Promise dates read off a lead-time table, then missed
Dates promised from what you hold and what is coming, with the evidence, and the cost of each way to close a gap.
What goes wrong today
The order desk quotes a date from a lead-time table.
Sometimes the stock is already in the warehouse and the customer could have had it sooner. Sometimes it is already promised to someone else and the date is missed. Either way, sales learns to pad, and the padding loses orders.
When stock is short, it goes to whoever asked first. Margin and customer priority play no part. Nobody records promised against delivered by SKU, so promises never get better, and a stale stock feed can produce a confident-looking date that is simply wrong.
Why existing approaches fall short
- Static lead times ignore what is on hand, in transit and on order today.
- Availability checks in most order-entry screens stop at stock on hand and rarely ask whether the factory can make the rest in time.
- Without a ledger of promised against delivered dates, buffers are set by habit.
How FLX4 addresses it
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PromiseNest lays out stock on hand, stock in transit and open supply on a dated timeline, finds the first date that covers the order and adds your policy buffer. Every promise carries its evidence, its sources and a confidence. When the data behind it is stale, it abstains and gives a conservative date marked for human review.
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When an order cannot be covered, it lays out the options with their date gain and cost: expedite, move production, use an alternate supplier or split the shipment. Orders below margin or over credit are flagged for a sales manager. In-transit dates come from TransNest's ETA, and production feasibility from the OpsNest scheduler.
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When stock on hand is short, capable-to-promise asks the OpsNest scheduler whether the rest can be made by the date. PromiseNest never writes to your ERP. An approved choice is recorded and passed to the team that owns it.
The loop, step by step
- 1 · Predict
Time-phase what you hold
On-hand, in-transit and open supply are laid out by date. The first date that covers the order, plus your buffer, becomes the promise.
- 2 · Predict
Check the data is fresh
Every input carries its last sync time. Older data lowers the confidence, and very old or missing data makes the promise abstain to a conservative date.
- 3 · Decide
Price the ways to close a gap
Expedite, move production, use an alternate supplier or split the shipment, each with its date gain, cost and margin effect. Scarce stock is ranked by margin and customer tier.
- 4 · Approve
A named person chooses
The customer-service lead approves the chosen option. Below-margin or over-credit promises are flagged for the sales manager.
- 5 · Execute
Hand to the owner
The approved choice is recorded and tagged with the team or product that owns it, for example an expedite for transport. Nothing is written to the ERP or another product from here.
- 6 · Learn
Keep a promise ledger
Promised and delivered dates are recorded per SKU, giving an on-time rate and a recommended buffer for the next promise.
What it helps you work toward
Outcomes are measured against a baseline we agree with you in writing.
Promises kept
Promised against delivered date, by SKU and customer tier, from the promise ledger
Less padding in quotes
Quoted lead time against actual lead time, before and after
Bad data caught before it reaches a customer
Promises that abstained on stale data, and how each was resolved
Margin protected in a shortage
Margin on orders served from scarce stock, by customer tier
What powers this solution
PromiseNest
A delivery date your team can keep, with the evidence behind it.
Explore PromiseNest →
TransNest
See the late truck before your customer does, and pay only the freight your contract allows.
Explore TransNest →
OpsNest
When a line stops or a vendor slips, the plan and the POs keep up.
Explore OpsNest →Integrations
PromiseNest reads stock, in-transit, open supply, capacity and customer terms through data views configured per deployment. It does not write to your ERP. The promise card sits inside your order-entry screen (e.g. an ERP sales order).
Bring us the decision behind this problem
In two weeks: the decision mapped, where money leaks, a baseline agreed in writing and a ninety-day plan with one target.
Read-only on day one. Your people approve every action. If the number does not move, you do not scale.