Is manual invoicing killing your 3PL's growth?


"We do it in Excel" they said.

I almost fell out of my chair. 😳

This 3PL was processing 1,000+ orders daily...

Managing millions in revenue...

And doing their invoicing manually.

Here's why this is dangerous:

MANUAL INVOICING RISKS

  • Missing billable activities costs you thousands in revenue
  • Excel errors compound over time, destroying profitability
  • Hours spent reconciling could be used growing your business
  • Delayed invoicing hurts your cash flow

THE REALITY

For small operations, Excel works fine.

When you're shipping a few truckloads?

Still manageable.

But everything changes when you hit:

  • Hundreds of daily orders
  • Multiple billing activities
  • Complex rate structures
  • Different client agreements

THE SOLUTION

You need a proper data management system.

Not because it's fancy.

But because it's the difference between:

  • Capturing 100% of revenue vs leaving money on the table
  • Spending hours vs minutes on invoicing
  • Growing confidently vs hoping you got the numbers right

​

All the Best,

Tucker

Tucker Fischer | Axle Digital Solutions

Get daily, non-technical data tips to accelerate your business's growth.

Read more from Tucker Fischer | Axle Digital Solutions

Moving data from one system to another seems simple on paper. But when implemented poorly, your entire analytics operation can collapse. I’ve seen teams spend months rebuilding pipelines that should have taken days to fix. Here are 3 critical components every successful data pipeline needs: Intelligent Alerts When something breaks, you need to know before your stakeholders do. Set up monitoring for pipeline health Create meaningful alerts that explain what failed and why Establish escalation...

Your dashboard projects are failing silently. Here’s why: They focus on one-off problems (should’ve been a simple data pull) They try to do too much at once (executive ambition gone wild) They measure everything but see nothing (classic dashboard ADHD) They track metrics nobody actually uses (requirements failure) They lack the right detail level (context matters) Instead: Target a specific, recurring business problem Build in phased releases (not big bang deployments) Focus on 3-5 critical...

Data models save businesses millions. But no one asks for them. Here's why that's a problem... As analysts, we focus on delivering what the business asks for. But sometimes the most valuable deliverables are never requested. Data models are the perfect example. I've NEVER been asked to create a data model by non-technical leaders. Yet in almost every analytics project, they're absolutely essential. The challenge? You'll never get a dedicated week to build them. So how do successful analysts...