Draft:NSTec Daylight Saving Time Predictive Analytics Project

The NSTec Daylight Saving Time Predictive Analytics Project analyzes the impacts and behavioral patterns related to the biannual time changes associated with Daylight Saving Time (DST). This project uses predictive analytics to assess factors such as energy consumption, health effects, road safety, and overall societal impacts that correlate with these time shifts. By leveraging data and analytical tools, the project seeks to provide insights that can help optimize systems affected by DST, potentially leading to recommendations for policy adjustments or public awareness campaigns. The ultimate goal is to enhance understanding of DST's broader implications on daily life and support data-driven decision-making.

Results

Through the detailed analysis of NSTec incident history for the week following DST (root cause), NSTec worker demographics and related aging process, memory retention, specific informative articles to target related causal factors, and a call-to-action, NSTec was able to achieve a company first for 2016: zero incidents.

On August 8, 2016, NSTec Daylight Saving Time Predictive Analytics Project research was published by OPEXShare, the US Department of Energy platform for Best Practices and Lessons Learned. OPEXShare is an electronic repository, a tool for achieving operational excellence, accessed by US Department of Energy employees and contractors to the US Department of Energy with a readership base of over 250,000 readers. NSTec Daylight Saving Time Predictive Analytics Project was required reading by the US Department of Energy employees and contractors to the US Department of Energy, including the Thomas Jefferson Accelerator Facility, Newport News, VA.

The US Department of Energy Operating Experience Committee (OEC), Coordinated by the Office of Analysis (AU-23), invited David Pechulis, NSTec Ergonomist, and principal data scientist, who conducted the historical incident research for the previous 12 years, data analysis, behavioral analysis, demographics, health-related factors, predictive modeling, behavioral modification strategy, and success for NSTec Daylight Saving Time Predictive Analytics Project to present to the OEC.

“Excellent work!” - Kirk Lackman, Deputy Chief EM3 DOE HQ

In November 2016, David Pechulis was awarded the prestigious Sustaining Outstanding Achievement in Research (Soar) Award from NSTec in coordination with OPEXShare, US Department of Energy. By August 2017, the NSTec Daylight Saving Time Predictive Analytics Project reached #4 out of 50 (Top 50) in popularity as determined by the readers of OPEXShare. The research was the second highest-rated for NSTec at #4. The highest-rated research on OPEXShare Top 50 for NSTec was qualitative research conducted by David Pechulis, Ergonomist, NNSS, Evaluating the Use of Sit to Stand Workstations published to OPEXShare on 01/09/2017. Evaluating the Use of Sit to Stand Workstations reached #2 out of 50.

Research significance

The Daylight Saving Time Predictive Analytics Project was significant for research in several ways:

1. Innovative Approach: The project utilized predictive analytics and data mining techniques to address a specific and recurring issue related to Daylight Saving Time (DST). This innovative approach provided valuable insights into the impact of DST on workplace safety and productivity.
2. Data-Driven Insights: By analyzing various factors such as sleep deprivation, worker age-related health data, and environmental factors, the project generated data-driven insights that could be used to predict and prevent incidents. This approach can be applied to other workplace safety and health research areas.
3. Practical Applications: The findings from the project had practical applications in improving workplace safety and reducing lost workdays. implementing preventive measures based on the project’s insights could lead to a safer and more productive work environment.
4. Communication Strategies: The project also emphasized the importance of effective communication strategies to ensure employees understood and remembered the preventive measures. This aspect of the research can be valuable for other safety and health initiatives.

Overall, the project contributed to the broader field of occupational health and safety research by providing a data-driven framework for addressing the challenges posed by Daylight Saving Time.

Background

National Security Technologies (NSTec) was the management and operating contractor for the Nevada National Security Site (NNSS), which is part of the U.S. Department of Energy's (DOE) National Nuclear Security Administration (NNSA). NNSS conducts high-hazard operations, testing, and training in support of NNSA, the U.S. Department of Defense, and other agencies.

NSTec worked closely with several national laboratories, including Lawrence Livermore National Laboratory, Los Alamos National Laboratory, and Sandia National Laboratories, on various national security programs. They also collaborated with other federal agencies to fulfill their national security missions.