With Big Data, Companies Can Predict Your Success Before Your First Day On The Job

The need for high-performing employees, and for hiring the right candidate for the right job at the right time, has never been greater. Here’s how the talent hunt is being transformed.

With Big Data, Companies Can Predict Your Success Before Your First Day On The Job

We are not what we eat, as many people like to say–we are what we do.


Since the “big bang of culture” about 50,000 years ago when Homo sapiens survived and the Neanderthals didn’t despite their larger brain cavities and more robust physiques, humans have evolved to a stage where we identify ourselves by what we do more than any one of the other three dimensions that define us, namely the food we eat, the company we keep, and the faith we follow.

We also discovered at the time the tremendous power of social interaction, where 1 + 1 adds up to greater than 3. Then, it helped our species survive; now it rules almost every waking moment. And today, the combination of work as identity and the power of social interaction is playing a huge role in shaping the workplace and workforce. Identifying ourselves by what we do is inextricably linked with seeking meaning in our work, as this gives us a sense of greatness and significance in the larger scheme of things and of fulfilling a higher purpose. And this desire on the part of humanity to find meaning at work has led to epochal changes in the way individuals make decisions about job selection and tenure and the way organizations go about recruiting and retaining people.

A great example can be found at Kenexa, where we defined our mission of serving humanity a number of years ago, and I found that we were attracting and retaining employees for whom this held a great deal of meaning and purpose. People tend to talk about passion for one’s work leading to success and engagement; we have found that the intersection of passion, pay, and purpose is what really engages a person to be the best they can be at their work. A third facet that is influencing the way we work is the rise of big data analytics. Humans have been creating and storing data at an exponential rate for thousands of years. What’s different now is the paradigm shift both in the way data is stored and how it’s being viewed and utilized. We now have the awareness, the analytics, and the technology to use this big data for the benefit of humanity. And a significant aspect of this is the harnessing of big data to benefit the most valuable asset of an enterprise, its people.

Big data is starting to penetrate nearly every aspect of business, from how organizations market their products and services to how each step of the manufacturing process impacts the bottom line to the people they hire. If you apply for a job today, you can be sure your prospective employer is going to be checking out your personal brand across all the social networks you are part of to see if you are a good candidate to hire. The advent of social networks and the tremendous amount of data being generated by multiple channels have also given individuals massive choices and the discernment to make choices about the products they wish to buy and, increasingly, the companies they choose to work for. There are four basic reasons we use data:

  1. To make decisions.
  2. To try and predict the future and act on it.
  3. To benchmark ourselves against others.
  4. To create language around which we can tell stories or communicate with one another (for example, how do I read my engagement data to show the impact of leadership in my organization?).

As enterprises are going through this journey with big data and social business tools, the larger companies have a significant edge in terms of access to data from their hiring systems and using predictive analytics, assessment, and behavioral tools to make selections. This has also enabled them to move into another arena where they are now using sentiment indices to predict the capability, culture, and capacity of individuals as they come into the workforce and the company.

What does this mean for individuals? Essentially, it gives them the ability to choose where and how they want to work, to obtain better insights on mapping a career path for themselves, and to draw on the collective knowledge and experiences of the organization in order to adopt best practices, solve problems innovatively, and be far more productive at work, confident that their talents are being maximized. This leads them to be fully engaged with what they are doing and with the organization, which is a winning situation for both. Engagement at the most basic level translates into your waking up every morning excited about going to work.


Personally, I define work as “doing something I don’t want to do”–and that actually applies only to exercise in my case. The rest is what I love doing. So typically, engagement leads to people being far better and healthier individuals, better partners/spouses, better children, and better community members. On an enterprise level, the combination of analytics and human behavioral insights gives companies better sourcing capabilities and better predictors of where their next level of talent is going to come from, with the ability to predict the success of potential candidates before they even walk through the door. To hire individuals who are the best fit for every job–not only in terms of their abilities and skills, but also based on culture fit. Data from performance management solutions and surveys can be used to increase efficiencies, to increase engagement, and to increase productivity, which will have an impact on the top and bottom line. For HR, the competitive advantage lies in analyzing and using the large amounts of employee-generated big data to drive productivity, service, innovation, execution, and employer/employee behavior.

An interesting advantage of big data is its use to dissipate workplace myths. For example, a popular myth is that employees need a strong work-life balance to be engaged. Actually, we’ve discovered that engagement levels rise when employees are mission-driven, often by a big project or challenge, when they typically have increased work hours and reduced personal time. Another example is the conventional wisdom that says successful salespeople must have an outgoing personality, are naturally friendly, and are able to get along with everyone. What IBM Kenexa’s team of more than 100 behavioral scientists and researchers discovered, by studying more than 1,000 salespeople in several companies across diverse industry verticals, is that success at work is more likely to occur when salespeople have emotional courage and persistence. This is the ability to stay engaged at work and keep trying even when you’ve been told no time after time. Our data shows salespeople who exhibit these traits consistently are the cream of the crop in their profession.

A recent study by IBM revealed that 70%of CEOs claim human capital is the single biggest contributor to sustained economic value. At the same time, paradoxically, unemployment levels are high but 65% of global companies are having trouble finding candidates with the skills their workforces require. So the need for high-performing employees, and for hiring the right candidate for the right job at the right place, has never been greater.

Thanks to data analytics, organizations are in a better position to study potential candidates and pinpoint with amazing accuracy those who have the capability to do the job, the capacity to learn new skills that may be needed in the future, and who are a good match with the culture of the company. We call these the three essential Cs of business success, and believe that understanding and hiring for these are the unquestionable keys to giving any enterprise a distinct competitive edge, giving employees the meaning they crave in their work and, as a result, shaping a better society.

Rudy Karsan is founder of Kenexa, an IBM company and provider of recruiting and talent management solutions to engage a smarter, more effective workforce across an organization’s most critical business functions. The company was acquired by IBM in December 2012.

[Image: Flickr user Francis Mckee]