Analytics Use Case #1: Cultivation Output Comparison

An in-depth, top-down comparison of strains allows cultivators to understand which plants produce more finished flower versus trim or waste by automatically measuring the apportionment of each harvest. Seeing this information in an easily-digestible format helps the cultivation team determine which strains to cultivate for the most usable output and the least waste and trimming. Since hand-trimming is labor-intensive, knowing which plants produce the least amount of trim by weight will help cultivation teams ensure the maximum return on their time and efforts.

Analytics Use Case #2: Test Results & Benchmarks

Giving cultivation managers a historic view of each strain’s test results helps the grower identify which strains and grow locations produce the best output based on tested cannabinoids. It also helps determine which genetics could use refreshment based on declining cannabinoid test scores quarterly or yearly. If the growers’ tests fail, the Reporting Suite dashboard will also showcase the reasons for failure and the specific product packages that were affected. Having all of the details on what failed, why it failed, and where it failed allows the grower to retrace their steps and take steps to ensure future tests pass with flying colors.

Analytics Use Case #3: Compliance / Red Flags

To help avoid regulatory hassle, we’ve designed a compliance dashboard to show the most common indicators for non-compliance to assist investors, owners, and compliance managers in identifying and correcting these issues - before regulatory officials discover them. You can also configure StashStock’s compliance Reporting Suite dashboard to send alerts or warnings to cultivation and compliance teams. This feature, combined with internal auditing via touchless RFID technology and compliant label printing, makes StashStock the ultimate solution for maintaining full compliance and keeping regulators at ease.

Analytics Use Case #4: Forecasting Yields

After tracking and compiling all of the cultivation licensee’s data, StashStock’s Reporting Suite will apply machine learning to predict future yields and product outputs based on input activity. For example, when the cultivator plants 20 clones, the predictive Reporting Suite will estimate when those plants will be ready for harvest and what that harvest will yield in terms of wet or dry weight. As StashStock analyzes the grower’s data and track record over time, additional harvests will provide more data for the predictive Reporting Suite to refine its estimates and improve its accuracy.