General briefing

The Handtmann Group is a globally active, family owned technology enterprise headquartered in Biberach an der Riß, Germany. The group combines long term entrepreneurial thinking with advanced industrial technologies and employs several thousand people worldwide. Handtmann operates through multiple business divisions, including Light Metal Casting, Systems Engineering, Plastics Engineering, Process Technology, and Processing, serving industries such as the automo-tive, mechanical engineering, food technology, and pharmaceutical sectors.

Within the group, Handtmann Light Metal Casting is a core division. The division focuses on the development, production, and machining of high quality aluminum die cast components, prima-rily for the automotive industry, including structural, chassis, and powertrain related parts.

Challenge

Handtmann works with many different types of data, including market data, production data, customer data, and engineering or construction data. Today, this data is stored across many se-parate systems and tools, such as SAP, Microsoft Office applications, and various production and machine specific software systems. Because data is distributed, heterogeneous, and often diffi-cult to combine, business departments cannot use it efficiently for analysis, decision making, or advanced use cases such as artificial intelligence.

To address these challenges, the organization plans to build a central data platform that consoli-dates relevant data sources and enables self service data usage. The platform should allow busi-ness users to independently access, combine, and analyze data while ensuring data quality, transparency, security, and scalability. In addition, the platform should create the foundation for advanced analytics and future AI driven applications.

Considering these challenges, Handtmann raises the following question:

How can an AI-based, scalable, self-service data platform unify fragmented business and production data into a secure, governed, and AI-ready ecosystem and enable decentralized decision-making across the Handtmann Group?

Questions to be explored

The following questions guide you in developing your concept and showcasing the value of your MVP:

What is the core problem being addressed, and how does it manifest in the current situati-on at Handtmann?
What measurable business value does the proposed solution create for Handtmann?
Which alternative solution approaches could be considered instead of implementing a cent-ral data platform, and how do they compare?
Which constraints (e.g. technical, organizational, legal, ethical, or economic) must be taken into account when addressing this problem?
Which skill development and change management measures are required to ensure success-ful adoption and effective use of the data platform?
Which factors are critical to ensuring the successful implementation and long term operati-on of the data platform?
How can Handtmann scale the data platform from initial use cases to an organization wide solution?
How does the minimum viable product (MVP) demonstrate both technical feasibility and business value?
Which governance, compliance, and security aspects must be considered when implemen-ting and operating the data platform?
Which data layers should be integrated to ensure effective data ingestion, transformation, and consumption processes (e.g. ETL / ELT)?
How can the data platform be integrated into Handtmann’s existing IT and data infrastruc-ture?
How should the data platform be designed to serve as a foundation for future AI applica-tions?

Requirements

Business Impact and Measurability: The solution must provide clear metrics and key performance indicators (KPIs) to measure its impact and effectiveness in addressing the identified business challenges.
Security, Compliance, and Data Governance: The solution must implement robust access controls, security mechanisms, and governance structures to ensure compliant and secure handling of sensitive business data.
Organizational Ownership and Accountability: Clear ownership and responsibilities for the platform must be defined across business and IT. Roles such as data owners, platform owners, and product owners should be explicitly assigned to avoid governance gaps.
Traceability and Auditability: All data transformations, logic definitions, and results must be transparent, reproducible, and auditable to ensure accountability and trust in the solution.
Integration Capability: The solution must integrate with SAP S/4HANA as the ERP system and Microsoft 365, and remain open for the integration of additional data sources, such as production data from different ma-chines.
Automation Capability: Logic and workflows created by users on the platform must be executable automatically, either on a scheduled basis or triggered by events.
Technology Foundation and Architecture: The solution should be based on open source technologies and follow modern software archi-tecture principles to ensure scalability, flexibility, and maintainability.

Goals and outcome

The goal of this challenge is to design a scalable data platform concept that can evolve from ini-tial use cases to an organization wide solution. In addition, participants are expected to de-monstrate that the proposed solution is technically feasible and valuable by means of a Mini-mum Viable Product (MVP).

Moreover, a successful solution:

can realistically be implemented and adopted within the organization
addresses long term operation, maintenance, and ownership concepts
serves as a foundation for future AI applications

The winning team will have the opportunity to present their solution at Handtmann and discuss potential implementation with the digitization and data science team.

Knowledge base

Once you have decided on this business case, you will receive details regarding the specific or-ganizational and technical conditions, as well as the APIs and data sources available (structure and content).

Sina Zimmermann and Torben Disselhoff are available for Q&A sessions via Microsoft Teams at the following time slots:

17.04. – 10:00
12.05. – 10:00
09.06. – 10:00