Annual Averages or Reporting Averages

You now have the option to choose between calculation methodologies. But what do they mean, and when should you use each?

Annual Averages: The Complete Picture

What are they: Actual SOC levels measured for each individual year of your assessment.

Think of them like: Your farm’s annual rainfall records - some years higher, some lower, giving you the complete weather story.

Show real year-to-year variations

Reveal the complete data story

Useful for understanding what actually happened each year

Can be more volatile due to weather, seasonal effects

When to use Annual Averages:

Understanding which specific years had best/worst performance

Analyzing impact of management changes in specific years

Technical discussions with agronomists or soil scientists

Detailed operational planning

Reporting Averages: The Clear Trend

What are they: Smoothed values using 3-year averaging to show underlying trends in your soil carbon.

Think of them like: A weather forecast showing long-term climate patterns rather than daily fluctuations.

Clear, stable trends that are easy to understand

Less affected by unusual weather years or one-off events

Better for strategic planning and communication

Used in official reports and carbon credit applications

Latest year is always provisional (uses annual data until future data is available)

When to use Reporting Averages:

Presenting to investors, board members, or stakeholders

Strategic planning and long-term goal setting

Marketing and public communications

Carbon credit reporting and verification

Regulatory compliance

Real-World Example

Here’s how the same farm data would look using both calculation types:

Annual Averages (Complete Picture)

2019: 850 tonnes SOC

2020: 820 tonnes SOC (drought year - natural dip)

2021: 880 tonnes SOC

2022: 910 tonnes SOC

Reporting Averages (Clear Trend)

2020: 850 tonnes SOC (smoothed using 2019, 2020, 2021)

2021: 870 tonnes SOC (smoothed using 2020, 2021, 2022)

2022: 910 tonnes SOC ⚠️ provisional - uses annual value

Key Insight: The reporting values clearly show an upward trend, while the annual values reveal that 2020 was an unusually challenging year. The most recent year (2022) is provisional because we need 2023 data to calculate the proper 3-year average.

Quick Reference: Which Values Should You Use?

Business Decisions & Communication

Use Reporting Averages

Designed to be stable and clear for strategic planning

Understanding What Happened

Use Annual Averages

Shows the complete story, including challenging years

Carbon Credit Programs

Use Reporting Averages

Specifically designed for regulatory and verification purposes

Q: Why are my annual averages more variable than my reporting averages?

Annual values show the real year-to-year changes, including impacts from weather, seasonal variations, and management changes. Reporting values smooth these out to show the underlying trend.

Q: Why does the latest year look the same in both annual and reporting averages?

The most recent year is “provisional” in reporting values because we need future data to calculate the 3-year average. Until next year’s data is available, the reporting value equals the annual value for that year.

Q: When will my latest year’s reporting value be finalized?

Once the following year’s data is processed, the previous year’s reporting value will be updated with the proper 3-year smoothed calculation.

Q: Which values should I use in my sustainability report?

Use reporting values. They provide a clearer picture of your long-term progress and are less likely to be misinterpreted by stakeholders.

Q: Do both values come from the same underlying data?

Yes, both come from the same satellite measurements of your property. The difference is in how they’re processed - annual values show raw yearly averages, while reporting values apply smoothing to reveal trends.

Q: Which values are more accurate?

Both are accurate for their intended purposes. Annual values accurately show what happened each year. Reporting values accurately show the overall trend by filtering out short-term variations.