Applied case study
Growth Mindset built forecasting and line planning software for a Bay of Plenty kiwifruit postharvest operator. The tool grew from a focused planning request into a configurable planning layer used across several packhouses.
Multi-site planning
The client operated across several packhouses. Each site had its own grader setup, equipment limits, packing preferences, labour assumptions, and local way of preparing the next run.
A useful tool could not assume one standard line setup and force every site into it. Planners needed to know what the fruit was likely to produce, which products should be targeted, and how each site's equipment should be used before production began.
The software also improved the fruit size forecast itself. Growth curves based on days after full bloom were used to estimate size profiles before fruit reached the grader, and those forecasts became useful beyond the optimisation model.
System map
The planning method needed biological forecasting, pack planning rules, and site settings to work together without treating outputs as another input.
Source information
The forecasting layer used the details that shaped the likely fruit profile before packing.
Planning logic
The model mapped fruit forecasts through the rules and limits that mattered for each packhouse.
Planning outputs
The system produced outputs that could support site planning, review, export, and reporting.
The build
The system linked size forecasting, pack planning, and site configuration in one planning process.
Size profile forecast
The model estimated fruit weight and size profile using sample data, days after full bloom, variety rules, and storage path information.
It mapped the predicted weight distribution into the relevant size bands, giving planners an earlier view of tray mix and packout assumptions.
Site configuration
A common calculation engine sat underneath the tool, while local teams could manage grader specifications, equipment capability, rate settings, labour assumptions, planning priorities, and export preferences.
This kept the planning method consistent while allowing each site to reflect how its packhouse actually worked.
Line planning
The software converted the size forecast into expected trays, recommended equipment use, manual packing requirements, and site-ready line planning outputs.
The aim was not one generic answer. It was a plan that reflected the selected site's equipment, priorities, and production habits.
Saved outputs
The tool saved plans and produced Excel and PDF outputs that planners, production teams, and managers could review.
Structured outputs could also feed reporting or automation layers, which made the planning result available beyond the planning screen itself.
Business value
The tool gave each packhouse a stronger starting point before fruit reached the grader.
Teams could plan from expected size profile, tray mix, and packout assumptions before production began.
Each packhouse could adjust grader settings, equipment limits, labour settings, rates, and priorities around its own operating environment.
The client chose to use the size profile forecasts beyond their role as inputs to the line planning model.
Saved plans, review screens, and exports gave teams a clearer record of assumptions, outputs, and production intent.
Transferable value
This case study shows Growth Mindset's ability to build practical planning software for complex postharvest operations.
The work combined stronger fruit size forecasting with configurable site rules, giving several packhouses a shared planning method that could still fit their own equipment, priorities, and ways of working.
Discuss a project
A focused consultation can clarify the shared method, the local settings, and the outputs each team needs to review before production starts.