📏 How Do You Measure Yield?

🌱 Your Last Harvests

Yield (lb/light) Strain (optional)

📈 Scenario Context

Number of Lights ?This scales the yield gap into total pounds so we can show you the dollar impact across your whole operation. Per room

Harvests per Year ?How many times per year do you actually harvest the same room? Used only to annualize the best-run scenario. Same room, per year

Flower Rooms ?Total flower rooms in your facility. Scales the dollar impact. If you only want to see one room, leave at 1. Total active rooms

Wholesale Price ?Your average net price per pound. Used to translate the consistency gap into dollars. Doesn't affect your consistency score. $/lb

Calculations run in your browser. The tool uses the population standard deviation of the entered harvests to calculate relative dispersion and does not make a calculation API request.

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Enter at least 4 harvests

Your relative-variation calculation, yield chart, and best-run scenario will appear here as you type.

Frequently Asked Questions

What exactly is "coefficient of variation"? ▼

This tool calculates CV as the population standard deviation of the entered harvests divided by their mean, expressed as a percentage. A CV of 10% means that standard deviation is 10% of the average; it does not guarantee every harvest lands within 10% of the average. Compare like with like because cultivar, room, measurement method, and sample size can change the result.

Why should I compare the same strain separately? ▼

Cultivars and phenotypes can have different output ranges, so mixing them can make the overall comparison less like-for-like. Entering strain names lets the tool show a separate descriptive CV when at least two entries share a name. That reduces one comparability problem, but it does not isolate process variation from room, plant-count, quality, timing, or measurement differences.

What does the best-run dollar scenario mean? ▼

It asks what gross revenue would look like if every future harvest matched the best result you entered. That is an optimistic counterfactual, not the measured cost of variation, a forecast, or profit. Added production, processing, sales, tax, quality, and feasibility constraints are not included.

How many harvests should I enter? ▼

Four is the tool minimum. Six to eight comparable harvests usually provide a more stable descriptive picture, but this is still a small sample. Keep meaningful outliers and annotate their context rather than removing them only because they change the score. The tool treats all entries equally.

Does this tool track my data? ▼

The calculations run in your browser, and the fields are saved in browser local storage so they can persist when you return. The tool does not make a calculation API request. Standard public-page usage analytics still apply as described in the privacy policy.

Why Yield Consistency Matters More Than Peak Performance

A best run is useful evidence, but it is not a promise about the next room or cycle. Relative variation helps describe how tightly a set of comparable harvests clusters around its average.

Coefficient of variation (CV) captures something average yield alone misses: standard deviation relative to the average. It is descriptive. It does not identify why runs differed or prove that the best observed result can be repeated on demand.

What Variation Changes

When saleable output varies against a similar cost base, revenue predictability changes and a lower-output harvest can carry a higher cost per pound. The difference between the average and best run is still not automatically recoverable. It may include cultivar mix, room differences, quality tradeoffs, unusual events, or measurement changes.

Coefficient of Variation	Rating	What It Means
Under 8%	Tighter band	Lower relative dispersion in the entered sample. It does not prove the process is controlled.
8-15%	Moderate band	Moderate relative dispersion. Check whether the runs are truly comparable.
15-25%	Wider band	Wider relative dispersion. Review cultivar, room, timing, and exceptional events.
25% or more	High Variation	High relative dispersion in this sample. Investigate the records before assigning a cause.

These bands are Growgoyle planning heuristics, not published cannabis-industry standards. Small samples can move sharply when one harvest changes.

What Drives Yield Variation

Several recorded differences may be worth reviewing when comparable harvests vary. None of these categories is automatically the cause, and overlapping changes can weaken a conclusion:

Environment. Review temperature, humidity, VPD, light-cycle timing, canopy temperature, and unusual incidents across the same crop windows. Confirm sensor placement and data coverage before interpreting a difference.

Genetics and starting material. Cultivar, phenotype, mother source, clone age, rooting quality, plant count, and starting uniformity can change the comparison before the flower room does.

Root-zone and irrigation records. Compare feed, runoff, substrate readings, irrigation timing, equipment events, and recorded interventions. A difference is evidence to inspect, not proof of a single mechanism.

Execution and crop events. Missed work, schedule changes, maintenance, pest pressure, disease response, labor constraints, and harvest or drying differences can all affect how comparable the finished numbers really are.

From Variation to Consistency

Investigating variation starts with a comparable record. Keep batch-level data for environment, root-zone and irrigation readings, work, maintenance, observations, crop events, harvest, quality, and final saleable yield.

A comparison can organize recorded differences between two runs and show which evidence supports or limits a possible contributor. It cannot prove that one difference caused the outcome, especially when several changes overlap or data is missing.

Use the Grow Efficiency Scorecard to compare four operating ratios with transparent reference bands, or learn more about how data-driven yield optimization works in practice.