> [!meta]- Document Info > **Author**: [[Chris Burgner]] > **Full Title**: Snowflake’s Forecast Transformation With Brad Floering > **Category**: #articles > > **Summary**: Snowflake rapidly grew as a software business, excelling in accurately forecasting its unique usage-based pricing model. Brad Floering led the transformation of Snowflake's forecasting process, contributing to a successful IPO in 2020. Their innovative approach involved developing sophisticated models to predict customer usage behavior and revenue with high accuracy. > > **Source**: [Original URL](https://wrap-text.equals.com/p/snowflakes-forecast-transformation) ## 📄 Full Document → [[Snowflake’s Forecast Transformation With Brad Floering]] ## 🔦 Highlights & Commentary - To accurately forecast Revenue, you have to understand the consumption behavior of the customer over the contract period.  Brad found that customers on usage-based plans follow a more geometric consumption curve, resulting in the team over-forecasting in the short term and under-forecasting in the back half of the contract period compared to a seat-based model ([View Highlight](https://read.readwise.io/read/01jbw22zap01d17gxmcj3bmekg)) -  ([View Highlight](https://read.readwise.io/read/01jbw23jjzwnpk700pdnj4sy1w)) - firmographic data is not easily standardized.  As an example, how do you bucket Amazon into a single “industry vertical” or account for the “company size” of customers rapidly scaling their headcount? ([View Highlight](https://read.readwise.io/read/01jbw2kc80166qhkyrhqh23akt)) - Note: This is true for all types of segmentation - a significant dependency to an IPO was bringing Revenue forecast accuracy within +0-2% and never under ([View Highlight](https://read.readwise.io/read/01jbw2yxx27pw4kkxbypjsmkx3)) - Note: This is going to be extremely disruptive in new outcome/success based pricing models - implementing a set of data quality rules to the training set, especially those that removed noise from one-off outlier events. ([View Highlight](https://read.readwise.io/read/01jbw30t65f07hn2vxjz92cgt7)) - Note: Standards & practices are the foundation - Most Finance and Operations teams claim to be stuck waiting for the quarter to close before they can run reporting and analysis, but the window to take action has closed by that point.  Teams need to find ways to tap into real-time insights and inform proactive decisions before it’s too late. ([View Highlight](https://read.readwise.io/read/01jbw3em73d0606vze4de0n0v9))