This course is designed to provide you with an understanding of the role of data and technology in human capital management. Every topic in the course will be covered in the most practical way so that learners get hands-on experience. In the course we use the 4Ts principle: Task, Theory, Technique and Technology so that there is always a connection to organizational performance objectives, an overview of underlying theories and principles, and specific tools which help achieve business objectives. You will learn ● what combination of data, technologies, and tools can be used in people management processes to improve organization’s performance ● how to use some of these tools and how to select the ones that suit your objectives and budget ● to design individual and team development plans and measure its ROI for the organization ● how to figure out the qualities that lead employees to their best performance so you know what to encourage in current and look for in new employees ● how to identify the right channels to recruit your employees or team members ● what combination of monetary and non-monetary motivation tools work best for your organization ● how to predict what people will leave in the near future and how to make sure some of them stay ● how to measure engagement and make a strong organizational culture improve performance
Lecture 3 Course Structure
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来自 Moscow Institute of Physics and Technology 的课程
人力资源分析概论
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从本节课中
Introduction
As the name suggests, this module will introduce the course and its content, as well as give an overview of what triggered the explosion of People Analytics.
与讲师见面
Ilya BreymanAdjunct Professor
Center of Innovative Educational Technologies
Alexey DolinskiyAdjunct Professor
Center of Innovative Educational Technologies
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.
