As the cannabis industry continues to grow, the need for efficiency has become front and center for cultivation businesses. Like any industry, accurate and quantitative information and a rapid feedback loop is critical in optimizing operations. For decades, lean methodology has been adapted across industries like CPG, Manufacturing and Banking to dictate strategies that will minimize waste and produce the most value for customers. In this article, we’re examining four adjustments operators can make to achieve lean cultivation in cannabis.
Lean Methodologies & Cannabis Cultivation
Lean methodology came about as an antidote for a rapidly expanding and volatile global market — much like the cannabis industry today. The approach works toward rapid iteration and minimized waste at each step of the process, enabling an operation to put no more or less resources into a product than absolutely necessary. Lean principles take all aspects of the business into consideration, identifying what’s working and what isn’t, in parallel. By dictating strategy in real-time, lean aims to eliminate waste, optimize processes and boost innovation.
Such an approach fits in well with today’s cannabis industry where increased competition, falling wholesale prices and high tax rates squeeze operators.
Below are some tips and tools that help operators achieve lean cultivation:
1. Trade tracking for measuring
Tracking the full business and usage of resources is the first step toward lean operations. For this, cultivators turn to Enterprise Resource Planning (ERP) technologies. Ideally, these systems integrate across the business to track the lifecycle of the product.
Since ERP’s record data points like costs, time to market and movement of product, they are complementary to lean. However, these systems provide an analytical view that supports cultivation decisions retroactively, they don’t do much toward shortening feedback loops and informing real-time decision making. In cannabis where quick decisions (i.e. pests and diseases management) are key to the success of an operation, ERP systems often leave much to be desired.
ERPs also typically prioritize integrations with traceability software (like Metrc), significant effort is required to ensure operators are tracking inputs, process effectiveness, crop health and labor efficiency. While giving operators a macro view of the business, they fail to offer detailed views or real-time data that dictate lean strategies. And, as management expert and consultant Peter Drucker notes, “you can’t manage what you can’t measure”.
Instead, lean cultivations are those which move away from simply tracking toward monitoring & measuring all the factors which impact crop performance.
What commercial cultivation should be actively monitoring & measuring: i) Environmental conditions: Temperature, humidity and VPD ii) Plant inputs: Water, nutrients, treatments iii) Processes and Crop Registration: Pruning/de-leafing, spacing, branching, pest/disease detection iv) Labor: Efficiency & proactivity of staff; scale what works, kill what isn’t v) Genetics: specific needs of varying genetics
2. Trade Subjective with Objective
The way we monitor & measure a cultivation has changed significantly since commercial cannabis hit its stride.
In its simplest form, monitoring and measurement is done manually and decisions are made subjectively. Cultivation labourers monitor thermostats and humidistats, visually inspect crops to identify issues and anecdotally pick out processes that produce good yields. With these methods, best practices are subjective, varying from person to person and delivering only a small amount of added control. This method is also highly labor intensive and, in the era of 280e tax issues, expensive.
To achieve a more objective system, cultivation operations have employed various sensors and monitoring equipment to pick up and digitally track data at room- or crop-level. Smart sensors and crop steering softwares do a better job of standardizing monitoring to offer performance insights. Moreover, the ability to collect such data throughout the cycle — down to the strain or plant-level — exponentially increases knowledge about strains and genetics. This insight then drives a better understanding of how to optimize conditions for the best yields.
3. Trade aggregate for granular
Much of the tracking software sensors and crop steering products on the market today collect aggregate data — i.e. at the room or crop level. This aggregate data does aid in shortening the feedback loop and setting environmentals once dialed in, but it still misses nuances and specific detail of individual plants or microenvironments; it provides a final answer, without information on the myriad of factors which get us there (i.e., root cause).
Instead, when looking for tools to help achieve lean cultivation, operators should look for technology with plant-level capabilities. Granular data uncovers how each of the hundreds of touch points (inputs, labor and processes) in the lifecycle of a single plant add up to impact the final crop. Further, it can highlight how individual growers contribute to the collective team result, providing guidance on how to support and scale quality task execution of the team.
This granularity also allows operators to catch issues more quickly (pest issue in the room vs a specific plant with an issue), optimize inputs and identify successful processes (effective pruning and labor touchpoints). This granularity uncovers the real causes of waste, identifies the most effective processes and shortens the innovation cycle.
4. Trade analysis paralysis for smart communication
It’s great to talk about granular data and most operators would probably agree it’s the goal. But, like anything, there are costs to weigh.
When using simple crop steering or monitoring tools, it’s true that more data points means more human effort — whether physical labor to collect data or the required analysis to make sense of it all. Instead, operators who desire a lean cultivation model now have access to smart tools which simplify the collection and analysis of data and make communicating findings simple. Vision technologies have made the continual collection of such data at scale possible in numerous industries to date, including conventional agriculture. This type of technology, like Adaviv’s Mantis™ Crop scanner, is now also entering cannabis cultivation and can support scouting (pest, disease and stress detection), yield forecasting (growth tracking and prediction) and crop registration (plant KPIs like flower counts).
Likewise, smart digital tools can allow operators to log spatio-temporal data (i.e., plant location and time of development) — while also speeding up communication of information. Smart software can reduce the time between issue detection and resolution from days or weeks to minutes. These tools often utilize simple technology, like SMS, to notify of issues and severity and integrate with supply chains to proactively order what you need, just in time.
Conclusion
Lean methodologies are not new. They’ve been employed across multiple rapidly-changing industries. Now, with bigger, more precise data, a new generation of efficient manufacturing (Industry 4.0) is emerging. While young, the cannabis industry is a prime target for adapting existing and new lean principles to minimize waste and, ultimately, offer the most value to customers.
At Adaviv, we’ve built modern products that allow cannabis cultivators to tap into these methodologies and technologies, providing more visibility, control and communication over their businesses. Our belief is that, with innovative technology and a deeper understanding of the cannabis plant, operators can run a Lean Cultivation™.
To see our product in action or to learn more about if the Adaviv tools would fit with your business, please get in touch.