Every article about farm management software has an interest in the answer, and this one is no exception — it is published by a company that makes some. So this page starts from the opposite direction. Before we talk about what software to choose, we should be honest about the strongest competitor any product in this category faces, which is not another product. It is the spreadsheet you already have, and for a great many farms it is the right answer.
The useful question is never “is farm software good?” It is “does my farm have a problem that software solves, and does it have it badly enough to be worth the cost of switching?” Those are two separate tests, and a lot of farms fail the first one and buy anyway.
Read this knowing who wrote it. This page is published by Farm40, which sells farm management software. That does not make it wrong, but it should change how you weigh it: assume we have a thumb on the scale, and hold everything here to that suspicion. The test we would apply to ourselves is the one we set out below — whether the first 90 percent of this page still helps you if you never buy anything. If it does, it earned your time. If it reads like a brochure, close it.
The spreadsheet is the honest default, not the beginner’s mistake
There is a quiet snobbery in the software industry about spreadsheets, as though a farm still keeping records in one has simply not grown up yet. Ignore it. A spreadsheet has four properties that are genuinely hard to beat, and any vendor who waves them away is hoping you will not notice what you are giving up.
It is free, which for a pre-revenue enterprise or a farm running on thin margins is not a small thing — it is the whole decision. It is infinitely flexible: a column is a column, and you can invent a new one the moment your operation needs it, without waiting for a vendor to decide the feature is on their roadmap. It carries no vendor risk — nobody can raise its price, discontinue it, get acquired, or lock your history behind a lapsed subscription. And everyone can already use it, which means there is no training, no adoption curve, and no new person to onboard when your teenager or your neighbour helps out at harvest.
Put concretely: a market-garden operation with one grower who enters the plantings, the harvests, and the sales into a single sheet on a Sunday evening has a records system that is cheaper, more adaptable, and less fragile than anything you can buy. If that describes you, the rest of this page is about a problem you may not have.
A spreadsheet breaks at four seams, and only four
The spreadsheet is not defeated by farm size or by ambition. It is defeated by specific structural pressures, and it is worth knowing them precisely: if none of them presses on your farm, you do not need software, and if one of them does, no amount of discipline will make the sheet hold.
- More than one person, entering at once. The moment two people need to write into the record concurrently — one at the barn, one at the packing shed — a shared sheet starts overwriting itself, and the version in the truck is a day behind the version on the laptop. This is the seam that opens first and hurts most.
- Records that must constrain, not describe. A sheet is testimony about the past. It cannot refuse to let you do something. When a record has to stop an action — the classic case being a withdrawal window that should make an animal impossible to sell — a flat sheet can warn a person who happens to look, but it cannot enforce.
- Relationships between records. A harvest lot that has to know which planting it came from, which in turn has to know which inputs were applied to it, is a chain, and a flat sheet models a chain badly. You end up copying identifiers between tabs by hand, and the copy is where the errors live.
- Retrieval under time pressure. A sheet is fine to search on a Sunday. It is a different thing at a loading chute with a buyer waiting, when the question is “is this specific animal clear to sell” and the answer is thirty rows down a tab someone renamed.
These map directly onto the harder recordkeeping problems a farm runs into — the constraint problem is the heart of livestock management, and the relationship problem is the heart of traceability. If your records have grown into either shape, the spreadsheet is not failing you because you kept it badly. It is failing you because you asked it to be a database, and it is not one.
Evaluate a product by the questions that expose a bad fit
A feature list is written to be agreed with. It tells you what a product does, not where it will hurt. To see a product clearly, ask the questions it would rather you did not, and watch how comfortably it answers.
Can I get my data out, in a format I can read, without asking you? This is the first question, and if the answer is anything other than a plain yes with a file you can open yourself, stop there. Your records are the asset; the software is a tenant improvement on top of it. A product that makes leaving hard has made a decision about the balance of power between you and it, and told you what it is.
What happens to my records if you go out of business?Most software companies fail, and a farm outlives most of them. The only real protection is a current, readable export in your own hands, so this collapses back into the first question. Ask it anyway: the way a vendor answers a question about their own mortality is informative.
Does it work with cold hands, standing up, with no signal?The record that matters is captured at the moment of the work, not reconstructed at a desk that evening. If the product assumes a warm office and a full bar of signal, its records will be approximations, because the honest ones will be entered late or not at all. This is the same discipline that decides whether a spray record is real or remembered.
Is the compliance field on the form where the work is logged, or on a separate screen nobody opens? Software that puts a “compliance” tab somewhere off to the side has designed the most important records to be optional. The withdrawal date, the re-entry interval, the lot number belong on the same form as the treatment or the application, captured in the same breath — not quarantined on a screen visited only when an auditor is booked.
Who can see my data? Ask where it is stored, who at the company can read it, and whether your farm’s records are separated at the database rather than merely filtered in the interface. A vendor who cannot answer plainly has not thought about it, and you are about to hand them your whole operation.
Migration costs a season, not a subscription
The price on the pricing page is the least of what switching costs you. The real bill is paid in time and in truth. The time is the season you spend re-entering the history you already had, typing last year’s plantings and treatments into a new system so that this year’s records have something to sit against. That work is invisible on any budget and it is the reason most migrations stall.
The truth cost is worse, and less discussed. For the six months during a migration, you are running two systems, and each of them is half-true. The old sheet has the history; the new software has the recent entries; when a buyer or a certifier asks a question, you check both and hope they agree. A farm in this state is more exposed than one that never switched, because it has two records and no single source of truth.
The way through is to refuse the temptation to backfill everything. Pick a boundary the farm already respects — the start of a crop year, a fresh group of animals, the first day of a certification cycle — and move forward from that line while leaving the old history where it sits, exported and archived. A migration that runs with the calendar instead of against it is the one that finishes. This is where a clean handle on your farm recordkeeping before you move pays for itself: a tidy sheet migrates in a weekend, and a messy one migrates never.
Most software failures on farms are adoption failures
When a farm says the software did not work, it almost never means the software lacked a feature. It means the records stopped getting entered. The trial started well, the first month looked promising, and then calving happened, or the rain came, and the app quietly fell out of the daily routine because entering the data was one more thing to do after the real work was finished.
This is the failure that no comparison of features will predict, because it has nothing to do with features. It has to do with whether the easiest way to record the work is also the correct way. If logging a treatment properly takes longer than scribbling it on a whiteboard, the whiteboard wins, every tired evening, until the software is a subscription nobody opens.
So before you weigh any feature, weigh the friction. Watch where the data entry will actually happen and who will do it. Ask whether the person with the least patience for screens — the one who does the treating, the spraying, the loading — will find the honest path faster than the lazy one. If they will, the software has a chance. If they will not, a spreadsheet everyone actually updates beats a database nobody does.
Be sceptical of anything an assistant claims to compute
A newer line on every vendor’s pricing page is an AI assistant, and it deserves the same suspicion as everything else, sharpened. An assistant that reads your records and helps you find one is genuinely useful. An assistant that performs its own arithmetic on your figures, or invents a regulated interval it half-remembers, is dangerous, and the two can look identical in a demo.
The question to ask is architectural: does the assistant quote numbers the application already computed, or does it do the sum itself. The first retrieves; the second is a confident guess wearing the authority of software. A withdrawal date, a cost per acre, a re-entry window — these must come from the record and the label, never from a language model’s best impression of one. We treat this at length in AI in farming; read it before you let any assistant near a number that has consequences.
Where we stand, since we built one of these
Everything above applies to us, so here is where Farm40 sits, stated plainly and with its limits attached. The live demo needs no signup, and the 7-day card-on-file trial gives you every module with $0 due today. After the trial, the plan is a flat $19 a month for unlimited farms. There is a live demo at the app with no signup: real screens, seeded data, so you can judge the friction yourself before you type a single record of your own.
Your records leave in a format you can read. There are twelve one-click CSV exports, and we would rather you take one on a schedule and keep it somewhere we cannot reach than trust that we will be here forever. That is the question we told you to ask every vendor — can I get my data out, without asking — and you should ask it of us too, and check the answer rather than take our word for it.
The limits, because they are the honest part. Farm40 is young and built by a small team, which means it moves quickly and also that it has gaps. There is no separate equipment screen — equipment lives inside operations, and if you want a dedicated asset register you will not find one. There is no compliance-report generator that assembles an audit packet for you; the records are on the forms where the work is logged, which is the right place, but you assemble the packet. And the AI assistant is a read-only question-answerer with a monthly question quota — it names which tools it ran to find an answer, it does no arithmetic, and it does not act on your behalf. You should know those gaps now, from us, rather than discover them after you have moved a season of history across. And if a clean spreadsheet is still serving you, the most honest thing we can say is: keep it, and come back when one of the four seams starts to tear. Working out what each enterprise actually costs is a fine reason to move; a vague sense that you ought to have software is not.