Best Buy Co., Inc. is able to predict that a 0.1% increase in employee engagement results in an increase of over $100,000 in the store’s annual income. Organizational Network Analysis (ONA) is a hot topic and a powerful technique to improve organization effectiveness. VoloMetrix found that the size and amount of a salesperson’s network inside their company is a more important leading indicator of sales, than the time salespeople spend with customers. You don’t need to spend months learning R programming, and you don’t need to buy expensive SPSS statistical software. This course teaches you how to use Excel for Predictive HR Analytics and ONA. You will learn how to predict employee performance, predict employee resignation with ONA graph metrics, predict employee’s sales with ONA data, predict Ethnic & Gender Diversity’s impact on EBIT, predict training’s impact on customer service and sales, predict employee resignation, predict workplace accident, etc.
- Application of analytics
- Overview of Analytics tools (Apache Spark, Excel, Minitab, Python, R, SAS, SPSS, SQL, Stata, Tableau)
- Setup strategically aligned HR dashboard & metrics
- ARHAT Predictive HR Analytics Framework designed by the course leader
- Strategies for Analytics Projects Quick Wins
- Statistical analysis with Excel. E.g. Correlation, Multiple Regression, and Logistic Regression.
- Organizational Network Analysis (ONA). Learn to predict employee resignation with ONA graph metrics, predict employee’s sales with ONA graph metrics, build an ONA survey, visualize ONA with Excel NodeXL, and formulate ONA Interventions.
- Compensation & Benefits Analytics. E.g. Predict people who will accept less than 5% pay increase, predict employees faking sick leave.
- Strategic Workforce Planning Analytics. Learn the Strategic Workforce Planning steps, and how various industries forecast its manpower needs.
- Performance Analytics. Learn to predict employee performance based on their “Organizational Network Index”, “Competency”, & “Personality Traits”.
- Diversity and Inclusion Analytics. Learn to predict Ethnic & Gender Diversity’s impact on EBIT.
- Training & Development Analytics. Learn to predict training’s impact on customer service and sales.
- Health, Safety & Environment (HSE) Analytics – Predict workplace accident with engagement scores, staff tenure, forecasted revenue, with age, years of service, sick leave taken, etc.
- Predict Employee Resignation – Learn Turnover Predictors, flight risk scoring, Probability Tree Model for Employee Churn. Predict employee flight risk with travel time, marital status, compa-ratio, gender, age, commute time, etc
- Data Visualization Techniques with Excel
Logistics & System Requirements
Please bring your personal laptop with Windows Operating System, Microsoft Word, and Microsoft Excel. You will be taught how to install free MS Excel and Word add-ins in your personal laptop during the workshop. Try not to bring Apple laptops as some of the Excel and Word add-ins may not work on Apple laptops. If you are bringing your company laptop, you may need your IT department to allow you to install add-ins to your laptop during your workshop period, or to install the following add-ins for you prior to your workshop:
- “Analysis ToolPak” for MS Excel
- “Excel Solver” for MS Excel
- “NodeXL” for MS Excel
The trainer, Cedric Ng Mong Shen has more than 20 years Global HR experience (Asia, Americas, Africa, Middle-East) in various Top Fortune 100 US/European/Asian MNCs, covering Technology, Manufacturing, Oil & Gas, Logistics, and Hospitality Service industries. Cedric has a Master’s in Business Administration (MBA) from University of Strathclyde, and a Bachelor in Economics & Sociology from National University of Singapore (NUS). As a HR thought leader, he has published several HR books. His books are rated by customers, and are sold worldwide in markets covering America, Europe, Middle-East, Africa, and Asia.
Who Should Attend?
- Those who can’t afford to buy expensive statistical software like SPSS or SAS.
- Those who can’t afford to spend months learning R or Python programming, but need to quickly deliver some analytics results.
- HRBPs who does analytics as an additional side role.
- HR people who wants to take their first steps into the analytics world.
- Data Scientists who are searching for ideas & case studies on what HR issues they can study in their own company to generate improved business results.
- Most importantly, for those who love to use Excel!
Registration and coffee will be at 08.30 each day and the course will commence promptly at 09.00 each day and conclude at 17.00 each day. There will be an hour for lunch in the middle of the day at about 13:00-14:00, and a short refreshment break in both the morning and afternoon.
Module 1) Introduction
1.1) Applications of Analytics
1.2) Overview of Analytics tools (Apache Spark, Excel, Minitab, Python, R, SAS, SPSS, SQL, Stata, Tableau)
Module 2) Predictive HR Analytics Framework
2.1) Analytics Maturity Model
2.2) Strategically aligned related HR dashboards & metrics
2.3) ARHAT Predictive HR Analytics Framework
Module 3) Strategies for Analytics Projects Quick Wins
3.1) Stakeholder Analysis
3.2) Power Interest Matrix
3.3) Action Priority Matrix
3.4) Court rulings on Analytics cases
Module 4) Basic Statistical Analysis with Excel
4.1) Basic Statistics
4.2) Probability Tree
4.4) Multiple Regression
4.5) Logistic Regression
Module 5) Organizational Network Analysis (ONA)
5.1) Applications of ONA
5.2) Build an ONA survey
5.3) Visualize ONA with Excel NodeXL
5.4) ONA Interventions
5.5) Predict employee resignation with ONA graph metrics
5.6) Predict employee’s sales with ONA graph metrics
Module 6) Compensation & Benefits Analytics
6.1) Market-Ratio Analytics
6.2) Compa-Ratio Analytics
6.3) Flight Risk Formula
6.4) C&B Communications
6.5) Probability Tree for C&B
Module 7) Strategic Workforce Planning Analytics
7.1) What is Strategic Workforce Planning?
7.2) Steps in Strategic Workforce Planning?
7.3) Strategic Workforce Planning Examples?
Module 8) Performance Analytics
8.1) Predict an employee performance rating based on their “Social Network”, “Skillsets”, & “Personality Traits”.
8.2) Probability Tree for Performance
Module 9) Diversity and Inclusion Analytics
9.1) Convert diversity into an index
9.2) Predict Ethnic & Gender Diversity’s impact on EBIT
Module 10) Training & Development Analytics
10.1) Calculate impact of Training on Earnings Per Share (EPS)
10.2) Predict training’s impact on customer service
10.3) Probability Tree for Training & Development
Module 11) Health, Safety & Environment (HSE) Analytics
11.1) Correlation: Predict workplace accident with engagement scores, staff tenure, and forecasted revenue
11.2) Logistic Regression: Predict Workplace Accident with age, years of service, and sick leave taken
11.3) Probability Tree for Health, Safety & Environment
Module 12) Predict Employee Resignation
12.1) Turnover Predictors
12.2) Flight risk scoring
12.3) Probability Tree Model for Employee Churn
12.4) Correlation: Predict employee flight risk with travel time, marital status, compa-ratio & gender
12.5) Logistic Regression: Predict employee flight risk with compa-ratio, age, & commute time
Module 13) Data Visualization Techniques with Excel
13.1) Clustered Column Chart
13.2) Combination Charts
13.3) Pie Charts
13.4) Scatter Plots