As the Managing Editor of TechDecisions it’s my job to find the best ways to improve processes using technology so I can tell my audience about it. We often write about Internet of Things, Artificial Intelligence, and Data and Analytics. As a result, I’m always looking for ways different industries are utilizing future tech so I can bring that information to you. Today, I get to talk about the marijuana industry.
It’s a bit unconventional, I know. Perhaps even a little controversial. But the fact of the matter is that marijuana is one of the fastest growing market segments in the country. Just look at the revenue generated in Colorado alone. Thanks to the legalization of marijuana in a number of states, marijuana growing operations are becoming legitimate almost overnight. However, many of the top growers have been using grassroots techniques for years. The industry is ripe for some technological advancement, and there are some really cool things going on in marijuana grow facilities that can be applied in many manufacturing environments.
In the latest TD podcast I got to speak with Marco Hegyi, CEO of GrowLife, Inc. His company provides tools for grow operations, and has recently announced a new growing system that will introduce data, analytics, and automation into the grow cycle. First, though, a quick disclaimer:
“What we’ve announced is a complete growing system, and one of the attributes of this growing system that we’re testing out right now is the collection of data in the grow facilities,” says Hegyi. “That is not a product that is being sold today. It has been designed, it has provisional patents around it, and it’s being tested, but it hasn’t been delivered to market yet. So I can tell you what we’re working on and the vision for the utilization of this data, but, just to clarify, it’s not something that we’re providing today.”
Analytics, Automation, and Marijuana
While this future tech will remain in the future (for now), Hegyi has a long career in the technology sector. Hegyi served as Senior Director of Global Product Management/Search Marketing at Yahoo starting 2006. Prior to Yahoo, he was at Microsoft leading program management for Microsoft Windows and Office beta releases aimed at software developers from 2001 to 2006. Now he runs GrowLife and hopes to introduce new technology into an industry with massive potential.
“With our data, our intention is to help the cultivators see, as the product is growing, consistency in variances. So when you start seeing a drift away from how the plant was growing in the first cycle, then you would make adjustments, whether it be additional nutrients, different lighting ranges, there’s so many variables,” says Hegyi. In the case of GrowLife, they are tracking for 27 different variables as the plant grows.
Anyone with a garden understands how difficult it can be to grow plants and crops. When you walk into a grow operation you’ll see thermostats and hydrometers tracking performance of growth. These sensors are already in use. GrowLife also utilizes cameras with built in sensors. In tandem, these sensors track the variables around the grow operation – lighting, heat, water, soil, air quality, and so on. That’s the data.
The analytics come with processing that data to determine the best instance of different variables. When the yield comes through, the cultivators will understand what batches are better than others. They can then go into the data, and analyze it to learn what variable levels lead to a better or worse crop yield. Moving forward, they can ensure that the levels are uniform in order to create the best yield, thanks to the information gleaned from the data. That’s business intelligence.
GrowLife takes it one step further, taking the data, analytics, and business intelligence and automating different processes to provide a less variable yield.
“The sooner you capture these alerts the sooner you can take action,” says Hegyi. “We see it as three phases. Phase one is to collect the data, which is what we’re doing now. The second phase is to build the AI to take action on that data – simply an alert of variances to a high-low. The third one is the one we’re most excited about, and that’s where the automation comes in.”
For example, the system will send an alert when temperature or humidity fall outside of the desired range. So while the cultivator is at home sleeping, there is something watching over the crops. The cultivator gets the alerts, makes some phone calls, determines there is a power outage, and gets the problem fixed before the crop is ruined.
Going further, the same automation system could determine the outage itself and turn on a backup system. It could also adjust lighting – traditionally a manual operation that involved chains and pulleys, the GrowLife system utilizes LEDs and measures variables in order to push in closer or pull away further from the crop.
The Education of Automation
The marijuana industry is one that is particularly sensitive to the quality of its product. Cultivators are given top dollar if they are able to provide above average marijuana, because customers will pay extra for quality products. It’s not unlike the food or drink industry – a quality steak is worth more than that in the discount rack, and a high-end whiskey is worth far more than its brand name counterpart.
It’s not just the marijuana industry that is wary of AI and automation. Many manufacturers are hesitant to introduce computer programs which could go awry into industries that have primarily relied upon the human touch. However, Hegyi thinks that it’s a lack of education about what automation really is that is the culprit.
“There is confusing terminology, in some cases over-reach and over-promising that’s being done by a lot of people. The way we look at the problem is that we don’t want to displace the talent used to grow high quality product,” says Hegyi.
Related: My TechDecisions Podcast – Episode 44, Marco Hegyi of GrowLife, Inc.
He uses the example of doctors. How do you get doctors to perform better diagnoses? You give them more information about the problem that a patient is having. While you wouldn’t trust AI to treat the patient (yet), you can trust AI and automation to gather and deliver the information needed to treat patients. So it goes on the manufacturing floor.
“That’s how we see the cultivators. You get the laborers less involved, and you move the value-add to the quality,” says Hegyi. “You don’t want to have people taken out of the equation, you want to have the people’s skills applied to the equation in the best possible manner.”
If you have ten people growing 100 plants, you can give them tools that allow those same people to grow 500 plants. What you’ve done is cut the cost per plant by 80 percent. You don’t have to lay people off, or hire new people, and you get a much larger yield. It’s a matter of scaling at the least possible cost. Which is a problem for the cannabis industry in particular. Getting the cost down is essential, and the way to do it is with a systematic approach.
While we’re discussing the marijuana industry, the point remains for any manufacturing facility – data, analytics, business intelligence, and automation technology help scale. These technologies help get the cost of production down, or the amount of production up, or both, with the same amount of labor and time. That means savings, added profit, less overhead, and all of the fun buzzwords the accounting department loves to hear. It doesn’t matter whether you grow weed, corn, kale, build headphones, or mix up medication – analytics and automation on the manufacturing floor will be a necessity to survive.
If you enjoyed this article and want to receive more valuable industry content like this, click here to sign up for our digital newsletters!
Well written article