Predictive HR--Analytics

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HR ca not operate in traditional ways any more

The technology driven data management is a necessity .
HR analytic is pretty useful in driving crucial decisions.about work force
especially in IT sector.

Here are few tips.If you liked least you could do is to share

also read my latest book in Amazon

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Predictive HR--Analytics

  1. 1. ECTOTHERMIC –HR- ANALYTICS PREDICT AND PRESERVE Dr. Sarma HR SME 6/27/2013 Dr.sarma/hr/analytic 1
  2. 2. What is covered The new vocabulary Ectothermic analytic Social media impact Why and what predictive analytics can do HR analytics new normal HR to Create the driver Predict or perish 6/27/2013 Dr.sarma/hr/analytic 2
  3. 3. New Vocabulary • Corporations need to look “outside-in” for robust analytic reporting • i will call it ectothermic analytic • Risk is mostly from out side • Even attrition is more due to pull power than push power • Revenue loss is due to competition from out side • Fraudulent intrusion biggest security threat is from out side 6/27/2013 drsarma/hr/analytic 3
  4. 4. Past to future tetra bites of data of information being generated every single which is being used to answer, fairly accurately, what will probably occur in the future Analytics is shifting emphasis from trend analysis based purely on internal data to presenting scenarios of the future 6/27/2013 drsarma/hr/analytic 4
  5. 5. Social media impact Predicting the future sounds mystical Predictive ANALYTIC is touching every human on Earth who accesses internet day to day existence is now being exploited by social media and then the analytics. 6/27/2013 drsarma/hr/analytic 5
  6. 6. Ectothermic analytic • HR must shift gear to what I would call Ectothermic analytic • Just as an organism that regulates its body temperature largely by exchanging heat with its surroundings business entities must focus on external data sources to adjust internal heat 6/27/2013 drsarma/hr/analytic 6
  7. 7. Why ectothermic? • Competition- risk comes from out side • Growth- depends on external market changes • Fraud risk- enormous intrusion happens from outside • Customer expectation-changes as per competitive offerings outside the organization 6/27/2013 drsarma/hr/analytic 7
  8. 8. Traditional BI is not valid • Standard business intelligence and reporting methods provide value by summarizing the past. • Scorecards, dashboards, KPI metrics, OLAP, ad hoc queries deliver a retrospective analysis. • They are all 6/27/2013 drsarma/hr/analytic 8
  9. 9. Analytic impacts every day life: • When you shop in Supermarkets they know more about you as frequent shopper card • Credit rating companies gather every person’s financial history in order to predict how credit worthy that person is – how much money to lend, employers determine how responsible a person is, 6/27/2013 drsarma/hr/analytic 9
  10. 10. Life is no more isolated • In Major League Baseball data about every move made by every player during every game is gathered to predict who the starter should be against a particular team. • Satellites collect enough digital information on people, which if printed, can fill the whole earth , and these data mining and predictive capabilities were instrumental in finding and tracking Osama Bin Laden • Companies are mining millions of tweets and stock transactions a day in order to predict stock performance 6/27/2013 drsarma/hr/analytic 10
  11. 11. • Analyzing historical data is no more effective but predictive analytics is necessary as enterprise wide practice to sustain competitive advantage • predictions are being made about behaviors as information that comes from several thousands of sources. 6/27/2013 drsarma/hr/analytic 11
  12. 12. What predictive analytics can do • Every business’s success is all about managing risks that arise in future. • Decision makers therefore have to bet top dollar to determine the best course of action to minimize challenges. • Employee related risk management ,by measuring monitoring and predicting - must be the core HR process • From people point of view everything - indifferent employee, non performing ones, high performing ones, the sentiment they have about values spoken by leaders pose the risk if not managed with foresight and not hindsight . 6/27/2013 drsarma/hr/analytic 12
  13. 13. HR Reporting is next phase back0ffice automation • HR is currently delivering information to managers and executives on items that they already know, --headcount forecasted to be by quarter-end or year- end • what a past performance rating was, how many may be going on vacation. • These items are important but do not tell the business anything new and is primarily they are nothing but the next phase of Human Resource “back office” automation. 6/27/2013 drsarma/hr/analytic 13
  14. 14. Analytical Technology. • Built upon mathematics, probability, statistics, and database technologies, predictive modeling capabilities, known as machine learning -- proven routes. 6/27/2013 drsarma/hr/analytic 14
  15. 15. • HR to be true “business partner”, needs to tell the business scenarios’ that are predicted with high accuracy to happen in the future, across all levels of the organization, and provide recommendations on how to fix or exploit it. 6/27/2013 drsarma/hr/analytic 15
  16. 16. What HR analytics need to do • Use dimension-free data exploration to find answers on employee productivity and qualifications, to help to determine the appropriate size for the workforce. • Dash board on how work experience and education should affect starting pay grades • Shift from Head count reporting to telling that X additional people need to be hired because specific individuals in specific levels with specific skills are expected to leave and join the competitors • Report on the reasons they will leave e.g., the pay increase that has been given in the past 24 months, or not meeting the top performers expectation. 6/27/2013 drsarma/hr/analytic 16
  17. 17. Non traditional reporting • Report is never made on actions HR is taking if 16 of your top performing rare skill leave and join your customers after analyzing top line impact of attrition? • Factor analysis of engagement • if index is below 50% on trust will HR sit quiet? 6/27/2013 drsarma/hr/analytic 17
  18. 18. Now or Never • Human Resource organizations are having difficulty in delivering even defect free accurate headcount reports • How then they are going to predict well? • An attitude that predictive analytic is something to be explored is the wrong approach. 6/27/2013 drsarma/hr/analytic 18
  19. 19. Justify HR Funding • Forrester Report -companies spend less than 1% of their business intelligence budget on HR. • With HR making up, on average, 31% of a company’s total operating costs, HR analytic must be one of the top 3 funding areas. • The current model for today’s HCM Analytics just does not provide that “business driver” to spend more • HR needs to find “business driver”, as discovered by other functional areas, to tell the organization what it does not already know, 6/27/2013 drsarma/hr/analytic 19
  20. 20. Gain support to get the funding • All of this is predictive analytics and without it HR will continue to struggle to obtain the funding and support for their must-have analytics initiatives. • HR can do predictive analytics today by partnering with organizations (e.g. sales, marketing and engineering) that have predictive analytics already in place to make quantifiable and actionable predictions about the workforce in areas that the business does not know about. 6/27/2013 drsarma/hr/analytic 20
  21. 21. Create the Driver • In 3 weeks Oracle was able to predict which top performers were predicted to leave the organization and why - this information is now driving global policy changes in retaining key performers and has provided the approved business case to expand the scope to predicting high performer flight . 6/27/2013 drsarma/hr/analytic 21
  22. 22. Critical areas for HR Predictive analytics • 1.Turnover modeling. Predicting future turnover in business units in specific functions, geographies by looking at factors such as commute time, time since last role change, and performance over time. One can accelerate hiring efforts accordingly, reducing lead time time and panic hiring, which can lead to lower cost, higher quality hiring. • 2. Recruitment advertising /HRBranding effectiveness: HR Branding efforts based on Response modeling for advertising jobs. 6/27/2013 drsarma/hr/analytic 22
  23. 23. HR –Predictive analytic • 3.Targeted retention. Find out high risk of churn in the future and focus retention activities on critical few people • 4. Risk Management: profiling of candidates with higher risk of leaving prematurely or those performing below standard. • 5. Talent Forecasting. To predict which new hires, based on their profile, are likely to be high fliers and then moving them in to fast track programs 6/27/2013 drsarma/hr/analytic 23
  24. 24. Final words • HR is at a cross roads where analytics is concerned. • In order for HR to be successful in analytics it must embrace the shift towards predictive analytics. Without making the shift, HR will not be able to deliver on the promise of being a “Business Partner”. • 6/27/2013 drsarma/hr/analytic 24

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