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Beginner’s Guide to HR Tech A glossary of nine commonly used HR Tech terms

Glossary: Nine HR Tech terms explained

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Page 1: Glossary: Nine HR Tech terms explained

Beginner’s Guide to HR Tech

A glossary of nine commonly used HR Tech terms

Page 2: Glossary: Nine HR Tech terms explained

© 2016 EdGE Networks 2

1. Predictive Analytics

Plays a plays a huge role in mitigation and

having a plan B ready in case of an HR

emergency. huge role in mitigation and having a

plan B ready in case of an HR emergency.

What it is

Predictive analytics is making statistics-backed predictions for the future, by analyzing

current or historical data. It can help HR leaders make better predictions on future

hiring and recruitment needs by analysing data like current age and skill sets of

employees; business growth and attrition rate.

What it does

Helps predict probable scenarios when a company

suddenly needs to hire a number of employees;

or when people are most likely to leave.

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© 2016 EdGE Networks 3

2. Data Management

Helps save a lot of time in

extracting and analysing huge

amounts of data by structuring

it well in advance

Makes employee data easily

accessible by storing it at a

central place

Plays the crucial role of

keeping sensitive employee

data safe

What it isData management refers to designing policies, practices and procedures to manage information. Data

Management can be split into three stages:

• Data design- it refers to the way data is structured and organised

• Data storage- it refers to the different ways in which data can be stored- in hard drives, RAM storage

or the cloud.

• Data security- It refers to keeping data safe from thefts and having a back up ready in case of

technical glitches.

What it does

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© 2016 EdGE Networks 4

3. Business Intelligence

Helps make the right hiring and

letting go decisions which are

backed by data and not pre-

conceived notions

Helps improve candidate

screening

Supports fair remuneration

based on performance

What it is

Business Intelligence is making the effective use of data and information to make well

informed, sound and viable business decisions. In includes various elements like data

quality and interpretation, data mining, data analysis and reporting.

What it does

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© 2016 EdGE Networks 5

4. Workforce Analytics

Helps develop new and

efficient recruiting methods

Helps retain the best talent in

the organisationHelps make better HR decisions

What it isWorkforce Analytics allows people to find meaningful trends and patterns in employee related

data. The inferences could be based on basic information on, for instance, the skill set of

employees, interests and hobbies, tenure served at previous jobs, amongst others. It’s an

intricate process that involves compilation, manipulation and analysis of data.

What it does

Page 6: Glossary: Nine HR Tech terms explained

© 2016 EdGE Networks 6

5. Demand and Supply Forecasting

Helps the organisation prepare

in advance for expansion plans

and upcoming projects

Estimates the number and kind

of people needed and available

to execute plans

Help determine replacement

needs of employees and initiate

promotions, transfers and team

shuffles

What it isDemand forecasting, as the name suggests, means estimating the number of people required

with the right skill set to accomplish upcoming tasks.

Supply Forecasting, on the other hand, means estimating the number of people who will be

available to accomplish a certain future task.

What it does

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6. Cost to Hire Analysis

Helps HR departments better control their hiring

costs by identifying all possible inefficiencies

What it isAll external hiring comes at a cost. This cost could be hidden; for example cost of time spent in

poring over tens of dozens of resumes to find that ideal mix of candidate; or it could be plain

and obvious like cost of advertising a job vacancy. Cost to Hire Analysis makes use of historic

hiring data to analyze and identify the various cost heads; and then suggests ways and means

to reduce or contain certain large cost heads.

What it does

For organizations hiring people in large numbers,

it can add precious dollars to the bottomline.

Page 8: Glossary: Nine HR Tech terms explained

© 2016 EdGE Networks 8

7. Joining Probability Analysis

Identifies profiles of candidates who are more

likely to join

What it isOften, candidates accept job offers and then back out from joining. Joining

probability analysis includes building a probability score for all candidates as an

indicator of how likely they are to join.

What it does

Helps avoid the loss incurred when a promising

candidate refuses to join

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© 2016 EdGE Networks 9

8. Hiring Channel Mix Modelling

Helps HR departments focus on

those channels that have

performed best for their hiring

needs

Streamlines the hiring process Optimizes hiring costs

What it isHR executives make use of several channels for hiring their candidates – including employee

references, recruitment consultants, social media and so on. Hiring Channel Mix Modeling

analysis previous hiring data to identify all channels that have led to hiring for an organization

and the interplay between them. It can then go a step further and pinpoint the channels that

have been most fruitful in hiring.

What it does

Page 10: Glossary: Nine HR Tech terms explained

© 2016 EdGE Networks 10

9. Attrition Analysis

Helps make risk scores which help predict which

employees are more likely to resign, at what time

and the reason behind their resignation

What it isTo understand attrition analysis, one must first understand the concept of flight risk. Flight risk refers to the risk associated when an employee is looking to switch jobs. It is the HR’s job to devise methods to retain talent in the organisation. Attrition Analysis helps reduce flight risk by adopting a predictive approach and identify problem areas in advance.

What it does

Helps create employee retention programs

Page 11: Glossary: Nine HR Tech terms explained

© 2016 EdGE Networks 11

Want to learn more on

HR Technology?

Page 13: Glossary: Nine HR Tech terms explained

© 2016 EdGE Networks 13

Thank you