Technology Category
- Analytics & Modeling - Big Data Analytics
- Platform as a Service (PaaS) - Application Development Platforms
Applicable Industries
- Buildings
- Equipment & Machinery
Applicable Functions
- Sales & Marketing
- Warehouse & Inventory Management
Use Cases
- Inventory Management
- Virtual Prototyping & Product Testing
Services
- Cloud Planning, Design & Implementation Services
- Data Science Services
About The Customer
The customer in this case study is the National Broadband Network (NBN), a government-owned organization in Australia. NBN is responsible for designing, building, and operating Australia's wholesale broadband access network. As part of its operations, NBN has a data analytics team that was spending a majority of its time on data preparation rather than on analytics. The team is composed of highly skilled analysts who were becoming frustrated due to the imbalance in their work. The business leaders of NBN were also facing challenges in managing stakeholder expectations due to the limited insights they could provide.
The Challenge
The National Broadband Network (NBN), an Australian government-owned organization, was facing a significant challenge with its data analytics team. The team was spending 80% of their time on data preparation and only 20% on actual analytics. This imbalance was leading to frustration among the highly skilled analysts who knew they could deliver more insights if they had more time. The business leaders were also facing challenges in managing stakeholder expectations due to the limited insights they could provide. The goal was to flip this '80-20 rule' and enable the data scientists and the analytics community to spend 80% of their time on providing actionable insights with business value.
The Solution
NBN embarked on a journey to build a robust and scalable solution. The process started with data architecture and modeling based on the requirements for reporting and analytics. Data ingestion was a key area where Alteryx was involved, bringing in multiple sources of data across NBN's sales and marketing activity. Data management and governance were also crucial, and NBN partnered closely with the Chief Data Office to ensure best practices were followed. The journey was divided into three phases: Prototype, Operational, and Cloud Big Data. In the Prototype phase, a marketing mix and attribution model was built out to provide insights back to the marketing function. In the Operational phase, the reporting platform was centralized, and self-service dashboards were developed. In the Cloud Big Data phase, performance and operational reporting were produced, and an AWS stack was implemented. Throughout the journey, change management was a key focus, and the solution was branded as Nexus.
Operational Impact
Quantitative Benefit
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