Data & Analytics @ ALDI SÜD

To reflect the vital role played by data analytics at ALDI SÜD and to increase awareness of the importance of data in our group of companies, we have set up our own organisational unit. Our mission is to drive forward the topic of data and analytics for the ALDI SÜD Group and along our value chain.

ALDI SÜD: “Good things for everyone”, also based on data

Our Data & Analytics organisational unit brings together all the company’s data and analytics initiatives, unlocking data-driven value for the ALDI SÜD group worldwide. The  unit provides even deeper insights into products and stores, such as availability in our warehouses. This initiative has also helped improve data consistency and transparency throughout the entire ALDI SÜD Group at a rapid pace: not only is the data better structured (e.g. through customised data modelling), but it is also easier for all stakeholders to understand, thanks to uniform data governance. This enables the company to respond more quickly and efficiently to ever-changing customer requirements and market conditions.

The ALDI Data & Analytics unit coordinates our strategy and initiatives in the area of data and analytics in close cooperation with the regional and national business entities. After all, each of the data solutions is aimed at mastering the specific challenges of at least one ALDI SÜD country or region. With customised, easy-to-implement solutions, the unit delivers real added value on-site and plays an important role in ensuring the success of business activities. Through close coordination, it is possible to determine and specify local requirements for data and analytics solutions. With their various functions and skills, the teams join force to develop the prioritised use cases. This creates dynamic interaction that promotes innovation and efficiency. When it comes to use cases in particular, new ones are frequently added to generate additional added value for the organisation.

An agile organisation helps manage growth and change

Since its foundation, the Data & Analytics unit has adopted an employee-oriented, agile organisational structure (similar to the “Spotify model”). By combining different agile methods, cross-functional teams known as “squads” can organise themselves flexibly without neglecting the individual development of each employee. In addition to the squads, there are experts in the same job function (e.g. data engineers or data scientists) who belong to so-called “chapters”. These chapters serve as a platform for exchanging knowledge and experience, developing best practices and supporting each other beyond the boundaries of a single squad.

In terms of technology, the analytics world has changed significantly since the unit was founded. This means that many companies that relied on their own Hadoop clusters in the past when implementing data science and big data use cases have now transitioned to more modern cloud solutions. ALDI DX has, too. Consequently, the importance of continued training and the corresponding expansion of employees’ skill sets is growing. The greater level of maturity in the data and analytics area also means that topics such as DevOps, MLOps, operations, automation and scalability are becoming increasingly important.

Error culture means doing things differently sometimes

In times of rapid growth, having an agile organisational structure and an open feedback and error culture helps us to try out new things. True to the motto “fail fast”, the Data & Analytics unit keeps things working while learning from mistakes. 

Key learnings from its two-year growth journey include, for example, the need to be flexible at all levels – from developers to senior management. There are the typical roles that have become established in agile data organisations: Data Engineers, Data Scientists, Frontend Developers, Machine Learning Engineers, Product Owners, Scrum Masters, Data Stewards and more. However, an agile team works together towards a common goal of implementing a use case successfully. This means that a Data Scientist may sometimes take on data engineering tasks, or a Data Engineer may help out as a Front-end Developer, and vice versa. The key is working together to create a product with added value.

Over time, the ALDI Data & Analytics unit has also learned a lot about how to best build a squad. In the beginning, the main focus was on data science, but it has since become clear that data engineering is just as important.