Predictive –hr analytics

04/07/2023 Dr.sarma/hr/analytic 1

ECTOTHERMIC –HR-ANALYTICSPREDICT AND PRESERVE

Dr. Sarma

HR SME

04/07/2023 Dr.sarma/hr/analytic 2

What is covered

The new vocabularyEctothermic analyticSocial media impactWhy and what predictive analytics can doHR analytics new normalHR to Create the driverPredict or perish

04/07/2023 drsarma/hr/analytic 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


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


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.


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


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


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


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,


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


• 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.


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 .


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.


Analytical Technology.

• Built upon mathematics, probability, statistics, and database technologies, predictive modeling capabilities, known as machine learning -- proven routes.


• 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.


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.


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?


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.


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,


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.


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 .


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.


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


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”.

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