To Say It’s The ‘next Big Thing’ Is Incorrect. For Those Who Have Found Out How To Use Big Data, It’s Already Paying Dividends.
By Jerry Roche
Emerging technologies, Cloud computing and the era of “Big Data” aren’t just transforming how we deliver employee learning and development. They’re changing how we lead, organize teams, motivate employees and marshal resources, enabling us to make smarter decisions that drive targeted results.
That shift requires chief learning officers to adapt and innovate how they deliver learning to the organization at large and how they prepare leaders to succeed.
“Big Data is a massive explosion, a growth in data being generated and captured on a daily basis,” says Ben Willis, senior director of Product Strategy at Saba. “It’s tempting to blame the bird (Twitter) or social media. It’s the advent of Cloud computing, mobile computing, and all sorts of fantastic new technology. The numbers are staggering. Twitter is generating 1,000 tweets per minute, but it’s not alone. Google records 700,000 searches every hour, Facebook 700,000 status updates every hour — and YouTube reports 600 new videos being uploaded every minute!”
Another staggering statistic: 168 million emails are sent every second, according to Willis.
Eric Bruner, chief technologist at GP Strategies, says that the most current information on Big Data is two years old. “But data is doubling every 24 months,” he notes. “In one business day, you would fill up more than 20 million file cabinets for one company, Walmart.”
The problem for businesses is sorting and analyzing Big Data — and doing it before new data comes in. “Being able to do something with it quickly is one of the real challenges,” Bruner further notes.
“Along with mountains of data came new roles and new technologies.” says Willis. “Older technologies were not able to scale up to accommodate all the new data. New technologies like algorithms have allowed us to get smart about Big Data. Computers can be taught to learn on their own with new algorithms. This sounds scary and futuristic, but the reality is that these systems are in use today. One example is spam filters.”
Another example might be IBM’s “Watson,” which is being called a cognitive computer that is forging a new partnership between humans and computers that scales and augments human expertise. “Exciting examples of machine learning can be found in the medicine and financial – investing – markets, ” Willis says. The perfect use of big data might be intelligent mentoring.
Each employee would get his or her own personal computer- based mentor that works around the clock, learns from what the employee inputs and what he or she does. Experiences make the compu-mentor “smarter,” and it returns the favor by finding content that the employee needs or likes and locating relevant human mentors to help solve challenges.
In the corporate/organizational setting, Big Data can assist with career planning, learning recommendations and succession planning, among other functions like learning.
“We can move beyond SCORM in terms of what learning is tracked, where and how,” Willis observes. “We want to capture learning wherever, whenever and however it’s occurring. In particular, your LRS (learning record store) needs to be hosted in the Cloud so it’s easily accessible and hosted on Big Data technologies.
“Learning is shifting toward non-traditional models. You want to make sure that you are positioning things correctly with various stakeholder audiences by communicating actively with them and involving HR and legal teams in terms of how you’re capturing the data and what you’re doing with it. You must use data for positive purposes, [but] it’ll be a process of change.”
Bruner adds: “We have access to learning data that we can correlate to business data, specifically around hiring, engagement, performance and business outcomes. So [learning professionals should] make sure you are partnering with HR and I.T. folks. You won’t be able to convince the CEO to invest in Big Data without doing so. It’s how you leverage the investment. It’s a co-share. Be an advocate for data-driven decisions to business problems.”
The Newest Research
SNS Research’s latest report indicates that global spending on Big Data technology was expected to reach nearly $30 billion by the end of 2014.
Originally used as a term to describe datasets whose size is beyond the ability of traditional databases, the scope of Big Data has significantly expanded over the years. It now not only refers to the data itself but also a set of technologies that capture, store, manage and analyze large and variable collections of data to solve complex problems.
Amid the proliferation of real-time data from sources such as mobile devices, Web, social media, sensors, log files and transactional applications, Big Data has found a host of vertical market applications, ranging from fraud detection to R&D.
Despite challenges relating to privacy concerns and organizational resistance, Big Data investments continue to gain momentum throughout the globe. SNS Research estimates that Big Data investments are expected to register a compound annual growth rate of 17 percent over the next six years.