The occursus model© for data-based decision-making
This model strengthens leaders in making well-informed decisions, embeds data literacy and a shared data culture, creates orientation within complex organisations, and connects data, people and processes into a learning system.
occursus does not treat data as an end in itself, but as the foundation for orientation, prioritisation and responsible decision-making in complex systems.
My purpose is, that organisations make better decisions – decisions based on relevant data and capable of solving real problems effectively.
01
Analysis and Contextualisation
Analysis of existing data landscapes, systems and sources; positioning data within the context of strategy, organisation and decision-making processes; and clarification of the truly decision-relevant questions.
02
Building Data Literacy and Data Culture
Developing a shared understanding of data and KPIs, strengthening interpretation capabilities, and establishing an open, learning-oriented data culture.
03
Building a network
Connecting internal and external experts, involving business units, management, IT, academia and partners, and breaking down silo structures.
04
Facilitation Formats
Design and facilitation of dialogue, working and decision-making formats; translating data into clear narratives and visualisations; and fostering shared interpretation instead of isolated reporting.
05
Structuring and Implementation
Defining clear decision-making processes, roles and responsibilities, embedding data-based decisions into everyday practice, and deriving concrete actions.
06
Controlling and Learning
Reviewing impact and goal achievement, challenging assumptions, deriving learnings and continuously evolving decision logics.
Data-Driven Decision-Making for Organisations and Destinations
Organisations today have access to more data than ever before. At the same time, many leaders struggle to translate this data into meaningful strategic decisions.
Data alone does not create insight. Only when data is interpreted, discussed and connected to concrete questions can it become a reliable basis for decision-making.
Through occursus I support organisations, destinations and companies in creating the foundations for effective data-driven decision-making.
Data-Driven Decisions in Organisations
Many organisations already collect large amounts of data. Nevertheless, strategic decisions are still often based mainly on experience or assumptions.
The challenge usually lies not in the data itself but in the structure of decision-making processes.
Together we analyse:
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what data is already available
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which information is actually relevant for decisions
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how data can be presented and interpreted clearly
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how decision-making processes are structured
Based on this analysis we develop a decision architecture that connects data, experience and dialogue.
Data Literacy and Data Culture
One of the biggest challenges in working with data is not technology but organisational culture.
Many organisations already have dashboards and reports, yet teams have never learned how to truly use them.
Therefore a central part of my work is the development of a strong data culture.
This includes:
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building data literacy within teams
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understanding how to interpret data in context
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creating structured decision processes
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facilitating dialogue around data and insights
The data:room as a Space for Data-Driven Decisions
An important element of this work is the data:room by occursus in the Kammgarnfabrik in Hard near Lake Constance.
The data:room is a curated environment for organisations that want to explore complex questions and make better decisions based on data.
Three elements intentionally come together here:
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data
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space
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dialogue