Simplified freight rate management via an intuitive interface, enhancing data accuracy and minimizing manual work
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Enterprise UX
Internal Tool
UX Design
Client
US Foods
Project Duration
10 Months
Role
Designer
Overview
The current process for collecting and preparing updated vendor published rates is fragmented and heavily manual, resulting in delays, errors and inefficiencies. Vendors submit rates in various unstructured formats- ranging from email bodies to different formatted spreadsheets and PDF files which then require extensive human intervention before integration into the rate engine calculation process. The goal was to equip 10 team members of the Freight Rate Management group with a powerful internal management system to improve their accuracy, speed and audit ability by automating data entry and validations.
The Problem
High Input Variability Creates Operational Drag. All Published Vendor’s surveys and pricelists require validations, corrections, data enrichment, conversions and reformatting before uploading to MS Access database.
Heavy Reliance on Manual Validation and Conversion. It takes an average of 1 hour to complete vendor survey processing and validation. Complex processing could take more than half a day. This step consumes 80% of the total update cycle time.
Fragmented and Complex Workflow. The process spans multiple tools – email, Excel, Acccess, Python scripts and Snowflake in VDI and in local machine.
Research
Before designing solutions, we mapped the full freight rate intake process with stakeholders and users. The goal was to understand how rate updates were actually completed in practice rather than how the system was intended to be used. We collected data on the effort and length of time it takes for each rate update and the role human error plays in the whole user journey.
The mapping revealed that the workflow relied on spreadsheets, email communication, and manual validation to complete a single rate update. The users struggled to maintain accurate rates efficiently, which impacted downstream pricing and decision-making.
Because the interface did not surface necessary context, users created their own parallel processes to compensate for missing visibility.
Key Findings
Fragmented tools created inefficiency
Users depended on multiple external tools — spreadsheets, internal documents, and communication channels — to validate and complete a rate update. The system functioned as a storage database rather than a working tool.
Limited visibility caused manual verification
Users could not easily see the status or impact of rate changes. To avoid mistakes, they manually cross-checked data before submission.
The interface did not support large workloads
Rate updates were handled one entry at a time, even when users received large batches of changes from multiple vendors. This significantly slowed throughput.
Users could not trust system feedback
The system required manual refreshes to confirm updates. Users were unsure whether changes had successfully saved, leading to repeated checking and duplicated work.
Navigation increased cognitive load
Critical information was distributed across multiple screens, forcing users to remember values while moving between pages.
Research
Based on the key findings, we created a new user journey map that focused on reducing manual work and improving user confidence in the system.
Design Opportunities
Consolidated management interface
We redesigned the workflow so users could review and validate rates within a single workspace instead of switching between external tools.
Search and filtering
Advanced filtering allowed users to quickly locate specific vendors and updates, replacing manual scanning through large datasets.
System visibility and automation
The interface surfaced validation feedback and update status in real time. Users could immediately see whether updates were complete or required correction.
Real-time data updates
The system dynamically updated the interface based on the latest data, removing the need for manual refresh and reducing uncertainty about whether changes were saved.
Bulk actions
We introduced bulk approval and rejection capabilities so users could process batches of rate changes simultaneously rather than processing updates individually.
Approach
Workflow Optimization: Designing Beyond the Interface
Early process mapping revealed that the inefficiency originated upstream in how freight rate data entered the system. The UI was only one step in a larger operational pipeline.
Users were not simply updating rates — they were receiving surveys & pricelists from vendors, validating them, correcting inconsistencies, and then entering the information into a spreadsheet. Because this intake process was manual, errors and delays occurred before users even reached the interface.
Instead of treating the problem as a screen redesign, we approached it as a workflow optimization problem.
Automated Intake & Validation
Vendors submitted surveys and pricelists in multiple formats. Previously, analysts manually reviewed each document and re-entered the data into the system, which was time-consuming and error-prone.
To reduce manual handling, the new workflow allowed users to upload surveys to a shared intake location. The system automatically extracted rate data and performed initial validation checks, such as missing fields and formatting inconsistencies.
This shifted the user’s role from data entry to verification. Instead of typing information line by line, users reviewed system-parsed entries and focused only on resolving flagged issues.
Once the data is extracted and validated by the system, the rate update is identified in the management system and requires review and approval before finalizing the rates in the system.
Analyst Review
Automation alone was insufficient because freight rates often required contextual judgment. Therefore, the process incorporated a human review stage.
After automated extraction, analysts review and approve within the rate management interface. They are presented with a snapshot of rate variances for the new survey/pricelist update that require review before an approval.
This approach balanced efficiency and reliability:
• Automation handled repetitive formatting and validation
• Analysts handled exceptions and decision-making
By separating data ingestion from verification, the system significantly reduced manual entry while preserving accuracy.
Approach
Centralized Rate Table
The rate table displayed key attributes — vendor, freight program, effective date, and last updated date— in a single view. This reduced the need for users to memorize values while switching pages and allowed them to compare entries side-by-side. The table organizes the company vendors into a clear hierarchy. This allowed users to scan rows quickly and expand the rows only if needed.
Locating Information Quickly
Users frequently needed to find specific vendors and new vendors among hundreds of entries. Instead of manual scanning, the interface provides filtering and search.
Users can narrow results by vendor, status, and different attributes allowing them to immediately focus on relevant updates and reduce review time.
Improving User Confidence
A major pain point was uncertainty about whether updates were saved correctly. To address this, the interface provided immediate feedback after each change. The table dynamically updated based on the latest data, removing the need for manual refresh and reducing repeated verification steps.
Signals & Exception Management
Users received system-generated signals for:
New Lanes: Notification when new shipping lanes are detected.
Rate Data Exceptions: Alerts for missing, expiring, or high-variance rates.
Rate Pipeline: Visibility into the status of rate updates and exceptions.
Signals and exception alerts proactively guided users to issues needing attention and ability to make quick judgements on actions that needed to take place based on the signals displayed.
Approach
Designing for High-Volume Work
The Freight Rate management team rarely processed a single vendor rate update a day. Multiple vendors typically submitted pricing changes in large batches, sometimes affecting dozens or hundreds of routes at once. In the previous system, each entry had to be opened, reviewed, and approved individually.
This turned a routine task into repetitive work and significantly slowed throughput. To align the system with real working conditions, we introduced multi-row selection and bulk approval.
Multi-Selection
Users can select multiple rate entries directly within the table. Selection persists while filtering or navigating within the workspace, allowing users to review subsets of data without losing progress.
This supports the natural workflow: scan → identify related entries → review → approve.
Safe Approval
Bulk actions introduce risk. Approving incorrect rates could impact vendor pricing and billing, so the design needed to prioritize confidence as much as speed.
To mitigate errors, the workflow includes:
• A pre-approval review panel
• Highlighted variances for any potential problematic rates
• Required confirmation before finalizing changes
This allowed users to benefit from efficiency while maintaining control over decisions.
Outcome
Bulk approval transformed the task from repetitive data handling into decision-based review. Instead of performing the same action repeatedly, users could evaluate groups of related rates and finalize updates in a single step, significantly reducing manual effort and mental fatigue.
Results + Takeaway
Reduced manual effort
Automated survey intake and inline editing eliminated the need to manually re-enter rate data. Users primarily performed review and correction rather than transcription.
Faster processing of rate updates
The table workspace and bulk approval allowed analysts to process groups of rate changes in a single session instead of handling entries one at a time.
Improved data accuracy and higher user confidence
Built-in validation and visible error states helped users identify issues before submission. Teams reported fewer downstream corrections and less need to re-verify rates outside the system.
Reduced training overhead
New users were able to understand the workflow more quickly because the interface aligned with their real tasks instead of database terminology.
Although formal quantitative tracking was limited for this internal tool, post-launch observations and stakeholder feedback indicated clear operational improvements.
I initially viewed the problem as an interface usability issue, but process mapping revealed that the largest inefficiencies existed in the workflow surrounding the product. By addressing data intake, validation, and review together, the final solution improved the overall process rather than just the screen users interacted with.
