Digital Transformation at wienerberger

Digitalization and artificial intelligence (AI) are no longer visions from the future, but crucial factors for a company’s success.

The journey toward digital transformation is particularly challenging for decentralized organizations with a large number of independent locations. wienerberger has more than 200 production sites in 28 countries worldwide and thus faces the challenge of efficiently standardizing IT processes across all its business sites and countries.

At the same time, AI is changing the way companies work – in areas from production to maintenance and decision-making. What role does AI play today and what does the future hold?

In this interview, Franz Lesiw, CIO & SVP Group IT & Digitalization offers insights into wienerberger’s digital transformation, how the company uses AI and the importance of IT security in an increasingly networked world.

Efficiency and costs in particular pose a challenge in digitalization: No two wienerberger plants are the same – each one has its own processes and standards. A brick plant needs a different IT solution than a pipe factory, and the different IT solutions themselves are also becoming increasingly specialized. 

Franz Lesiw: The particular challenge facing us is that wienerberger is an international group with a centralized headquarters, but that it also has strong local structures. It is not therefore a matter of countering decentralization as such, but of reconciling centralized and local requirements in the IT organization. At wienerberger we do this by combining centralized and local structures in an integrated IT organization. What counts is our people’s expertise, not where they work – responsibility is borne both globally and locally.

To maintain this balance, we need clear roles and also flexible responsibilities. This allows us to pool our expertise, avoid silos and makes it easier to adapt the system to individual areas. In this respect, digitalization is not just a technological issue, but also a question of organizational structures and culture.

Franz Lesiw: Our digitalization strategy is based on a standardized architecture: the infrastructure, such as the network and the communication architecture, is the foundation on which we can build further processes. Only if this foundation is standardized and secure will everything that is built upon it work. Regardless of whether you have a group-wide platform used across multiple sites and countries or a country-specific solution, they all need the same backbone.

Conversely, at wienerberger we use these platforms to enable scalability, i.e., we try to achieve the best possible results in both directions: Standardization and individualization.

The umbrella project to extend our Enterprise Resource Planning software solution (ERP/SAP) is a good illustration of how important it is that IT and the business work together.

This project has lifted our platform, which is used in over 25 countries, to a new technological level. The project was driven by IT but implemented in close collaboration with the business. A key factor in its success was the close involvement of all participating countries and the high level of transparency in the decision-making processes. 

With the advent of so many AI chatbots and AI search engines, artificial intelligence has gone mainstream. So, there is a lot of hype about it. In companies, too, artificial intelligence is increasingly being used in business processes. 

Artificial intelligence is much more than a temporary fad – it will permanently change the way companies work and grow. However, a pragmatic approach is essential: AI should be used where it adds real value.

Not everything that claims to be AI is actually AI - and nor should AI be allowed to get everywhere. Despite all the enthusiasm for the technology, it is important to ask critical questions and to first understand the problem before attacking it with the “AI sledgehammer”.

At wienerberger, AI therefore plays a supporting role in two areas: in automation and workforce efficiency on the one hand, and in data science or data analytics on the other.

Where employee efficiency is concerned, we use tried-and-tested tools where AI can show off its strengths – in particular, for creative and text-based tasks. One example of this is Microsoft Copilot, which we are currently rolling out across the Group for all white-collar workers.

In the area of data science, the applications are more specific and involve collecting data from production processes or machine control systems and then using AI to process it.

Take for example a project at wienerberger Austria. The challenge: the amount of manual work required to deal with customer inquiries about product compatibility. Currently, office staff have to compare multiple product data sheets by hand. Our solution therefore is to use a Large Language Model (LLM) that is “fed” with internal data and allows the targeted processing of customer inquiries via an AI supported chat.

In addition, the collected data can be used to optimize production processes with the help of AI. Having a collection of production data for a particular plant lets you identify certain anomalies and question processes, such as “Why is shift A 10% more productive than shift B?”, “What settings did shift A use that made it more efficient than shift B?”

Traceability is important in any technology – but especially where AI is concerned. The AI should not be a black box and must be closely monitored and controlled. The result of an AI query must be transparent and traceable. This prevents misinformation and ensures that decisions are transparent and comprehensible.

While digitalization brings numerous benefits, it also presents companies with new security challenges. The increasing networking of machines and systems in particular requires a stronger focus on IT security. This is not just a matter of technical solutions but about raising employees’ awareness of cyber-attacks, such as phishing and social engineering. 

The more digitalization there is, the more important IT security becomes. Notwithstanding all the advantages, increasingly networked machines also harbor challenges. They require closer cooperation between IT and OT teams (Operational Technology).

The problem of social engineering and the resulting threat of malware now also plays a prominent role in IT security. In a large, decentralized company, individual employees are especially vulnerable to phishing attempts. 

Suggestion: Data protection and compliance are essential and require a combination of clear governance, the right technology and a conscious corporate culture.

We have established a structured data protection organization that defines clear responsibilities in IT and the business areas. Furthermore, we have appointed data protection officers (DPOs) in our regions and at our plants to ensure that data protection measures are embedded both locally and globally.

In terms of technology, we rely on secure storage, encryption, regular backups and strict access controls to ensure optimum protection for sensitive data.

Our corporate culture, though, is also a crucial factor: Our approach is to minimize and classify data - less is often more. This means that we don’t store data for longer than is necessary but systematically delete it when it is no longer needed - even though storage capacity is hardly a constraint these days.