Between data quality and process intelligence – what we’re working on

When I look back over the past two weeks and click through the various boards, it’s like looking into a kaleidoscope: many colours, many facets, yet the longer you look, the clearer a pattern emerges. This pattern is not shaped by individual tickets or product names, but by overarching questions. One of them is: How do we ensure that data becomes reliable information? Quality assurance is at the heart of our business, and this is clearer than ever in our day-to-day work. In consulting and product development, colleagues have been working intensively on approaches for automated address and data clearing processes. Workshops focused on how clever fuzzy algorithms detect errors without needing human feedback, and how these mechanisms can be integrated into customer-specific systems. One thing became clear time and again from the discussions: clean data is the foundation for robust analyses and thus for any well-founded decision. This makes it all the more important that we not only offer tools, but also convey understanding – something the consulting team has impressively demonstrated in client meetings.

A second recurring theme emerged from a completely different angle: the integration of processes across system boundaries. In several projects, the focus was not on individual services, but on the interaction between ERP, CRM and platform solutions. This is where the strengths of BPM tools such as ITEROP and the importance of a well-thought-out solution design come to the fore. The teams asked themselves how to model business processes without getting lost in the modelling, and how to orchestrate data flows in such a way that redundancies are avoided and compliance checks take place automatically. This work is heavily influenced by consultancy; it requires us to understand our clients’ business logic and translate it into technical workflows. In internal sessions, we discussed which interfaces should be connected to first, how we can consistently utilise modern APIs, and what role our own services play in this. The conclusion is clear: good integrations create freedom because they relieve the operational business whilst simultaneously delivering reliable data in real time.

A third topic has a more normative dimension. Regulations surrounding artificial intelligence and data protection are evolving rapidly. With the AI Act, the EU has created the world’s first comprehensive legal framework that addresses the risks of AI and aims to ensure its trustworthy use. For us, this means understanding the principles of ‘Privacy by Design’ and ‘Explainable AI’ not as buzzwords, but as an integral part of our product development. There was a lively discussion in the Jira comments about the impact the new regulations will have on our algorithms, how we design training measures, and what verification mechanisms are needed to ensure our solutions remain compliant. Particularly exciting was the exchange between colleagues from Compliance, Development and Consulting: whilst some explained the legal framework, others contributed real-world examples. This dialogue has led to a shared stance: technical innovation is only sustainable if it is also ethically considered.

Alongside these major topics, we focused on the question of collaboration and knowledge transfer. Several teams explored how to incorporate customer experiences, feedback from pre-sales phases and insights from support cases more quickly into product design. There were prototypes for new demo environments, brainstorming sessions on automated migration paths, and regular exchange forums where colleagues from marketing, development and consulting worked together on specific issues. It is these interdisciplinary moments that drive us forward as a company. They remind us that data quality is not just about technology and that compliance is not merely a legal necessity, but that it is always about the combination of subject matter expertise, process understanding and technology.

This paints a picture of the last 14 days that may seem varied, yet is underpinned by a few consistent themes: we are working at the foundation – data quality. We are focusing on interfaces and processes to create solutions that go beyond individual systems. We engage with new regulatory frameworks, not because we have to, but because we believe that responsibility is part and parcel of technical excellence. And we foster collaboration that shares knowledge across departments, so that business requirements are transformed into sustainable solutions. This interplay is what makes our job so appealing – and it keeps us moving forward.