The Hidden Costs of Unconnected Production Data
How to Use Production Data to Create a Reliable Foundation for Operational Excellence
Machines are connected, MES and ERP systems are in use, and dashboards provide key metrics—and yet the information truly needed for quick and well-informed decisions is often missing.
The problem is usually not a lack of production data. What’s missing is a shared context.
Differing KPI definitions across plants, manual analyses in Excel, complex machine integrations, or AI projects without reliable results are often symptoms of the same structural challenge: While production data is collected, it cannot be consistently understood, reliably utilized, or efficiently reused.
What does a fragmented data architecture really cost?
The consequences are not limited to IT and integration projects. They generate ongoing costs—through additional interfaces, repetitive engineering work, maintenance efforts, ad-hoc local solutions, and dependencies on individual experts.
Added to this are costs that don’t appear in any project budget: delayed decisions, a lack of transparency, and untapped potential in analytics and AI.
The Executive Management Guide “The Hidden Costs of Unconnected Production Data” explains why many of these challenges cannot be solved by additional individual integrations—and what role Industrial Data Management plays in addressing them.
Here’s what you’ll learn in the Management Guide:
- Why more production data doesn’t automatically mean more transparency
- What hidden costs arise from fragmented data and integration architectures
- Why many supposed integration problems are actually architectural problems
- How Industrial Data Management turns machine data into trustworthy, contextualized information
- The 7 requirements a future-proof Industrial Data Platform should meet
- How a shared data foundation supports rollouts, analytics, and AI applications
- How you can assess the maturity level of your own production data strategy using an 8-point checklist
From “Machine-Connected” to “Data Usable Company-Wide”
That’s why leading manufacturing companies are taking a more forward-thinking approach to data integration: Production data is captured once, enriched with context, and then reused across different systems and applications.
The goal: a scalable and trustworthy data foundation for MES, ERP, SAP DM, analytics, AI, and other applications—and thus a robust foundation for operational excellence.
