L&D Data science process - Communicate results

Learning and Development Consultant
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This is the final article in a series I have been writing on the learning and development data science process. I wrote in an earlier post that the learning and development data science process has six steps which are:

  1. Frame the problem (or define question that needs to be answered with data)
  2. Collect the raw data needed to solve the problem (answer the questiion)
  3. Process the data (data wrangling)
  4. Explore the data
  5. Perform in-depth analysis (machine learning, statistical models, algorithms)
  6. Communicate results of analysis

This article covers the final step, Communicate results. In any learning and development analytics project, if the previous five steps have been done properly, then a person should have drawn some conclusions from the data analysed that helps to answer the problem framed in step 1. The insights derived now need to be communicated to the relevant stakeholders in a way that is clear and understandable. Most stakeholders don't need to see the details of our analysis or the data we used. They want to understand what our results are and why we we believe those results are valid. While there are technology tools that can help to communicate results from an anlytic project, it's best to use tools that almost everyone are familiar with and the obvious choice would be a PowerPoint presentation or a very short MS Word document.

For instance in the case of XL Support, the fictional case I've been using, the l&d team at this stage would have identified a good estimate of people's learning needs in the four areas specified:

  1. Compliance training
  2. Specialist training areas
  3. Leadership development
  4. IT skills

The team will then do a costing estimate with this information that will allow them to draw up a learning and development budget. That information can be presented in a simple PowerPoint presentation. The findings presented from the l&d team must be:

  • clear and concise
  • easy to understand
  • intelligible
  • relevant

Ultimately stakeholders must get the answer they are looking for. As you can see this is one of the most important aspect of the process. It doesn't matter how much analytic techniques we use or how sophisticated the tools we used are, if key stakeholders don't believe or undertsand our results then the effort we have put into stages 1 to 5 in the process won't matter.

I am currently in the process of writing a short ebook that introduces learning and development analytics that will cover:

  1. What learning and development analytics is
  2. The learning and development analytics process
  3. The four levels of learning and development analytics
  4. Examples of analytics in practice.


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