# Understanding HR Analytics: A Comprehensive Guide

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## Introduction to HR Analytics

In today's data-driven world, Human Resource (HR) Analytics has become a vital component for effective management in organizations. It allows HR professionals to analyze data, derive insights, and make informed decisions based on empirical evidence rather than intuition. In this comprehensive guide, we will explore the essence of HR analytics, the various types it encompasses, the critical tools required, and how HR managers can apply analytics to their practices.

## What is HR Analytics?

HR Analytics, also referred to as People Analytics or Workforce Analytics, is the process of gathering, analyzing, and interpreting data related to an organization’s human resources. By harnessing HR analytics, organizations can:

- Understand and improve employee engagement.
- Optimize recruitment strategies.
- Enhance performance management systems.
- Address learning and development needs effectively.
- Make data-driven compensation decisions.

## The Types of HR Analytics

HR analytics can be categorized into four main types:

### 1. **Descriptive Analytics**

This type focuses on understanding historical data and what has happened in the past. Key outputs include:

- Descriptive statistics (means, averages, etc.)
- Reporting of HR activities and trends.
- Historical performance metrics.

### 2. **Diagnostic Analytics**

Diagnostic analytics seeks to understand the reasons behind past outcomes. It answers questions like:

- Why did recruitment yield fewer candidates last quarter?
- What contributed to high employee turnover?

This type often employs correlation and regression analyses to find relationships between data points.

### 3. **Predictive Analytics**

By utilizing statistical models and machine learning techniques, predictive analytics forecasts future trends based on historical data. It is instrumental in:

- Anticipating employee attrition.
- Projecting hiring needs.
- Forecasting training needs.

### 4. **Prescriptive Analytics**

This advanced type goes beyond predictions to provide recommendations on possible courses of action. It answers questions like:

- What are the best strategies to improve employee engagement?
- How many HR resources are required to fulfill upcoming recruitment demands?

## Key Functions of HR Analytics

For effective application in organizations, HR analytics is generally associated with six core HR functions:

**Recruitment**: Evaluating the effectiveness of recruitment channels and strategies to attract talent.**Selection**: Analyzing data from the selection process to determine the quality of hires.**Learning and Development**: Identifying skills gaps and assessing training effectiveness.**Performance Management**: Measuring employee performance metrics and establishing key performance indicators (KPIs).**Compensation**: Analyzing salary structures, benefits, and equity among employees.**Employee Engagement**: Monitoring employee satisfaction and engagement levels to enhance retention.

## The Role of HR Managers in Utilizing Analytics

HR managers play a crucial role in leveraging analytics to make their departments more efficient. Key responsibilities include:

- Formulating metrics based on organizational goals.
- Regularly collecting and analyzing relevant data.
- Crafting strategies based on the insights gained from analytics.
- Presenting data-driven findings to stakeholders to help with decision-making.

### Gathering Questions for Analytics

To effectively implement HR analytics, start with these foundational steps:

**Identify key questions**: What do you want to resolve with analytics?

Examples: "How many candidates should we attract to fill vacant positions?" or "Which training programs yield the highest ROI?"**List down relevant variables**: Determine the data points you'll need to gather.**Collect and analyze data**: Monitor changes over time and see how they align with your key performance indicators.

## Tools and Techniques in HR Analytics

Several analytical tools and techniques are essential to conducting effective HR analytics:

**Statistical Methods**: Mean, median, mode, and standard deviation for descriptive analytics.**Visualization Tools**: Use software such as Tableau or Power BI to present data visually—graphs, histograms, pie charts, etc.**Regression Analysis**: For predictive analytics, models can identify relationships between various HR functions and outcomes.**Data Management Systems**: Implementing HR Management Information Systems (HRMIS) to capture and analyze employee data efficiently.

### Understanding Software and Visualization

The visual representation of data is vital for conveying insights clearly and effectively. Some tools include:

**Histograms**: To display the distribution of employee ages or performance ratings.**Bar Graphs**: For showing numbers across departments or the gender pay gap.**Pie Charts**: Useful in representing recruitment sources, showing internal versus external applicant ratios.

## Conclusion

In conclusion, HR analytics is a transformative tool that enables organizations to make informed and strategic decisions regarding their human resources. Understanding the various types of analytics, core functions, and tools available is essential for HR managers aiming to harness data for organizational success. By focusing on descriptive analytics initially, HR professionals can develop a strong foundation that paves the way for future advancement in diagnostic, predictive, and prescriptive analytics. The journey may seem complex, but the insights gained can lead to substantial improvements in hiring, engagement, and overall performance management within an organization.

will learn the basic things about the HR analytics what HR analytics is what are the types of how HR manager makes the

decision what are the things that HR manager does what HR manager should know in order to use the HR analytics in his

or her organization so it is the basic and introductory session on HR analytics so let us start with the content what is

the content so first thing that we will understand that is the uh introduction to HR analytics so that this is the

first thing that is what we will discuss next question that HR analytics can answer what type of questions that HR

analytics can answer what type of questions that you can frame and then you can get the questions answers of

those questions next one is the types of an analytics what are the types of the analytics so here you can see there is a

three types of the analytic four types of the analytics descriptive right and then what are the

tools of the descriptive analytics how you can visualize Predictive Analytics right and what are the questions that HR

managers should answer types of analytics difference between Mis and HR analytics right so these are the things

is the HR analytics human resource analytics some people say it is the people analytics some people say it is

the workforce analytics so but meaning is the same right things that are done under these analytics is the same so

what I suggest for all HR Manager for starting purpose what this should do about this HR analytics so this should

remember the six functions of the HR right so being a in any organization you are working each manager or each HR

department has to perform minimum six functions so what are those functions so first first function is the

learning right so some in some organization you will see training right so learning fourth function is the

development right you need to develop the employees fifth fun function is the performance measurement of performance

management system and sixth function is the compensation you need to give a salary also right so related to these

function each manager has to make a decision so in this particular course we will learn the basic Matrix related to

these six functions right how you can manage the recruitment effectively by using those matrics right next function

selection how you can manage the selection how you can manage the learning how you can manage the

development how you can manage the performance management system and compensation right so under these three

so these three are the synonyms of the HR analytics whether you call it HR analytics whether you call it people

analytics Workforce analytics but meaning is the same right so basically you will see the matrices related to

you are working first ask what are the basic questions that you need to answer in day-to-day work life right so while

working what are the questions that you need to answer so if you are working in the recruitment Department then people

may ask you how many people you should attract to fulfill the vacant positions which are there how you should if you

are working in the L&D Department training and development department then you may ask what what is the level of

the skill that is required in your employees right and how they can achieve that level of uh uh skill right skill

Gap analysis that you made do it in performance you may ask who is the best performing which department is the best

performing how the salary component should be decided so such kind of questions that you need to answer in

day-to-day right so how you can find out the solutions or answers of those questions through the analytics that is

what we will learn in this course right I hope various matrices that we will discuss in this course that those matric

will help you to find out the solution so I hope so if somebody is saying HR analytics people analytics Workforce

analytics so meaning is same there is no difference in these terms right people analy whether you call it people

analytics HR analytics Workforce analytics everything is same right so I already said what are the things that

will come right I'm not saying if you want to take some other things also that also you can include like engagement is

there leadership analytics is there right motivation that is what you you can case but most of the topics that you

can cover under these six functions only so engagement that you can bring it under the uh performance right and

motivation so if you can see the Learning and Development and performance and compensation both

things can address this motivation issue of the employees so that is how you can bring the motivation aspect under these

functions so if you will think any aspect related to the R analytics you can divide or you can bring under these

six categories just think about it right now question comes what type of questions that you can answer so what

has happened right descriptive questions like what has happened so what has if you are saying your recruitment is

effective so why what has happened so why that recruitment is effective right so if you know the number of application

that you receive after the uh job posting so because of that you are saying that recruitment is effective so

why it is effective what has happened so the number of application has come more so that is why we are saying if you are

people so you are seeing on the basis of quality of hire right that people that you have hired that is good they are

questions that HR analytics can answer for the HR manager HR analytics will help you to find out the answers of such

kind of questions so let us understand the types of analytics so so that you will understand which type of analytics

analytics that we discuss in any so so four types of the analytics so first type is the descriptive

analytics second one is the diagnostic analytics third one is the Predictive Analytics and fourth one is the

prescriptive analytics right so in this course we will focus more and more on this descriptive analytics right so all

60 lessons that you will see in this course they are focusing on descriptive analytics diagnostic predictive and

prescriptive after this course we will develop new course in that we will focus on diagnostic predictive and

prescriptive but in this course uh you will see we are focusing only on descriptive so I suggest the all HR

manager before going to this diagnostic predictive and prescriptive first implement this descriptive

statistics in your department and then think about diagnostic then think about predictive and then go for the

prescriptive right because the moment you will move from descriptive to diagnostic little more little bit more

statistical knowledge that you required the moment you will go diagnostic to predictive then more advancement

Advanced Techniques that you have to learn right and when you will go predictive to prescript Ive then you

have to learn this mathematical modeling and you have to learn uh operational research tool tools and technique also

complexity will increase right and currently most of the organization they are not having the sufficient things

which is required to develop a effective HR analytics department so that's why I recommend in initial stage you start the

using this start this Statistics using uh analytical tool that you start using uh that is the descriptive you should

use the descriptive analytics more and more in the initial stage the moment you feel you have developed the

framework uh for this uh descriptive analytics then you should uh then only you should move toward the diagnostic

and Predictive Analytics right because until or unless you have the knowledge of this statistical tool and techniques

you don't have the uh database sources of the data in your organization to collect the right kind of data which is

required and you don't have capability to transform the data right so if you don't have such kind of capabilities

then think about developing these capabilities and after that you implement the all types of the analytics

right so in detail we will discuss what type of capabilities is required to develop a effective HR analytics unit in

the uh organization so in detail we will discuss but as of now you understand if you don't have the effective team then

don't think about advanced level of the HR analytics you start with descriptive so I hope so descriptive will answer

what kind of questions what has happened and what is happening right and diagnostic will answer why did it happen

whatever has happened so why it happened right so that relationship related things or difference uh related things

uh that is what this diagnostic analysis will answer so what are the tools and techniques that will be used under each

category we will discuss in upcoming slides now third type of analytics Predictive Analytics will tell what will

happen in the future right so recruitment that you said this year thousand people thousand application

that you have received so next year how many you will receive that you can predict through the Predictive Analytics

this year you selected 100 employees next year how many employees that you will select that

you can predict through the Predictive Analytics prescriptive so here just you can understand right if you have to hire

200 employees right and then how many HR manager you need in the organization if you want to add identify how many number

of HR manager is required to hire 200 employees so in this case you can use the prescriptive so this is a

optimization problem right to hire the 200 employees how many HR managers is required effective number so through the

optimization you can find out the solution for this prescriptive analytics so that is how you can use this

different type of the analytics to answer these type of questions so I already say if you don't have uh enough

capability to use this analytics in detail then you can start with descriptive one right so I hope this all

HR manager understand so in which stage you are what kind of capabilities you have so accordingly you can decide the

level of uh analytics that you will Implement in your department but this four type of analytics that exist in

data science next so let us understand what are the tools and technique that you can use for the descriptive

analytics so first thing that you can use average simple average so in coming sessions that you will see I will use I

will calculate various types of average related to the uh recruitment selection performance compensation so simple

average that you can understand what if you want to know how young your department is right so simple thing that

you can do you can calculate the average age of your department employees simple so if you can calculate the average age

of your EMP in the department in whichever Department that you are working that will tell you how young

your department is right so whether it is Young between uh 20 to 25 25 to 30 30 to 35 40 50 what is the age that you can

see in the same way you can calculate the a average salary right average salary that is what

you can calculate and then you can understand same way you can if you want to calculate the gender pay Gap then you

can calculate the salary for male and you can calculate the salary for female so that is how you

can calculate the various type of averages that is what we will discuss in in upcoming sessions related to

you can uh make various decisions so this is the descriptive analytical tool first second one that you can see

standard deviation so deviation from the mean so whatever so that if you want to understand the outlier how many outliers

are there right so deviation from the mean so what is the average mean and how much is the deviation so if deviation is

high then you can say that data is very variation is there same thing uh that you can see uh in the variance also so

how much variance is there in the data how much it is varying whether it is concentrated towards the mean or it is

deviated from the mean so that is what you will understand through the standard deviation and mean so if standard

deviation is very high in term of your age right then you can say that some of the young people are there in your

organization and some of are very old if standard deviation is very low then you can say that the ages of the employee

who are working they are very close and people are from the same age group deviation is high then you can say that

people are there in the department they are not from the same age group because deviation is there standard deviation is

very high same that you can use the mode mode is frequency right so whichever number is coming so if you want to know

from which age category maximum number of people are there right so mode that you can calculate certain age categories

that you can say so let us assume 25 to 30 30 to 35 so from which age category maximum number of people

are there so now you can see the mode that is what you can see from which age category which age group most of the

people are there simple counts that you can count like number number of application number of selected candidate

number of rejected candidate so simple count that you can have that also can give you the number and based on these

numbers you can calculate the ratio you can calculate the percentage you can calculate percentage raos right and then

you can present effectively so these are the descriptive analytical tool that you can use in your HR related functions in

order to make the decision so if you are using these kind of tools and technique then you can say you are using the

descriptive analytics in the HR functions right so I hope these are the simple tool and technique that each HR

manager would be able to interpret so that is why I was saying you should focus first on descriptive analytics and

then you think about the uh Advanced one so these are the calculations that that you can do related to the performance

compensation learning development Recruitment and selection these all Concepts that is what you can use and

then you can do the calculation in these functions and then you can make a decision related to it right and now let

us come to the visualization from the descriptive analytics perspective so here you can make the

histogram right so histogram that you understand right write that you can make the graphs and in detail you will

understand in upcoming sessions where I will discuss various types of the histogram related to recruitment

selection performance compensation learning development right by using all three visualization tool you will see I

have used Tableau I have used powerbi I have used this Excel by using these all three tools you can make histograms it

is not necessary you have to use only powerbi and uh tblo or Excel any tool that you can use in order to visualize

this data whichever you are comfortable with but in this course we will be learning all three tools to visualize

the data so when you are using the descriptive analytics so you can use this histogram to visualize the data one

of the tool is there next thing that you can say to show the proportion of the things right so let us take the

recruitment you want to show the sources of recruitment right so internal versus external so what is the percentage of

is the proportion of the external through which you have received the number of application right so that you

can put it through the pie chart right next thing that you can use the bar graph right bar graph that is what you

can make it right so bar graph that is what you can make you so number of employee how many employees are there in

various Department what is their gender what is their salary what is their performance level performance rating so

these are the things that you can show through the bar graph so you have understood in descriptive analytics

which analytical tool that you which statistical concept that you can use and how you can visualize that particular

data now let us move to the diagnostic right so in diagnostic first let us understand what kind of questions that

you can answer so initially I can suggest you can start with descriptive and then slowly slowly you can move

towards the diagnostic also right so I hope HR manager has this much knowledge to uh implement this diagnostic after

the descriptive but start with first descriptive and then go for the diagnostic so what type of questions

are observing this where did it occur so where it is happening is the Matrix we are monitoring related in any way to the

things that we have collected the data for so whatever data that we have collected related to the dependent

variable so is there any way it is related to the independent variable because if independent variable and

dependent variable are not related then what kind of relationship that you are calculating if you are calculating the

number of people who left the organization right so are you able to establish the relationship through any

logic is there any logic right so if that logic is missing between these two independent and dependent variable in

which you are trying to explore the relationship that is what you need to think of right and if logic is there and

then what is the strength of the relationship so you already know the correlation value right 0 to 1 and + 1 +

1 2 - 1 between zero right so in between somewhere you may say you may get so correlation value could be positive and

we have collected so whatever data that we have collected so how much variability our matric has accounted so

such kind of questions that answer of such kind of questions that you can get through the diagnostic analytics now let

us come to to next aspect what are the tools and technique that we used in diagnostic analytics so in diagnostic

analytics that you can see from number uh from descriptive in numbers means mode median standard deviation variation

from here we have moved to the some advanced level tool so here you can see that we we will calculate correlation

category Anova two category Anova right and T Test also we can say t test so T Test anoba correlation regression factor

analysis cross tabulation principal component analysis correspondent analysis multiple correspondence

analysis so such kind of analysis that we use under the diagnostic analytics in this course we will learn only about

descriptive analytic tool the next course that uh we will develop in that course we will talk about diagnostic

analytics in detail right there we will discuss about correlation regression analysis of variance Anova factor

analysis cross tabulation principal component analysis right so these all things that we will discuss in the next

course but as of now you understand in diagnostic analytics these are the tools that comes now let us talk about the

next aspect ECT that is the visualization so how you will visualize this data which is related to the

diagnostic analytics so you can use the scattered plot to visualize the data regression plot

graphs please understand your variables carefully establish some logic between those variables and then use this uh

data visualization tool Excel PBI or Tableau to make these graphs right so for Diagnostic analytics you can use

this scatter plot Recreation plot plot of residual box plot and multiple density curves right so that is what you

can use now third type of analytics that comes that is the Predictive Analytics right so in the case of Predictive

our uh course right so next course that we will build in that we will focus on descript Diagnostic and predictive in

this course we have covered in detail descriptive analytics so all these descriptive numbers mean mode averages

that is what you will see all decisions that we are making in this course related to the HR functions that we are

the that we have made only on the basis of the descriptive so six functions that we have covered in our uh in this course

those functions are recruitment selection learning development performance and compensation so for

Predictive Analytics what are the tools uh so tools First Tool is the regression analysis so various types of the

regression that we have linear regression curvy linear logistic so these are the various types of the

regression when we will develop the next course in that we will discuss in detail decision trees and its variance random

Analytics right so that we will cover in the next uh course that we will develop and these are the visualization tools

that you can use line chart scatter grams and correlation plot in order to visualize the predictive data and this

is the prescriptive so if you will see very few organizations have used this type of analytics till dat right so

because for applying this analytics you need to have you high level of statistical knowledge and operation

necess knowledge and mathematical modeling if you know these things then only you will be able to do uh you you

will be able to use the prescriptive analytics in your organization right so after uh this second uh course then we

can think about this prescriptive also right what is the difference between Mis and analytics right so if

you will see this HR misis in one line I can say that HR Management in information system is the source for the

data right so on a if you are having this H Ms then related to employee you will get the all information right so

you may get a information which you want related to the employee age gender Department wise right but when you have

to make some decisions then you have to capture the data through some Matrix right so you will develop some Matrix

and hrms will give you the uh raw data from that raw data you will process you will transform you will make it

meaningful by using HR metric and then you will make a decision so I can say that HR IMS is the source of raw data

right that you are needed to make a decision so that raw data that you can collect from the HR IMS and then you can

process it according to the HR metrics which metrics that you have make it and by by make uh by calculating these

matrices you can take a certain decision related to the HR processes so in the case you can say that HR analytics

offers the more than HR metrix through its potential to connect with HR processes and decision with organization

performance so HR Matrix will give you that data and then as a HR manager you will link with HR process and

organization and performance and then you will take a decision related to the HR function so that is the HR analytics

HR IMS will give you just data and that data you need to process and then you have to make a decision so this is the

difference between at HR IMS and HR analytics so basic questions that you might be asking to yourself how does

this HR analytics works so one thing that I want to tell you that you should remember this lamp model so whatever

analytical tool that you are using right so first thing that you should remember this lamp model so lamp model L stands

for logic so whatever thing that you will do in HR analytics without logic you will not do anything right m stands

for major so first you will apply logic and then you will measure and then you will process it and then you will make a

analytical tool without logic that may not give you the right answer which you are looking for so first you need to

apply the logic so if two relationships are there how this recruitment is related with the selection right

effectiveness of the recruitment is related with the selection Effectiveness if you find any logic then apply that

develop the majors then develop measures means develop the HR metrix develop the HR metrix process

that data and use that processes process the data or outcome of that metrix all right and make a decision so this is the

one model that you can see this how HR analytics Works second thing that you can see that like a balance scorecard HR

scorecard is also there whatever HR initiative that you have taken like related to The Learning and Development

processes right related to for example customer handling so this new training programs how it has reduced

the number of customer how it has improved the process so you can see some process related outcome like number of

customer complaints and when number of customer complaint have reduced then how it has impacted the profit of that

organization so that is how you can d the HR score card in order to develop the logic and linking the people

strategy and performance of the various department so if you have taken any initiative related to the HR department

so how it is impacting the business processes and how these processes are impacting the business outcomes so that

through that link you can develop this HR scorecard and then you can so you should know how this HR analytics works

so these are the two approaches that you can uh think how HR analytics works so first and foremost important thing is

before applying any analytical tool you should be very much clear with your logic what why you are doing this

particular analysis if you have this answer then go ahead with this and then measure it process it and make a

decision related to that particular problem so if you remember I had suggested the way to apply in the

organization being a HR manager whatever questions that you are having right make a list of all those questions after

collect the data list of variables and then think about the data analysis after collecting the data so in

these four steps you can use this HR analytics next so what does HR Analytics process so you can see the processes

related to these statistical analysis that the whatever we have discuss descriptive prescriptive so these are

the processes of the HR analytics what is required to successfully implement the HR analytics so first thing that I

would say the analytical skills of a person because so skill of the HR professional so person who is working in

the HR department they should have the analytical skills and second thing that information technology so HMS I was

talking about so you should have this HMS so that you will be able to have a data you will be able to capture the

data and you will bring that data together and then you will be able to analyze it and third thing that I would

say basic knowledge of data analytical tool and technique so if you are having these three things then you can s

outcome of the HR analytics so you can see very uh you will be able to understand the relationship between

various processes of the HR and out business outcome so in this case that you can see Employee Engagement how it

is related with the store performance so HR metrics are the key majors of the HR outcomes so what are the HR outcomes

what are the outcome of the recruitment potential candidate how many candidates have applied so that will be measured

through the HR Matrix how many people are selected after the selection process will be measured through the HR Matrix

so thank you I hope you would have learned the basic things related to the HR analytics so welcome to this course