How does Scientific Management suggest improvements should be made?

Scientific Management, developed by Frederick Winslow Taylor in the early 20th century, emphasizes the importance of systematic study and analysis in improving work processes and productivity. The theory advocates for making decisions based on objective data rather than subjective opinions or individual experiences.

Improvement under Scientific Management is achieved through ongoing analysis and data-driven results. This involves breaking down tasks into smaller, manageable parts, studying their efficiency, and determining the best methods to enhance productivity. The focus is on measuring performance, analyzing workflows, and applying standardized practices to ensure that operations are as efficient as possible.

In contrast, seeking improvements through consensus with all employees does not align with the principles of Scientific Management, which prioritizes scientific methods over individual opinions and group discussions. Increased employee meetings might facilitate communication but do not directly correlate with the systematic analysis that Scientific Management advocates. Random evaluations lack the structured approach that data-driven assessments provide, making them less effective in identifying specific areas for improvement.

By relying on continuous observation and empirical evidence, Scientific Management provides a framework for organizations to optimize their operations in a methodical manner.