Whenever someone talks about the “future of learning” nowadays, the same topics inevitably come up: augmented reality, virtual reality, machine learning, artificial intelligence, and data. But, while they’re discussed in future tense, several of these “trendy topics” aren’t exactly new. For example, I managed a virtual reality attraction at Walt Disney World 10 years ago. And Netflix demonstrated the power of data 3 years ago when they constructed the hit show House of Cards based on viewer habits and preferences rather than relying on human creativity alone. So, while several of these “futuristic” topics aren’t necessarily brand new, we are just now starting to realize their potential applications, including within the workplace. This is especially true of data … I’m sorry … BIG data!

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Modern technology is already helping organizations gather mountains of data about their customers. Resulting insights shape everything from product development to marketing strategies. The same potential exists within the workplace, but most companies have failed to identify and leverage this data to gain powerful insights and drive business results. It’s beyond time for employers to catch up with the consumer world and leverage data to evolve our workplace experiences, especially as related to learning and performance.

At Axonify, we’ve been partnering with global enterprises to leverage data to drive learning, capability and business results for quite some time. For example, our Behaviors capability is helping Walmart collect almost 1 million real-world observations every month, which are then used to target refresher training for employees who have an identified performance gap. We are also using machine learning and adaptive technology to improve our partners’ content and support strategies and firmly establish connections between knowledge and business results. We’ll be sharing plenty of continued insights on these efforts in the near future.

To that end, this month’s curated insights dig into the current potential for BIG data.

How data and machine learning are ‘part of Uber’s DNA’ from TechRepublic

Uber is now synonymous for industry disruption via technology. Ask any cab driver! This TechRepublic article digs into just how foundational data is to Uber’s continued business strategy. Data-driven machine learning enables the company’s user experience obsession, which just happens to be its biggest differentiator in a competitive transportation marketplace. The article also makes a great point about “clean data.” Organizations must be smart about how they source and use data. Just using data for the sake of using data will likely lead to faulty insights and poor decision-making.

At WeWork, Humans Supply Data for Its “Giant Computers” from Fast Company

Shifting from the consumer world to the world of work. My industry peer, Melissa Daimler, recently transitioned from her role as Head of Learning at Twitter to become SVP of Talent with WeWork, an organization that provides communal working and living spaces. Coincidentally, Fast Company recently featured WeWork in an article exploring how it uses data to maximize the employee experience in its shared office spaces. Think about how difficult it can be to find open meeting space in your office. Now layer onto that experience the fact that co-working spaces include a mix of people from different organizations, industries and roles. WeWork is tracking data on facility utilization to not only improve the existing experience but also develop its future spaces. This is a great example of how data based on what people actually do at work can shape our ability to better support them.

Data: Evolve Your Learning Strategy from Art to Science from Lori Niles-Hofmann

Now let’s shift focus from where we work to how we learn at work. “Imagine sitting down to develop a learning design strategy and already knowing the optimum length, medium, style, and tone, and even the best day of the week and the time of day to launch your content.” Lori Niles-Hofmann posits this idea as part of her recent blog post exploring the strategic value of data to improve learning design practices. Many L&D pros are quick to point out that learning is just as much art as it is science. I don’t entirely disagree, but I do think there is a natural order of operations to these concepts. Rather than operate based on hunch or past practice, we must leverage data to better understand our audience and provide content and experiences that REALLY work and drive the desired business outcomes.

EEOC Panel Looks at Implications of Big Data in Workplace from SHRM

Leave it to HR to suck all the fun out of the data conversation! I’m kidding … kinda. Seriously, workplace data doesn’t just represent a tremendous opportunity to improve our employees’ learning and performance experiences. It’s also a road fraught with danger for those who don’t understand and appreciate the greater implications of data-driven decisions. This SHRM article rightly points out these concerns and suggests best practices for employers who are looking to make better use of their data. We must not only consider our legal obligations but also our responsibility to our people in ensuring predictive models and frameworks are vetted continuously for accuracy and fairness. In addition to using data to inform learning strategy, we must train everyone involved, especially frontline managers, on how to best use data in their decision-making.

People analytics reveals three things HR may be getting wrong from McKinsey

One of the most interesting parts of the BIG data shift will be seeing just how ineffective many of our current practices really are. Just compare the types of original programming coming from the data-driven Netflix shop nowadays as compared to traditional networks. Many tried and true strategies are going to get thrown away thanks to newly identified patterns and insights that could only be discovered through modern technology. This McKinsey article provides a few great examples of established HR practices that are beginning to evolve based on the improved use of data. It also highlights the readiness of the learning function to focus on high-priority, data-ready initiatives. Not only should HR be leveraging data to find and motivate talent, but it should also leverage these principles to determine how to best develop and retain highly-coveted employees.

Realize it or not, we already live in a data-driven world. Most workplaces are simply playing catch-up in hopes of gaining the same types of insights and efficiencies that marketers have been using for years. Rather than thinking about this idea as part of the “future of learning,” L&D pros must shift mindsets and embrace the current potential of BIG data. Seat times, completions and level one surveys were never enough to justify L&D value. We are no longer limited to “training data” and must take advantage of new ideas and partners who can bring data to life in our everyday learning and performance work.

How could your organization make better use of existing data to improve employee experiences? Share your thoughts in the comments below, and check the Axonify KNOWledge Blog next month for our next curated post. For a behind-the-scenes look into my personal curation efforts, check out my Flipboard, including my Curious about Data Magazine, where I post new articles on a variety of workplace learning topics every day.

JD Dillon

Author: JD Dillon

JD Dillon, the principal learning strategist at Axonify, has spent 15 years designing and implementing learning and performance strategies for respected global organizations, including The Walt Disney Company, Kaplan, Brambles, and AMC Theatres. With his practical approach and ability to integrate science, technology, storytelling, and pure common sense, JD delivers modern solutions that enable employees, improve organizational performance, and drive business results. In his current role with Axonify, JD works with an award-winning team to boost employee knowledge and performance for leading organizations through the application of modern learning practices and cutting-edge technology.

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