PlanAI overview

Learn how Sustainability Insights PlanAI can help you create data-driven sustainability strategies and how to use it.

Video Tutorial

Overview

The PlanAI feature enables users to create data-driven, multi-year strategies to achieve their sustainability goals in cost effective ways. By using Regrow’s AI driven insights to optimize for both projected emissions reductions and program costs, PlanAI helps users to prioritize investments into on-the-ground MRV (Monitoring, Reporting, and Verification) programs.

The PlanAI feature is particularly useful for users who need to:

• Forecast the carbon impacts of multiyear, forward looking investment scenarios 
• Prioritize investments by choosing areas within their supply chain with the highest potential to reduce and remove emissions.
• Secure regen ag budgets by showing realistic financial projections and ROI across investment scenarios. 

What is a Plan?

A plan is a recommended multiyear pathway that is optimized to meet your climate targets, based on your supplier data. Each Plan consists of a collection of proposed on-the-ground carbon intervention MRV programs.

Each individual MRV program consists of a subregion, a specific commodity grown in that subregion, and a practice change (or set of practice changes). For each MRV program, Regrow forecasts the annual change in emissions, the annual cost for that project, and the increase in area adopting regenerative agriculture practices in that region.

What is the user journey in PlanAI?

When users enter the PlanAI feature, they have two options: generate a Regrow recommended plan, or create their custom own plan using user-inputted assumptions and parameters. 

Why does Regrow Provide a Recommended Plan?

For users in early stages of their regenerative agriculture journey, we’ve found that they often benefit from a plan that offers assumptions grounded in Regrow’s database and historical experience with carbon programs. Furthermore, there is no requirement for the user to input any data to generate the Regrow recommended plan (beyond choosing their supply regions at the Configure stage), meaning that users can view Regrow’s recommended plan instantly, and have a foundation to iterate on.

What assumptions are in Regrow’s Recommended Plan? 

To calculate the projected area enrolled in a program over time:

• First we look at the total acres that are growing the crop(s) of interest in each configured supply shed. For example, let’s assume that you’ve drawn a supply shed of 1,000,000 acres, with 600,000 acres of corn, your crop of interest. 
• Of those 600,000 acres of corn, let’s assume that 100,000 do not have any abatement potential according to Regrow’s emissions model (this could be for a number of reasons, including that they have already adopted a number of regenerative practices, or that they are in a soil type that isn’t conducive to soil-organic carbon sequestration). 
• For year 1 of your program, we then assume that half of one percent (.5%) of the 500,000 acres of corn that have a sizeable abatement potential will be the starting size of your program, as we typically see that companies will pursue pilot projects during the first year of implementation and those tend to be smaller in size. 
• In this example, 2,500 acres will be part of the program in the first year.
• From there, Regrow applies a growth rate formula based on our internal data from historical programs that we have observed., as can be seen below for this hypothetical program:
  • Year 1: 2,500 acres in the program
  • Year 2: 7,500 acres in the program (3x growth vs year 1)
  • Year 3: 15,000 acres in the program (2x growth vs year 2)
  • Year 4: 30,000 acres in the program (2x growth vs year 3)
  • Year 5: 45,000 acres in the program (1.5x growth vs year 4)
• All these rates are editable to project a more conservative or a more aggressive path to regenerative outcomes.
• This process is replicated across all of your supply sheds

• Costs are calculated based on an assumed per-acre fee for grower incentive payments and an assumed project implementation cost per acre. These assumed costs in Regrow’s recommended plan, which are editable by the user, are informed by both public databases and Regrow’s internal data. 
• Plan ‘ROI’ is calculated by comparing the estimated cost per ton (an aggregated measure of grower incentive payments and project development costs) to an internal price of carbon (IPC), which is used as a proxy for the carbon benefit.
  • It is important to understand that PlanAI uses ‘intervention’ accounting to estimate the future carbon outcomes. This means that PlanAI attributes the entire estimated carbon benefit of a crop to the forecasted abatement per acre that a user sees. If a user instead chooses to use ‘inventory’ accounting, it is possible that the estimates in PlanAI will need to be slightly adjusted. 

In PlanAI, users will see projects recommended according to their carbon abatement potential per acre. Abatement potential per acre is calculated as the forecasted difference between the business as usual scenario, and the intervention scenario on each acre in a user’s supply shed. 

Intervention Scenario:

• For each combination of “practice change x crop x region” available in each of your supply sheds, Regrow estimates the emissions produced for each acre of your focus crops.

Business as Usual:

• For the same combination of crop x region, Regrow estimates the emissions produced per acre where all the fields in the region continue with currently observed agricultural practices. 

If a user wants to build their own Plan, what are their customization options? 

Users can customize several parameters to create a more tailored plan based on their specific goals and circumstances. These options include:

1. Commodity, Subregion, and Intervention Selection:
   • Regrow Generated Recommendation: PlanAI uses all crops and regions, as well as all available modeled interventions. 
   • Customization: Users can choose to prioritize a crop, region, or intervention type as the guiding parameter for prioritization.  
2. Adoption Rates:
   • Regrow Generated Recommendation: Regrow will automatically increase the area of each project in the recommended plan year over year (see section on growth assumptions above for more details). 
   • Customization: Users can adjust growth rates to reflect more aggressive or conservative goals. They can do this uniformly across all MRV projects, or for any specific project.
3. Costs + Benefits:
   • Regrow Generated Recommendation: Regrow pre-fills a cost per acre for grower payments and a cost per acre for project implementation (marketing, training, on-farm support), and assumes a marginal annual increase in costs. Regrow also assumes a benchmark, which is generated by using data on internal prices of carbon, and carbon offset market prices to calculate ROI vs investing in those alternatives. Data for incentive cost per acre for each intervention are sourced from here and here. Data for benchmarks are sourced from here and here.
   • Customization: Users can adjust the grower payment and project development cost per acre to reflect more aggressive or conservative goals. Also, they can customize their internal price of carbon, or carbon offset alternative price. This can be done across all MRV projects, or for each specific MRV project. 
4. Volume-weighted Abatement Potential:

   • PlanAI provides an option for ranking based on volume-capped abatement potential. This allows users to:

     • Prioritize regions with the highest potential for emissions reductions, weighted by sourcing volume.

     • Compare abatement opportunities across supply sheds based on both emissions intensity and total sourced volume.

     • Choose between ranking purely by abatement potential or factoring in volume constraints, offering more precise decision-making in regenerative agriculture investments.

     This enhancement ensures that customers not only identify high-emitting supply sheds but also target investments where they can drive the most impact, aligning sustainability initiatives with sourcing priorities. See here for the methodology used to optimize your plan for commodity volumes sourced per subregion and instructions on how to set that up.