Predictive analytics is the future of data consulting. Predictive analytics leverages advanced statistical techniques to analyse current and historical facts to make predictions about future or otherwise unknown events.
As a result of Covid-19, this process is becoming more commonly understood. From managing outbreaks to informing how the economy re-opens, predictive models have dominated public discourse for the past 18 months – and will continue to do so well into the future.
But predictive analysis has applications beyond the world of epidemiology. In fact, its scope is nearly limitless – especially as more industries begin exploring how to use it to enhance their processes. Likewise, the development of user friendly analytics software like Alteryx means these tools are more accessible than ever.
Faced with a need to transform its business model to focus on direct-to-consumer, Hawkers Beer partnered with The Data School to use Alteryx Advanced Analytics to optimise its business processes. The brewer has now expanded the use of data analytics across its sales and product teams to improve forecasting and reach new customers.
Through predictive data analytics, Hawkers Beer can adjust its production when there is high inventory, long production or replenishment lead-time, as well as variances in demand for its product. By performing cash flow forecasting, the brewer was able to analyse its real-time data and make the decision to temporarily withdraw from the Queensland market last year to strengthen its bottom line.
Alteryx has an suite of predictive tools that can be used to do this type of modelling – if you’re new to these, I recommend reading my colleague Alex Chan’s excellent introductory blog on their use.
Alteryx also has a number of challenges you can use to test out these features without needing real world data. These are a great starting place for understanding their use, and how you can apply them to your work as an analyst.
5 Alteryx Challenges To Practice Using Predictive Analytics
Predicting Baseball Wins
Use case: The Baseball season has completed and it’s time to project next year’s win totals.
ARIMA Time Series
Use case: A retailer would like to forecast how many units of a particular product will be purchased from their locations based on a historical trend.
Have we reached Peak Pumpkin
Use case: Have we reached Peak Pumpkin? Is the time of the demand for EVERYTHING PUMPKIN losing steam? Has Maple Pecan become a force to be reckoned with?
Just another game?
Use case: What’s the difference between predicted values and actual values for the New England Patriots regular season games and Super Bowl games?
Data Driven Cocktail Recipe
Use case: A fun Alteryx challenge that uses predictive tools to come up with a cocktail recipe.
The Complete Guide to Alteryx Analytics for Beginners: P1 – The Data School Australia
Sean Gu’s excellent three part series on predictive analytics
The Data School – Predictive Analytics Schema
An great explainer on structuring from predictive workflows from the Data School UK
The Data School – 3 steps to work with regression analysis in Alteryx
A quick guide to get you up and running on regression analysis.