Big Data in Human Resources: Talent Analytics Comes of Age

Gartner expects the market for BigData and analytics to generate $3.7 Trillion in products and services and generate 4.4 million new jobs by 2015. While most of the talk is about applying BigData to marketing and consumer businesses, there is an even bigger opportunity to apply BigData to Human Resources.  (We call it Talent Analytics.)
What is BigData in HR?
There are around 160 million workers in the US alone, and most companys’ largest expense is payroll. In fact in most businesses payroll is 40% or more of total revenue, meaning that total US payroll expense is many billions of dollars.
How well do organizations truly understand what drives performance among their workforce? The answer: not really very well. Do we know why one sales person outperforms his peers? Do we understand why certain leaders thrive and others flame out? Can we accurately predict whether a candidate will really perform well in our organization?
The answer to most of these questions is no. The vast majority of hiring, management, promotion, and rewards decisions are made on gut feel, personal experience, and corporate belief systems.
This is like the Vice-President of marketing spending millions of dollars on a new marketing campaign because he or she “always does it this way.” It’s an obsolete way to make decisions.

 

An Example: Hiring the Best Sales Person
Let me give you an example:
One of our clients, a large financial services company, operates under a belief system that employees with good grades who come from highly ranked colleges will make good performers. So their recruitment, selection, and promotion process is based on these academic drivers.
Several years ago one of their analysts performed a statistical analysis of sales productivity and turnover. They looked at sales performance over the first two years of a new employee and correlated total performance and retention rates against a variety of demographic factors.
What they found was astounding. The results are shown below.

Fig 1: What really matters in sales performance (financial services company)
What did drive sales performance:

• An accurate, grammatically correct resume
• Having completed some education from beginning to end
• Having successful sales experience in high priced items
• Demonstrated success in some prior job
• Ability to work under unstructured conditions.

What did NOT matter:

• Where the candidate went to school
• What GPA they had
• The quality of their references.

Data Tells the Story
If you’ve done a lot of hiring, you know how hard it can be to assess an individual’s likelihood of success.
Well, despite a 30 year belief system which made this company successful, data showed a different story. Once this data was put back into the recruiting process, the company saw more than $4M improvement in revenues in the next fiscal period.  
BigData Tells a Story, but We Have to Listen
Companies are loaded with employee, HR, and performance data. For the last 30 years we have captured demographic information, performance information, educational history, job location, and many other factors about our employees. Are we using this data scientifically to make people decisions? Not yet.
This, to me, is the single biggest BigData opportunity in business. If we can apply science to improving the selection, management, and alignment of people, the returns can be tremendous.

How to Leverage BigData in HR
How do you leverage this huge opportunity in your company? Well often you have this data already, but you need the analytic experience and skills to perform the right analysis. And it all starts with asking the right questions.
Most companies have lots and lots of HR data (employee demographics, performance ratings, talent mobility data, training completed, age, academic history, etc.) but they are in no position to use it.
Our newest research on HR systems shows, in fact, that the average large company has more than 10 different HR applications and their core HR system is over 6 years old. So it takes effort and energy to bring this data together and make sense of it.
Most importantly of all, there is a real discipline to data analytics. It demands skills in data analysis, cleaning, statistics, visualization, and problem-solving. Most HR professionals do not yet have these skills, so companies have to find these people and bring them together to work on HR data.

Fig 2: Bersin by Deloitte Talent Analytics Maturity Model

Now is the Time
Now is the time to focus on talent analytics. Our clients are working on many high-return applications which apply to nearly every business:

• Employee retention – what creates high levels of engagement and retention?
• Sales performance – what factors drive high-performing sales professionals?
• Accident claims – what factors and which people are likely to create accidents and submit claims?
• Leadership pipeline – who are the most successful leaders and why are some being developed and others are not?
• Loss analysis – why are some locations more prone to theft and loss and what causes the variation?
• Customer retention – what talent factors drive high levels of customer satisfaction and retention?
• Expected leadership and talent gaps – where are our current talent gaps in the organization and what gaps can we predict in coming years?
• Candidate pipeline – what is the quality of our candidate pipeline and how do we better attract and select people who we know will succeed in our organiation?

Over the last ten years we have been studying applications of measurement within HR and this area has now risen to the top. When we asked HR leaders to describe their top opportunities for value creation late last year, “measuring and predicting talent performance” rated among the top three.
BigData in HR is here.

Original Source : http://www.forbes.com/sites/joshbersin/2013/02/17/bigdata-in-human-resources-talent-analytics-comes-of-age/