TrakSYS in Action
454%
3-year ROI
$3.25M
in revenue gained annually
28%
fewer manufacturing errors
$2.32M
in savings on materials costs
9 Months
to payback
Through in-depth interviews with leading global manufacturers, International Data Center (IDC) worked to establish the value and impact of Parsec’s manufacturing execution system, TrakSYS, on manufacturing operations. In its 20-page analysis, IDC explores the cost and resource efficiencies businesses gained by utilizing TrakSYS.
To discover IDC’s findings, download the value study now.
- Proof points from executive summary.
- Achieve better business results by saving on material costs, enhancing team performance, and reducing manufacturing errors.
- Improve the efficiency and effectiveness of plant floor operations.
- Increase the productivity levels of operations staff across production, maintenance, and quality control.
Download our value study to learn more.
Want to learn more about how TrakSYS is optimizing manufacturing
operations worldwide? Explore our customer-centric case studies now.
Gartner® Critical Capabilities for MES
Parsec Scores Highest in 3 out of 4 Use Cases in 2023 Gartner® Critical Capabilities for MES.
MES: The Key to Strong Manufacturing Compliance Amid Changing Regulations
Learn about the most important manufacturing compliance regulations and how an MES (or Manufacturing Execution System) ensures total control of your production.
Leveraging TrakSYS for Digital Twins in Manufacturing
Discover How TrakSYS facilitates the creation and optimal utilization of digital twins.
Nearshoring vs. Onshoring: What Are They and How Do They Affect the Manufacturing Industry?
Learn the difference between nearshoring and onshoring and how they impact the manufacturing industry.
The Business Value of TrakSYS: Four Key Takeaways from IDC’s Recent Study on the Platform
IDC conducted in-depth interviews with a selection of Parsec customers to uncover why industry leaders across Europe and America chose TrakSYS.
AI + MES
Learn how your MES can improve the efficiency of pharmaceutical production by streamlining AI-driven process automation