Bøger af Mong Shen Ng

Predictive HR Analytics, Text Mining & Organizational Network Analysis (ONA) are hot topics and powerful techniques to improve organization effectiveness. Best Buy is able to predict that a 0.1% increase in employee engagement results in an increase of $100,000 in the store's annual income! VoloMetrix found that a salesperson's network size within 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 & you don't need to buy expensive SPSS statistical software. This is the only book that teaches you how to use Microsoft Excel for Predictive HR Analytics, Text Mining & Organizational Network Analysis (ONA) with step-by-step print-screen instructions: 1) Predictive HR Analytics: Use Excel's Statistical Analysis tools (Decision trees, Correlation, Multiple & Logistic Regression) to run Predictive HR Analytics. You will learn how to predict Ethnic & Gender Diversity's impact on EBIT, predict training's impact on sales revenue, predict employee resignation, predict impact of staff engagement on sales, predict workplace accident, etc.2) Organizational Network Analysis (ONA): Run ONA using Excel's network analysis tool. Learn how to convert an employee's organizational network into a score & then predict if they will be a high-potential (HiPo). You will also learn how to predict employee performance and resignation with ONA graph metrics. E.g. an employee is predicted to be a HiPo with performance rating of "9", if his "Social Network Score" is "16", "Social Network Diversity Index" is "3" & "Competency Score" is "8". 3) Text Mining, Sentiment Analysis & Word Clouds: Mine text from social network posts, employee engagement surveys & Glassdoor comments, then run Sentiment Analysis using Excel & visualize the insights with "Word Clouds". Learn how to predict a company's average employee attrition rate based on its sentiment. E.g. a company's average employee attrition rate is predicted to be 8%, if unemployment rate is 3%, GDP growth is 2%, Glassdoor public sentiment rating is "5", and engagement score is "7".

Best Buy can predict that a 0.1% increase in employee engagement results in $100,000 increase in income. Though Amazon didn't promise a heart-warming employee experience and didn't promise work-life balance, it is among the top organizations in overall employee satisfaction. Endorsed by Dave Ulrich, this is the 1st & only book that incorporates Employee Experience & Engagement with Predictive Analytics. It offers a fresh way to cultivate engagement using 4 Engagement Bags: Bag 1) Inspire with Engagement Investment: Inspire with Predictive Analytics, and Inspire with Stories & Data Visualisation Techniques. Learn how to predict the impact of Employee Engagement on Revenue, Customer Satisfaction, Workplace Accidents with Excel using predictive analytics techniques such as Correlation & Regression. Bag 2) Inspire with Engagement Fertilizers: Making employees happy, doesn't mean they will work hard for the organization. Use the 5 "Engagement Fertilizers" to build great employee experience & engagement: (i) Engagement Fertilizer 1: Basic Needs - Soil, Rain, Sun (ii) Engagement Fertilizer 2: Social Needs - Birds (iii) Engagement Fertilizer 3: Growth Needs - Nutrients (iv) Engagement Fertilizer 4: Meaning - Healthy Tree (v) Engagement Fertilizer 5: Expectations - Fruits! Bag 3) Sentiment Gathering: Pulse Surveys, Focus Groups, Glassdoor Reviews, IISS Engagement Diagnosis Questions. Bag 4) Sentiment Diagnosis & Prescription: Engagement Metrics & Dashboards, Bar Charts, Radar Charts, Correlation, Regression, IISS Engagement Prescriptions, Sentiment Analysis with "Azure Machine Learning" & Word Clouds. Endorsement by Dave Ulrich Exceptional!!!!! This is truly great work. There are some things I really really like: (i) Building engagement on the past. So many things I read make it sound like engagement is a completely "new" topic (eg., some of the work on experience). You have positioned the evolution of the idea very nicely. (ii) Linking to key business outcomes ... I really like your work on Employee Engagement and Customer Engagement and other business outcomes. (iii) Using statistics and analytics to identify more subtle insights. (iv) Offering ways to visualize and use the engagement work. Again, marvelous work. Thanks for taking the time to write it. By Dave Ulrich, Speaker, Author, Professor, Thought Partner on HR, Leadership, and Organization, United States

You don't need to spend months learning Python, R, or SQL programming language, and you don't need to learn and buy expensive statistical software like SPSS or SAS. This is the only book that teaches you Predictive Analytics using Excel (which you already have)! This book not only share with you the analytics findings of other companies, but also teaches you how to derive it by yourself. It covers the ARHAT Predictive HR Analytics framework, teaches you data-storytelling & data-visualization techniques, and teaches you how to use Excel's statistical tools (Decision trees, Correlation, Multiple Regression, Logistic Regression, Chi-Square) with step-by-step print-screen instructions. This is the only book that covers the full HR Analytics scope (Benefits, Compensation, Culture, Diversity & Inclusion, Engagement, Leadership, Learning & Development, Payroll, Personality Traits, Performance Management, Recruitment, Sales Incentives) with numerous real-world examples, & shows how Predictive HR Analytics with Excel can help you: (1) Predict who are the people at risk of leaving using Decision tree, Correlation, Excel Logistic Regression, etc. (e.g. employee aged 30, who stays more than xx km from the company, who is rated "average for performance", has a 90% probability of resigning in her 3rd year.).(2) Identify where the best people come from and how successful a candidate will be if hired using simple correlation (E.g. Customer Service staff and Sales staff with x & y personality traits are likely to be good performers if hired).(3) Predict impact of Employee Engagement on customer satisfaction, revenue and Shareholder Returns, etc. using Excel Multiple Regression. (e.g. 1% increase in employee engagement leads to $100k increase in company revenue, 2% increase in customer satisfaction, 1% increase in Shareholders return, 1-day reduction in average sick leave, etc.).(4) Predict financial impact of training using Excel Multiple Regression (e.g. training satisfaction rating of xx leads to $y increase in company revenue).(5) Predict Diversity & Inclusion's impact on revenue and EBIT (e.g. convert your company's ethnic diversity mix to an index number, then use Excel Multiple Regression to predict if your company's diversity Index is x your company's Sales will be $y and EBIT will be z%).(6) Predict employee absenteeism and accident, using Chi-Square.

Your CEO returned from a management retreat with a new global vision, core values, and business plan that will revitalize and rebrand the company. As the Global Rewards Director, you are tasked to review employee benefits globally across all countries and all business units, and align them with an overarching corporate strategy. Do you know what to do? Benefits are important. Employees have no incentive to stay if your company benefits are the same as others. If people come for money, they will leave for the same reason. Benefits, especially unique perks, reflect the culture of an organization and differentiates the employer brand. However most companies adopt the "follow the herd" strategy of positioning their employee benefits at the "market median", thereby forgoing their opportunity to be an industry trend-setter. You don't need to be Google or GE to be an industry trend-setter. Any company can be an industry trend-setter. This book teaches you: 1) How to develop a Global Benefits Strategy aligned to Corporate Vision, Values, and Strategy. 2) How to brand the employee benefits that your company want to be known for and be an industry trend setter. How to inspire your employees to be story-carriers and ambassadors to amplify your employer brand, practices and culture. 3) What are the benefits practices and tax laws in various countries. How to setup and align employee benefits in Mergers and Acquisitions (M&A) and new country setups. 4) Do you have difficulty getting Trade Unions buy-in to reduce employee benefits? Do you have difficulty convincing your CEO and CFO to enhance employee benefits? Do you have difficulty explaining why your organizations can't give employees cash allowances instead of benefits? Learn how to get multiple-stakeholder buy-in for Benefits changes using the MPEP Methodology.

You don't need to buy expensive statistical software like SPSS. This book teaches you R (R can be downloaded for free), People Analytics, Social Media Analytics, Text Mining and Sentiment Analysis. It is written for people with absolutely NO knowledge of R programming, with step-by-step print-screen instructions. The sample R codes are kept simple, short & straightforward so that you are not overwhelmed with too much unnecessary information, and focuses on the R codes relevant to people analytics, so that you'll be up-and-running in no time. If you are new to R programming, this is the book for you. As R is developed specially for statistical analysis, you can run complicated statistical number crunching (Correlation, Multiple & Logistic Regression, etc.) by simply entering a few commands. This book covers a wide People Analytics scope (Benefits, Compensation, Culture, Diversity & Inclusion, Engagement, Leadership, Learning & Development, Personality Traits, Performance Management, Recruitment, Sales Incentives) with numerous real-world examples, and shows how People Analytics with R can help you: 1) Run Social Media Analytics, Text mining & Sentiment Analysis with R. 2) Predict employees' flight-risk using R's Correlation & Logistic Regression function. 3) Identify the personality traits of top performing Customer Service staff and Sales staff using R's correlation function.4) Predict impact of Employee Engagement on Customer Satisfaction, Revenue and Shareholder Returns, etc. using R's Correlation & Multiple Regression function. 5) Predict impact of Learning & Development on Sales, using R's Multiple Regression function.6) Predict Diversity & Inclusion's impact on Revenue and EBIT using R's Multiple Regression function. You'll be taught how to convert your company's ethnicity diversity mix (70% Chinese: 20% Malay: 10% Indian) to an index number (e.g. diversity index of 2.7), then use R's Multiple Regression to predict your company sales, if your company's "diversity Index" is 2.7 and if you spend $90 on advertising.