HOW THE LACK OF DATA ANALYTICS, AI AND MACHINE LEARNING IS HURTING LPS' BOTTOM LINE

“Without data you’re just another person with an opinion.” Edwards Deming, Statistician

It is secret that licensed producers have to do a lot of tests on their cultivars whether for R&D, batch release, sales to other companies or numeros reasons in between.

The overall process of testing that generally happens today:

• LP sends the dried flower to a certified lab using a courier company or dropping the sample off at the lab.
• The lab leaves the sample in queue for an average of 4 to 5 days before they start processing the samples.  The testing process then take, on average, 1 to 2 days.
• The test results are then stored in the computer system of the lab instruments such as chromatography systems.
• The lab then reformats the test data and either emails them to the LP or sends it on a paper letter along with the COA, certificate of analysis.

If the LP,  or lab,  finds any issues or irregularities in the samples or tests the whole process will have to be redone. This sometimes taking longer than the orignial tests as they have to find the possible issues and resolve them.

In this process, LPs are left waiting for days at the mercy of the labs timing.

This creates a significant risk factor as the results can come in late and the LPs may miss the prime harvest time.

Also, when the LPs receive their tests results, it is usually in the form of a PDF file attached to an email or in the form of a printed letter couriered to the LPs. Once they get the results, LPs usually try to store them by manually entering them into an in-house system like a spreadsheet. This is a cumbersome process.

Despite all the efforts LPs take, these test results can very convoluted and usually there is not a proper data analytics in place that helps them understand the growth rates of certain cultivars. This process also makes it very difficult for the LP to track other factors such as temperature, water and humidity because the labs only generate the basic test results.  The LPs would have to combine the environmental data with the lab results in their spreadsheets to be able to make a proper decision on growth trends and other factors for each strain and cultivar.

“Test results sent by the labs often get very convoluted over time and usually there is not proper data analytics in place that helps LPs understand them after a while.”

Most LPs often do not have all the resources to streamline this process leading to two major risk factors:

1- The test data LP's store in their spreadsheet is often not comprehensive, accessible and lacks potenitally important factors. They often lose the test results as it turns into a needle in the haystack. So basically they have invested their time and money to do the tests and now they don’t even have them to make a decision.

2- Lack of proper analytics and machine learning will lead them to make  judgements which are based on half-data half-gut check when they are working with various strains of cannabis. With proper data analytics, they can significantly maximize their return on investment (ROI) as they can know exactly what to do with each strain.

There is a much better way to do lab tests:

• The samplesare prepared for in house tests
• Easy to use tests are done and the test results are immediately available in the cloud
• The data analytics and AI system in the cloud organizes the data and based on the information available, shows the LP the trends and what should be done as the next step.

Simplied, fast testing, with proper reporting and data analytics  is the essence of success!

Selective Lab has a data analytics system in the cloud, which is connected to our CannabiMeter(TM) so as soon as the potency tests are performed, the test results appear in the cloud immediately. When talking to us, ask about SelectiveLIMS(TM) and we will tell you about how to do in-house trend setting and other R&D activities with it.