Unit 4 Session 11.pptx

Online MBA Semester I Organizational Behaviour and Human Resource Management Course code - (OMBA-103) Unit 4 : Lesson 11 : HR Analytics Part - I Human Resource Human Resource Analytics Management Human Resource Human Resource Analytics Management Learning Objectives: • Understanding HR Analytic...

Online MBA Semester I Organizational Behaviour and Human Resource Management Course code - (OMBA-103) Unit 4 : Lesson 11 : HR Analytics Part - I Human Resource Human Resource Analytics Management Human Resource Human Resource Analytics Management Learning Objectives: • Understanding HR Analytics • Defining HR Analytics • HRM Functions and HR Analytics • Skills needed for HR Analytics • Why HR Analytics • HR Analytics Levels • Benefits and Challenges Human Resource Human Resource Analytics Management Evaluating an HR management plan for success includes looking at recruitment policies, hiring processes, the extent to which HR is part of the company's strategic plan and how effective HR leaders are at strengthening the employer-employee relationship. There are several approaches to human resource evaluation. The most prominent of them are: audit approach, analytical approach, qualitative and quantitative approach, balanced scorecard perspective and benchmarking Human Resource Human Resource Analytics Management HR Analytics HR Analytics can be defined as ―a methodology for understanding and evaluating the causal relationship between HR practices and organizational performance outcomes (such as customer satisfaction, sales or profit), and for providing legitimate and reliable foundations for human capital decisions for the purpose of influencing the business strategy and performance, by applying statistical techniques and experimental approaches based on metrics of efficiency, effectiveness and impact‖ (Lawler, Levenson & Boudreau, 2004;Boudreau & Ramstad, 2006). Human Resource Human Resource Analytics Management Skills needed for HR analytics Human Resource Human Resource Analytics Management Human Resource Human Resource Analytics Management Human Resource Human Resource Analytics Management Human Resource Human Resource Analytics Management Human Resource Human Resource Analytics Management Human Resource Human Resource Analytics Management Descriptive. Traditional HR metrics are largely efficiency metrics (turnover rate, time to fill, cost of hire, number hired and trained, etc.). The primary focus here is on cost reduction and process improvement. Descriptive HR analytics reveal and describe relationships and current and historical data patterns. This is the foundation of your analytics effort. It includes, for example, dashboards and scorecards; workforce segmentation; data mining for basic patterns; and periodic reports. Human Resource Human Resource Analytics Management Predictive. Predictive analysis covers a variety of techniques (statistics, modeling, data mining) that use current and historical facts to make predictions about the future. It‘s about probabilities and potential impact. It involves, for example, models used for increasing the probability of selecting the right people to hire, train, and promote. Human Resource Human Resource Analytics Management Prescriptive. Prescriptive analytics goes beyond predictions and outlines decision options and workforce optimization. It is used to analyze complex data to predict outcomes, provide decision options, and show alternative business impacts. It involves, for example, models used for understanding how alternative learning investments impact the bottom line (rare in HR). Human Resource Human Resource Analytics Management Practitioners propose five steps of analytics (Fitz-Enz J., 2010): 1.Recording the work: hiring, paying, training, supporting, retaining; 2.Relating to the organization’s goals: quality, innovation, productivity, service; 3.Benchmarking: comparing our results to others; 4.Descriptive analytics: understanding past behaviour and outcomes; 5.Prescriptive analytics: predicting future outcomes. Human Resource Human Resource Analytics Management HR Analytics Vs HR Metrics Human resource analytics (HR analytics) is an area in the field of analytics that refers to applying analytic processes to the human resource department of an organization in the hope of improving employee performance and therefore getting a better return on investment. Human Resource Human Resource Analytics Management Human resources metrics are different measurements that are used to show the value that the human resources function provides to the organization. These measurements demonstrate how effective the efforts of the human resources department are to the overall success of the organization. Human Resource Human Resource Analytics Management HR and Workforce Analytics Concepts Human Resource Human Resource Analytics Management Benefits of HR Analytics • Recognize the factors which turn the employee satisfaction and productivity. • To determine the individuals KPIs on the business. • Enabling HR to demonstrate its benefaction to achieving corporate goals. • Provide information necessary to acquire, maintain, develop, and retain the right employees. Human Resource Human Resource Analytics Management • Align people, processes, and technology around common goals, helping users understand progress on key performance indicators. • Measure the strategic value of human capital investments. • Support pre-defined and ad hoc analysis, forecasting, and modeling to quantify human capital assets and support fast, strategic decision-making Human Resource Human Resource Analytics Management Challenges in HR Analytics: • Inconsistent and inaccessibility of data, • Data quality issues, • Lack of standard/generic methodologies to analyze HR data, • Executive buy-in, • Skill gap in analytical knowledge & experience, • Funding issues, • Wrong or not targeting the right analytical opportunities, • Problems in initiating the project. • Improper timing. Human Resource Human Resource Analytics Management Most widely used analytical methods / techniques include: •BCG matrix •Brainstorming •Benchmarking •Gap Analysis •Mind Maps •Pareto principle, Pareto principle 80-20 rule •Six Questions •SWOT Analysis