield Rate
(Parts Processed − Rework entries − Repaint/Reclaim entries) ÷ Parts Processed. Combines assembly rework and powder coat reclaim into one build-quality %. Sept 2025 baseline: 95.1%. Every point of improvement directly reduces COGS.
Source: Notion Rework Log · Repaint Log · Assembly LogMonthly
Log data maturing — Q2 baselines directional
Supporting Tier 2
  • Yield - Reworks
    Raw count of assembly rework entries from the Rework Log. Pairs with Total Yield Rate: the count reveals whether the rate is moving because volume changed or because the defect rate changed.
  • Yield - Powder Coat Reclaim Rate
    % of parts through powder coat that required a full repaint. Sept 2025 baseline: 2.66%. Isolates the coating station's contribution to Total Yield Rate.
  • Yield - Rework by Root Cause
    Distribution of Rework Log entries by Issue field (wrong finish, alignment, missing hardware, etc.). Coaching and SOP tool — separates systemic defects from individual ones, and in-house from supplier-caused.
  • Yield - QC Pass Rate
    % of items that passed final QC testing in the Assembly Log (Test Result = Pass). Station-specific quality at final test — directly measures whether items are passing before shipment. Identifies the testing bottleneck.
  • Yield - Rework Time
    Total hours spent on rework per month from the Rework Log. Pairs with Yield - Reworks count: the same number of rework events can mean very different labor cost depending on how long each fix takes. Sizes the actual cost of defects beyond just counting them.
Tier 1 · Fulfillment · Customer
Avg Order-to-Ship Time
Mean days from Shopify order creation to ShipStation ship date, for all non-sample orders fulfilled in the month. Dutton Brown's promise is 1–3 weeks (7–21 days). This is the actual number — Production owns it.
Source: Shopify · ShipStationMonthly
Supporting Tier 2
  • Fulfillment - On-Time Shipment Rate
    % of orders shipped within 21 days of creation. Reveals the tail: a good average can hide a subset of orders that consistently run late. Target: 95%+.
  • Fulfillment - Backlog Age
    Count and composition of open orders by age — a visibility metric for understanding where orders sit in the production cycle. Supports scheduling and capacity decisions. Methodology for categorizing backlog items (large orders, holds, standard queue) to be refined with Catherine.
Future: Production & Shipping Dashboard
Planned

The KPI Map above covers what the floor reports monthly. A separate automated dashboard is planned to give Production and Operations a richer operational view — pulling directly from existing data sources with no manual entry. Items below are candidates for that dashboard.

Production Mix — Items Built by Type
Monthly count of items assembled, broken out by product type (Pendant, Sconce, Chandelier, Flush Mount, Hardware, etc.). Pulled automatically from the Assembly Log via the SKU relation to the Products database. Helps Catherine plan coating batches and parts staging, and gives Operations visibility into what's coming off the floor before it ships.
Notion Assembly Log → Products · Automated · Planned
Weekly Shipping Summary
Automated weekly view of the full shipping data Janet and Catherine currently enter manually: $ Shipped, Items Shipped, Orders Shipped vs. Received, $ per Order, Shipping Boxes, Hardware Boxes, Total Boxes, Pallets, and Returns. Same data — pulled directly from Shopify and ShipStation instead of entered by hand. Eliminates the manual step and enables trend views across any time window.
Shopify · ShipStation · Automated · Planned
Shipping AOV & Returns
$ per Order (shipped) and Returns count — two signals from the Weekly Shipping Data not surfaced in the monthly KPI review. Shipped AOV diagnoses whether Value Shipped shifts are mix-driven or volume-driven. Returns flag product quality or fulfillment issues before they show up in trade feedback. Candidates for Tier 2 promotion once the automated source is live.
Notion Weekly Shipping Data → Shopify · Candidate Tier 2