Automation is an investment in your business that isn’t always easy to make when considering the additional costs involved; however, streamlining cultivation practices and automating certain manual tasks can provide many benefits to cannabis growers. Total Grow Control CEO Derek Oxford shares how automation, and the information that can be gathered from it, can help cultivators improve their products, as well as their profits.

1. What problems can automated processes help you avoid?
Automation reduces human error by taking over the daily mundane tasks that can easily be forgotten or missed, and tasks that can be calculated or measured incorrectly, allowing the grower to focus more on the plant and the operations.
2. What size facility should consider automation?
Once you begin to cultivate more than 20 plants, an automation strategy begins to make sense.
3. How can automation affect my bottom line?
Efficiency, efficiency, efficiency. Completing production tasks correctly and consistently with precision always reduces waste of materials and labor, which, if done well, will significantly impact your bottom line.
4. What processes can be automated?

There are many. Lighting control (up to five wavelengths); recipe control for all systems during the plant’s entire life cycle; CO2; temperature; humidity controls; nutrient/pH systems that provide automatic delivery; nutrient inventory management; and data logging of critical parameters (pH, temperature, CO2, water, humidity, etc.).
5. How can automation help me collect data about my grow?
Centralized automated systems collect multiple data points on every aspect of the grow cycle that can be stored, retrieved and analyzed. This information can be used to find patterns or paths to better yield and reduction of cost. You can’t improve something that you can’t measure.
The interpretation and the use of data in future production cycles is one of the most important things after taking the first steps of automation.
This should be a slow, thought-out and methodical process, identifying one data point at a time. And after identifying the data point, making decisions about how the data will be used, and generating a plan about how to move forward once issues are discovered. Simply gathering data is not enough. Cultivators must use that data from their automated processes to make well-informed improvements.
For example, a water meter can be used to determine how much water is being fed to the plants. If the results show that there is too much, or too little, that can be easily corrected during the grow. After yield is calculated, that data can be compared against the water meter data, and the cultivator can tailor the next crop to duplicate that process for future harvests.