The High Value of Making Cannabis Operations More Intelligent

Across 18 U.S. states and Washington, D.C., cannabis is legal for adults 21+, and in 38 U.S. states medical marijuana is legal—signaling a shift toward greater adoption and acceptance. This, however, is the only area of unification when it comes to the cannabis industry as state-driven initiatives are all vastly different on the regulation of the substance, making protecting assets incredibly difficult for cannabis businesses despite strict regulatory requirements to do so.

Although many businesses deal with some form of regulation, the U.S. cannabis industry has some of the highest compliance regulations because it is not yet federally legal. Within those state regulations lie complex clauses specific to the physical security and surveillance monitoring aspects of protecting the business. For example, in Illinois, cannabis businesses are required to have a “security system designed to prevent and detect diversion, theft, loss of cannabis or currency, and unauthorized access.”

Some states have even stricter regulations, with mandates around retention and/or frames per second on surveillance footage. In Alaska, for example, footage must be kept for 40 days and be time and date-stamped, while in Illinois and Massachusetts cannabis businesses must keep footage for 90 days. In California, the state requires 1-megapixel cameras but some local regulations set the bar at 8 megapixels, while Michigan requires cameras to record continuously at 720p resolution.

The cannabis industry has some of the highest compliance regulations because it is not yet federally legal.

Additionally, some regulators require monthly checks to ensure the performance of security equipment is meeting compliance standards—all of which requires human capital, time, and an advanced level of systems organization.

But regulatory issues aren’t the only challenges that the industry faces:

• Multi-state operations. Typically, large cannabis operations have locations in multiple states where sales are legal, but with different regulatory requirements. It’s tedious to share infrastructure (such as centralized security operations) and therefore, information, across state lines. Because it’s illegal to move product across state lines, it’s also highly inefficient and expensive for businesses to be Multi-state Operators (MSOs). Centralizing shared services such as security can have huge cost-saving implications, which might not be available to cannabis operations.
  
  
• Protection from seed to sale. Cannabis is unique in that often, a single organization drives everything from seed to sale, including grow houses, storage, processing, transportation, and retail. Each of these stages has the potential to take place at different locations based on the scale of the operation, making oversight and the protection of assets expansive.
  
  
• High-value assets. Cannabis as a crop (the plants themselves) is a high-value target, but the finished product sold by retailers, as well as various concentrates, is easy to steal and sell. You also must consider that retailers conduct business largely in cash, as they are unable to use FDIC-backed banks to deposit money. This means that high-value assets are frequently on-site and require additional security.
  
  
• Workplace safety. In the world of cannabis, there are two areas of safety focus in the workplace: physical safety in the production, manufacturing, and distribution of marijuana; and safety at physical retail stores. Each focus has a complex set of factors that require attention by businesses.

Intelligent Tech Breakthroughs for Cannabis Operations

One differentiator for cannabis operations to address the challenges above includes shifting from reactive to proactive security initiatives through the implementation of hyper-intelligent and thorough security technology. This includes vigilant monitoring of public forums, integrated protection elements, assessing active threats, reducing false alarms, and removing silos of information.

Public forum vigilance. Criminals are getting a little more sophisticated in their coordination, but fortunately for the good guys, they’re not getting any smarter. Most vigilantes are planning organized retail crime attacks in plain sight, using public social media forums and messaging applications.

A perfect example of this is a Best Buy in Anoka County, Minnesota, that recently fell victim to a flash mob style attack. Even with high-scale security practices in place, a robbery was coordinated and strategized via social media. The suspects, who may be responsible for similar thefts in the area, were found to have coordinated via Facebook posts. They even had a Facebook page bragging about their organized retail thefts. Social media monitoring tools could very well have picked up this coordination proactively.

Cannabis businesses have not been left out of the newest flash mob trend, and have arguably been amongst the hardest hit.

Cannabis businesses have, of course, not been left out of the newest flash mob trend, and have arguably been amongst the hardest hit. Investing in monitoring technologies can help cannabis organizations to detect threats well in advance of the events happening and can be the difference between workers operating out of fear of the unknown or confidence in their ability to have the information they need to safely do their job.

Reducing false alarms. More than 90 percent of critical alarms were estimated to be false alarms in 2019. The greater amount of intelligence derived from incoming data from multiple sensors, in conjunction with learned behavior, the fewer false alarms for security teams.

Say you have a faulty sensor on one of your doors that’s producing a false alarm. Its physical and metaphorical noise creates a nuisance for your operators, and after spending time and resources responding to it and checking on the alert multiple times, they start to ignore it. Later that week, a legitimate alarm comes from that sensor. That sensor is now “the boy who cried wolf” and is quickly ignored. And it’s not just about missing these alarms, but the monetary cost associated with having to deal with each of these false events (causing more than $3.2 billion in loss nationwide to be exact). Within the cannabis industry, this is heightened since there are such a high number of sensors legally required, making it exponentially more expensive than a traditional business.

As machine learning is applied to incoming alarms over time, operators are able to rely on this data to accurately reflect real-time urgency. This provides the cannabis industry with better tools to determine how to allocate resources across operations.

Removing silos of information. One of the biggest challenges that many businesses face with security is the presence of multiple data points from a variety of sources: video feeds, access control logs, intrusion/fire alarms, social media monitoring software, and Dark Web oversight to name a few. As explained previously, cannabis businesses are legally required to have an exorbitant amount of sensors to meet certain compliance requirements.

A video of an individual entering a building, an intrusion alarm, or a social media monitoring alert all may mean very little by themselves, but together can tell a powerful story of an intruder entering a building who has recently Tweeted about his intention to rob a cannabis business in your area.

Without a centralized place to funnel incoming alerts and capture the full picture of an event, all this data becomes noise. To stay on top of all of this data without the appropriate technologies in place would require a large number of employees creating redundancies, needless expenses, and inefficiencies.

By applying intelligence to learned behaviors, assessing incoming alerts, delineating false alarms, and alerting guards only when a true incident occurs, businesses can streamline the efficiency of securing their assets.

The Next Frontier for Cannabis Security

In the cannabis industry, the growing number of imposed compliance regulations met with ever-present security threats affirms the need for turn-key surveillance and workplace protections that effectively monitor crime and theft, employee safety, and abide by industry regulations.

By removing silos in technology data points, we can create an environment where multiple data points are funneled through software that intelligently derives more proactive oversight for security scope and operations.

Ryan Schonfeld, founder and CEO, HiveWatch, was tired of hearing the phrase "because that's the way it's always been done” from security professionals. After starting a successful consulting practice and later founding his GSOC-as-a-Service company, RAS Watch (now HiveWatch’s Swarm), Schonfeld saw the need for a SaaS platform to make security leaders more aware, more connected, more proactive, and more informed. The result is HiveWatch, a Security Fusion Platform that works with existing security systems, enabling users to reduce noise, and add an intelligent orchestration layer to help companies manage their current security programs.