Monde Nissin Australia

Transforming Monde Nissin into a data-driven decision maker with automated analytics

Aginic worked with Monde Nissin Australia in partnership with Microsoft to develop an automated analytics and reporting solution that enables Monde Nissin to manage its operations with greater insight, efficiency and precision. 

Mark Alexander
Mark Alexander

The situation

Monde Nissin Australia (MNA) owns and manufactures some of Australia’s favourite brands across grocery, frozen and chilled such as Nudie, Black Swan, Wattle Valley, Peckish and Quorn. 

MNA also owns Menora, a national face-to-face sales and independent distribution business into Australian independent stores with MNA’s own iconic, as well as agency, brands across fresh, chilled, frozen, confectionary, grocery and household. Menora has a national sales & merchandising field force that consists of over 110 dedicated and passionate people that visit metro and regional customers.

MNA was created as the result of three family businesses that joined the global Monde Nissin family in 2014. Monde Nissin sells brands in over 45 countries and has over 3000 talented people working across the globe.

 

 

MNA was at the beginning of their data and analytics journey having recently embarked on an initiative to enhance their IT and Data capability. MNA’s goal is to become a data-centric organisation and they engaged Aginic to establish automated reporting built off an enterprise data warehouse. 

“Monde Nissin Australia was facing a few challenges.” says David Anderson, MNA’s  CFO. “It was difficult to make data-driven decisions. We didn’t have a single source of truth with our data. Our data was in disparate systems. It was difficult and time-consuming to manually pull together the data and create reports. The Leadership team and I found it extremely hard to run the business as effectively as we knew it could be run if we had good data, analytics and automated reporting.”

The Aginic approach

Our approach to this project revolved around the solution being designed and delivered in small increments that delivered maximum value to MNA’s end user. Design thinking, user experience and experimentation are fundamental to Aginic’s way of working, and we applied these principles when working on this project. We built with the future in mind so that the solution enabled long-term flexibility and adaptation . 

Our multidisciplinary team, with expertise in data platform engineering, analytics, user design and agile delivery, worked closely with MNA to reach their goal of developing an enterprise data analytics and BI-reporting platform. We focused on the end-user value that the platform would enable and adopted an agile approach to allow for regular validation of customer value. 

We delivered frequent drops of end-to-end capability through a series of Minimum Viable Products (MVPs) in 2-week sprints. This allowed user feedback and technical feasibility to be managed successfully and allowed us to focus on maximising customer value and reducing complexity through incremental delivery of outcomes. This way of working provided MNA with high visibility of project progress, comfort around technical elements, and the ability to rapidly iterate improvements throughout the project.

“It took some practice, but we ended up working so efficiently with the Aginic team with daily stand-ups, fortnightly showcases and retros. Initially, the retros provided the highest benefit enabling MNA and Aginic to achieve a superb working rhythm. Their delivery manager kept the project on track. Aginic’s designer was also critical to the success of the project. We used design thinking from the start and the end result was that the end-users had a high degree of engagement with our BI reports. It ended up being ‘one team’ with the Aginic and MNA people working together as one.” stated Rehman Hameed BI Manager Monde Nissin Australia.

We kicked off the project with a Discovery & UX Design phase. This phase set up the successful delivery of the whole project. We challenged assumptions and evaluated the highest risk aspects of the build through hands on development of narrow proofs-of-concept. This process included reviewing the current use cases and requirements developed by the MNA BI team, digging into source data, and starting to form a view on data models and establishing a data dictionary. The Discovery phase produced a delivery roadmap with revised scope and timelines for all MVPs at a high level with a detailed breakdown of the work for the first MVP. The roadmap also proposed the implementation approach by use case.

This phase was followed up with a two-week Experiment phase. We experimented  to provide the perfect testing ground for users to get the first glimpse of what’s possible with the fist use case, a Sales dashboard. In this phase we started to dig further into the technical requirements and set up the required infrastructure. This included the end-to-end flow through of data from the source system, through staging areas, database tables through to the reporting layer. 

We took the learnings from the experiment phase and hit the ground running in our first Delivery sprint. We delivered the first minimally viable product (MVP), which was the Sales team’s first report. This report enabled managers and the 100+ sales force to have almost real-time data on hand in the field to make optimal data-driven decisions.

We then delivered the remaining use cases in Finance, Manufacturing, Inventory, and Procurement creating over 20 reports whilst building out the Enterprise Data Warehouse in nine delivery sprints over a six-month period.

The principles that guided our approach to building MNA’s modern cloud data platform were:

  • Enterprise scalability, which allowed the data team to grow and adapt with the changing needs of the organisation
  • A preference towards performant tools and services, allowing for the processing of both big and small data using the same pipeline 
  • Security was built-in, drastically limiting the potential for, and impact of data breaches 
  • Managed services, thus increasing time spent on delivering business value 
  • DevOps-oriented: tools and services are built around continuous integration/delivery principles, are geared for “fail fail” development approaches and employ best practice agile delivery techniques such as automated testing and self-documentation
  • ELT (Extract-Load-Transform) over ETL (Extract-Transform-Load)
  • Proven but exciting technology that data teams love to use

The solution

Aginic built over 20 reports in PowerBI from an enterprise data warehouse built on Microsoft Azure using 59 source tables, 140 SQL models and 223 automated tests.

  • Data Sources: Pronto was the main data source for the project, supported by flat files for budgets and forecasts. During the course of the project several flat files were successfully migrated into Pronto or Monde Nissin’s Sharepoint environment to ensure better governance of the data.
  • ELT Tool: We used Azure Data Factory (ADF) to ingest data from the source system (Pronto), and make it available on an Azure Storage Account. This was performed using a custom PowerShell script using the AZCopy utility. The next step was using the Copy activity in ADF to land the data in the Azure SQL Database ready for transformations
  • Azure Storage Account: was used as a staging location for source system data,, before being copied into the SQL database.
  • Azure SQL Database  We used the Azure SQL Database service as the Data Warehouse. It provided seamless integration with our other tools, and great performance when needed for heavy data transformations. Using the vCore purchasing model allowed us to easily scale up and down as needed.
  • dbt:  We used dbt (data build tool) which works with a variety of different data warehouses, to clean and transform the data in the Azure SQL Database, making it ready for consumption. Using dbt’s out-of-the-box automated testing and version-controlled documentation meant that we had more time to build models providing crucial business value for Monde Nissin, while not compromising on data quality and integrity.  This layer also provides data to data analysts for additional ad-hoc analysis.
  • Reporting layer: Reports made for the five use cases and for end-user consumption were developed in PowerBI Desktop and published into PowerBI online workspaces for the business-user consumption.

The following diagram illustrates the high-level solution architecture:

“We pulled all the data from our source systems into an EDW which has set us up for the future. Using Microsoft Azure, we collaborated with Aginic to create an automated analytics and reporting solution that has the ability to deliver almost real-time insights to our various business units to make optimal data-driven decisions,” said Rehman Hameed BI Manager Monde Nissin Australia 

Business outcomes

Aginic worked closely with MNA as ‘One Team’ to deliver a data analytics platform on Microsoft Azure. With the MNA team, we co-created over 20 automated BI reports for teams in Sales, Finance, Manufacturing, Inventory and Procurement.

The MNA business is now more efficient and effective. The  BI team is saving days of manual work doing data extraction, modelling and reporting. The Sales people have figures at their fingertips enabling them to track sales, budgets and shortfalls to identify areas of improvement. The Finance team now trusts the data and the automation of reports has saved days of manual work. Manufacturing and Inventory teams can now make accurate data-driven decisions reducing significant waste and potentially saving millions of dollars a year. Procurement can also now accurately track spending and identify areas of potential savings.

“Firstly, the analytics and BI reports have transformed our business. We are now able to make real time data-driven decisions and trust the data. Secondly, we are so much more efficient now. We have saved literally days of work every week through the automated analytics and reporting processes.” said David Anderson, MNA’s  CFO.

Get in touch with Mark Alexander

Mark is passionate about enabling clients to make data-driven decisions, and making the complex simple! He bridges the gap between business and technology translating data and analytics into business value. Mark loves all things sport and health and migrated into data and analytics through elite sport being a Sports Physiotherapist at three Olympic Games with the Australian Triathlon team. Mark loves travelling and camping with his three awesome kids and amazing wife.

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