August 2019
This two-day intensive workshop is specially developed to provide a solid foundation in financial analysis and decision-making, both from the perspective of the company and specific projects.
Financial Skills for Non-Finance People is an interactive workshop format including exercise, case studies, and real world projects to improve participants understanding and application of:
- Financial analysis tools and how to apply them to value new products and programs
- Basic and advanced techniques to make tradeoff and a portfolio decisions for product investments
- Financial techniques to communicate and sell advanced R&D, platform and architecture programs
October 2019
Training Dates: Oct. 2-3, 16-17, 30-31, Nov. 13-14, and Dec. 4-5.
Participants in this 10-day duration course will learn the theory and application of tools and methods for successful completion of improvement projects in a manufacturing business environment. Tools for the application of the Six Sigma DMAIC (Define-Measure-Analyze-Improve-Control) improvement strategy will be introduced with hands-on exercises and tutorials to ensure rapid learning and knowledge retention. The training style is tell-show-do, with a strong emphasis on individual hands-on exercises and team-based activities. Training workbooks are comprehensive, self-contained, and serve as excellent references for learning and review. Classroom training sessions are interspersed with periods of work on actual company-supported improvement projects.
Find out moreToday’s highly competitive environment leaves no time for trial and error. Design of Experiments (DOE): Introduction provides a structured method for determining the relationship between factors affecting a process and the output of that process. With this information, you can quickly develop the optimum balance between factors leading to dramatic improvements in quality, cost, and productivity. Participants in this 16-hour course will gain a firm understanding of the statistical concepts and basic principles underlying Design of Experiments.
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