HR Analytics First module corporate expericence.pptx

HR Analytics First module.pptx

1. VTU IV SEM MBA BUSINESS ANALYTICS AREA HUMAN RESOURCE ANALYTICS 22MBABA404 HRA UNIT 1 - HR ANALYTICS

2. HR Analytics in Perspective Analytics is based on data. HR analytics is the science of gathering, organizing and analyzing the data related to HR functions like recruitment, talent management, employee engagement, performance and retention to ensure better decision making in all these areas. Role of HR Analytics HR management software offers real-time data analytics that helps you hire, retain, and develop the best talent. Human resource analytics also called as workforce analytics or talent analytics enables your HR managers to make better decisions based on hardcore data. Analytics helps in predicting retention and offers extensive modelling capabilities for workforce planning. Workforce analytics enables you to calculate how many employees would retire per year, the type of candidates needed to replace them, and from where those new hires can be recruited. This helps in categorizing and prioritizing action plans that address the potential talent shortage

3. DEFINITION- ANALYTICS Analytics is a meeting of art and science. The arts teach us how to look at the world. The sciences teach us how to do something. Analytics is first a mental framework, a logistical progression, and second a set of statistical operations. Human resources (HR) or human capital analytics is primarily a communications device. It brings together data from disparate sources, such as surveys, records, and operations, to decorate a unified, actionable picture of current conditions and likely futures. This is an evidence-based approach to making better decisions.

4. Analytics is divided into three levels: Descriptive Analytics-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. Predictive Analytics- 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. Prescriptive Analytics-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

5. TWO VALUES The purpose of analytics is to find the best path through a mass of data to uncover hidden value. Value comes in two forms: financial and economic . There is a distinct difference between these forms initially, yet they eventually combine. Economic data includes practical, non-cash significant items or processes affecting material resources. Examples include market reputation, customer satisfaction, best companies to work for, and community relations. Financial data are often referred to as off– balance sheet assets. Each of them eventually should turn into financial value as stockholders invest in company stock, customers purchase products or services, high-performing personnel seek employment with the organization, and favourable community support ensues. Financial value examples are cash and other liquid resources such as stock and bonds. These are recorded on the income statement and balance sheet, the building blocks of accounting

6. VALUING HR ANALYTICS IN THE ORGANIZATIONAL SYSTEM

7. The Building Blocks of Analytics

8. The Levels of Analytics

9. Description of levels of analytics

10. HR ANALYTICS: THE THIRD WAVE FOR HR VALUE CREATION

11. Capturing Value through Third-party Analytics Arrangement Project-based HR analytics. This is typically a one-time consulting-type engagement where the organization needs a solution to a pressing problem within a fixed time frame. This is presently the most popular engagement model. Ongoing-relationship / outsourcing-based HR analytics. There are broadly two types of arrangements here: As part of HR outsourcing arrangement. This is on an ongoing basis as part of an existing outsourcing engagement (a multi-process HR outsourcing engagement or a single-process outsourcing engagement such as Recruitment Process Outsourcing (RPO)). There are two different constructs in which it works: Business-as-usual (BAU) construct. The outsourcing contract does not specify the usage of analytics but the buyer expects the service provider to utilize analytics in a BAU construct to make incremental improvements Specified analytics construct. In this case, analytics is specifically mentioned in the initial contract or incorporated at a later stage.

12. Service level agreement (SLA) / Key performance indicator (KPI)

13. APPROACH TO HR ANALYTICS

14. LOCATING THE HR CHALLENGE IN THE SYSTEM- CURRENT ADOPTION AND CHALLENGES Traditional HR mindset. Organizations’ internal limitations with the three building blocks of analytics. Many organizations are ill-prepared to take on the analytics journey by themselves. A common hurdle is the lack of internal talent well-versed with statistics/analytics knowledge within HR. Additionally, organizations may lack appropriate analytics tools or the technological capability. Lastly, lack of a unified data warehouse due to unequal HR systems might act as a bottleneck, especially for broad scope HR analytics usage High investment cost. For an organization to embark on the analytics journey on their own, it will require a high upfront investment in terms of people, technology, and data. Hiring analytics talent is a big investment. Considering the lack of HR-specific analytics talent in the market, the company will also have to invest and develop cross-functional talent between the fresh-hired analytics people and internal HR team. Investments in analytics tools or a unified data warehouse are also costly propositions High operational cost. Some of the attractive HR areas where analytics can make a difference, such as compensation designing and performance management, are point-in-time activities which occur every year only at specific time-intervals. Any organization attempting to gain the analytics advantage for just these point-in-time activities will still have to maintain a vast analytics infrastructure (people and tools) throughout the year, thereby raising operational cost through a fixed cost component.

15. JOURNEY OF HR ANALYTICS JUSTIFICATION- MEASUREMENT- EFFECTIVENESS- VALUE CREATION- IMPACT HR VALUE CHAIN   1.Efficiency 2.Effectiveness 3.Impact HR MEASUREMENT MODEL:   It speaks in terms of Efficiency, Effectiveness & Outcome

16. HRA FRAMEWORK Measure the individual Behaviors, Traits or Reactions- Measures of the reactions of various groups (top management, customers, applicants or trainees) What individuals have learned How their behaviour has changed on the job

17. Include various ratios HR Ratios (accident frequency or severity) Calculating percentages (labour turnover) Measuring central tendency & variability (such as standard deviation of performance, shortages & surplus) Measures of correlations (for example measures of association between employee satisfaction & turnover) STATISTICAL SUMMARIES INCLUDES & SPEAKS ABOUT INDIVIDUAL MEASURES

18. HR measurement journey in tune with the HR maturity journey understanding the organizational system ( LEAN) In 1987 a research team from MIT studying the Toyota production system coined the term LEAN, to describe the system as one that “ needs less of everything to design & produce products economically at lower volume with fewer errors ” Womack & Jones (1991) defined LEAN as a way to do more with less –less human effort, less equipment, less time & less space – while coming closer to providing customers with exactly what they want.

19. LEAN Organization System:   A lean organization system describes a business or business unit that holistically applies lean principles to the way it plans, prioritizes, manages & measures work. LEAN organization system – Two fundamental concepts of LEAN   Eliminate anything that does not add value to customer Work systematically & continuously to create more value to the customers   KEY PRINCIPLES OF LEAN SYSTEM   Build Quality   Deliver Fast Defer Commitment Respect People – lean systems are designed to maximize the customer value & minimizing the waste, lean system encourages that allow everyone to do their best work.