Times flies! There was an era of Manpower Planning...also Sales Forecasting & different techniques were used to do so....accurately to the extent possible.
Now, we talk of Workforce planning which is more exhaustive than Manpower Planning or to put it simply, Workforce Planning includes Manpower Planning. Sales Forecasting for the Annual Business Plan (ABP), later became Rolling Sales Plan, however this was a controversial one...since it was more about a build up on last year...may have discounted sandbagging or dumping...however, the market was/is not always predictable! Now, it is the era of Predictive Analytics- from hard data like attrition, retention, consumer demographic patters to soft data such as consumer behaviour, career growth path of a hi-po (High Potential) employee in the organisation , an employee's probable tenure in the organisation--- attempt is being made to "Predict IT All".
Management is as much a science as much as it is an Art- then, can we predict everything about every human resource- thoughts, actions, behaviour? What are we trying to do & why? In HR, data entry & computing has moved on to become HR Analytics. We have moved from local made HRIS (Human Resource Information Systems) to People Soft, then SAP, to BIG Data- WorkDay which is a Cloud based Data system.
Predictive analytics is the branch of the advanced analytics which is used to make predictions about unknown future events. It uses many techniques from data mining, statistics, modelling, machine learning, and artificial intelligence to analyze current data to make predictions about future. Often, the unknown event of interest is in the future, but it can be applied to any type of unknown whether it be in the past, present or future. It is widely used to solve real-world problems in business, government, economics and even science-from meteorology to genetics. Experts use predictive analysis in healthcare primarily to determine which patients are at risk of developing certain conditions like diabetes etc.
As super computers get more and more super, you'd think that eventually we'd be able to calculate the position and interactions of every atom in the universe and be able to accurately predict the future. Science, government and private enterprises are asking if they can predict future events by creatively crunching massive amounts of data made available by you! There is a frenzy around this & we are trying to play demi-gods by trying to predict everything including "the art of managing people"-Please note that it is an Art!!!
Predicting turnover is the most common area where predictive analytics is being used by Human Resource professionals in organizations. Others include assessing the quality of hires, and forecasting the benefits and return on investment of training programs. However, today, many companies are still grappling with the question of how predictive analytics can improve talent management issues. Despite a slow start, we see that the HR function/professionals are starting to embrace data. In 2013, Deloitte reported that 57 percent of HR departments increased their investment in measurement and analytics.
Firstly, data has to be compiled from disparate systems that don't always talk to each other and often don't agree when they do. Pertinent data resides in systems tracking payroll, time and attendance, applications and educational programs, among other things. Today, tools to integrate that data are few and far between. One does find a few vendors offering solutions in this regard.
Next, resources have to be found to develop the technical tools required to manage and analyze talent and recruitment data. That presents a challenge to many HR departments, which are rarely given the same priority as sales, marketing or operations when it comes to securing IT resources since many have outsourced this.
Perhaps the most fundamental changes involve HR itself. While the idea of HR becoming a strategic partner to the wider organization isn't new, the idea of using analytics to accomplish that goal is. This poses challenges both in terms of skills and addressing issues surrounding privacy and compliance. Talent data is very different from, say, manufacturing data, and companies need to be careful in how they present even summary information.
Talent management, is typically viewed as a "soft science," but the increasing application of data changes that. I would say one can teach an HR person, analytics, but you can't teach an analytics person, HR. HR is unique when it comes to data. There are certain nuances in its structures and hierarchies. It would be like telling a software guy to go figure out the hardware specs.
The good news is that we have moved beyond mundane data entry & report generation to exploring more advanced permutations & combinations of basic data to forecast trends, future events in most fields that science can explain. Behaviour, thoughts & soft acts continue to be unpredictable since rationale or logic does not govern human behavior. It is managed and motivated by numerous factors not found in text books or various theories of management!