Surviving SuiteScript #2: Know Your Data

A lot of problems in NetSuite don’t come from bad code.

They come from building against data that doesn’t exist in production.

Had a client a while back integrating Shopify into NetSuite.

3 stores.

Not “same setup, different branding.”

3 stores that behaved differently.

• different order flows
• different fulfillment timing
• different edge cases
• different data coming in

Same integration.

Completely different realities.

How many sandboxes did we have?

One.

And it didn’t match any of them.

So what do you do?

You pick something that looks close enough and start building.

Saved searches look right.
Transforms work.
Scripts run.

Everything feels solid.

Then you hit production.

Orders don’t follow the pattern you tested.

The data structure in sandbox was different
because the orders were entered differently.

Values you assumed were consistent… aren’t.

Now you’re dealing with:

• partial data
• unexpected nulls
• extra records
• missing relationships

And the same logic that “worked”…

starts doing weird shit.

Not clean failures either.

That would be easy.

Instead:

• one order processes fine
• the next one breaks
• the next one half works
• the next one creates something you didn’t expect

So you go back to the code.

Nothing obviously wrong.

Because there isn’t.

The problem is what the code is running against.

We built around what we thought the data looked like.

We were told the data was representative.

We had no ability to inspect what we should actually expect.

It wasn’t.

And this is the part people underestimate:

This isn’t annoying.

It’s imperative.

Because if your sandbox doesn’t reflect production…

you’re not validating anything.

You’re guessing.

You see this everywhere in NetSuite:

Saved search returns exactly what you expect
→ until joins pull in more than you thought

Script loops 200 records fine
→ until it’s actually 2,000

Integration behaves clean
→ until one source sends something slightly different

It’s never the happy path that causes the issue.

It’s everything just outside of it.

What actually fixes it

• get data that represents production
• test against edge cases, not just clean records
• stop assuming consistency
• inspect what’s actually coming through

Because once you actually understand your data…

you build differently.

The takeaway

If your data isn’t real…

your results aren’t either.