At the latest edition of Indoor Ag-Con, Jeremy Shechter focused his presentation on how data collection should work as an operational tool in commercial cannabis cultivation.

Jeremy, founder of Open Source Horticulture, opened by challenging a common assumption within the cultivation community. “We’re not as good as we think we are,” he said, pointing to the gap between perceived performance and what can actually be demonstrated. Without data, he argued, operators tend to rely on preconceptions rather than evidence.

Genetics, Jeremy explains, cannot be evaluated in isolation. “Genetics don’t just happen in a vacuum,” he said. In other words, data collection becomes the only reliable way to understand how genetics behaves in different rooms, facilities and operating conditions.

Profit figures alone, he adds, rarely tell the whole story. Teams may be able to articulate a number, but struggle to explain how that result was achieved. “Show me the dashboard,” Jeremy said, describing situations where performance claims fall apart because historical data is not available or cannot be accessed. In those cases, memory fills the void, even though, as he said, “our memory is very bad.”

© Eelkje Pulley | MMJDaily.com

The importance of setting goals
Jeremy envisioned data as a mechanism that allows teams to move toward defined goals. “One of the most important drivers for people is moving toward a goal,” he said, and progress is only seen when it’s measured consistently. Without solid data, goals remain abstract.

A recurring point in the presentation was the need for moderation. To illustrate this, he quoted Leonardo Da Vinci: “Simplicity is the ultimate sophistication,” Jeremy said, describing the tendency to overcomplicate data systems. He argued that not all data is worth collecting, and that excessive measurement often creates noise rather than insight.

Deciding what data matters, Jeremy insists, should not be left to chance. “Data is not created equal,” he said, “teams can easily spend time collecting information that doesn’t impact results. KPI selection should be driven by leadership and tied directly to business performance, then clearly communicated to crop managers.”

Entrepreneurship then becomes the key. “If a data point doesn’t inform a decision, it shouldn’t be treated with the same rigor.” Jeremy used room pressure as an example, explaining that while deviations from a set point can indicate a problem, they don’t necessarily correspond to long-term performance tracking. In other words, trends are more important than isolated readings.

Data collection systems
Jeremy also discussed the structure of effective data collection systems. “It has to be top to bottom,” he said, describing the need to follow every step of the process from cultivation to packaging. “Those systems have to be custom built for each facility.” He again emphasized the importance of keeping it simple and easy. “If you want to keep doing something, keep calm,” Jeremy said. Adding steps to any process increases friction and reduces compliance, whether in cultivation or data entry.

Paper-based workflows were highlighted as a persistent problem. Jeremy described the operations involved in entering data and then transferring it to a computer, a process he noted is inefficient and error-prone. Fully digitized systems, using tablets or mobile devices, were presented as a basic requirement for reliable data access.

Towards the end of the session, Jeremy touched on how data influences decisions beyond crop metrics. He noted that some cultivars can produce high yields but perform poorly after drying, becoming brittle or difficult to handle. Without tracking these results, operators run the risk of optimizing for numbers that don’t translate into finished product performance.