In the complex world of human pharmaceuticals, structured processes are more than just a mark of quality—they are essential for regulatory compliance, efficiency, and scalability. But what happens when a company is faced with a multitude of supposed processes, without knowing how many of them are actually being followed?
Data Overload Instead of Process Clarity
company in the human pharma sector faced a common challenge of our time: a vast, heterogeneous collection of data related to various workflows—but no clear structure. Like puzzle pieces without a picture, the information was waiting to be assembled into a meaningful whole.
The tasks were clearly defined, yet complex:
- How many processes actually exist?
- What do these processes look like in their current state?
- How can they be documented and visualized?
- Manual analysis was out of the question. The data volume was too large, and time was too limited. That’s when a key realization emerged: only the targeted use of artificial intelligence could provide a solution.
As one process team member later put it:
“It quickly became clear: without AI, we wouldn’t have been able to complete this project in the planned timeframe.”
AI-Powered Process Analysis
The main goal was to automatically extract process-relevant information from the existing data collections and turn it into a structured process description—including an initial visual draft.
Timeline: Weeks, not months. Speed was the critical success factor.
Structuring Processes with Microsoft Copilot Studio
The AI solution was chosen for its pragmatic approach: Microsoft Copilot Studio. Implementation followed several steps:
- AI-guided data processing instructions:
Clear guidelines for using AI, tailored to the data landscape. - Prompts for data extraction and visualization:
Targeted inputs to identify process-relevant content and generate BPMN 2.0 diagrams. - Training a small user group:
Users were empowered to work effectively with the AI and generate the desired outputs.
From Chaos to Structure
The results speak for themselves. What began as a data mess turned into a clear, structured overview of all current processes—a roadmap through the maze of actual workflows. For each identified process, a detailed description was created directly in Copilot and later transferred to Word. This documentation now serves as a reliable reference for all stakeholders, turning insights into actionable guidelines.
A particularly valuable outcome: the visual representations. Initial process diagrams were generated as code and could be used directly in BPMN.io. This transformed abstract workflows into clear, visual models that made complex relationships instantly understandable.
Time Savings Through AI
- 35–65% less effort per process
- Only 25% of AI-generated processes required significant manual revision
From Chaos to Clarity
This project clearly demonstrates how AI in process management doesn’t just support—it creates real value. With the right expertise and a clear goal, even an unstructured data landscape can be transformed into a structured process map in no time.