Predicted vs Actual demand — walk-forward backtest
Supplier concentration (click to filter)
Spend by category (click to filter)
📋 Procurement insights
deterministic · auditable
📦 Inventory & warehouse cycle · live snapshot (now)
🎯 Demand planning & forecast · full backtest (all years)
🏭 Sourcing & supplier risk · all-time spend (year view on the Spend tab)
How to read this scorecard
🟢 on target · 🟡 watch · 🔴 act. Metrics are computed live from the SCM Master API
(inventory, spend, and 12-month forecast backtest). Metrics that require PO / receipt /
GL data not exposed by the API (Perfect Order %, OTIF, Cash-to-Cash, PPV) are intentionally
omitted rather than fabricated.
Period:
Total Spend
–
all-time · selected scope
Units
–
items procured
Avg Spend / Unit
–
blended
Categories
–
in scope
Spend by category (click to filter)
Supplier split (click to filter)
Product detail (click a row to filter)
Product
Category
Units
Spend
% of total
SKUs Tracked
–
active products
Below Safety Stock
–
replenish now
Stockout Risk
–
cover < lead time
Inventory Value
–
on-hand × price
Warehouse capacity — committed vs free (inbound is reserved so you don't over-order)
On-hand vs safety stock
Days of cover (red = below lead time)
Replenishment pipeline · Reorder Point = burn × lead + safety
Product
On hand
Safety
Lead (d)
Reorder pt
Days to reorder
Action
Next ETA
Forecast accuracy ⓘ
–
1 − WMAPE · pooled · higher = better
Forecast bias
–
over / under · drives safety stock
Forecasts
–
evaluated
Worst Category
–
improvement target
MAPE (simple mean) sits in the detail below — it is inflated by intermittent SKUs with near-zero actuals (dividing by a tiny number), so WMAPE + bias are the reliable headline for this demand profile.
Predicted vs Actual demand
Accuracy by category · 1 − WMAPE (higher = better)
Error trend over forecast months
🧮 Clean-sheet should-cost — the margin lever
Addressable Savings
–
vs fair target price
Avg Cost Gap
–
quote vs target
Products Modelled
–
with a BOM
Total Margin Stacked
–
quote vs cost floor
Quote vs Target vs Floor (per product)
What this is
A clean-sheet teardown rebuilds each box from components — memory &
flash indexed to commodity markets (DRAM/NAND), metal & PCB to their indices, and
CPU/GPU as a list-price benchmark band. That yields a defensible cost floor.
Headline gap = quote vs target (floor + a fair margin the
supplier would accept) — no one sells at cost, so this is the credible ask. The
floor is the backstop: total margin stacked in the quote, a ranking
signal for where to push. The floor moves with the memory market, so the number stays
current as DRAM swings.
Gap by supplier (who's furthest above floor)
Product
Floor
Target
Quote
Gap→target
Gap %
🧾 Total Cost of Ownership — beyond the sticker price
Portfolio TCO
–
over – assets
Total Cost %
–
ΣTCO ÷ baseline
TSCMC %
–
excl. acquisition (SCOR)
OpEx Share
–
run-cost vs TCO
TCO by layer, per asset class (stacked €)
What this is
TCO = acquisition + landed + deployment + lifetime OpEx + end-of-life
− recovery. Acquisition is what we actually paid; the rest is the cost
of owning and running the box over a 5-year life.
TSCMC % (Total Supply-Chain Management Cost) deliberately
excludes acquisition — by the SCOR/APQC definition it measures the cost
of operating the chain, not the hardware itself. On power-hungry GPU nodes,
lifetime OpEx can rival or exceed the purchase price — which is exactly the
number a sticker-price comparison misses.
Per-class detail (avg per asset)
Class
Assets
Acquisition
OpEx
Landed+Deploy
EOL−Recovery
Avg TCO
📦 Orders — what's arriving, and what it covers · current year
Open orders
–
in flight
Incoming units
–
not yet delivered
Delivered (YTD)
–
orders
Inbound value
–
open POs
Delivery accuracy
–
on time or early
Avg slip
–
vs promised ETA
Worst slip
–
single order
Tuning
promised vs actual
planned-delivery match
Order pipeline click a row to see its contents · soonest arrival first
PO
Supplier
Status
Units
Value
Covers gap
Promised
Actual / now
Slip
No orders for the current year.
AUTONOMOUS PROCUREMENT
Decision loop & audit trail
The agent advises; deterministic code decides. Run the gate (dry-run by default), watch the three checks resolve to a tier, and read the permanent audit log below — click any row to trace a decision to its inputs and, when placed, its purchase order.
DRY-RUN
Intake — run a purchasing decision
Capacity OK?—
Price in band?—
Confidence ≥ bar?—
—
Decision audit trail (append-only · newest first)
When
Product
Qty
Total
Tier
Conf
PO
No decisions logged yet — run the gate above to create one.