TEST CODE HERE

Staying on top of your crew’s work is a constant task, so you probably have a good idea for how to best plan your crew’s work. But if you want to grow or scale your farm in the most efficient manner, equipping your crew for high performance is key.

Kasey and Heath took time out of their busy lives to join us for a webinar on how they manage one of the most important aspects of growth: efficiently planning their crew’s work.

They took us through a day in the life of a farm manager: setting up workflows, equipping the team for high efficiency, and reviewing completed work. Below is a quick summary and a few questions on how Bryant Ag operates and plans their crew’s day. For the complete interview, listen to the webcast on demand.

Passing Down the Farm With Succession Planning

Kasey Bamberger and Heath Bryant manage all aspects of Bryant Ag – a successful and growing operation in Washington Court House, Ohio. They are third generation business partners currently operating in seven counties.

Kasey and Heath attribute their success in growing their business with efficient management practices and a succession plan that keeps all of their knowledge and farm data in one place.

How do you go about setting up your day and tracking the day’s work? “We do a lot of planning and training. We have daily meetings with our ops managers, usually at night or early in the morning to decide what needs to be learned, done, and what equipment to use where. We assign equipment, tasks, and track as-applied input usage. In case we need to make changes to tasks in real-time, we use Granular so we have an accurate record of who did what and when.”

How do you evaluate areas you want to improve on? “We look for mistakes and corrections that were made. We also make sure that operators are not choosing a generic input when the as-applied input usage is different. This is how we measure our efficiency to make the right decisions.”

How do you adjust if things don’t go according to plan? No matter what, “rain or shine, everyone always comes to work.” Unpredictability will always happen, so we “use generic crop plans for each farm” for the most flexibility. Granular’s Mobile App gives us a quick way to change up the day using the unplanned work features.

What made Bryant Ag decide to go with Granular? “We felt like it was a good way to gain knowledge about our operation quickly. I have more of a business background, managing our office staff and managing landowners and financials. Heath manages the production end, so we feel like we make a pretty good team. We also know that there’s power knowing all areas of our operation. When we first met with Granular, we were so excited because it was a great way for me to understand what was going on in the fields without having to be in the fields, because we know that’s not where I’d be best utilized at. It also gave Heath the platform to have a better understanding of the financial end of our operation without having to sit behind a desk all day.”

Decisions Based on Efficiency and Data

Kasey and Heath are efficiency-driven. They keep a constant pulse on their crew’s work at the field level, they have multiple test plots to analyze historical data, and they are carrying out their family’s legacy with smart succession planning. All ways they’ve used to grow and scale.

Bryant Ag has also pushed for digitizing their entire operation so they can utilize data which allows them to make financial decisions with more speed, confidence, and precision. Learn more about Bryant Ag’s best practices and how relying on Granular keeps them operating at high efficiency.

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According to the USDA’s 2014 Tenure, Ownership, and Transition of Agricultural Land (TOTAL) Survey, 39% of the 916M agricultural acres in the U.S. are rented. And a good portion of those rented acres are owned by individuals or partnerships who do not directly farm the land. There is speculation that absentee owners, cropland owners who don’t live on the farm they own, are a growing segment of the owner population. A few factors are driving this trend:

  • Growing interest in cropland as an investment – Institutional investors, including pension funds, private equity, and endowments have turned to cropland as an attractive asset class.
  • Consolidation in farm operations – According to the Census of Agriculture, the percentage of cropland acres operated by farms over 2,000 acres grew from 34% in 2002 to 42% in 2012. This growing segment of large farms are choosing to expand their operations through rental versus ownership.
  • Generational transition of ownership without transition of the operation – According to the TOTAL study, 64% of cropland owners’ owned acres were transferred inter-family. As the next generation inherits the land but doesn’t return to the farm to take over operating it, the absentee owner population grows.

But exactly what proportion of cropland acres today are managed by distant or “absentee” owners? The AcreValue data science team answered this question by analyzing our rich proprietary dataset of millions of cropland parcels in the lower 48 states, with a focus on those acres growing crops (we use NASS’s Cropland Data Layer to determine whether a parcel is cropland).
In addition to observing the exact boundaries and location of cropland parcels, our data includes the names and addresses of each parcel owner, sourced from CoreLogic, a property data and analytics company. This is a uniquely rich dataset — to our knowledge, we are the only team with access to a nationwide dataset linking detailed parcel-level data with ownership information. By comparing the location of a cropland parcel to its owner’s address, we are able to calculate the distance from the parcel to its owner. To keep things simple, we calculate distances “as the crow flies”. We ran this calculation for each of the millions of cropland parcels in our dataset.
Nationally — excluding Alaska, Hawaii, and any counties without data coverage — we find that 13.4% of cropland acres have owners located more than 100 miles away, while 9.1% of cropland acres have owners more than 200 miles away. For comparison, 200 miles is roughly the distance from Iowa City, IA, to Chicago, IL. Interestingly, the rate of absentee ownership varies considerably by geography: in some counties it is much higher than the national average, while in other counties the absentee ownership rate is close to zero. The maps below show the percentage of cropland acres with distant owners, by county, using either 100 miles or 200 miles as the threshold for an owner to be “distant” from his or her cropland.
absentee ownership
Source: , NASS Cropland Data Layer
 
Several counties in northern Iowa have high rates of absentee ownership, as seen in this zoomed version of the map:
absentee ownership
 
Here is the national map again, this time using 200 miles from land to owner as the threshold for absentee ownership:
ownership absentee
 
Which counties have the highest rates of absentee ownership? The table below shows the top 10 counties for distant ownership, limiting to counties with significant cropland acreage and using 100 miles as the threshold for distant ownership.

The top absentee ownership counties are spread across the country: there are several top counties in California, Iowa, and Texas. Kings County, in California’s central valley, is an interesting case: San Francisco and Los Angeles are both above 100 miles but generally below 200 miles from Kings County (although some cropland in the northern part of Kings County is slightly more than 200 miles from the southern parts of LA). Since large amounts of Kings County cropland is owned by people living in SF and LA, the absentee ownership rate is high using a 100 mile threshold, and much lower using a 200 mile threshold. The situation in Tulare County, CA, is similar.
As ownership information changes over time, we will be keeping an eye on how these trends evolve, though we expect the rate of change to be slow. In the meantime, if you’re interested in taking a deeper look at our parcel and ownership data, please visit acrevalue.com.

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Learn how Granular helped a real farm discover that their variety choice was costing them $800 per acre

The most effective farm organizations use data to organize their production plans and make financially-driven decisions. There are common variables to consider when making these decisions that often include land costs, seed variety, fertilizers, and chemicals.

Does your data help you make decisions based on the profitability of those variables? How much does your variety choice impact your bottom line? What if you had your financial data organized to answer these questions?

In this case study, we examine how a Granular customer was able to answer these questions about their decision to farm early maturing potato varieties to speed up their cash flow. We took a look at how they used performance data to evaluate how this decision affected their per-acre profit on each potato variety.

An Early Cash Flow Opportunity

The potato farm we worked with, let’s call them King Farms, had 4,000 acres of contracted potatoes that would not be paid until delivered this coming December. To speed up their cash flow, they chose to plant two early maturing varieties, setting aside 640 acres, and splitting the land allocation in the following way:

  • Pike: 520 acres
  • Atlantic: 120 acres

King Farms wanted to know if selling these early maturing varieties was a profitable decision, and which variety had better performance. The CEO assumed Atlantic potatoes were not as profitable as Pike, but did not have the data to know for sure. Rather than relying on instinct, he wanted to see if Granular could help him determine the financial contribution of how each variety impacted their bottom line since he had captured all task and financial data within Granular.

Running Data Analysis

Using Granular’s Profit Analyzer software, King Farms looked at their operational data to quantify the per-acre profit performance based on the potato variety. This is possible because Profit Analyzer traces tasks, revenue, and variable costs down to the acre.

With a few clicks, King Farms was able to visualize the contribution (revenue less variable costs of land and inputs) of each potato variety, which can vary by as much as $2,100 per acre as you can see in this chart:

potato profit analyzer

Let’s now take a look at the contribution of the two early-maturing varieties, Pike and Atlantic, to answer our main question around how profitable the early cash flow decision was. We also compared those early varieties, using the entire season’s varieties as a benchmark. The measure used is the contribution, which is revenue less variable expenses at the variety level.

farm-contribution

Although yield drives revenue, it isn’t always possible to know if your profit is because of yield or cost mid-season, but with Granular, King Farms was able to conclude in-season using the data which informed this analysis.

In this case, revenue was a larger driver than costs, but the key metric is contribution margin. Atlantic outperformed Pike contributing $2,333 per acre to  Pike’s $1,565 per acre, representing a difference of 63% contribution to the bottom line vs. 52%. This contribution margin considers allocated variable costs, broken out in the chart below, giving King Farms a true picture of their profitability. You can also see how the early maturing varieties are benchmarked against all potatoes in the enterprise.

VARIABLE COST BREAKDOWN BY VARIETY

atlantic pike potato contribution margin

Better Data = More Profit

What we found was that Atlantic outperformed Pike at $768/acre which is a hefty 11% difference in King Farms’ bottom line when considering the contribution margins of each variety. If he had planted Atlantic on all 640 acres, King Farms could have made significantly more, almost $400,000 in profit.

Farm Contribution Margin

There are a multitude of factors that come into play when attempting to make plans for which crop varieties to plant. Farm conditions, such as topographic land features, biotic factors, and climate are top of mind. However, now that King Farms has this data, they can plan for next year with the best information at the ready. Granular’s Farm Management Software empowers growers by surfacing and quantifying the benefits of important farm decisions.

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Your yield data may come from your combine, grain cart, or from truck scales, but each has shortcomings that may impact your farm decisions.

This harvest, growers will spend significant time and money trying to get accurate yield data from combine yield monitors, grain carts and/or truck scale tickets. However, each of these sources has varying degrees of accuracy, depending on how well they are calibrated and maintained. Your source of yield data and how well it’s maintained can play a major factor in your farm decisions.
So how do you know that your yield numbers are accurate? We will discuss three sources of yield data, their shortcomings, and what implications inaccuracy can have on your decisions.

The Three Sources of Yield Data

You may decide to invest in a truck scale system for your bin site, a grain cart sensor to measure moisture and weight, or a yield monitoring system for your combine. How accurate are these sources of data, on average?

Truck Scale Data

If calibrated and maintained, truck scales have the lowest error. However, these scales are often far from the field and require someone to attribute the load to the right farm and field, possibly on a paper ticket that needs to find its way back to the office. Lost or misattributed loads could significantly contribute to yield error. This often leads to significant investment in tools and time to measure yield closer to the field, potentially slowing down harvest operations. One missed load on a 100 ac field can lead to error of 0.5% (assuming 180 bu/ac corn and a load is 1000bu).

Grain Cart Data

You might be using grain cart or combine data to track yield. The data you get from grain carts is only as good as your calibration with truck scale weight. If calibrated correctly, manufacturers such as Digistar and Avery Weigh-Tronix state that the data should be within 0.1% to 1% accuracy of your scale weight.  But grain cart measurements typically are burdensome for an already busy grain cart operator, and don’t factor in moisture reliably, leading to another source of error.

Combine Data

Like grain carts, your yield monitor data is only as good as its calibration with grain carts or scale weights. Our customers tell us their yields reported by the combine are 5-10% off. Only a handful of our customers use combines as a source of truth today. Any miscalibration in any of these can lead to more than a 10% error in your yield data.

Farm Financial Implications

Knowing the accuracy of your yield data is one thing, but knowing the implications of inaccuracies is another, especially for crop insurance and the perceived financial implications.

Crop Insurance Premiums

If you can track and submit digital harvest data, your crop insurer has more insight your crop production risk and your farming practices, which can help the insurer to better underwrite and price your risk (i.e. your premium).
However, don’t forget that if you submit data using precision Ag harvesters, you will be required to prove that your harvester and grain cart are calibrated within 3% of scale weight. If you do not, then you are subject to the same rules as those growers who do not use precision technology, which means that you’re required to submit proof of your actual production (which is a lot of work!). Additionally, for any yield error you encounter, you will also have to update your crop insurance records.

Topline / Margin Analysis

We developed a simple table to illustrate the ramifications of a 0.1%, 1% and 10% yield error for corn and soybeans on your top line.

If you use your combine as your only source of harvest data, for example, and your combine was off by 10%, you could potentially have 10% more or less of your perceived inventory. Assuming that you harvest 180 bu/ac corn, you could have up to 18 bu/ac more or less in your inventory. Now let’s say you planted 1,000 acres of corn at a price of $3.50/bu, a 10% error in yield means you can misrepresent $63,000 on your bottom line.
You will probably not lose $63,000 from this mistake, but think of the impact to your field level decisions, crop inventory, and grain marketing. Here are a couple of examples:

  • On a field with small margins and a high yield error, you can make a different decision on what crop to grow, or not grow. Growing a less productive crop based on inaccurate data has financial ramifications and can cost you tens-of-thousands of dollars each year.
  • For grain marketing, a high yield error might cause you to over or under contract your inventory.
  • Land rental renegotiations are coming up shortly, imagine having to explain a 10% error on your crop share. This might not have any financial implications, but can damage your credibility with your landlord.

Mistakes with yield data can impair your ability to make accurate farm decisions and can harm existing relationships with buyers and landlords.

Get Your Yield Data Right

It takes a lot of time and money to invest in the right tools and technology to track accurate yield data. Whether you get your yield data from your harvester, grain carts, or truck scales, we know how important your yield data is to your farm decisions. We’ve created a FMS platform to help you reconcile and understand your yield from all data sources to improve your grasp on your farm’s bottom line.
 

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Making profitable farm business decisions is difficult. We get it. Farmers have been using Excel spreadsheets for decades, so why would you want to fix what’s not broken? With the complexities that come with farming, dynamic decisions are required. Can you make the best decisions based on completely static data in farm spreadsheets?  
Due to Excel’s static data, businesses have said goodbye to spreadsheets and hello to cloud business software. Construction companies have adopted software like Procore, the aviation industry has adopted IBM, and just about everybody else has adopted Salesforce. The Agriculture space is no different, and many farms have been making strides towards using real-time cloud software. Excel spreadsheets are again becoming obsolete as farmers are adopting new ways to track data. Excel spreadsheets limit farmers from being efficient and evolving their business in five critical ways:
1. Time Savings: Many farmers would rather spend more time in the field than in the office looking after cumbersome spreadsheets. Farmers first take notes in the field, and then spend hours doing manual data entry in the office. Granular automates data collection and organization, helping you to focus on making key business decisions and spending time with family. Farmers are limiting themselves to the information they can collect due to the time it takes to manually update multiple Excel spreadsheets.
2. Lack of Real-Time Data: Spreadsheets limit your ability to make accurate, real-time decisions. You may be creating a budget every year, but struggle keeping it updated as plans are changed unexpectedly. Granular allows you to track costs at the individual field level and keep track of cost of production. Mistakes such as spraying the wrong chemical in the wrong field are no longer a major problem.
3. Poor Communication: Excel makes it difficult for multiple users to update and act on the data being collected. Through Granular’s Mobile App, teams can quickly communicate and coordinate activities while out in the field. There are even turn-by-turn field directions included, so new and seasonal workers don’t need to waste hours each day trying to locate where they need to be.
4. No Data Science Integrations: Data only becomes more valuable over time in Granular. Integration of data science allows you to analyze field level data over the span of multiple years. Excel makes it difficult to look at various years’ worth of information that is spread out across numerous sheets. Granular easily presents this information so you can compare year by year and even measure variances in your actual and forecasted numbers.
5. Can’t Scale: With Crop Planning, Inventory Management, Inputs, Operations, and Financials, you’ll have to separate each aspect of your farm into multiple spreadsheets. Pieced together, this data does not work cohesively, inhibiting your ability to scale. For farmers who are looking to expand their business, they need a data platform that will grow with them, not hold them back.
Spreadsheets have been used for decades, but they are no longer a viable option for large-scale farm operations. Excel makes it difficult to manage all the data on your farm, which can lead to inefficiencies along the way. Granular incorporates planning, operations, inputs, and financials to reveal your most important insights. In an article by The Progressive Farmer, Danny Klinefelter, suggests making technology decisions “By The Numbers.” Your farm business is constantly evolving, with new information flowing in all the time. Isn’t it time to use a tool that is as dynamic as your business?

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“Financial analysis” can be associated with a wide range of reports, terms, and metrics: income statement, P&L, break-even analysis, cash position, or net profit to name a few. While these are important indicators of your farm’s financial health, the best business decisions are supported by the right slice of data at the right time, analyzed in the right way.

Take, for example, a decision related to your land costs. Imagine that you rent two fields at $200/acre, and both leases are up for negotiation. You need to decide whether it’s worth renewing the lease on either or both of these fields.

How Much Value Does Each Field Contribute to Your Bottom Line?

field financial return

There are many approaches to this decision. As a start, financial data will only help if (1) split out by field, and (2) put on equal footing by showing per-acre values. One common approach is to view the net profit of each field.

At first glance, you might conclude that each acre on Field A adds negative value to your bottom line. But baked into this number are overhead costs like office rent that are incurred at the enterprise level, and are typically converted into a per-acre equivalent and spread uniformly across all fields. Regardless of whether or not you renew the lease on Field A, no matter what you do on the field, office rent will remain the same. There are certainly enterprise-level decisions where these costs are important to consider, but they can often lead to the wrong conclusion when making field-level decisions. To see why, let’s take another approach.

Focusing on Contribution

Here, we’ve taken the same data and isolated only those costs that directly result from each respective field’s operations. Subtracting these field-specific costs from the field-specific revenue gets you to a metric called contribution margin, or contribution for short.

field contribution financial return

Taking this approach, it’s clear that both fields actually contribute positive value to your farm’s bottom line. Every acre on Field A contributes $54 to your bottom line, which means your enterprise as a whole has more profit to help cover overhead like office rent.

The Drivers of Contribution

While it might be intuitively clear that both fields’ leases should be renewed, there remains the open question as to why Field B contributes so much more value-per-acre than Field A. Imagine if the underlying cost drivers were captured and organized in such a way that you could “double-click” on them and identify what was contributing to this outcome.

When costs are captured at this granularity, it’s easy to compare two fields and identify the cause for lower contribution: on average, every acre on Field A incurs twice as much in equipment costs than Field B. This is where an activity-based approach to financials becomes very powerful: when equipment costs are based on your operations – like the machine hours recorded when harvesting the field – they reflect the realities of producing a crop on an oddly shaped field vs a square one. This shows with data something that might be obvious by looking at the field shape, but hard to quantify.

In the past, we’ve quantified the impact of field shapes on your operational efficiency. With the approach outlined above, you can estimate the impact on your financial efficiency as well. Focusing on a metric like contribution lets you understand the value each field brings to your bottom line and understanding the drivers of contribution helps you fine-tune your business. For example, the increase in equipment costs can help you negotiate a lower rent for an oddly shaped field when you discuss the terms of your lease renewal.

Farm Management Software Does the Heavy Lifting For You

The usefulness of this analysis depends heavily on connecting financial numbers to operational activity. It’s also what makes it very hard to do and keep up-to-date manually. Moreover, different decisions will lead to different paths of analysis. You may want to view groups of fields, by crop, or by different time periods.
This is what farm management software can automate: it can keep a flexible view of your financials up-to-date so that you have the latest data surfaced in a way that makes it easy to act on the conclusion. Learn about how Granular’s Farm Management Software can help you get the right slice of the data, analyzed in the right way so that you can become a more efficient, profitable farm.

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How a Potato Grower Found 11% More Profit Using Granular

Learn how Granular helped a real farm discover that their variety choice was costing them $800 per acre

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September 11, 2017

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For years, Wall Street traders have used sophisticated models to measure market risk. They’re buying and selling based on this data, and billions are on the line – they’re confident in the math behind these models. The USDA uses similar models to price insurance. Can the same techniques be used to help determine your chance of a profitable season?

Since these tools aren’t widely used by laypeople yet, there isn’t a lot of public data on how well these models perform for commodity crops. In the post, The Chances of Sub-$3 Corn (And How to Reduce Them), we described how these models work in theory; in this post we’ll examine how well they can actually predict the future.

To help you understand how all this works, let’s start with a poker analogy. If someone told you the chance of drawing a three-of-a-kind was about 2%, how would you verify that? You could play thousands of hands with your friends, counting the times a three-of-a-kind was drawn, and you’d get a number close to 2%. Sounds easy! It turns out we can calculate the odds of $4 corn in much the same way: for each day of market data, we make predictions on the final price of corn and compare that to the actual final price.

Unfortunately, doing this isn’t as easy as playing a night of poker. With poker, the deck never changes. There’s one fundamental difference with crop prices: since the price of corn changes every day, the odds of $4 corn change with it. To deal with this, we’ll change our focus from a specific price to a specific risk level: in other words, we’ll answer the question, “when our model says the chances of something is 10%, how often does that actually happen?”. The chart below can help you visualize how these predictions look over time.

Figure 1 – Chart showing how futures prices and our price risk model evolves over time. We plot the daily CBOT future price, a reference line showing the final price of corn in December, and the daily calculation of the “10% Risk Level”. Over the long term, we expect the final price to be above the “Predicted 10% Risk Level” 10% of the time.

The blue line – the “Predicted 10% Risk” – shows one of our price predictions over time. If the final price is above that range close to 10% of the time, we’re getting the outcome we predicted. It’s like we’re drawing as many three-of-a-kinds as we expected we’d get.

But this chart shows us only one year of predictions. It’s like trying to guess our odds from a few hands of poker – we might not draw a single three-of-a-kind and think our odds are 0%. We need to validate this over many years. Over the long term, if the final price is above the 10% risk line close to 10% of the time, this suggests the model is pretty accurate.

We ran the same analysis for every corn future from 2001 to 2014 – a full 14 years of trading data. Just like we did for the 10% risk level, we assessed our accuracy for other risk levels, too. How often were prices above our predicted 5% risk level? 6.3% of the time. What about our predicted 20% risk level? Prices ended up above it 20.2% of the time. How well did the model fare for corn across all years of data? Surprisingly well. We summarize the accuracy of our model in Figure 2.

Predicted Risk Level Measured Outcome
5% 6.3%
10% 11.3%
20% 20.2%
80% 84.3%
95% 97.3%
99% 99.7%
Figure 2 – Summary of model accuracy for corn futures from 2001 to 2014.

The folks over at Farmdoc have turned this model into a tool that answers our original question: what are the odds you’ll have a profitable season? Enter a price and you’ll see the chances that corn will end below it. If you can assess your chances of a profit, you can make more informed decisions on crop insurance, hedging, and other mechanisms to limit risk. Learn the 3 Practical Farm Risk Management Strategies from our previous blog.

Use these tools to make more informed risk management decisions – plan your farm like a trader would.

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With another historically tough year ahead for farmers, it is worth spending some time looking at one of the most important financial decisions farms will make for 2017: which crops to grow.

A lot of factors go into this decision: crop rotations, landowner agreements, and in particular, financial projections. In a previous post, we looked at how profitability has varied for corn and soybeans in the past…in any given year the difference in profitability is often $50/acre or more. In other words: choosing your crops is important! However, it isn’t easy…deciding on crops for 2017 means making assumptions about price and yield, and a few bad assumptions can completely wreck a budget. In this post we show how to run a simple sensitivity analysis to illustrate how you can figure out how to get a handle on how “sure” you can be of making the right choice.

The Easy Part: Expenses

Estimating your costs (even down to the field level) is relatively straightforward if you are using modern farm management software. There is always some uncertainty in how much herbicide or fungicide may be needed, but these effects are small compared to our next topic.

The Hard Part: Revenue

The real uncertainty in planning comes from price and yield assumptions (i.e. revenue!) for the upcoming year. While nobody knows exactly what prices and yields will be next November, the best farmers know how to play the odds: insert your favorite poker or baseball reference here.
Price: there is obviously a lot of uncertainty in crop prices, and trying to predict them often involves trying to outguess the market..something we don’t advise! However, there are two things to keep in mind when planning for the next year:

1. The futures/options markets provide tools to estimate price risk. The value here is similar to knowing that the odds of getting a full house in poker is 2.6%. With those odds, it would be crazy to count on getting dealt a full house; similarly, right now it would be crazy to count on $5/bu corn.
2. Prices of crops are strongly correlated (e.g. when corn prices go up, soybeans usually do too), which means that if you are careful, picking the most profitable crop is actually quite a bit easier than estimating the final price of any given crop. More on this later in the post.

Yield: the story is very similar to price: there is a lot of uncertainty here! The upshot is:

1. Your historical yield data can give you a lot of information about the odds of various yield scenarios, and
2. The yields of various crops are correlated to each other in a way that is very similar to price.

Putting It All Together

If you have a good handle on all of the above, making that critical decision on what crops to plant (and where!) can be be surprisingly clear. For example, it is easy (and true!) to say that even with today’s prices corn will be more profitable than beans if corn yields are really high and bean yields are low. However, that is a pretty unlikely scenario. How unlikely? That can be understood with the sensitivity analysis shown below in Figure 1, where you can see that soybeans beat corn in every single historical year given the current cost assumptions. Of course, your yield and cost structures will be different than the Illinois university budget, so it’s important to run these numbers on your own.

Granular_budget_assumptions_yield_sensitivity

Figure 1. Sensitivity analysis showing the relative profitability advantage of corn over soybeans as a function of yield. Costs are taken from the University of Illinois 2017 crop budget, and we assume prices of $3.86/bu for corn and $9.94/bu for soybeans. We have overlaid historical trend-adjusted state average yields to illustrate how corn and soybean yields are correlated. For example, from the historical yield data, we can see that it is unlikely to have a year of 200 bu/acre corn and soybean yields less than 50 bu/acre.

Now what the effect of uncertainty in crop prices? While this uncertainty can be estimated via analyzing options prices, here we’ll use historical crop prices in our sensitivity analysis. The results are shown below in Figure 2. You can see that only in 3 years (2011, 2012, and 2013, all years of extremely high prices) did marketing year average prices end up in a regime where corn would be more profitable than soybeans given our current costs and yields.

Granular_budget_assumptions_price_sensitivity

Figure 2. Sensitivity analysis showing the relative profitability advantage of corn over soybeans as a function of price. Costs are the same as Figure 1, and we assume yields of 180 bu/acre for corn and 55 bu/acre for soybeans. We have overlaid historical inflation-adjusted state average prices to illustrate how corn and soybean prices are correlated. For example, from the historical price data, we can see that it is unlikely to have a year of $5.00/bu corn and soybean prices less than $10.00/bu.

What does this all mean? If your cost and yield structure is similar to the University of Illinois budget, the answer is clear: history suggest that it is very unlikely that corn will be more profitable than beans for you this year. Keep in mind, though, that basis can vary a lot from region to region, and every field has its own cost structure and yield expectations. Because of this, you should make sure to run your own numbers…it could easily mean $50/acre to you!

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AcreValue teams up with WestWater to bring transparency to water rights market

Our mission at AcreValue is to help the agriculture industry understand and analyze farm values. In the West, farm values cannot be analyzed without considering access to water. As a first step towards addressing this important variable, we’ve teamed up with WestWater Research to bring information about water rights into our platform. AcreValue users will have exclusive access to WestWater’s Waterlitix data, the largest and most comprehensive source of water right sale and lease information in the United States.

Our WestWater partner, Clay Landry, provides some insight into the market:

The Growing Value of Water

As the Nation’s largest water user, farmers and ranchers have always understood the importance of water. The US Department of Agriculture estimates that agriculture accounts for nearly 80% of the nation’s water use and over 90% in many western states. Now more than ever, other sectors of the economy are starting to realize just how important water is to their financial future – from housing development to the power sector to Wall Street portfolios. No sector seems to be immune.

Water Rights Market

Throughout the West, water rights determine how water is allocated when supplies are scarce. Nearly every farm and ranch in the western US that irrigates has some type of water right, contract or ownership interest in water. In most cases, these rights were established under an antiquated legal concept known as the prior appropriation doctrine, which gave the first person to divert water for a beneficial use a property interest in continued use of that water. Each western state has developed its own laws and regulations governing water rights that are unique to local issues and customs. As a result, water right systems across the West are notoriously arcane with a complicated set of rules.

Markets for water rights have emerged over the last thirty years to meet growing demands and solidify existing water supplies across the arid western United States. These markets have developed in response to traditional large scale water users seeking out alternatives to constructing costly new infrastructure projects. In 2015, more than $800 million and nearly 2.0 million acre-feet of water rights were traded through purchases and leases – the agricultural sector represented nearly 80% of the total supply of volume traded.

Water rights markets are highly regionalized and typically are defined by surface and groundwater hydrologic boundaries. Currently, there are over 25 established and emerging regional markets across the West. The most active of these include California’s Central Valley, the northern front range of Colorado and the Pacific Northwest.

The Value of Water

The value of water rights is highly regional and varies significantly. Several factors influence the value of water rights including location, current use, water right reliability, legal complexity of the right, and buyer type among others. In Colorado, for example, CBT water shares, which have a streamlined and established regulatory process, trade at prices 3-4x higher than other water rights in the same area that are subject to more complex regulatory reviews. In California, during the recent drought, agricultural buyers drove prices to all-time highs as they outbid cities for the first time to secure water for recently planted tree nut orchards. The development and growth in water market activity around the West has driven the emergence of sales of water rights separate and distinct from land.

Opportunities and Challenges for Water Right Owners

Legal and regulatory disputes over water rights will increase as supplies are stressed by drought and growing demand. On the flip side, the development of markets for water are creating opportunities for water right owners to supplement farm income through water sales and leases.

The following are a few sensible steps that water right owners should take if they are concerned about legal challenges or are interested in exploring water marketing opportunities.

1. Know Your Water Rights – Water rights are like any other asset and require managing. Your rights will define how much water you’re entitled to, as well as, when and where it can be used. Water rights can take a variety of forms including the right to divert directly from a river or groundwater source. Properties within an irrigation district or ditch company may hold a contract or share certificate that entitles them to a portion of the water right held by the district or company. There may be additional covenants and restrictions as well as assessments if your water is supplied through a district or ditch company.

2. Maintain Good Records – Make sure you have copies of your water rights. This includes contracts or share certificates if you’re in a district or ditch company. Most water rights have an administrative record that is maintained by the state agency responsible for regulating water. The administrative record should date back to the year that your right was established, which in some cases may be as far back as the mid 1800s. Additionally, maintaining good water use records will help quantify and protect your water rights. This becomes particularly important if you anticipate a sale of your farm property. Most informed buyers will want to confirm that the water rights have been used and that there is no risk of forfeiture due to lack of use.

3. Map Your Water Rights – Mapping your water rights is important to first, confirm you own the water right, and second, to confirm that your current irrigation practices match up with the authorized place of use under your water rights. Comparing landownership parcel maps with water right maps will help confirm ownership. Second, farming practices or field alignment often change over time resulting in water use outside of the authorized place of use. This may not be a major issue and can usually be corrected through a regulatory process with your state water management agency. You may also want to consider mapping any pipelines or ditches that you rely upon for water delivery to your property especially if your headgate or delivery system is located on a neighbor’s property. You will want to confirm and verify easements for these structures.
In conclusion, to take advantage of opportunities in the water market and effectively market your rights, make sure you have the ownership documentation in place, your water use history recorded, and maps verified. And stay tuned in the coming months for water market data to become available on acrevalue.com!

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Build a competitive advantage in a modernizing farmland market with Granular’s FMS and AcreValue

Three years ago, Mike and I set out to build farm management software (FMS) to help farms make better business decisions by making better use of their farm data. We realized early on that while farms were using Granular FMS to optimize their existing operations, they also wanted tools to help them grow their farms.
Helping Farms Grow Bigger with AcreValue
Our customer had to make a big land related decisions. These are just a few examples of the hard questions farms had to answer:

What rent should I pay for my existing land?
Do I have the right profit margin and management controls to expand?
If so, what ground can I add to my operation and at what price?
How do I market myself effectively to prospective new landlords and capital partners?

That’s why Granular acquired AcreValue and launched it as our second product in January 2016. Patterned after Zillow and similar tools in residential real estate, AcreValue aggregates real estate and agronomic data on every parcel of farmland in the U.S., offers valuation estimates and publishes comparable sales.
Farms commonly use AcreValue to foster relationships with their landowners. When they are looking to rent or purchase land, they come to the table with professional AcreValue reports on the value of the land, soil ratings, crop history, sales data and more. This puts them in a much stronger position to market themselves to a new landowner or a capital partner and have a successful negotiation.
Launching New and Powerful AcreValue Features
AcreValue has taken off in the last year, attracting not just farmers, but also landowners, brokers, appraisers and bankers. AcreValue’s 30K+ registered accounts visit the site over 100K times each month and usage has been doubling every six months.

Over the next few months we will be adding valuation estimates in more states, water rights data, custom mapping tools, and sale listings. We will also be launching a paid version of AcreValue, called AcreValue PRO, with powerful search tools that allow users to prospect for land nationwide using screening criteria like owner, valuation, size, soil quality and more. With both its FMS and AcreValue products, Granular is working to give its farm customers a competitive advantage in the modernizing land market.
Integrating AcreValue with Granular FMS
The farmland real estate market and the farming market are both professionalizing and consolidating. Both markets are becoming less local, less relationship-driven and more business-oriented. We believe that the relationship between landowner and farm operator is going to become more professional, more transparent and more data-driven over time.
Granular FMS already helps farms share production data with landlords, calculate share rent, and analyze rental rates relative to yield history. Using our relationships with large institutional land investors, Granular has brokered many introductions that have helped our FMS customers connect with institutional capital partners interested in their geographic area. But this is just the beginning.
In the coming months, we will launch advanced AcreValue features that are only available to farms using Granular FMS. These features will allow Granular farms to market themselves on a confidential and pre-qualified basis to landlords and get early notification on land coming up for sale.
We believe Granular FMS and AcreValue together give our customers the right tools to manage better (profit per acre) and bigger (more acres) farms.

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