Riviana Foods Case Study · AutoO2
How AutoO2 turned a weight puzzle into a solved problem, and cut freight costs 5–10% per lane across Riviana's operation.
The increase in weight per truck "adds up in terms of cost savings."
Rice ships in every size. Trucks were weighing out before they were full.
Trucks weighing out short
Heavy products couldn't reach legal weight limits before trailers were physically full, so payload capacity was left behind on every load.
Expertise-dependent loading
Mixed-weight placement required experienced loaders, and knowledge was constantly lost to turnover.
Hidden freight cost at scale
Small per-truck gaps compounded across 10,500+ annual shipments into a significant avoidable expense.
Weeks of onboarding per loader
No systematic load guidance meant productivity suffered during every new hire's ramp-up period.
AutoO2 turned a weight puzzle into a solved problem for this Riviana Foods case study.
Dimensions, weight, stacking rules, and customer-specific requirements for every SKU in the shipment, ingested before building the load.
Weight, cube, axle distribution, damage risk, and stacking constraints resolved simultaneously: heavier products beneath lighter ones, every axle legal for every destination state.
Loaders receive exact visual placement instructions on screen. No expertise required, so new operators are productive in days, not weeks.
Maximum legal payload, no axle violations, damage-free. What was planned is exactly what ships, and it is immediately measurable from day one.
This Riviana Foods case study, in numbers: more weight, less cost, no expertise required.
In short, the results below are measured outcomes from Riviana's Memphis operations, not projections.
Zachary Dale, Supply Chain CI Manager at Riviana Foods, says the increase in weight per truck "adds up in terms of cost savings."
Questions about the Riviana Foods results
How does AutoO2 solve mixed-weight truckload problems?
AutoO2 solves mixed-weight truckload problems by simultaneously optimizing axle weight distribution, cube utilization, stacking rules, and damage prevention. Unlike rules-based load builders that apply constraints sequentially, AutoO2 finds the global maximum load: heavier products on the bottom, lighter SKUs above, every axle legal for every destination state, automatically, every shipment.
How much freight cost reduction did Riviana Foods achieve with AutoO2?
Riviana Foods achieved a 5–10% freight cost reduction per lane using AutoO2 load building software. The weight gap per truck was small, but applied across 10,500+ annual shipments, the annual cost was significant. ROI was achieved within 90 days of deployment.
Why does per-truck payload gap matter at scale?
For a shipper running thousands of truckloads per year, even a small payload gap per truck compounds into a large amount of avoidable freight spend annually. Each underloaded truck means paying full freight cost for a partial payload. AutoO2 eliminates this gap by maximizing legal payload on every load, every shift.
How does AutoO2 reduce loader training time?
AutoO2 generates step-by-step visual load plans that guide loaders through exact product placement for every shipment. Loaders follow on-screen instructions without needing prior mixed-weight experience. Riviana Foods reduced loader training time by 80%. New operators were productive in days instead of weeks, and the knowledge of how to build a legal, optimized load is embedded in the software, not in individual employees.
What systems does AutoO2 integrate with?
AutoO2 integrates directly with ERP and WMS systems to pull item master data, order details, and stacking constraints, then generates optimized load plans and visual diagrams automatically, without manual input. No TMS or WMS replacement required. AutoO2 works alongside existing systems. Learn more about system integration and automation.
