People Analytics

Human Resource Solution, Division manager, Unitask

People Analytics

Human Resource Solution, Division manager, Unitask

“HR analytics are NOT about HR, but about the business”

Dictionary

HR Analytics

The underlying goal of analytics is to identify patterns that can inform strategic decisions.

HR Metrics

Help HR and the organization evaluate the efficiency, effectiveness and impact of their HR systems, programmes and processes. They help evaluate how well HR is performing.

HR Reporting

Captures basic facts about an organization and helps managers and leaders track and manage their teams and workforces.
.It quantifies the current state

 

People analytics is the process of discovering, interpreting and communicating meaningful patterns in workforce-related data to inform decision making and improve performance.

It is not only about data analysis but also about change management – generating meaningful insights to drive behavior change and increase organizational effectiveness

Old rules Vs. New rules

New Rules

People analytics is viewed as a business analytics team the works across the business to drive business results

Analytics focus on business problems such as sales productivity, workforce effectiveness, high-potention retention, fraud, accident patterns

The people analytics team operate as asenior level reports to CHRO, and serve business leaders across the company

The people analytics team is a multidisciplinary team, with a focus on business consulting and problem solving

Old rules

People analytics is viewed as an HR team focus on advanced analytics within HR

Analytics focus on HR topics such as retention, engagement, learning and recruiting matrices

The people analytics team lives in HR operation and report to HR technology

The people analytics team is a small set of technical experts with data management & statistival skills

6 reasons why People Analytics will be central to the future of HR:

4. New and emerging data sources will help companies improve competitive advantage.

 


 

5. People data needs to be put in the hands of the people in the business that need it.

 


 

6. There is some serious talent in the people analytics space.

1. People analytics is the centerpiece of a digital HR agenda.

 


 

2. Those that aren’t good at people analytics are not ready for AI in HR.

 


 

3. People analytics underpins organizational design and new work models.

 

1. People analytics is the centerpiece of a digital HR agenda.

 


 

2. Those that aren’t good at people analytics are not ready for AI in HR.

 


 

3. People analytics underpins organizational design and new work models.

 


 

4. New and emerging data sources will help companies improve competitive advantage.

 


 

5. People data needs to be put in the hands of the people in the business that need it.

 


 

6. There is some serious talent in the people analytics space.

“analytics is no longer a ‘good idea’ for HR, it is now mandatory.”

People Analytics 3.0

People Analytics 3.0

Some Challenges facing
HR Analysts

#1 Disparate systems producing multiple data sets.

 


 

 #2 Accessing data sets outside HR.

 


 

#3 Implementation of the GDPR.

 

Some Challenges facing
HR Analysts

People Analytics

#1 Disparate systems producing multiple data sets.


 #2 Accessing data sets outside HR.


#3 Implementation of the GDPR.

 

People Analytics

The Eight Step Model for Purposeful Analytics

?Why under take the project

Step 2

Build Hypotheses

Building and clarifying a hypothesis for “testing” beliefs about the causes of business issues. Strong hypotheses should guide the data gathering and analysis phases in a way that links to business questions

Step 1

Frame Business Questions

What is the business reason? Why are you taking this project? Is this analytics work is really necessary

?How should the project be carried out

Step 4

Conduct Analysis

This is where the methodology and statistics are applied to data to test the hypotheses and provide the basis for insights. Without this step, the fundamental building blocks of any analytics project simply do not exist; without performing analysis, patterns in data will never be discovered

Step 6

Determine Recommendations

Out of the insights what will be recommended to the executives. Recommendations are what business leaders and, in this case, project sponsors need

Step 3

Gather Data

Most relevant data for testing the hypotheses and determining whether data quality is sufficient to proceed

Step 5

Revel Insights

First, analysts cannot assume that project sponsors and stakeholders are able to derive the most pertinent insights themselves. Second, If analysts present only data and analysis without insights, executives and project sponsors might draw their own conclusions to best fit their preconceptions

Step 3

Gather Data

Most relevant data for testing the hypotheses and determining whether data quality is sufficient to proceed

Step 4

Conduct Analysis

This is where the methodology and statistics are applied to data to test the hypotheses and provide the basis for insights. Without this step, the fundamental building blocks of any analytics project simply do not exist; without performing analysis, patterns in data will never be discovered

Step 5

Revel Insights

First, analysts cannot assume that project sponsors and stakeholders are able to derive the most pertinent insights themselves. Second, If analysts present only data and analysis without insights, executives and project sponsors might draw their own conclusions to best fit their preconceptions

Step 6

Determine Recommendations

Out of the insights what will be recommended to the executives. Recommendations are what business leaders and, in this case, project sponsors need

?What will result from the project

Step 8

Implement & Evaluate

Decisions making as a result of this project, Actions based on these decisions, Evaluating the project against whether it returned value to the organization

Step 7

Get Your Points Across

Communicate the outcomes of the project to the sponsor or other stakeholders

Key Conditions for Success Project

  • Start with the business Strategy.

  • Focus on generating actionable insights.

  • Combine business, people and organizational data.

  • Invest in building analytical and data-driven practice skills and a more data
    driven culture and mindset.

  • There’s no point undertaking workforce analytics unless there is appetite in the business to do something with it.

business Strategy Start with the

actionable insights Focus on generating

business, people and organizational data Combine

Invest in building analytical and data-driven practice skills and a more data driven culture and mindset

There’s no point undertaking workforce analytics unless there is appetite in the business to do something with it to do something with it

Organizational Network Analysis (ONA)

Organizational Network Analysis (ONA)

Visualizing and analyzing formal and informal relationships in your organization

:Using ONA can help

Use talent more effectively

by minimizing role confusion and redundancy

Transform organizations in a smarter way

by identifying formal and informal leaders who can be counted on to facilitate change and help accelerate the realization of transformation benefits

Increase operational effectiveness

by building an organization that is structured to increase collaboration and exchange of information between the right people

Who are the "poeple"?

A Millennial job interview

Michak Taub

Michal Taub Ovadia

מנהלת חטיבת פתרונות HR

בעלת תואר ראשון במנהל עסקים עם התמחות במשאבי אנוש ותואר שני במדיניות ציבורית.
עוסקת מעל 20 שנה בתחום מערכות המידע ומשאבי אנוש.
לפני תפקידה ביוניטסק כמנהלת חטיבת פתרונות HR, עבדה באוניברסיטת תל אביב, ביעל תכנה ואמדוקס.
מיכל מובילה את תחום משאבי אנוש בענן ב 4 שנים האחרונות, היא אחת מהראשונות שעוסקות בתחום זה בארץ ובעלת ידע וניסיון עצומים בתחום.

Michak Taub

Michal Taub Ovadia

בעלת תואר ראשון במנהל עסקים עם התמחות במשאבי אנוש ותואר שני במדיניות ציבורית.
עוסקת מעל 20 שנה בתחום מערכות המידע ומשאבי אנוש.
לפני תפקידה ביוניטסק כמנהלת חטיבת פתרונות HR, עבדה באוניברסיטת תל אביב, ביעל תכנה ואמדוקס.
מיכל מובילה את תחום משאבי אנוש בענן ב 4 שנים האחרונות, היא אחת מהראשונות שעוסקות בתחום זה בארץ ובעלת ידע וניסיון עצומים בתחום.

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