Thursday, September 19, 2013

Webinar on How Big Data has transformed Learning and Talent Development

Yesterday, I had attended a webinar organized by Training magazine Network ( on How Big Data has transformed Learning and Talent Development. The facilitator for this session was Jeffery Berk, who is Chief Operating Officer for KnowledgeAdvisors. KnowledgeAdvisors is a human capital analytics solutions and technology firm that helps organizations measure, communicate and improve the impact of their people by better managing processes through reliable metrics.
Jeffrey works closely with clients to optimize their talent development investments through measurement and analytics tools. Jeffrey, a CPA, is also an adjunct professor of management at Loyola University and author of the book "Champions of Change: The Manager's Guide to Sustainable Process Improvement" and co-author of the book
"Human Capital Analytics: Measuring and Improving Learning and Talent Impact".
The objective of this session was to:
  • Define ‘Big Data’ and its impact on business
  • Provide ‘Big Data’ fundamentals for understanding and context
  • Discuss ‘Big Data’ in the context of L&D and Talent Development
  • Provide examples and suggestions to L&D and Talent managers to leverage ‘Big Data’
Jeff began with a definition of Big Data, which has become a popular term today. He defined Big Data as a phenomenon that harnesses information in novel ways to produce useful insights or goods / services with a significant value. He also stressed the fact that how Big Data has revolutionized learning and talent development as well. Next, he gave some examples from the daily life to explain how Big Data has transformed the society on the whole. He gave an interesting example of H1N1 Flu virus that had been spreading and how Big Data helped to allocate the resources to the areas most affected due to this disease because of the data analysis conducted. He also gave another interesting example of Oakland A's who had 20 game winning streak in 2002 because of data analysis conducted. It was because of Big Data that they won a 1st place. Big Data harnesses information to produce better decisions for better learning programs to provide value for learning. Jeff also stressed on the fact that Big Data is catching up fast and how data driven decisions have become more of a reality today. He then listed the five components     of Big Data, which include:
  • Volume: Defines the large amounts of data. He gave a perfect example of Walmart and how they use Big Data to collect more data to fill 20 million filling cabinets of data in a day.

  • Velocity: Defines the speed of collection and processing. He illustrated this concept with an example of location data on the mobile phones and how it predicts the cars in shopping malls to determine the holiday sales.

  • Variety: Defines the range of data types and sources. He illustrated this component with an example of how Smartphone users user different applications such as email, messaging, music, Internet, and so on.

  • Value: Defines better decision with the data. Jeff illustrated this component with an example of how Memphis police use data to determine where to patrol thus reducing crimes by 25%

  • Veracity: Defines reliable and accurate data. Jeff illustrated this concept with an example of “Who wants to be Millionaire” program and how it predicts the audience to be right 91 percent of the time and the expert to be correct 65 percent of the time.

He talked about the various Big Data terms, such as Algorithmics, Datafication, Data Exhaust, Data Tombs, and Messy Data. Messy Date allows for imprecision by relaxing standards for error, such as voice recognition software application. He then talked about what is and what is not Big Data. Big Data is correlation, which means finding patterns of data and not causation, which means to be much more precise and for big data it is much more precise. Big data is prediction and not precision, and he also explained that more data you have, the more you are able to analyze for better decisions rather than less data

Big Data is also about messy data and not clean data, and it focuses on what and not the why, which means what learning programs are better and not why are they better thus allowing it make better decisions

Jeff then listed the three ingredients of Big Data: Data, Skills, and Mindset. You must have data or access to it, you need tools or expertise to mine insights, and you need not be an expert in noble analysis and then finally you need a mindset to see the potential and unlock value.

According to Harvard Business Review, “Data-driven decisions are better decisions. It’s as simple as that.”  Peter Drucker says that “You can’t manage what you don’t measure.”

Now, the bigger question as to how it is related to learning and development and how Big Data is useful for Instructional Designers (ID). As an ID, we can use big data to help us report our business impact to our stakeholders and clients to market our learning. Big Data helps to measure the training where you can pull out sales data from a CRM application and compare it to your training programs, and then find a delta between those who attended the training versus those who did not attend it. Jeff then illustrated the five components of Big Data with examples of how they are related to learning and development. He then explained the key metrics of talent development, which include Efficiency, Effectiveness, and Outcomes. According to Jeff, Big Data helps analyze the pattern of data in the learning programs of an organization.

Finally, we had a Q&A round where he concluded that today it is becoming a collaborative effort between IT and various departments such as HR and Learning to build Big Data strategies and analyze the data to evaluate and measure the training.

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