Free tool
What is your slow close actually costing you?
The sale is the easy part. Behind every order is the reconciliation that has to tie out in NetSuite before you can close, and for most multi-channel brands, that work quietly eats a chunk of a finance hire every month. Adjust the three inputs and see the number.
Your setup
DTC, Amazon, Walmart, Target, wholesale/EDI: each one settles differently.
What the manual close is costing you
~$40,500/ year
About 75 hours a month spent matching payouts to NetSuite, roughly 47% of a finance hire, doing work no one wants to own.
And it blocks the close: the books can't start until every channel's payout reconciles. Best-in-class is a 2–3 day close; manual reconciliation drags it to two weeks or more.
Estimate · based on what NetSuite + Celigo brands tell us + the CFO.com / Ledge 2025 close benchmark
How we estimate this
No black box. Here's the model.
We would rather show our work than dazzle you with a number you can't check. Every input maps to a sourced assumption.
01 · The hours
We start from what the NetSuite + Celigo brands we work with tell us: reconciliation runs about 30 hours a month on a single channel and climbs to 70–130+ hours as channels stack up. About 40% of marketplace payout records need a manual touch.
02 · The math
We scale those hours by your channel count and order volume, then multiply by the loaded hourly cost you enter. Outputs are rounded. It's a directional estimate, not a quote.
03 · The close
A 2–3 day close is best-in-class; manual settlement reconciliation drags the close to two weeks or more, because the books can't start until every payout reconciles. (CFO.com / Ledge 2025 Month-End Close Benchmark.)
Want the real number for your stack instead of an estimate? See how Vista Recon reconciles it deterministically.
That number doesn't have to be yours.
Vista Recon matches every marketplace payout to NetSuite and posts a reconciled result, so the hours come back and the close starts on time. Bring us one settlement file and we'll show you on your own data.