And welcome back again, in this last video of the first module we will talk about the cost structure, and touch upon the levels of human resources [INAUDIBLE]. There are seven modules in this course. In this introductory module we have already talked about the cost itself, and its principles. We will also talk about the importance of human resources data analytics will change in society, technology, and human resources function. And we will go over the aspects of people analytics capabilities. The second module, we'll discuss the centerpiece component of the class, performance management. Understanding how performance is managed is paramount to utilizing people management tools that affect performance. In all subsequent modules we will refer to performance metrics. To measure the influence of various people management processes on organizational performance. The third module, will deal with culture and values, which are similarly hard to measure even though they affect performance on strategic and organizational level. The fourth, and fifth module, we'll discuss engagement as well as non-monetary, and financial incentives. In the sixth model, we will cover probably the most fun and talked about part of recruitment in workforce management. And the final model will be dedicated entirely to management people development programs, and measuring their return on investment. Most businesses spend a lot of money on people. Depending on the industry, and organizational structure, some 40% to 70% of expenses are directly or indirectly connected to employees. However, without proper analytics, how do we know if we spent the money in the right way? People analytics is a set of tools that helps us to understand whether what we're doing in terms of. Human capital is right, and beneficial for the organization. Efficient spending is the first challenge people solves. Human capitol is a key answer for many organizations, and it is also a key competitive advantage for many market leaders. It drives business performance. Yet it is which is an obstacle to performance improvements. Making alterations in what, and how we measure, using the second part of the. Finally, efficient investments. Not all organizations pay competitive salaries, but they often make additional investments in attraction, selection, assessment, and development. The last part alone is approximately $1,200 to $1,400 US per employee in the United States. Those investment decisions, and improving them is yet another challenge people wanna analytics is solving. Most other business functions naturally started applying data, and logics long time ago. Manufacturing, marketing, finance, it had to come to human resources. Knowing that part of people management is a necessity, not an option anymore. There are two facets of human resources data analytics. One is the quality of the data itself. This includes the timeliness, and consistency of the data. The most advanced analytics tools would be rendered useless if your data can't be trusted or doesn't measure what matters. The second facet, is what you do with your data. At the fundamental level, you collect, measure, and report statistics and conduct descriptive analytics. You try to understand what happens. How many employees left? What was the attrition level last year? What was the median salary at your call center? At the basic level, you do this reactively, when asked. At the more advanced reporting level, you do this proactively. Building dashboards for executives who can act upon this data providing analysis of trends, and doing benchmarking. At the Advanced Analytics or Diagnostic Analytics level, data from different sources, both internal and external, are integrated. At this point, you're able to answer questions like, why is my attrition so high? Why are some of my employees more productive than the others? Why did some of my employee's performance decrease after we started subsidizing lunches? Predictive analytics is a level that allows you to integrate even more data including business performance data. You'll answer questions about the future. What'll happen if I implement the dual compensation model? How many employees will I need if I open a new location next year? Prescriptive Analytics uses deep learning to support, or even automate decision making based on your external and internal data analysis. It allows you to predict the future.
