As always, it's an interesting and profound analysis!
Let's start from the end – the most valuable player will be the one who creates a comprehensive IT farm management system based on clear data and AI algorithms, integrating all external and internal data sources. 🚀
This will serve as the primary framework for business planning and operational management, providing data for accounting operations and tax reporting. 📊💰
In this ideal scenario, a 👨🌾farmer will be able to open the 📱application in the 🌄 morning and ask the system (as Rhishi discussed in the latest issue about using LLM technologies),
"Hello! What's on our agenda for today? Please show me the current operational plan and yesterday's performance. How much money is in the account? What's the grain volume at the elevator? What payments are due today?" 💼
In Ukraine, we've already been fantasizing about this, collecting historical field data from various sources. 😉
The model of agri-operations can be well-described for all segments of agribusiness, making it easy to see where the need for human labor is reduced and indispensable. 🤖
🚜 Autonomous machinery will undoubtedly reduce the number of operators but will still require human involvement in the process of delivering goods to the field and loading them into the equipment.
Of course, at some point in the future, we'll reach a fully automated process from delivery to loading without human intervention, at the level of system identification and docking, much like spacecraft.🚀
👨🌾Staffing issues are specific to each country and segment of agribusiness. Given my previous experience with large agribusinesses, they have separate KPIs for the number of staff per 1,000 hectares (2,400 acres). 📉 The process of personnel optimization through process automation and organizational restructuring is ongoing every year. From memory, ten years ago, the average number of employees per 1,000 hectares was around 20-25 people, whereas today, a good benchmark is considered 10-12, and an excellent one is 7-8!
🎯I wonder if American farmers have similar metrics? 🇺🇸
The examples of Bushel and AgVend are spot on.
They each approach the farmer from their end of the process, creating a chain from input suppliers to farm management and the sale of the final product. AgVend wants to understand the market 📊 balance for planned farmer purchases of inputs for agri-retailers to balance the supply chain. A great idea! 🚀
Thanks for the link to the article "What is 'the next big thing' for agtech?"
After reading your text, I'm even more excited about the new possibilities I'm discovering as I delve deeper into the specifics of working in the U.S. agribusiness. 💰🌾🤝
Thanks so much for your thoughts Oleksandr! Great question on US farms having similar metrics per acre -- I imagine the USDA would have that data (and that it would likely vary greatly depending on the crop type grown with specialty crops having many more employees per acre than row crops).
Glad you enjoyed the "What is 'the next big thing' for agtech" article! Seana Day's other analyses of the agtech space are also very thorough and have been immensely helpful to me in better understanding the industry!
Yes, depending on the culture, the number of employees per 1000 acres will be different. There will probably be the most of them on strawberries :-) Although strawberry picking is already on the verge of a total transformation - the use of special “harvesters”. I had a berry farm, I know how many problems manual picking of berries generates.
It sure seems like automation should be a welcome development to agriculture, with labor shortages already here. Technology is not to be feared, it's a natural progression!
Absolutely! It makes sense that we are seeing automation getting traction in places where there are either labor shortages and/or labor costs are rising significantly, like for many specialty crops. Now just gotta make sure that the tech works consistently, across many different conditions, and provides ROI for the farm!
Thank you so much for this article!
As always, it's an interesting and profound analysis!
Let's start from the end – the most valuable player will be the one who creates a comprehensive IT farm management system based on clear data and AI algorithms, integrating all external and internal data sources. 🚀
This will serve as the primary framework for business planning and operational management, providing data for accounting operations and tax reporting. 📊💰
In this ideal scenario, a 👨🌾farmer will be able to open the 📱application in the 🌄 morning and ask the system (as Rhishi discussed in the latest issue about using LLM technologies),
"Hello! What's on our agenda for today? Please show me the current operational plan and yesterday's performance. How much money is in the account? What's the grain volume at the elevator? What payments are due today?" 💼
In Ukraine, we've already been fantasizing about this, collecting historical field data from various sources. 😉
The model of agri-operations can be well-described for all segments of agribusiness, making it easy to see where the need for human labor is reduced and indispensable. 🤖
🚜 Autonomous machinery will undoubtedly reduce the number of operators but will still require human involvement in the process of delivering goods to the field and loading them into the equipment.
Of course, at some point in the future, we'll reach a fully automated process from delivery to loading without human intervention, at the level of system identification and docking, much like spacecraft.🚀
👨🌾Staffing issues are specific to each country and segment of agribusiness. Given my previous experience with large agribusinesses, they have separate KPIs for the number of staff per 1,000 hectares (2,400 acres). 📉 The process of personnel optimization through process automation and organizational restructuring is ongoing every year. From memory, ten years ago, the average number of employees per 1,000 hectares was around 20-25 people, whereas today, a good benchmark is considered 10-12, and an excellent one is 7-8!
🎯I wonder if American farmers have similar metrics? 🇺🇸
The examples of Bushel and AgVend are spot on.
They each approach the farmer from their end of the process, creating a chain from input suppliers to farm management and the sale of the final product. AgVend wants to understand the market 📊 balance for planned farmer purchases of inputs for agri-retailers to balance the supply chain. A great idea! 🚀
Thanks for the link to the article "What is 'the next big thing' for agtech?"
After reading your text, I'm even more excited about the new possibilities I'm discovering as I delve deeper into the specifics of working in the U.S. agribusiness. 💰🌾🤝
Thanks so much for your thoughts Oleksandr! Great question on US farms having similar metrics per acre -- I imagine the USDA would have that data (and that it would likely vary greatly depending on the crop type grown with specialty crops having many more employees per acre than row crops).
Glad you enjoyed the "What is 'the next big thing' for agtech" article! Seana Day's other analyses of the agtech space are also very thorough and have been immensely helpful to me in better understanding the industry!
Yes, depending on the culture, the number of employees per 1000 acres will be different. There will probably be the most of them on strawberries :-) Although strawberry picking is already on the verge of a total transformation - the use of special “harvesters”. I had a berry farm, I know how many problems manual picking of berries generates.
It sure seems like automation should be a welcome development to agriculture, with labor shortages already here. Technology is not to be feared, it's a natural progression!
Absolutely! It makes sense that we are seeing automation getting traction in places where there are either labor shortages and/or labor costs are rising significantly, like for many specialty crops. Now just gotta make sure that the tech works consistently, across many different conditions, and provides ROI for the farm!