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As soon as we launched the first component of the automation, we saw an increase in our top-line compliance figure.
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Uber Freight empowers shippers with a comprehensive suite of logistics solutions, combining advanced technology with an extensive carrier network to optimize every step of the freight lifecycle.
Their offerings include managed transportation services, tailored capacity planning, and tech-enabled shipper tools that leverage AI and machine learning for streamlined freight planning, procurement, and execution — and when their managed transportation arm needed a solution for managing their track and trace processes, they looked to Parabola.
The challenge
Use case 1
Uber Freight works with hundreds of customers, many of which have unique processes for how to manage updates and tracking throughout the shipping process. It’s important that Uber Freight can let their customers know where loads are at any given time.
To accomplish this, the team was working in pods. Each pod was responsible for tracking their customers’ shipments, reaching out to carriers when they were missing information in the transportation management system (TMS), and inputting it into systems so they could send out updates according to each customer’s standard operating procedure (or SOP). It was an extremely manual process, and there wasn’t a streamlined way to handle it.
Alastair Streitz, Senior Manager at Uber Freight, was in search of a fix for the two big challenges he was facing in this model: 1) a lack of information from carriers and 2) juggling dozens of unique processes.
“How do we, in a more centralized and programmatic way, pull the data out of the TMS, and instead of having 30 people all with their own slightly different excel macros and their different SOPs sending out check call requests, push those out through one system that’s configured to make sure we’re still taking a customer-centric approach to getting shipping updates?” Streitz wondered.
This is where Parabola came in.
The solution
Use case 2
Streitz set up Parabola to run the same process that Uber Freight was doing manually: At its simplest form, it’s asking the carrier to either push check call updates through the TMS or send over the information so the team can input it manually.
But getting that tedious, manual job off of the pods’ plates took building a really thoughtful Parabola Flow.
Here’s how it works: Parabola scrapes a purpose-built Uber Freight database that houses tracking-related load data, and ingests it into a Parabola table to see where there are SLA breaches.
From there:
Parabola dedupes the information to ensure that there are no duplicate requests to carriers. Since carriers receive a huge number of emails, making sure that they’re as focused and streamlined as possible can improve carrier response rates.
From there, a series of Parabola steps would compare that data against a Google Sheet with carrier contact information to determine who check call requests needed to be sent to.
Up next, the data is broken up by load into the pods that are responsible for updating the shipment information, and Parabola formats emails that will automatically be sent on their behalf detailing delinquent shipments to the responsible carriers.
Parabola calls the Front API, where those emails are then sent from.
That whole process, from figuring out which shipments are missing updates, to cleaning the data and formatting it into digestible tables, and even sending the emails from the pods in charge of the shipments, happens without any human intervention.
This has been a game changer for Uber Freight.
The results
Use case 3
The results of implementing this automated track and trace process were both quick and impactful. The Uber Freight team realized:
- An up-and-to-the-right improvement in check call compliance — the key unit of success for the team running track and trace
- Cost savings as a result of operational streamlining
- A central SOP with built-in configurability to meet customer expectations
- Ability to scale the operation seamlessly as business grows
“As soon as we launched the first component of the Parabola automation,” Streitz began, “we saw an increase in our top-line compliance figure, even in just a week.”
As a reminder: That’s that check call metric, or the number that indicates how consistently Uber Freight is getting updates from their carriers on time.
“We’ve seen sustained levels of high check call compliance, it’s almost like every week we hit a new all time best,” Streitz said.
In terms of overall operational improvements, the bandwidth the Uber Freight team was using to cater to numerous SOPs (and all of their unique data) for hundreds of customers has been freed up due to implementing a tried-and-tested process that works for serving most of their customers.
The freed-up bandwidth previously spent on routine, administratively heavy, and transactional tasks is now refocused to the most critical, service-intensive tracking exceptions to deliver a better experience to their customers.
Uber Freight is passionate about providing a white glove experience — and this allows their customers to get better, faster insights into their shipments and leads to the kind of experience they’re known for providing.
Working with Parabola
I could beat around the bush and summarize what Streitz said when I asked him about his experience implementing this Flow and onboarding Parabola in general, but I’ll just let him speak for himself here: “It was extremely smooth, especially considering we were working through a very complex, arduous use case. I was incredibly impressed with just how quickly the team would pick up exactly what we were trying to accomplish and build out either a sample of how we might accomplish it or just build it themselves.”
“I felt very, very confident that the Parabola team was building to my use case and that whenever we found something that needed to be tweaked, we could take it to them and they would answer any questions. 10/10 onboarding experience.”
