METRC is a gold mine of data and you are not using it
Most operators think of METRC as a necessary evil to keep the state happy. Using it is required by licensed operators in 17 states, and most will do the bare minimum to stay compliant and keep the state off their back. That same information is you actually a fantastic resource of operational data and insight. The challenge operators face is consolidating and leveraging that data. Whether you use automated tools like Appature, or pull down excel exports to create reports, the following 4 tips will help make sure your data stays clean and maximize its value.
Garbage METRC data in, garbage METRC data out
It may seem obvious to say “enter your data accurately and on time”, but many operators struggle to keep up with the data entry and accuracy. The key is to standardize the process for collecting and entering the data every day. Not only does it keep you legal and reduce your audit risk, but it sets you up to take advantage of that data. Ensuring accurate and timely data entry means building compliance steps into your standard operating procedures. This includes:
- Making sure everyone is aware the task needs to occur
- Training your team on how to perform the task correctly
- Assigning clear responsibility for each task
- Spot checking for accuracy and conducting regular self-audits
Timely METRC data is accurate METRC data. If you don’t prioritize the data and its value, the work doesn’t get done.
Standardize strain and location names
Consistent naming practices is the most important way you can control and maximize your METRC data. As a company scales and add licenses, its common to grow the same exact strain under each license, or to have multiple licenses growing in the same location (a med and a rec license, for example). It is critical that you name the strains and locations the exact same in every METRC license.
For example, if you name one of your locations “Flower room 1” in one license, name that same room “Flower room 1” in all other applicable licenses, not “FR 1” or “Flower 1”. Without this, a simple task like compiling plant totals by location becomes significantly harder as you have to spend unnecessary time “cleaning’ your data to have the same location.
The same applies to strains. Imagine your cultivation team is doing a bi-annual culling of the bottom performing strains. You want to compare historical yield performance as part of that analysis. However, each strain is named slightly differently in each license, causing you to spend time renaming each strain in your data set to consolidate yield data. This takes time you don’t have and opens up the chance for error and faulty analysis.
Plant batch and harvest batch names
Unlike strains and locations, which should have one name, plant batches and harvest batches have more detail to them, and require a naming convention standard. A naming convention standard is a pattern by which all plant and harvest batches are named. This will allow you to quickly identify all the key information about the batches and harvests, but also give you flexibility to introduce new variables in the future. In your SOP, define a way to name your plant batches and harvest batches. The rules should be clearly defined, make sense, and serve a clear purpose.
We recommend for plant batches: “MMDDYYYY – Strain – Use” where MMDDYYYY is the day they were planted / cut (regardless of when they were entered in METRC), Strain is the strain name including pheno number, and “Use” is an identifier if the plants already have a pre-determined use. Examples include “Moms” or “R&D Testing”. If nothing specific applies, it can be left blank.
For harvest batches we recommend” “MMDDYYY – Strain – Use” as well, where “MMDDYYYY” Is the date of harvest (regardless of when it got entered in METRC), Strain is the strain name including pheno number, and “use” is pre-determined production use. Example could include “Fresh frozen” or “Pre-rolls”. If no specific use is currently planned, or will be used in multiple different products, then it can be left blank.
This makes clear to anyone within the org all the important information about each batch, but also gives flexibility in the future. Say you are running a crop from start to finish with a new set of nutrients. You can then tag the names with “MMDDYY-Strain-Use-Nutrients” so you can quickly identify them, and others, when analyzing your progress and results. Having consistent naming and hyphenating also allows for easy delimiting when pulling the data into a spreadsheet program or database.
Establishing a master product catalog
Inconsistent product names lead to multiple issues through the entire lifecycle. When items in METRC are not consistent, you make managing and controlling inventory unnecessarily difficult. Comparing product performance or even locating items in your systems can be extremely frustrating. By using a simple naming approach, you will make your life easier.
Items in METRC are a combination of principals from strains and locations in that they are constantly reused, and elements from plant and harvest batches in that they convey much more information. Once again you will want to use a standard naming convention for items, and use the exact same name across licenses for the reasons listed above. Any naming convention will work as long as it’s consistent and is defined with purpose and intent.
We recommend the following:
“(Strain or Flavor) – (Product type) – (size)”. Not every item will require every element, but should still fill in the blanks where appropriate. Additionally, you may choose to have item names be different based on their step of the processing process. For example, you may leave off the “size” portion if the item is referring to bulk version of a product, adding it only when it gets packaged for individual sale. Here are some examples:
- Sour Diesel Buds 3.5 g (Strain – product – size)
- Active THC Base (Product)
- Animal Mints Concentrate 1 g (Strain – product – size)
- Jack Herer Fast acting gummies 100 mg (Strain – product – size)
- Fruit punch rapid rush edibles 100 mg (Flavor – product size)
It’s never too late to start
All of these policies can be implemented now, even if you’ve been operating for years and your historical data is a mess. You can tackle one area at a time and see the results quickly. Appature can help you tap the value of your METRC data regardless of what shape it’s in. Let us show you how. Contact us today for a demo and a free trial at firstname.lastname@example.org