How Big is Big Data, What Is Semantic Search and Why Do Analytics Matter?
So how well do you know what these terms mean? And more to the point -- what do these trends mean for your talent processes, from sourcing to workforce planning?
We've pulled together some questions and answers on the new talent management game that company executives and HR people are just starting to play. Let's start with a brief quiz.
What exactly is big data?
Big data is data that is so voluminous -- and often so varied in structure and content -- that it cannot effectively be managed by traditional database technology.
Big data is all the data collected by the National Weather Service; it's all of the customer data that Walmart collects in the one million sales the retailer rings up per hour. And it's all the information on all the talented workers within your organization and everywhere else in the world who you might recruit to polish off a quick project for tomorrow or to help launch next year's Internet juggernaut.
When it comes to workforce planning, big data could change the whole game.
“The emphasis on data and analytics is stronger than ever,” says Katherine Graham-Leviss, president of XBInsight, a talent-assessment consulting firm in Portsmouth, R.I.
What are analytics -- and what are predictive analytics?
Whether for inventory management or talent assessment, companies have been using data analytics to guide business decisions for decades. So what’s new about today’s predictive analytics?
Two things: the quantity of valuable data available for analysis, and how semantics are brought to bear.
“The amount of data being generated today is so vast, and is accelerating so quickly, that it is nearly impossible, to use conventional analytics software to work with these new data sets,” says Earl Rennison, vice president of architecture for Monster.
“As a result, an entirely new class of software is needed to address data at the scale of data that is being generated.”
What is semantic search?
Microsoft, Hewlett-Packard, Google and Apple are just some of the global companies that are utilizing semantic search to tap big data and deliver better search results.
Semantic search goes beyond simple keyword analysis to examine context and retrieve content that matches the meaning searchers seek, not just the words they type -- creating more value in searches in many business domains, including talent management.
“SeeMoreTM adds semantic analysis to the mix, which is a huge step forward in being able to do very high quality analytics on unstructured data,” says Rennison. “Doing high-quality analytics on resumes and profiles is especially difficult because parsing and understanding the content is so difficult.”
"Semantic search of resumes helps recruiters and employers surface the top candidates more quickly and easily than simplistic keyword search engines," says Javid Muhammedali, vice president of product management at Monster, maker of 6Sense® Search Technology.
How are these technologies changing the talent pool?
In the 21st-century economy, the world is the employer's talent pool, whether it's a tiny software startup or a multibillion-dollar corporation.
“The big picture is coming up with a representation of every individual on the planet, and understanding their skill sets, aptitudes, interests, where they’re heading -- and where they want to head, which often isn't the same,” says Rennison.
Where in the talent management process can big data be applied?
Because big data relies on bottom-up, emergent trends, there are no boundaries to its potential uses.
“Organizations need to apply data to the entire employee life cycle, from recruitment and onboarding to professional development and succession planning,” says Graham-Leviss. “As employees grow within the organization, they will need different skills. It’s critical to predict where the skills gaps will be.”
Talent management goes deeper.
As organizations grow and expand the geographic reach of their workforce, it becomes ever more difficult to track who has what skills. That's a talent management shortfall that can quickly translate to a strategic disadvantage.
One solution may be big-data analytics and semantic search that parse the professional profiles of all employees. "SeeMoreTM lets companies see into their own workforce, and drill down into what’s within the resumes of their workers,” says Muhammedali.
Drilling down for hard-to-find skill combinations.
A big-data approach can uncover critical information in places you might never think to look – like finding a programmer with great communication skills by plumbing his activity on professional social media.
“Some of our technology clients want to know how to get the tech skills together with soft skills in their workers,” says Doug Palmer, who leads Deloitte Consulting’s social-business practice. “Validated skills are what’s important, not just what’s self-professed.”
We don't stop thinking about tomorrow, but what can we do about it?
Having a clear picture of your own workforce and the labor market is a great start to a big-data-informed talent strategy. But to build your company's future, you've got to go further.
“Predictive analytics let you look around the curve a little, to anticipate future talent needs,” says Muhammedali.
With predictive analytics using big data, SeeMoreTM enables organizations to solve a broad array of talent-strategy riddles, according to Rennison, yielding answers to mission-critical questions, such as: “Do I have the right workforce?" "Can I adapt my workforce to meet the company’s new challenge?"
Say I want to open a new office or factory in a different area -- where should I locate that facility, how will I be able to staff it?