Response-time simulator v1.3

What your response time costs you at quarter-end.

Revenue is recognized when the customer takes delivery — so your response time is money. Every day it takes to reflect a change (a supplier's new date, a new customer order, an order change) pushes your promises out of date, breaks OTIF, and slides proof-of-delivery into next quarter. This models what that costs — and what a faster response recovers. Dial in your response times below and watch it flow through.

Why Nordoon

Nordoon automates order handling on both ends — customer order entry and amendments, and supplier reschedule updates — so confirmations land in your ERP in minutes, not days. It also generates net-new data that becomes the basis for visibility and decisions. That drives the response lags below toward zero, which is what lifts OTIF and pulls revenue back into the quarter. Set your current response times, then take the lags to near-zero to size the gain.

Outbound · customer your response new
days
Customer PO received to sales order created in the ERP. Delay before demand reaches MRP.
days
Customer amendment (qty/date) to revised sales order. Delay before the plan re-nets.
Internal · your process buffers
%
Share of order lines gated by a purchased component — not ATP from stock.
days
Safety time between the feasible date and the date confirmed to the customer. Usually implicit.
days
Safety stock in days of supply. Absorbs a supplier reschedule up to this cover.
days
Order-to-delivery lead time you quote — the window a confirmation is exposed to a reschedule.
Inbound · supplier material & your response
wk
PO placement to goods receipt (GR). Longer lead times carry larger reschedules.
%
Share of open PO lines the supplier reschedules (in or out) per quarter.
%
Typical reschedule as a % of supplier lead time (25% of an 8-week lead time ≈ 2 weeks).
days
Time to update the confirmed date in the ERP after a reschedule. Until then MRP/ATP run on the stale date.
Economics & recovery days → $
Order volume per quarter.
$
Revenue per order, recognized at delivery (POD).
%
Current OTIF, before the response-lag effect modelled here.
%
Contractual OTIF target — below it, chargebacks trigger.
%
Chargeback per non-compliant order, as % of order value.
$
Cost to recover one at-risk order — premium freight, changeover, substitution premium.
%
Share of at-risk orders you actively recover — expedite, substitute, re-allocate, re-sequence, partial-ship.
% sub
Weighting from production re-sequencing (schedule-bound, slower) to substitution / re-allocation (faster, beats the confirmed date).
resequencing-ledsubstitution-led

Sliders are a guide — type any value in the number fields, even beyond the slider range.

The prize

Close the update lag

All the impact below is attributable to the days a changed date sits un-updated. Take the lag to same-day and it goes to zero — revenue lands in-quarter and the cost disappears.

$231krecoverable / year
The chain, live
8
response time (days)
97.5%
promise accuracy
91.4%
resulting OTIF
1.6
OTIF points lost
Supplier delivery date slips
Uncontrollable — and grows with lead time
+7d25% of POs · 4wk lead
YOUR RESPONSE
Internal response lag
Supplier update + order-intake + order-change, feeding stale ATP
8 daystotal response time
Promise made on stale ATP
Customer date set too optimistically
97.5%promise accuracy
Material late → OTIF miss
Binary — a full miss unless you recover it
91.4%OTIF
POD slips past quarter close
Revenue recognized in the next quarter
$38kslips / qtr

Output A · Revenue timing

$38.0k/ quarter
Deliveries that fail near close, pushing proof-of-delivery — and the revenue — into the next period.
Annualized slip$152k
Orders crossing close / yr4.1

Output B · Service & cost

1.6OTIF points lost
Pulls you below your customer's threshold — penalties apply.
Net late orders / yr (after recovery)33
Orders recovered / yr49
Penalties / yr$39k
Recovery spend / yr$39k
Annualized cost$78k
How this is calculated
Typical slip scales with lead time: slip = volatility × lead time — week-long lead times breed week-long slips.
Corrupted promises rise with your response time: f_bad = gated% × slip-rate × min(1, response time / window), where response time = supplier update + order-intake + order-change.
A corrupted promise misses OTIF when the slip beats your cover: P(miss) = e^(−(buffer + safety stock) / slip) → for week-scale slips this approaches 1.
OTIF drop before recovery: at-risk = f_bad × P(miss), on top of your baseline.
Operational recovery: you act on a share of at-risk orders (recovery rate) and only a fraction land in time, set by approach — effectiveness = 0.55…0.95 from resequencing-led to substitution-led. net miss = at-risk × (1 − rate × effectiveness). You pay for every attempt; only the ones that land avoid the miss, slip, and penalty.
Revenue slips the quarter when a net-failing order's delivery crosses close: cross ≈ (slip / 90) × 1.5 (end-of-quarter loading).
Annualized cost = penalties on net late orders + recovery spend on the saved orders.
Defaults are illustrative — overwrite them with your own OTIF, slip rate, and order economics. Impact only touches orders actually gated by a slipping material.
Recoverable revenue vs response time annualized — the upside of a faster response

The curve is the revenue you'd recover per year at each total response time; the dot is where you sit today, and the green drop to zero is what you'd gain by reacting in near-real time across supplier and customer changes. Every other lever reshapes the curve.

Nordoon models internal response time — how fast you reflect changes across your supplier and customer touchpoints — as the lever a business actually controls; external market and price signals are excluded by design. This tool is about execution (S&OE), the last and next few months, not long-term planning.

Disclaimer: This simulator is provided for illustrative and educational purposes only. All figures are model estimates derived from simplified assumptions and the inputs you supply, and may not reflect actual results. Nothing here constitutes business, financial, accounting, tax, legal, or investment advice, or any guarantee of outcomes. Any decisions you make are your own responsibility and should be taken in consultation with qualified professionals.