Becoming a data-driven cannabis enterprise
Turning raw data into actionable insights can be a game-changer for every cannabis company. Management no longer have to rely on gut instinct or FOMO to run their business.
Simply put, data-driven enterprises (DDEs) compete better, generate more profit and make less risky decisions.
A DDE leverages sensors, IT, statistical tools and data experts to collect, synthesize and analyze copious amounts of data from different sources.
Leveraging data-driven insights is a proven strategy to enhance the entire organization. This value has long been proven in other industries such as CPG, pharma, tobacco and alcohol.
I have helped cannabis firms drive a compelling ROI in these application areas:
1) Production – This area is ripe for optimization. Analytics initiatives have helped optimize growing conditions, reduce energy & water usage and better align capacity with demand given seasonal effects and consumption patterns.
2) Marketing – Brand managers have used analytics to determine the ROI of different media & promotional campaigns, fine tune their product portfolios and improve segment targetability.
3) Retailing - Analyzing POS and loyalty program data has helped retailers optimize their assortments, determine the best mrechandising displays and choose their ideal pricing & promotion schemes.
Becoming a true DDE is more than throwing some talented people and software tools at a pile of data and having them go at it. The vision should be about building capability.
I recommend leaders begin their journey by considering some thought-starters (examples below) before buying tech, redoing the org chart or hiring data scientists
> Vision & Culture
- What are the objectives and goals for your DDE?
- Does your company share data freely and regularly or is it ‘siloed’?
- Cannabis org charts are often in flux. Which department would ‘own’ this new capability?
> Infrastructure & Data
- Are your applications and infrastructure analytics-ready i.e. accessible, integrated and stable? Initially, your data sources will be the financial management, POS and ERP applications.
- What valid internal & external quantitative data is available to analyze? Whatever numbers you analyze should be accurate and current.
- How is data governance, security and privacy handled?
> Tools & Talent
- Do you have analytical tools to crunch and visualize the data? Common tools like Power BI and Tableau can support early analytics efforts.
- What is the level of data literacy, and where is it located in the firm? You don’t always need data scientists to derive value.
- With the reams of data available, you don’t want to suffer ‘analysis-paralysis’. Do your analysts think in terms of hypotheses?
#dataanalytics #operations #data #marketing #cultivation #decisionmaking