Explosive Growth Is With The Small Customers

Good Morning,

First, as always, thank you for joining.

So much going on and never enough time to all of it. It’s wild seeing what is happening in the market and what different service providers are getting exposed to behind the scenes.

The cost pressures are real. In my 20 years in this industry, I have never seen the small details and optimizations being so important to a business’ overall health and profitability.

It’s rough out there.

Here’s what this issue brings:

• Ryan Petersen and Flexport are back. While they are trying to do everything they can to spin their news, they are a spinning top of “pivots” that is showing where every provider is struggling
  

• I’ve been helping a few different 3PLs with data analytics and profitability. I’m sharing an example of interacting with ShipHero’s API to create a report and dataview that you can’t run from inside the WMS
  

• Amazon doesn’t want use their own stuff … but they want to sell it to everyone else

Small Shipments, Big Headaches: Flexport’s SMB Roadblock

Flexport wants to be the company that everyone loves.

These days, they are the company everyone loves to hate.

Its journey into aggregating smaller customers has hit a hard reality: scaling a business with smaller clients (especially Shopify stores) is way harder than it looks.

The company initially thought that stacking all kinds of small and medium-sized businesses (SMBs) would allow them to build a deep logistics operation.

The crown jewel was offering tech-enabled efficiency and a broad range of services to everyone.

But what they are finding is that these customers require just as much attention as larger ones, without bringing the volume to justify the costs.

The issue is that SMBs (often) need intense operational support: account management, performance management, and the complex logistics that come with handling a broad array of smaller shipments.

These processes require a hands-on approach, leading to high overhead costs that SMBs' limited shipment volumes can't cover.

Flexport (like MANY logistics providers) is finding itself pivoting back towards chasing larger customers, the ones whose volumes can justify the considerable investments in infrastructure and services that today’s customer promises require.

This shift brings its own set of challenges though.

Large customers are few and far between (in relation to the total market), and those that exist already have established relationships — either with other logistics giants or by building out their own capabilities.

This scarcity pushes logistics providers (including Flexport) into a fiercely competitive space.

It's a zero-sum game with only a handful of potential wins, leading to rough negotiations and razor-thin margins.

Shopify Logistics Acquisition: Integration Struggles

Flexport’s acquisition of Shopify Logistics in 2023 was supposed to be a turning point to expand its e-commerce value proposition.

But the integration has been far from seamless.

Despite new capabilities in last-mile delivery (and B2B distribution they added after), Flexport has struggled to make the acquired operations profitable.

Its expansion with five massive fulfillment centers (all about 1M sq ft) and becoming the preferred logistics partner for Shopify’s Shop Promise, added a ton of operational complexity.

Instead of simplifying their logistics network, Flexport has ended up with a domestic operation that requires continual optimization and cost management.

Cost-Cutting and Workforce Reductions

Since Ryan Petersen’s return in late 2023, Flexport has been HEAVILY focused on restoring financial stability.

While the company has improved its EBIT by almost $700 million within the last ten months (without raising prices for customers), they are still burning cash.

Even with multiple attempts to grow the business offer and revenue base, Flexport has regularly leaned on layoffs to try to balance the books:

• December 2022: 20% workforce reduction

• January 2023: 20% workforce reduction (about 640 employees)

• October 2023: 20% workforce reduction (about 600 employees)

• January 2024: 15% workforce reduction

• October 2024: 2% workforce reduction (the latest one)

These layoffs highlight the ongoing struggle to balance costs while maintaining service levels for their remaining clients (which has recent reports not being so great).

Broader Industry Challenges

The broader industry context further complicates Flexport's strategy.

The recent collapse in freight markets has left many logistics companies struggling with reduced revenue.

For example, ocean freight prices have tripled over the past six months, but the demand hasn’t followed.

This market volatility, combined with (ongoing) geopolitical disruptions, makes future forecasting incredibly difficult and increases the uncertainty for Flexport’s operational strategy.

The “Pivot” 🤢 To Larger Clients: Risks and Realities

The pivot (I hope one day this word dies) to larger clients exposes a deeper issue within the logistics industry - the relentless pursuit of scale without properly accounting for the different needs of diverse customer bases.

Lack of Large Clients:
Large customers are not only scarce, but most have also established deep partnerships with existing providers or built in-house capabilities.

Intense Competition:
Logistics providers are forced into intense competition for a limited pool of clients.

Cutthroat Negotiations:
Negotiations frequently drive margins down to unsustainable levels.

High Operational Costs:
Serving a broad customer base comes with a high-cost of operations that is difficult to sustain without consistently high volumes.

Flexport’s ambition to be a one-stop-shop for merchants, aiming to compete (even though they claim to “complement” not “compete”) alongside giants like Amazon FBA, requires significant adaptability — not only in service offering but in managing customer expectations and operational costs.

Flexport’s “New” Path Forward

Despite these challenges, Flexport’s focus on technology and operational visibility may give them an edge (at least against a number of the regional players).

The company has shown it can adapt by boosting profitability without immediately raising customer costs, hinting at a potential for deeper optimization.

As of October 2024, they are now focused on 3 key pillars.

1. Differentiated Service Offering
   Flexport's tech-enabled model aims to provide comprehensive logistics solutions across platforms like eBay, Amazon, Walmart and others for a variety of merchants
   

2. Focus on High-Value Clients
   They are now emphasizing larger, high-value clients while attempting to maintain agility to pivot as the market demands.
   

3. Transparency And Understanding
   Continue improving visibility and tracking for customers, a strategy similar to initiatives by industry players like Hapag-Lloyd.

For now, Flexport’s strategy hinges on delivering differentiated value without falling into the trap of competing purely on price.

The balance between managing costs and effectively serving both SMBs and larger clients will determine whether they can truly scale sustainably in a volatile market.

Do I think that they will succeed?

Honestly, not yet.

They are struggling with an “expectation versus reality” problem and are desperately trying to live up to an unrealistic image of what they (and at one point) the market thought they were.

Unless they fully embrace the grind that logistics is, they will keep burning all of their cash and trying to pivot until they go bankrupt.

Running a 3PL Operation These Days Requires Better Information

I’ve shared in the newsetter and on various posts on LinkedIn about different projects I work on.

Recently I started working with a few new warehouse clients.

Basically I’m helping them make more money.

To do that, I’m diving deep into their systems and transactions.

But there’s a really annoying thing happening.

Most of the time the systems don’t give access to enough data.

One of my clients for example uses an older WMS. Most people wouldn’t pick it today if they were just starting up. Not cool enough.

But, since it was built in a different era, you can EASILY get massive data dumps from the system.

Because of this, I’ve already helped them address a major issue that has impacted them since July.

I gave them:

• A full overview of a massive customer profile

• Identified what’s working and what’s not

• Showed them exactly why they are missing revenue in certain markets

• Showed they the dollar variances

Because of that, we quickly set a bunch of meetings with their different partners and are well on our way to recapturing that revenue (but more importantly, increased profitability).

The clients working with “modern” WMS options have had more challenges.

And this is because new systems these days don’t (usually) provide the same direct access to large amounts of data.

It’s a mixed bag.

Because these systems do on the other hand provide access to information via APIs, which can give you all kinds of options for automation and app integrations.

So here’s a particular challenge with the ShipHero WMS - Generate a daily report that shows items that haven’t been scanned to a container.

They have a solid API and have done a great job with their documentation. But, there are restrictions both on the GraphQL queries as well as rules around query costs and API call limits.

Additionally, not every field can be queried or filtered directly.

The shipping containers features of ShipHero are newer. And when I talked to them, not all of the updates you might want are available with the API.

Approach

For this, I tried two different tools using the same logic.

I wanted to see which would be easier to set up, execute and make the most sense to drive the right result.

The two options I used were:

1. Make.com

2. KNIME

Both of these tools can be used to generate this report.

Both can be set up to run manually or automatically.

Each of these workflows runs through the set of shipments for a defined time range.

The one property that we are looking for is “in_shipping_container”. Through the API access, it’s the only piece of information that is currently available for these (if I am wrong here and you have been exposed to some new and undocumented options, please let me know!).

The [in_shipping_container] property is basically a boolean results (true/false).

For this report then, we automatically run the query, get all of the shipment results then filter those results to the “false” transactions.

Since a 3PL provider will (usually) have more than 100 transactions (the ShipHero max page limit), you have to loop through multiple iterations of the query and aggregate the results before you can find everything for the date range.

So what are the pros and cons of each method?

MAKE

KNIME

Personally my vote is for KNIME.

But I have also been using that for A LOT longer than MAKE.

For me I find you would have more flexibility using KNIME to have multiple queries and workflows on the same canvas (MAKE only allows one), so that you can retrieve and create much more sophisticated insights faster.

Protip: Since this workflow requires you to run a relatively low level of detail, you can stack your gains on this but pulling the ship to state, zip, cost, carrier, shipping method, etc, with no real extract cost to the query.

This additional information can help to build out additional insights related to your customer’s activity, hot zones, avg package size, frequency of sales per zip or state, and so much more.

Always maximize what you get from any data that you pull.

JWO Didn’t Live Up To The Hype For Large Formats. But Can It Work For Smaller Ones?

Amazon introduced JWO in 2018 with its first Amazon Go store

They initially implemented JWO in its Fresh grocery stores and some Whole Foods locations to showcase the technology and build the grocery store of the future.

But they quickly hit a wall.

The technology requires a massive investment and is massive overhaul to install it into a retail or grocery space.

And the bigger the space, the harder and more expensive it gets.

(There was also quite a bit of news a few months ago about how “manual” the process was when it came out that Amazon had an army of people in India validating the technology’s accuracy).

Amazon has now made significant improvements to JWO's AI system.

In July 2024, they introduced a new multi-modal foundation model that increases accuracy in complex shopping scenarios. This update makes the technology faster, easier to deploy, and more efficient for retailers.

Despite scaling back JWO in its own stores, Amazon is "pushing hard" on the technology for third-party applications. They are focusing on reducing costs over time, which would make the technology more economically viable for a wider range of formats.

Amazon has realized the key for this technology surviving is to make it more accessible. They want to be the defacto option that small format retail spaces go to.

The data from JWO is the deep and future value of the system, the cashierless storefronts is just a vehicle for it.

If there’s one thing Amazon loves, it’s data.

To get that data, they need to focus on everyone else, and not themselves.

Think it will work?

Let me know your thoughts!

That’s it for this week. Thanks for being here.