3. HR Analytics
Analytics is not so much about numbers, as it is to do with logic and
reasoning.
Analytics is different from Analysis, which is the equivalent of number
crunching. Analytics uses analysis but then builds on it to understand the
'why' behind the figures and/or to predict decisions. Analytics is the
methodology of logical analysis.
Analytics requires the use of carefully constructed metrics.
HR Analytics is data based; it uses past data to predict the future.
It is not about the quantity of data churned; it is about the logic used to
link metrics to results.
4. BENEFITS OF HR ANALYTICS?
• Increased need for Data analytics tool in HR to make better
HR decisions.
• Better quality of hire is one of the HR data analytics benefits.
• A vital benefit of HR metrics and analytics is employee
retention.
• Transformation of HR as a strategic partner is one of the
benefits of workforce analytics.
• Business analytics in HR can help predict the hiring needs of
an organization.
5. WHAT SHOULD/COULD BE MEASURED?
• Overall Workforce Productivity.
• Employee Engagement.
• Recruiting.
• Manager Satisfaction.
• Retention and Turnover.
• Overall Monetary impact of HR on your
business.
6. CRITICAL AREAS FOR HR PREDICTIVE
ANALYTICS
1. Turnover modeling. Predicting future turnover in business units in specific
functions, geographies by looking at factors such as commute time, time since
last role change, and performance over time.
2. Targeted retention. Find out high risk of churn in the future and focus retention
activities on critical few people.
3. Risk Management. Profiling of candidates with higher risk of leaving prematurely
or those performing below standard.
4. Talent Forecasting. To predict which new hires, based on their profile, are likely to be
high fliers and then moving them in to fast track programs.
7. •Reporting of basic metrics, their frequencies & percentages by
various cuts followed by key highlights like monthly, quarterly, half
yearly tracking reports
•Tool: SAS/REPORT
•Techniques: frequencies , means, percentages
Level-1
Descriptive
analysis
•Derivation of some HR operational metrics which willhelp us in
tracking the efficiency of HR functions
•Tool: SAS
•Techniques: means, variance, control limits, ratios,
percentages etc.
Level-2
Operational
metrics
•Predictive analysis based on historical HR data. Attrition
forecasting, performance management, compensation analysis,
survey analytics, new hire strategies etc.,
•Tool: SAS BASE, SAS E-miner, Excel
•Techniques: Regression analysis, Time series analysis,cluster
analysis etc.
TRENDWISE ANALYTICS – HR ANALYTICS CAPABILITIES
Three levels of HR analytics and reporting
Level-3
Predictive
analysis
8. STAGES OF ANALYSIS
PREDICTIVE ANALYSIS
What can happen?
ANALYSIS & MONITORING
Why did it happen? What is
happening now?
REPORTING
What happened?
Complexity
9. Types of Analytical Models
PREDICTS
PREDICTS
PREDICTIVE ANALYTICS
Predictive Analytics
Current
Data
PREDICTS
Future
INFERENTIAL ANALYTICS
Analysis & Monitoring
Past
Data
Reporting
REPORT
Drawing
Conclusions or
Inferences
DESCRIPTIVE ANALYT
Representation of
Data and
Summarizing
10. IMPACT OF SOCIAL
MEDIA
Predicting
the future
sounds
mystical
Predictive
ANALYTIC
is
touching
every
human on
Earth who
accesses
internet
Day to
day
existence
is now
being
exploited
by social
media
and then
the
analytics
11. Executives; Corporate
Strategy Craft and
guide long term
workforce plan based
on given information
Finance; Controlling;
Budgeting Give input
regarding financial figures
and receives insights for
midterm financial planning
regarding the workforce
HR Business
Partner Consult with
Business Units based on
workforce intelligence
and drives action plans
as final deliverable from
the process
HR Administration; HR
Functions Recruiting, Staffing,
Talent Management and other HR
functions support fulfillment of
workforce action plans
HCM ANALYTICS CONSUMERS BY ROLE
Middle Managers; Line Managers
Execute on strategic plans and
manage organizational
performance to assure strategic
objectives are reached timely
and efficiently
Employee needs
contextual HR data
to perform better.
Stakeholders across the organization
HR Analyst Needs ad-hoc capabilities to do sophisticated
analysis and
14. DEFINITION
Competency: Competency refers to knowledge, skills, attitude that the teacher is
expected to demonstrate in his/her career. In the present study selected
domains like emotional intelligence, communication skill, computer literacy, and
professional advancements will be assessed. Concepts like performance
attributes, performance scores, self-assessment, job performance are used as
synonyms to competency and competency mapping.
• Competency mapping: Competency mapping is a process through which one
assesses and determines one’s strengths as an individual worker and in some
cases, as part of an organization. It generally examines two areas: emotional
intelligence or emotional quotient (EQ), and strengths of the individual in areas
like team structure, leadership, and decision-making. In the present context it
will cover EQ, basic competencies that a teacher should possess e g.,
communication skill, computer literacy etc.
15. TYPE OF COMPETENCIES
Core Competencies
Functional
Competencies
Leadership
Competency
Core
Competencies
Management
Competency
Business
Competency
Individual
Competency
16. TYPE OF COMPETENCIES
• Individual Competency– This type refers to a person’s own knowledge, skills, and attitudes
(behavior) that contribute to effectiveness in performance, as well as in dealings with other
people.
• Business Competency– This refers to the knowledge and skills required in a particular business or
industry.
• Management Competency– This refers to a set of competencies that are applicable only to
supervisory and managerial positions or roles, that are more commonly task-oriented.
• Leadership Competency– This refers to the required competencies for leadership roles such as that
of a team leader. These competencies make an individual effective in their position as leader of a
group.
• Functional Competencies– This type of competency is specific to a certain job. For example, a
computer programmer must be knowledgeable and skilled when it comes to various programming
languages such as Java, Python, and C++.
• Core Competencies– This refers to general competencies specific to an organization. It is the way the
organization and its members work.
18. COMPETENCY MAPPING
• Competency Mapping is a process of identifying key competencies for an
organization and/or a job and incorporating those competencies throughout the
various processes (i.e. job evaluation, training, recruitment) of the organization. A
competency is defined as a behavior (i.e. communication, leadership) rather than a
skill or ability.
• The steps involved in competency mapping with an end result of job evaluation
include the following:
1. Conduct a job analysis by asking incumbents to complete a position information
questionnaire (PIQ). The PIQ can be provided for incumbents to complete, or you
can conduct one-on-one interviews using the PIQ as a guide. The primary goal is
to gather from incumbents what they feel are the key behaviors necessary to
perform their respective jobs.
19. 2.Using the results of the job analysis, you are ready to develop a
competency based job description. This is developed by carefully
analyzing the input from the represented group of incumbents and
converting it to standard competencies.
3.With a competency based job description, you are on your way to begin
mapping the competencies throughout your HR processes. The
competencies of the respective job description become your factors for
assessment on the performance evaluation. Using competencies will help
guide you to perform more objective evaluations based on displayed or not
displayed behaviors.
4.Taking the competency mapping one step further, you can use the results
of your evaluation to identify in what competencies individuals need
additional development or training. This will help you focus your training
needs on the goals of the position and company and help your employees
develop toward the ultimate success of the organization.
20. PROCESS OF COMPETENCY MAPPING
1.Identify the department for which competency mapping needs to be conducted.
2. Identify the organizational structure and list down the grades and levels followed
in that organization.
3. Conduct job analysis and prepare a job and role description.
4. Using any suitable method of competency mapping collect data about the core
competencies of the employee.
5. Classify the obtained data into required skill set and further identify the skill
levels.
6. Evaluate and confirm the identified skill with immediate supervisors and heads of
other departments.
7. Preparation of competency calendar.
8. Mapping of competencies.
22. NEED FOR COMPETENCY MAPPING
Recruitment
& selection
Career
Planning
Training and
development
Succession
planning
Competency
Mapping
Performance
appraisal
Compensation
Replacement
planning
23. CASE STUDY
•This study is based on “People Analytics: Breaking Myths with Agility and Passion, "presented at
LinkedIn Talent Connect 2016.
•The Nielsen Corporation, is a global marketing research firm, with worldwide headquarters
in New York City, United States.
•Nielsen is a global data analytics company. Lots of companies collect data but don't know what to
do with it, and Nielsen takes the initiative to analyze it for them. They provide meaningful and
valuable results for companies. They are most well known for their television ratings.
•Nielsen created a predictive model back in 2015. This predictive model only included 20
variables, including age, gender, tenure, and manager rating. Over time, more variables were
added.
Keeping key talent at Nielsen
24. In 2015, the leader of one of Nielsen’s biggest businesses approached one of the company’s HR
leaders with a big question: do you know why people are leaving my team?
Around the same time, Mathur, the head of the company’s brand new “people analytics” program
and his team were trying to put hard data behind that very problem after finding that company-wide
attrition had been rising. They set out to build a basic model to answer what was causing it.
The irony of it all is that even though Nielsen is known for its expertise in Big Data, it hadn’t focused
on analyzing its own employees until 2015.
Within months, the team was able to identify the primary drivers of voluntary attrition. Nielsen has
since slashed regrettable voluntary attrition by nearly half - which in turn saved them millions of
dollars.
For HR and talent acquisition teams looking to start a people analytics program of their own,
Mathur offered a simple roadmap.
His recommendations.
His main target became preventing attrition. First, he had find a relatively simple model for
measuring and predicting it; then, it was about putting in place programs to fix it; and finally, he had
to measure their impact and share the results with executives in a compelling way.
He used the following formula-
25. To predict future attrition, instead of spending half a year tracking down perfect data, Nielsen built a
model with 20 simple points of employee data like age, gender, tenure and manager rating. They’ve
refined the model over time to include data like commute time and participation in CSR programs.
That model yielded myth-busting insights about how to keep employees at Nielsen on board. The
insights included:
The first year matters most. If employees don’t even reach it to their first performance review, their
likelihood of leaving rose exponentially.
Gender and ethnicity don’t play a role in tenure, which went against their initial hypothesis and became
something they are “very proud of.”
Though getting promoted pushes employees to stay, so do lateral moves – in a “pretty significant way,”
26. His team helped set up numerous programs to reduce attrition. After identifying attributes of
associates with the strongest likelihood of leaving the company within the next six months,
company leaders set up chats with the highest flight-risk employees. The result? 40% of the
group was transferred to new roles.
The team focuses on a few other people analytics projects, too. One tries to increase women in
leadership roles from the current 34% to reflect the nearly 50% representation within the
company. Another is Strategic Workforce Planning, which aims to ensure Nielsen retains
employees with the skills needed for the jobs of today and tomorrow. Yet another analyzes if
they’re hiring from the right universities, and which universities are successful at feeding talent to
particular business functions.
27. This exercise provided multiple insights, including that the first year mattered the most. First-year
employees where checked whether they’ve had their critical contact points. For example, the first
check-in with their manager had to happen within a certain time span after hiring, otherwise, it
would trigger a notification. This was a proven, important condition for first-year retention.
Although getting promoted pushed people to stay, lateral moves were also a strong motivator for
people to stay.
A significant outcome was that the people with the highest flight risk in the next six months were
approached and the company was able to move 40% to a new role. Making these lateral moves
increased an associate’s chance of staying with the company by 48%.
