Why We Forecast 5 Years Out

October 24, 2019

We pride ourselves on looking at the scattered points of data, the assortment of market effects, the messiness, and pulling it together into a point of view that can deliver actionable insights for our clients.

We have built our reputation on predicting markets for a product category that is as volatile as it is exciting by doing our due diligence and connecting to those in the know across markets and supply chains. Because of this, we were able to see the explosion of CBD coming before the market, standing out from the crowd to tell our clients that a seismic shift was on its way.

As part of our work we strive to provide market forecasts that span nations, monetary unions, and continents. During this time, we have been asked, ‘why our forecasts are limited to a five year view?'

Now we can get nerdy on this question, but for the sake of your time, let's stick to a quick description of the process and its limitations.

By their nature, forecasts rely on a wide variety of past and current data points to cast forward a projection of movements; if the future were a cliff, we are extending a ladder out beyond the edge. As that ladder is extended, its stability is increasingly suspect.

Our ladders, the models we use, rely on a base of assumptions and inputs that when aggregated contain variance that in the short term can be limited but in the long term may stray from original assumptions or past belief. We can read the intentions of a state legislature and forecast the likelihood of legislative passage or change in the near term, but it becomes increasingly more difficult to predict what that same legislature, or an entirely new legislature, may enact more than a few cycles from now.

While we are in business to provide a forward-looking perspective of the cannabis markets, the impact and robustness of models past the five-year horizon become unstable.

Robust models should be able to account for market movements, that is they should be able to have short term flexibility to cover a certain amount of possibilities. As we project forward, the total number of market events approaches levels that render the original model stale. To compensate, we are constantly monitoring our assumptions, inputs, scenarios and model results.

In an industry like cannabis, where markets and consumers move every minute, any forecast beyond a certain horizon would be a disservice to our customers and the industry at large.