Check out what Dan Ariely has to say about how our brain plays games with us and impacts our ability to learn. Many decisions we make are directly related to how we interpret information and, in most cases, we have an illusion of control.
Srinivas Krishnaswamy
We are barely scratching the surface of the potential of leveraging Big Data. Big players like SAP and IBM are already touting the phenomenal explosion in the volume of data generated by enterprises as the next gold mine for extracting competitive advantage.
By and large training departments are behind the curve when it comes to analytics (once again, there are exceptions and I am happy to make such sweeping statements and, hopefully, get away with it!) Seriously, I am still talking to big companies that don’t even have a LMS, and most of them that have a LMS are not using it properly!
But, there are companies that are pushing the boundaries when it comes to learning analytics. Standards like Tin Can API now allows us to take learner tracking outside the LMS and into the realm of social collaboration applications. I believe this will herald a truly interesting chapter when it comes to training. While training departments don’t necessarily create data on a large-scale, they can benefit from Big Data generated by the rest of the organization. Here are few scenarios:
- Sentiment Analysis on a product or service could unearth training deficiencies among customer facing employees and dictate curriculum revisions.
- Analyzing unstructured data pertaining to internal emails / instant messaging and structured data from the LMS could throw light on demand for training.
- Tracking chatter on LinkedIn groups, Glassdoor.com, and other public forums can tell you what people think about working for your company including what type of training is provided (just Google “training at “name of your company”).
- Customer education groups (especially in technology companies like Microsoft or Cisco) have a huge incentive in finding out how customers and partners assimilate and use their products, what use cases are more popular, what support calls are generated, and tie it back to training and certification programs. This particular example is a classic Big Data scenario as it involves processing static as well as real-time information from a diverse set of data sources.
Stay tuned for a more authoritative update on how Big Data and Analytics could be used for managing human capital.
Srinivas Krishnaswamy
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It’s the time of the year when we look back at the year that’s (almost) gone and predict the trends for the new year. I am not sure if Nate Silver is tracking workplace learning industry, but I will settle for what ASTD (and their sponsors) has to say about the state of Workplace Learning. You can read the full article from ASTD here. I have extracted the highlights for a quick dekko.
1. ASTD estimates that U.S. organizations spent approximately $156.2 billion on employee learning in 2011. Of this total direct learning expenditure, 56 percent ($87.5 billion) was spent internally. The remainder was split between tuition reimbursement, which accounted for 14 percent ($21.9 billion), and external services comprising 30 percent ($46.9 billion).
2. On average, employees clocked 31 hours of training in 2011, which is about one hour less than 2010 and six fewer hours than a peak of 37 hours in 2007. However, it is five hours more than employees were using 10 years ago.
3. The top three L&D content areas for the consolidated group in 2011 were managerial and supervisory; profession- or industry-specific; and processes, procedures, and business practices. Together these three content areas account for 36 percent of the learning content available in the reporting organizations. This is not significantly different from last year when the same three categories topped the list and accounted for 34 percent of the learning content available. The bottom three content areas, accounting for 17 percent of the total, are executive development, customer service, and basic skills.
Srinivas Krishnaswamy
McKinsey Quarterly recently published an article that quantifies the productivity gains that enterprises can leverage by switching over to social learning and collaboration platforms. The focus of this article was to share results from a study done across four industry segments – Financial Services, Professional Services, Advanced Manufacturing, and Consumer Packaged Goods. Here are some highlights:
1. Embracing social collaboration platforms for running operations (switching from emails and phone calls to collaboration channels that promote “many to many” communication and easier access to knowledge) can unlock $900 Billion to $1.3 Trillion in value in these industries alone.
2. Improved communication and collaboration using social technologies could increase productivity by 20 to 25%. According to McKinsey, Specifically, our research indicates that interaction workers typically spend 28 percent of each day (13 hours a week) reading, writing, and responding to e-mails. A huge amount of valuable company knowledge is locked up in them. As companies adopt social platforms, communication becomes a new form of content, and more enterprise information can become readily accessible and easily searchable rather than sequestered as inbox “dark matter.” Employees will be able to find knowledge in the organization more readily and to identify experts on various topics, given the expertise implied by their patterns of social communication. We estimate that 25 to 30 percent of total e-mail time could be repurposed if the default channel for communication were shifted to social platforms.
3. The potential for social technologies to create value through increased collaboration is greatest for the professional services industry. However, McKinsey reports that Management resistance and legitimate fears of breaching client confidentiality are factors limiting the potential of social technologies, executives say. Of course, this resistance comes at a cost: service providers risk failing to satisfy the rising demands of clients, some of which could be further along the social-leaning curve than they are.
4. McKinsey has also listed several examples of how companies are leveraging social collaboration and learning in a large scale for their operations. Here are a few of them:
Srinivas Krishnaswamy
Thanks to my colleague, Honey Dave, I am reading Learning in 3D, by Karl Kapp & Tony O’Driscoll. The book is about leveraging virtual worlds for learning in the enterprise. The authors make an interesting observation in the first chapter about the absence of new thinking and the rather unbelievable adherence to the classroom model as the primary means of delivering training within the enterprise. If you assume the learning function in an enterprise was a species, Charles Darwin would be stumped.
I have a rather unique opportunity of talking to customers about the challenges they face in managing their learning and training operations. A majority of my conversations center around the need to build new learning delivery models that go beyond just a classroom based model. For some reason, enterprise learning has missed the bus. Not that I am complaining!
Quoting from the book, if we had the ability to teleport an ancient Greek to the present time, showing him a classroom would cause very little dissonance. However, if you were to show this same Hellenic time – traveler a Wal-Mart store, an interstate highway, or a Boeing 747 jet, he would not comprehend what he was seeing….Ironically, while business has clearly learned to change, the learning function itself has not. To address this issue, learning leaders would do well to pay heed to Gloria Gery ’s assertion that: “ We don’t need new technology, we just need new thinking. ”
Srinivas Krishnaswamy
