Digitalization

Definition

Digitalization refers to the process of transferring analogue, manual, or paper-based processes, data, and workflows into digital systems. The goal is to capture, connect, and utilize information in a structured way in order to sustainably improve efficiency, transparency, and quality within organizations.

Expanded Explanation

Digitalization goes beyond simply converting paper documents into digital formats. It includes the implementation of digital systems, automated workflows, and connected data structures that holistically represent and optimize processes. In laboratory and industrial environments, digitalization affects areas such as data acquisition, documentation, analysis, system integration, and decision-making processes.

Without digitalization, data often remains trapped in silos, processes are prone to errors, and decisions are based on incomplete information. Digital platforms, cloud technologies, and automation make it possible to use data across systems, standardize processes, and unlock new capabilities such as AI-powered analytics and predictive models.

Key aspects of digitalization include:

• Digital data capture
  Replacing manual and paper-based documentation
• Process automation
  Reducing manual steps and sources of error
• System connectivity
  Integrating laboratory, analytical, and enterprise systems
• Transparency & traceability
  Creating consistent, end-to-end data flows
• Foundation for AI & analytics
  Enabling data-driven decisions and innovation

Relevance to LabV

LabV views digitalization as the foundation for Material Intelligence. By digitalizing laboratory processes, material data, measurement relsuts and workflows, LabV creates a central, structured data foundation that enables AI-powered analytics, automated workflows, and informed decision-making. Instead of relying on isolated tools, LabV connects data, systems, and processes into a seamless digital laboratory environment in particular for R&D.

FAQ

Why is digitalization important in laboratories and industry?

It reduces manual work, prevents errors, improves data quality, and creates transparency across processes and results—an essential prerequisite for efficiency, quality assurance, and competitiveness.

What is the difference between digitalization and automation?

Digitalization refers to transferring processes and data into digital systems, while automation builds on digitalization by executing recurring tasks automatically.

Which areas are typically digitalized?

Typical areas include data capture, documentation, analysis, quality management, system integration, and decision and approval processes.

Synonyms & Related Terms

Digital transformation, digital process design, process digitalization, digital workflows

Internal Links

Laboratory Informatics, Laboratory Data Integration, Data Synchronization, AI in the Laboratory, Cloud Computing, Material Intelligence