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Modern production facilities produce large amounts of data. The computational framework often referred to as big data analytics has greatly improved the capabilities of analyses of large data sets. Many manufacturing companies can now seize this opportunity to leverage their data to gain competitive advantages for continuous improvement. Six Sigma has been among the most popular approaches for continuous improvement. The data-driven nature of Six Sigma applied in a big data environment can provide competitive advantages. In the traditional Six Sigma implementation – define, measure, analyze, improve and control (DMAIC) problem-solving strategy where a human team defines a project ahead of data collection. This paper aims to propose a new Six Sigma approach that uses massive data generated to identify opportunities for continuous improvement projects in a manufacturing environment in addition to human input in a measure, define, analyze, improve and control (MDAIC) format.

The proposed Six Sigma strategy called MDAIC starts with data collection and process monitoring in a manufacturing environment using system-wide monitoring that standardizes continuous, attribute and profile data into comparable metrics in terms of “traffic lights.” The classifications into green, yellow and red lights are based on pre-control charts depending on how far a measurement is from its target. The proposed method monitors both process parameters and product quality data throughout a hierarchical production system over time. An attribute control chart is used to monitor system performances. As the proposed method is capable of identifying changed variables with both spatial and temporal spaces, Six Sigma teams can easily pinpoint the areas in need to initiate Six Sigma projects.

Based on a simulation study, the proposed method is capable of identifying variables that exhibit the biggest deviations from the target in the Measure step of a Six Sigma project. This provides suggestions of the candidates for the improvement section of the proposed MDAIC methodology.

This paper proposes a new approach for the identifications of projects for continuous improvement in a manufacturing environment. The proposed framework aims to monitor the entire production system that integrates all types of production variables and the product quality characteristics.

As organizations aim to become increasingly diverse, it is important to understand how perspectives of potential future leaders vary across culture and gender. This study aims to advance the understanding of the persistent gender gap in management.

Samples from the gender-segregated Qatar and the co-ed Denmark present a unique opportunity to investigate the potential effects of gender. Here, 115 Middle Easterners and 121 Scandinavians rated perceived importance of job-related skills, networking upward and serendipity in leadership acquisition.

Effects of gender showed that compared to men, women across cultures expected that serendipity has less to do with leadership acquisition. Middle Eastern women also showed low expectations regarding networking with people in powerful positions. Nevertheless, both genders showed conviction of meritocracy by rating job-related skills as the most important factor in leadership acquisition. Cross-culturally, Scandinavians presumed job-related skills to be more important than Middle Easterners.

Despite meritocracy beliefs, it appears that gender differences in perceived possibility of leadership acquisition contribute to the gender gap in management. Scandinavian women relied more on networking than Middle Eastern women, but still lacked faith in serendipitous opportunities compared to male peers. Perceived luck enhances achievement motivation. If men rely more on luck than women, then they are more confident in succeeding and more ambitious about pursuit of leadership. Women’s lack of faith in serendipity might affect their career ambitions negatively even in societies emphasizing equality.

This is the first study that directly focuses on gender differences in perception of opportunities for leadership acquisition through serendipity.