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.
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.
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.
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.
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.
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.