HR redefined as people analytic Managment

HR Analytics

For most of us HR refer to a person, whom we get introduced when you enter a company or when you say a final good bye to the company. In between entry and exit, most of us hardly get time or opportunity to talk to HR on one –on – One to discuss the problem, people are facing during their job, manager being not capable of handling the team or take appropriate action against issues raised by the team or anything related to employee satisfaction, whether it is salary, benefit, or personal issues.
Over the period of time HR has become more or less, a recruitment cell for the company, if the company is big enough in terms of employees, they have the volume of work in terms of people joining in and people quitting the job. But if there is a less attrition HR role in many cases is not justified.
HR orientation, which supposed to be into the interest of the employee finds a shift towards the employer, and the same ends up in convincing the employee on the behalf of company, rather than listening and solving their problem.
The other work of HR which mostly revolves around the administrative job and few routine job related to the fiscal year cycle is eventually being taken over by the Team manager itself.
Although as the name suggests Human resource management can’t be handled with in the current profile designed.It needs to be in sync with technology, analytic and business objective. in fact it has got the reach to all the places because, all the places have got the origin through HR gateway. But current status of the profile needs to be redefined.
Workforce Management Company, which took over majority of the in house work of the companies, is gaining the momentum in terms of searching the appropriate workforce, hiring, on-boarding, and even accountability of the wages paid is reasonable saving without carrying the overhead cost of the HR department.

HR Analytics / Workforce Analytics are the extended version of the conventional HR. which has got the amalgam of the business objective with the Human resource management and a blend of applied mathematics in it.
The role becomes very critical in technology driven companies, where workforce and technology both are dynamic, and if the management on the workforce doesn’t have the sync with both of these, it is hard to keep the attrition in control.

So, introduction of scientific approach in HR is a must to drive the business decision, and empower the HR professional.
Refer next post on:
“Count the employee pulse over sentiment analysis through Social media”

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Bubble Burst (Big data Vs Dot Com)

bubble burst
Like Dot com Bubble in 2000. and companies involved in Information technology and service providing through internet reached their peak and mostly start up, who and their investors who pushed in the product in anticipation of Too Much return, and the start ups used up all their cash resulted in majority of the dot-coms ceased trading after burning through their venture capital, many having never made a profit. Investors often referred to these failed dot-coms as “dot-bombs”.

The Current “BIG DATA” is the child of same dot com revolution, Many applications driven through internet over the ages bring the internet more a fun place than a serious IT Stuff. The current status of the internet access through handy and affordable devices like Mobile Tablet, laptop along with social media apps, which has given data generation power to millions of world population.

Since Data is the information, any technology which could drive such activity of storing, analyzing, and making sense out of that has become a part of this BIG DATA drive.

Social media is more of a qualitative data than Quantitative (Conventional data). Making sense out of Qualitative data is far more complex than quantitative data, specially when it’s in TB and GB of data size.

Above all the major question is, how far the big data could be accurate in supporting the business judgement and in turn their Strategy.
Start ups mushrooming, all across the globe joining the Big data race, but market is still immature in terms of ROI on this technology, and a structured and simplified approach.