What’s the basic step in getting your farm future ready? Automating documentation on your farm, says Lars Petter Blikom
Documentation is boring.
That’s the root cause of a lot of problems with documentation.
Here’s what happens in real life: Farmers take a lot of mental notes, things they plan to remember and use for future reference. They also take a lot of notes on a paper pad or any piece of easily available paper. Typically, this data needs to go into a report, for example, a spray log or a harvest log.
Mental notes are often forgotten, or they lose their accuracy over time, but they feed the farmer’s own experience. Anyone who has been farming for a few decades has observed many of if-this-then-that connections. Paper notes can be found on the farmer’s messy desk, behind the coffee machine in his kitchen, or under the seat of his tractor.
Everyone knows they can take notes on their phone, but no one does that.
We can talk about the need for structure, processes, and good business practice and be very convincing about the importance of keeping good documentation. It still won’t happen.
That’s why it needs to be automated.
Here are some examples of what I mean:
- If you ask a crew member to spray for you, do so in a storable and traceable format - that way, your spray log is automatically updated when the job is done. No need to remember to put that information into another system.
- If your agronomist shares an observation of disease in your fields, do so in a format that fits your logs for disease observations and conserves it for future knowledge building. Avoid putting yourself in the position where you have to remember it, and then write it somewhere.
- If your teams use a timesheet system, make sure they log hours on fields, job types, and any other type of breakdown you think might be useful in the future. This way, you avoid having to manually re-construct where all the hours were spent when you do your post-season analysis.
Achieving automated documentation is first about establishing work processes that lend themselves easily to automation before even getting into which data system you use for it.
Read this article about gathering data:
Every farm needs a data management plan
Data management and automated documentation go hand in. Every farm should create its own data management plan. This is much simpler than it sounds. It just needs two lists:
- List of data in. What data is my farm generating?
- List of data out. What do I need data for?
Here’s a simplified overview of this model for my farm:
The next step is to start exploring every item in the lists. Can the item be fully automated? If not, can it be significantly simplified?
The choice of that green box in the middle is key. When my partners and I started, we didn’t find agriculture-focused data management tools that we liked, so we built our own inside Google’s amazing universe of tools. When we reached the limitations of Google Drive, we started building more advanced tools – today, this is Farmable.
Choose your farm management system wisely
I realize that I am a salesperson at this point. Yes, my preference would be that as many farmers as possible choose Farmable as their farm management software, but for each farmer, I strongly advise that you take special care in the choice of system.
Regardless of your choice, take time to assess how it fits your farm, your work processes, and your documentation needs. Also, be prepared to make some changes to how you run your farm to make it more automation-friendly and to fit as best as possible with the data management system you choose – this makes it easier to realize all its benefits.
Making an extra effort in automating documentation practices will pay off in terms of reduced hours spent agonizing over reports and being better prepared for more technology-assisted farming in the future.
This is part six in a seven-part series on a farmer’s journey to precision agriculture.
Part 1: Precision agriculture isn’t what they say it is
Part 2: What problems will precision agriculture solve
Part 3: Reinvent how you gather, organize and use your data
Part 4: Why measuring return on investment per field is still a challenge
Part 5: What’s the biggest cost in agriculture? Labour.
Part 7: How variable zoning can lead to more precision in agriculture