Big data has revolutionized the talent landscape, promising new insights to help the way companies hire, manage, and retain their teams.
But is big data always better data? What if a company doesn’t have the resources to make sense of that data? The fact is that big data contains both bad data and beautiful data. And becoming a competent consumer of data is essential for optimizing selection science technology.
The 12th Annual SIOP Leading Edge Consortium, taking place October 21-22 in Atlanta, will explore this imperative. Hosted by the Society for Industrial and Organizational Psychology (SIOP), the theme for this year’s event is Talent Analytics: Data Science to Drive People Decisions and Business Impact and will showcase the power and promise of combining organizational science with new and emerging methods of data collection and analysis.
As a sponsor of the event, Shaker is thrilled to be a part of the dialogue about how data science and talent analytics continue to transform how companies make hiring decisions. This consortium will explore new strategies and technology for gathering data and the impact of this unprecedented level of information on companies’ people strategies.
But without theoretical rigor—and the right resources in place to analyze and articulate meaningful insights—big data is just that: a whole lot of information. And without a science-based approach to understanding it, you might be headed toward the wrong conclusions.
Consider the infamous example of curly fries, in which a large study found that smart people are more likely to “like” curly fries on Facebook, based on unfounded correlations. A possible reason for this? One smart person who is friends with other smart people liked curly fries. Since friends tend to “like” the same things, the curly-fries-liking phenomenon propagated through Facebook’s networks of smart people.
The moral of this story is that big data isn’t everything; just because it’s easy to quantify something doesn’t mean it’s useful or tells the whole story. Applying this principle to your people strategy is just as crucial. Without approaching big data from a theoretical standpoint, you may be tempted to make correlations that can lead to discrimination based on age, gender, race or other factors.
Instead, any initiative involving the use of big data for talent acquisition should be done from a foundation of science. To extract the most value, talent acquisition practitioners must learn how to collect relevant data and draw sound conclusions from it actively.
Since our inception, Shaker has been a leader in helping companies use selection science technology intelligently, empowering them to make fair, unbiased decisions about their candidates to create high-performing workforces.
Shaker is a science-based organization—I-O psychologists make up a majority of our team. The combined expertise of our skilled staff and over a decade of proven results enable us to help companies implement objective methods to improve quality of hire.
Shaker uses the most relevant data—not just readily available data—to help companies make smarter people decisions.
Shaker is excited to be part of this upcoming consortium and to continue to help companies go beyond meaningless associations in data to improve their understanding of how human characteristics can lead to positive business results.