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  • Developed externally facing dashboards using Power BI and embedded them into the wine company’s website.




Grape growers


Wine exporters

The Problem

A large wine group’s market insights team plays a key role in analysing key data sets and disseminating information to the Australian wine sector, which incorporates approximately 2100 wineries, 6000 grape growers and 1200 wine exporters.

The wine company wanted to give grape and wine businesses access to trustworthy data to support their ability to make data-driven decisions.

The Opportunity

Broadly, the opportunity presented was a leveraging of technology to enhance industry access to reporting data, thereby supporting the entire Australian wine sector in understanding markets and making strategic decisions. This would ultimately contribute to the growth and development of the sector as a whole, and increase the value of the wine company as a source of truth.

The Solution

The product of this project included two external facing dashboards developed using Power BI and embedded into the wine company’s website using Power BI embedded. Microsoft Azure was the cloud platform used with Azure Data Factory taking care of the data flow and triggers, Azure Data Studio to write SQL transformations and Azure DevOps for source control.

The National Vintage Survey (NVS) Dashboard displays data collected by the wine company regarding the tonnes and value of grapes grown, purchased and crushed by Australian wineries each year.

The Export Dashboard collates data from the wine company’s Licensing and Approval System – released quarterly – that reports Australian wine export data by market destination with fields including variety, label geographical claim and price points.

The benefits of this solution were as follows:

  • Accessibility: The dashboards are publicly available 24/7 on the wine company’s website with no login required, making access quick and easy for all stakeholders.
  • User-friendly Interface: The dashboards provide both high-level overviews and detailed access to the datasets, catering to the diverse needs of the stakeholders.
  • Informed Decision-Making: The dashboards present and filter information effectively, enabling grape and wine businesses to find facts and trends that can guide their business decisions.
  • Efficiency: Through the dashboard’s automated analysis and calculations, the wine company now has a greater ability to focus efforts on understanding markets and the decisions that need to be made to support grape and wine businesses.
  • Continuous Support: Post-implementation, Mantel Group has continued to work with the wine company in an advisory capacity across its entire data analytics platform, providing responsive and reliable support.

Our Approach

The approach involved working with the wine company in a cross-functional team of business and data analysts, designers, user experience gurus, data engineers, front-end web developers and delivery leads. Agile practices were used, and the development of the wine compan’s dashboards followed the Scrum framework.

  • Each sprint started with a planning session where goals and priorities were agreed upon.
  • The sprint involved daily stand-ups with all development teams, backlog refinement sessions and sprint reviews to showcase the incremental value presented back to stakeholders for feedback.
  • Before starting development, collaboration with the wine company occurred through a series of discovery activities, including a vision and objectives workshop, design thinking and UX workshops, way of working sessions and backlog creation. This suite of workshops was integral in laying out the foundation for the project roadmap.
  • User testing was conducted using a high-fidelity interactive prototype created in Figma. This tool allowed users to get the feel of the dashboard early in the piece without needing to wait for the build of pipelines or dashboards.
  • The user testing culminated in a final sprint that focused on improving the performance of the dashboards without adding any new features. Goals and priorities were discussed and expectations of performance for the final dashboard were agreed upon.
  • The final sprint re-created the data model and visualisation aspects of the dashboard to maximise performance.

The dashboard for the export and National Vintage reports required a combination of a complex set of SQL transformations and dynamic DAX formulas built in Power BI. The grouping of exporters by size required a dynamic calculation based on the dates selected in the filter where grouping is by year end.

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