Data Addiction overhauls forecasting for Aware Super

Data Addiction overhauls forecasting for Aware Super

Builds new platform using Azure Machine Learning

Credit: (c) Adrianocastelli |

Microsoft partner Data Addiction has helped build a data modelling platform for the newly rebranded super fund Aware Super. 

The Sydney-based Microsoft data and artificial intelligence specialist used the vendor’s Azure Machine Learning to build a new forecasting platform for Aware, reducing its reporting time. 

Data Addiction developed the architecture and enabled Aware to take a DevOps approach to the transition process, Microsoft claimed. The overall transformation process took just over nine months. 

Aware, formerly known as First State Super, previously used legacy platforms to predict growth for its $130 billion funds and 1 million customers. 

According to Microsoft, the legacy platform could not support multiple users running what-if modeling and had limited governance around change management and production deployment.  

Changes could be time-consuming and Aware Super had to make tradeoffs – either accept long run times for models or reduce the granularity to speed things up, the vendor added. 

Meanwhile, there was also often only one person able to make the final changes to the model – introducing key-person risk. 

“One of the objectives was to make sure that the solution was customisable, and that it could also deal with changes that we may or may not know today, but that we can see coming down the line, whether that’s a regulatory change or environmental change,” Richard McDulling, project manager investments, for Aware Super, said. 

“Part of the solution was to make sure that there was a way to easily adjust the model, and the logic, and the inputs, and the data analysis at the end, to capture that.” 

As such, Aware turned to Data Addiction and a number of Azure data services to reduce reporting time, increase enterprise transparency and establish digital foundations for the future.  

In order to ensure compliance but also flexibility with the modelling, forecast assumptions are now stored in a SharePoint list, which allows users to create scenarios by selecting from a list – with everything tracked for accountability. 

“This has helped democratise modelling at Aware Super,” Microsoft said. “In the past, only one person in the organisation was able to adjust the fund projection model, for example.” 

According to Aware, the new platform has “opened the door” for even more granular modelling now.  

Last year Data Addiction also assisted alcohol delivery service Tipple with an overhaul of its delivery and customer data analytics platform.  

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