A Learning Strategy for Big Data

Big data and analytics are going to make the CLO’s job easier. That is a bold statement given the challenge of getting in front of this kind of technology. However, once mastered, these tools enable learning leaders to make confident, evidence-based decisions.

They can track and predict what works and what doesn’t, and demonstrate impact on business results from learning initiatives. They help with questions such as: Which part of our sales program results in more people achieving quota? What is the reduction in time-to-competency for new service advisers who complete the enhanced program?

To make the most of it, first CLOs need to get up to speed on big data and analytics. Jenny Dearborn, senior vice president and CLO for SAP, an enterprise software company, brought in an expert to coach her and her team on big data. She said the most important part was adopting an analytics mindset to understand the methods and potential of these tools for the learning function.

Second, you need data specialists on the team. Kevin Oakes, CEO of human capital research firm Institute for Corporate Productivity, said a lack of analytical skills is the biggest roadblock to useful big data projects. The ability to transform enormous data sets into insight is critical and hard to acquire. Data analysts are in high demand, and few know the learning function. If hiring externally isn’t an option, some suggest hiring a college graduate with data skills, believing it is easier to train an analyst about learning metrics than to train a learning specialist on analytics.

Third, start your plan with the business impact in mind. Answer questions like: What business problem are we trying to solve? What results will the learning initiative influence? What data sets are needed to demonstrate the business benefit of the learning initiative?

Fourth, conduct a pilot. Dearborn said a test project allows the team to become familiar with the tools and to work out any kinks before a major program is launched.

Fifth, identify the right data — the data needed for insights and to track key results. It should meet the five V’s: volume — large amounts of data; velocity — timely data; variety — various types of data; value — relevant data; and veracity — reliable data.

Jeffrey Berk, chief operations officer for KnowledgeAdvisors, a CEB company focused on learning and talent metrics, said to collect data on the business outcomes likely to be affected, such as net promoter scores, customer satisfaction, employee engagement, time to competency and indicators of business alignment. One can then evaluate impact by comparing results internally, to external benchmarks or to business goals.

Sixth, get access to the data you need. The promise of analytics comes from gathering existing organizationaldata. The stumbling blocks to access are evident when you hear comments like, Why can’t that system talk to ours? Why won’t that department give us the data? Why does it take so long for IT to get us what we need?

In time you will have all you need: sales data for those attending advanced sales courses, key performance indicators for management trainees, 360 scores and performance ratings for leaders and more. But access to these data sets requires collaboration with business units, human resources and IT.

Seventh, clean the data. Strip out old or irrelevant data, and segment it to use the portion needed. For example, if you are collecting data on sales training, you may need data on individuals’ bonus percentages, but not on their benefits packages.

Eighth, analyze the data. Use statistics, trend analyses and comparisons to see what insights emerge. This is the hardest part, and the one where magic happens.

Finally, report the business impact of the learning initiatives up the line, and make evidence-based decisions based on your insights.

CLOs will be spending lots of time — the rest of their careers, most likely — mastering analytics. It is now the nature of business and life. Thirty years ago we said the same thing about software for business. Twenty years ago it was the Internet and online learning. Ten years ago it was social and then mobile. Today it is big data and analytics that are fundamentally changing the business of learning.

Original published on clomedia.com by Brandon Hall


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