About Growth Mindset
Growth Mindset helps businesses turn data into practical tools that make decisions easier. We keep things simple, clear, and focused on what matters most, without adding noise or complexity.
With more than 20 years of experience working with businesses of all sizes, we know that the best systems are the ones people actually use. You bring the knowledge of your business, and we bring the skill to turn that knowledge into tools that work.
About Rob
Rob helps businesses use data in ways that make a difference. He has a background in statistical and mathematical modeling, but his work covers the entire journey from raw data to something useful.
Much of Rob's work happens behind the scenes. He studies how data behaves, checks assumptions, and builds models that match how things really work.
Rob is the instruction manual that most analytics tools leave out. He makes sure that tools and methods fit the shape of your business, not some generic idea of one.
Rob helps teams see their data in a new way. This makes planning simpler, decisions clearer, and work more predictable.
What We've Been Working On
We worked with a large fruit exporter to cut downtime and make better use of their existing packing capacity. Their automated lines could run fast, but too much time was lost each time they had to reset for a new product. Together, we looked at how data could help guide those changes instead of reacting after the fact.
Operators often had to guess what sizes and grades would come from each supplier. Dashboards showed what had already happened, but nothing to help plan what was next. Grower data was incomplete, and priorities changed often. Some lanes ran short while others were overloaded.
We built a web app in Python that brought their data together. It connected to their SQL databases, read from spreadsheets and PDFs, and pulled live machine data into one place. The app used predictive models to estimate the size and grade mix for each grower, then suggested lane setups to match those forecasts. Operators could adjust plans, update run details, and test different scenarios such as run speeds, machine downtime, or shifting schedules. The system refreshed forecasts and recommendations as new data arrived or plans changed.
Setup times dropped from around half an hour to just a few minutes. Changeovers became consistent, downtime fell, and packing stayed aligned with current priorities. We kept everything running on their existing systems, with no new hardware or major changes needed.
