Using Big Data In Cannabis Legalization To Understand Successes and Challenges

Even with marijuana becoming more accepted, other challenges lay ahead.


Big data and cloud computing is sweeping through many industries right now and changing the game for nearly all of them. But one area you might not expect it to be making waves is in the medical cannabis industry.

Marijuana has been vilified since the 1970s, having been labeled as a gateway drug and a generally dastardly substance. Regardless of how you feel about it, states are now legalizing medical and recreational use of the drug for the first time. Florida, for instance, is one of the most recent to legalize marijuana and cannabis for medical use.

By 2020, it’s estimated to be a $1.6 billion dollar market in the state. That’s impressive, for sure. But where does big data fit into all of this?

Believe it or not, big data and related information systems can be used to make the industry more efficient, more soundly regulated and better for its customers.

Supply and Demand

Marijuana is grown and treated in many different ways, leading to separate strands, potencies, and doses. Yes — that’s 'doses' in the traditional prescription medication sense. The problem is that there are so many different kinds that it can be difficult to scientifically track the potency and benefits that go along with each type of cannabis.

In the medical world, this is extremely important. As you already know, the dosage of the medication you receive depends on the ailment. Some patients need higher doses, while others are fine with low doses. The same is true of medical marijuana. But because it's not regulated in the same way, it's going to be extremely difficult for vendors and retailers to deal with supply and demand. One particular type of cannabis, for instance, may be in higher demand among some markets and customers.

That’s where big data comes into play. Startups like Eaze in California are aggregating and supplying operational data to retailers to help deal with supply and demand. This can help growers track what types of cannabis are most needed and scale up, or down, to meet emerging customer needs.

Better Growing Sites

As the demand for medical marijuana grows, so will the need for locations and farms that cultivate the plant. The problem is that marijuana isn’t exactly green or safe for the environment. It’s not the plant itself that’s the problem — it’s how traditional growers handle the cultivation and harvesting processes.

Big data can be used to find better and more efficient growing sites both indoors and out. Did you know annual cannabis cultivation consumes the same amount of power as 1.7 million homes? It’s the power needed to keep the plant healthy and help it thrive, and it cannot be avoided if you plan to grow large supplies of the crop.

Furthermore, there are 450 cubic feet of air exchange per minute for every 1,000 watts of illumination. Considering this and the power requirements, it’s easy to see that marijuana is not a 'green' or environmentally-friendly crop.

But big data systems can be used to find the ideal space for growing and to come up with better power and resource solutions. In fact, it has to happen if we’re going to make this cash crop legal as a nation.

Customer and Personal Patient Profiles

Every customer who walks into a dispensary is akin to a patient. They have ailments, needs and certain requirements that must be met. It can be difficult for retailers to keep up with this information — especially when dealing with a large group of repeat customers.

Big data systems can help employees and brands track this information in a secure way. Imagine being able to reference a customer's medical issues every time they enter the storefront. This information would be incredibly beneficial for suggesting new types of marijuana, new doses and even new medication techniques.


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