OptaHaul: simplifying dairy logistics with role-based dashboards.

We started with a remote workshop to get aligned on roles, goals, and decision flows. From there, we ran weekly check-ins with regular demos, async feedback, and clear design deliverables.

Here's how we worked:

• used anonymized feedback from OptaHaul’s dairy clients (like Horizon and Dairygold) to understand what users needed most;

• mapped out key KPIs for each persona and grouped them around real decision-making flows;

• designed early dashboard concepts with modularity in mind, to allow for role-based views;

• prototyped directly in Figma, collaborating closely on structure and clarity.

To keep things simple and avoid overwhelming users, we designed the dashboards around a modular card system. Each card highlighted just one metric — like Distance or Tank Fill — with visual cues (trend lines, bar charts, color indicators) that made it easy to scan at a glance:

• card-based layout that scaled easily across roles and use cases;

• contextual filters (like haulier, route, supplier, or factory) available at both the dashboard and card level;

• minimal visual style with light grid lines, calm colors, and clear typography for easy reading.

Once users had a clear view of their daily metrics, we focused on helping them explore what could be improved. Clicking on a dashboard card opened a drawer with more information on the selected routes or hauliers, without leaving their current screen.

The goal was to let people get what they need fast and get back to planning with:

• inline filters and search inside drawers for quick exploration;
• one-click export for quick offline reports and team sharing.

The comparison module showed the differences between what actually happened and what OptaHaul recommended, so users could spot where costs or timing were off, and understand why. The interface included:

• side-by-side comparisons for “actual vs optimized” performance;

• dropdowns and date pickers to filter and test different scenarios;

• expandable route-level views with vehicle and delivery details;

• color-coded bars to flag differences between current and optimized outcomes.

To help planners think ahead, we added a scenario modeling module that let users see how changes, like adding a haulier or rerouting deliveries, could affect cost and performance over the next 6-12 months. It gave planners a way to try out ideas before committing and replace guesswork with real numbers.

Once users saw where performance could be better, we layered in suggestive UI elements to flag when a load could be cheaper or faster with a small change. Nothing intrusive, just enough to point to better options, while keeping users fully in control.

A few under-the-hood improvements were made to reflect the complex realities of dairy logistics and finance:

• flexible cost calculations that adapt to different haulier contracts and pricing setups;

• turnaround time broken into pump vs non-pump delays, so teams can identify what’s really slowing things down;

• finance metrics — like cost per litre and $/CWT — with filters by supplier, route, or factory.