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HR Analytics - Workforce Management using R
Rating: 3.6 out of 5(18 ratings)
124 students

HR Analytics - Workforce Management using R

Using erlang c formula to find out if and how many more agents does the bank need to maintain a good grade of service
Created byUnlock HR
Last updated 4/2020
English

What you'll learn

  • Work Force Management
  • Erlang
  • HR Analytics
  • R
  • Anatomy of Statistical Model to understand the technique of solving any business problem through analytics.
  • Learn how to understand Business problem and what are the key factors.
  • Getting the most out of data using basic analytics technique or you can say Exploratory Data analytics.
  • Applying feature engineering techniques to get in depth knowledge hidden inside the data.

Course content

8 sections16 lectures3h 32m total length
  • Business Problem2:22

Requirements

  • Anyone can take this course

Description

This course revolves around finding the right people to be deployed for a given task at the right time, to ensure that the customer expectations and metrics are being met.  As an HR professional or a business partner, you play an important role, which is managing the workforce.

In this course:

You will learn the basics of workforce management.

Tackle the problem of shortage of employees by performing resource management.

We will solve a business problem that involves customers getting dissatisfied with the customer care service, due to non-availability and high waiting time which leads to customers abandoning the calls.

You will study the call volume data and relate with employee demographics.

Learn about Erlang C and it's applications in Rstudio to predict the number of employees required on an hourly interval to meet customer expectations.

Master practical skills to solve an HR business problem using a Step-by-step approach called “Anatomy of a Statistical Model”.

Understand how to prepare and explore the data for meaningful insights.

Applying feature engineering techniques to get in-depth knowledge hidden inside the data.





Who this course is for:

  • HR proffesionals
  • Data Science Enthusisasts