My Energy to the Moon? Combining Human Energy Tracking with Financial Chart Analysis for Advanced Desktop Work-Life Tracking

The current working world is characterized by increased flexibility, complexity, and speed while work from home is on the rise. In this context, managing one’s resources becomes even more important to stay healthy, productive and reach one’s goals. One approach for this is to continuously reflect on individual work-related, mental and behavioral variables to retain a high level of human energy, productivity, and well-being during work. In this direction, we have already proposed and implemented a tool in the intersection of automatic computer-based activity tracking and continuous assessment of well-being [11]. The tool, called Desktop Work-Life Tracker (DWLT), can semi-automatically track variables such as human energy and sentiment, sleep quality as well as five user-defined variables in the evening. However, what is still missing so far are capabilities for advanced analytics to observe trends or spot patterns. In the work at hand, we first introduce the current tool. We then present two real-world datasets on human energy self-assessments and apply analysis methods known from financial chart analysis such as MA, MACD, Bollinger Bands and cross correlation. Results are promising and due to this, we report on our plans to integrate these advanced analytic capabilities into the existing DWLT.