The Context

Airspace is a time-critical logistics company that specializes in shipping goods across various industries like aerospace and hospital/health systems. 

For each order, customers are provided an instant quote based on parameters like the package information (such as its weight) or route information (such as the miles driven between pickup and drop-off). This quote is based on pre-agreed rates, which are configured on each customer's account by Airspace's customer success and/or finance members.

Initial Business Problem

Initially, I was tasked with a fellow product designer to implement a new pricing model for Airspace’s European expansion.  We conducted the following activities to gain more context:

• Audited our current pricing system (which was built for our U.S. pricing model) to understand how it could support the new model
• Interviewed 5 stakeholders about the current process to support quoting (as we were already shipping with customers in Europe), the logic to support the different rates, and their overall vision of pricing
• Worked with developers to understand the project scope with the new logic required

The audit of existing rate logic vs. how the new model was expected to work. At least half of the existing rates could not support what we were pricing customers in Europe, as indicated by the red.

We concluded that our system needed to handle more than just “European rates”, so we reframed the project to address a larger, underlying problem that our business was facing.

Refined Business Problem

As Airspace expanded globally and continued to address more unique shipping and customer requirements, the limitations of our pricing system became increasingly evident.  New requests to update rates were surpassing R&D's capacity to implement them.
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This created several ripple effects:

01. Financial and operational efficiency declined
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Our operational and finance teams were creating workarounds to manually price customers for numerous charges that weren't supported by the existing rate sheets.

Ops would sometimes input individual rates to price customers. Due to how tedious this was, they'd often enter in a singular "special rate" instead, which made it harder for the finance team and analytics team to accurately assess margin and meant less transparency for customers.

4 finance members spent over 10 hours each week looking through an exceptions report to find and manually adjust orders due to unique customer pricing agreements that the system couldn't automate.

02. Customers experienced reduced transparency and decreased trust

Instant quoting could no longer be a selling point for new customers if the initial quote was not accurate. If there were errors on our invoices that went unnoticed (due to resource strain from our own internal team not being able to address all the pricing errors) or took too long to get addressed, that would put us at risk of losing business with our customers.

These inefficiencies ultimately hindered our revenue growth and profit margin.

The Challenge

How might our pricing system accommodate an assortment of complex customer and business needs?