A leading German organic food manufacturer created a comprehensive digital twin of its administrative processes within just three days using AI-supported, role-based micro-interviews. This innovative approach provided rapid, end-to-end transparency into how work is actually performed across the organization, forming a reliable foundation for their ERP target vision and digital transformation roadmap.
The client is a mid-sized German food manufacturer specializing in organic dairy products. With over 200 employees and multiple production facilities, the company had grown significantly over the past decade. However, this growth had led to increasingly complex administrative processes that were poorly documented and highly dependent on individual knowledge.
The company was preparing for a major ERP implementation but faced a critical obstacle: they lacked clear visibility into their actual business processes. Traditional process documentation methods had proven too slow, too expensive, and often failed to capture how work was really done.
Critical process knowledge was locked in the heads of long-tenured employees, with no systematic way to extract and document it.
The ERP project timeline demanded rapid process discovery, but traditional workshops would take months and disrupt daily operations.
Existing SOPs were outdated and didn't reflect actual work practices, leading to a dangerous gap between documented and real processes.
Previous documentation efforts had met resistance from employees who felt their time was wasted on lengthy interviews and workshops.
Working with Machines Like Me, the company deployed an AI-powered micro-interview system that conducted automated, conversational interviews with employees across all administrative departments. The system used natural language processing to guide contextual conversations, automatically extracting and structuring process information.
Short, focused 10-15 minute conversational interviews conducted by an AI agent, designed to minimize disruption while maximizing information capture.
Interviews were tailored to each employee's specific role and responsibilities, ensuring relevant and accurate process information.
AI automatically synthesized responses across multiple interviews to build comprehensive process maps and identify patterns.
All captured knowledge was transformed into a searchable digital twin, enabling instant access to process information.
The entire process discovery initiative was completed in just three days, a fraction of the time traditional methods would require.
System configuration, role mapping, and launch of first interview rounds with key process owners.
Conducted over 400 micro-interviews across all administrative departments simultaneously.
AI synthesis of all interviews, generation of process documentation, and validation with department heads.
The digital twin initiative delivered transformative results, providing unprecedented visibility into the organization's processes and establishing a foundation for continuous improvement.
“In three days, we achieved what would have taken us six months with traditional methods. But more importantly, we finally understand how our business actually operates, not just how we thought it did.”
The rapid timeline kept information fresh and employees engaged, leading to more accurate capture than drawn-out traditional methods.
The AI interviewer asked consistent questions and captured responses objectively, eliminating the bias that often creeps into human-led workshops.
Short, focused interviews respected employees' time and resulted in higher quality responses than lengthy workshop sessions.
The digital twin isn't a one-time deliverable but a living asset that can be continuously updated as processes evolve.