As technology continues to transform cultivation techniques across both the cannabis and broader agriculture markets, one has to ask, why are all these new techniques required now? Is this just technology looking for a problem to solve? While skepticism about any new technique is healthy, in this case, all the hype behind data-driven cultivation is very real. As with most industries around the globe, data-driven approaches are transforming how we approach what was once considered a mature industry.
This is because data-driven industries are capable of identifying problems and solutions faster than any other method, as well as enabling said industries to react to these issues in real-time. The result is an iterative process of constant refinement and improvement, one that is not possible without a steady stream of real-time data. With cannabis and agriculture, this ability to understand and react in real-time generates enormous and immediate benefits to the cultivators that implement such techniques.
We define “data-driven” as any cultivation that is leveraging detailed information on the microclimates within a facility directly from nearby sensors, which is then fed into some type of management system. This management system then enables the cultivator to derive insight on how to manage the facility from the data generated, as well as take action based on those insights. With that definition in mind, let’s take a look at the top five reasons the future of cultivation will be driven by data.
Reason #1 – Rise of Wireless Sensor Networks
One technology rapidly growing in use across multiple industries is now making its way into cannabis – the use of wireless sensor networks to gather and deliver the data cultivators need to mange their cultivation. While sensors have been used in cannabis and agriculture for many years, this new breed of wireless sensor network is very different from what’s come before. Some of the characteristics of this new breed of agtech sensor include:
- High-Density deployments– the scalability and density of these new sensor networks are critical to today’s much larger cultivations, as they need to provide thousands of data points to showcase the microclimates that can exist in as little as a single square foot. New technologies can scale to millions of square feet while delivering the granular data necessary to truly give a real-world view of what’s happening in the facility.
- Sensor reliability– Sensor failure can really but a crimp in a data-driven cultivation. However, most high-density wireless deployments have largely alleviated this issue.
- Low-power– new proprietary wireless protocols are setting new milestones in low-power usage, far exceeding even industry standards like Z-Wave, Zigbee, and Bluetooth Low Energy.
- Richness of the data provided– unlike previous generations of sensors, which could often only report on one specific type of data, today’s sensors are capable of delivering multiple fronts, including humidity, air pressure, moisture, soil Ph, and much more.
- Programmability – Just as importantly, as new points of measurement become critical, most of these sensors can be easily updated remotely as software improves or new algorithms become available.
Reason #2 – Maintaining State-by-State Compliance in the U.S.
We’re all hoping that the federal government gets its act together and sees the light regarding the cannabis market. I think we also all know that’s not going to happen for a number of years at a minimum. But in the meantime, as the U.S. industry is still in its infancy, cultivators need to maintain compliance with a complex, dynamic and constantly changing set of standards, many times across multiple states. In California for example, there are whole counties that have barred cannabis cultivation, but incorporated entities within that country have allowed it. And that’s just knowing whether you can participate in this industry or not.
By employing a data-driven model throughout their facility’s infrastructure, cultivators can ascertain their compliance status immediately. Or, just as importantly, find out when something is wrong and immediately make a fix. Water use, fertilizer use, type of nutrients distributed, IPM strategy, Seed-to-Sale procedures, and power consumption all play into maintaining compliance. A data-driven model enables cultivators to set and monitor compliant parameters, but also react quickly when and if those parameters change. This is particularly important for medical cannabis, as a consistent product with specific properties is required.
Reason #3 – Demand for Greater Yields
If there were ever a common goal among cannabis cultivators, near the top would be generating the most flower possible from each given plant. In order to achieve this goal, that means plants need to be as healthy as possible, receiving the correct lighting, nutrients, environmental conditions, and fertigation possible. By implementing a data-driven model, cultivators get real-time access to the overall health of their crop, enabling them to immediately take action when something seems amiss. But just as importantly, by evaluating data collected over time, cultivators have the capacity to refine their techniques in ways never before possible. Best practices for multiple strains are much more easily identified and have become a critical tool for any cultivator that wants to get the most out of their efforts. This model is rapidly becoming a “must have” in order for cultivators to compete effectively in a rapidly expanding market.
Reason #4 – The advent of Automation in cannabis cultivation
Although, automation has been a part of the cannabis industry for multiple years now, its importance increases exponentially within a data-driven cultivation model. For all of the insights garnered from a data-driven cultivation, they are worthless without the means to easily implement strategies based on those insights. Automation and control systems such as those from Argus, TGC, and Priva, serve as the engines that enforce the new parameters demanded by data-driven insights.
When something needs to be adjusted, automation systems enable cultivators to quickly and easily react in real-time and make wholesale changes to their infrastructure, sometimes even making these effects remotely. More than just solving near-term problems, automation is a valuable tool in effecting those best practices that are gathered over time.
Reason #5 – Need for ROI from cultivation infrastructure
To some extent, it could be argued that the previous three reasons also contribute to a crop’s Return-on-Investment (ROI). This is true, but then, so does any incremental improvement to a business. For the purposes of this article, we’re looking at the hard ROI of the capital infrastructure in which all cultivators must invest; lighting, benches, fans, IPM, irrigation … the list goes on.
Prior to data-driven cultivation, ascertaining the efficacy of an infrastructure choice could be just as much about gut feeling as it was about hard evidence. With a data-driven model in place, cultivators will know precisely what kind of value they are getting from the infrastructure choices they’ve made. And in the hyper-competitive market of cannabis, that knowledge can make or break the ROI on your crop.
Next Steps for the Industry
Taken together, these five reasons make a strong case for an industry where data-driven cultivation becomes the norm rather than a technological goal to be achieved. From the advancements in tech, so the surge in cannabis-related startups focused on this market, there is clear demand for this approach. From the cultivator’s perspective, implementing the many technologies involved in creating a true data-driven cultivation can be intimidating to say the least. But given the increasing pressures faced by the entire industry in additional competition, shrinking profit margins, environmental impact, and maintaining compliance, data-driven cultivation provides the best possible option to competing effectively.