Success Metrics–Data Analytics (Part 2)

What are success metrics? In our previous article we discussed the four types of learning analytics tools that can be used to produce a better eLearning product:  descriptive, diagnostic, predictive and  prescriptive.  But what do these tools actually measure?  How can they be whittled down to achieve success?

We’re going to turn to the professional association, eLearning Guild, for some examples of the types of data that can be measured, catalogued and analysed.

These measurements included learning activity, performance, business, and demographic data sets.

Let’s look at the first category, learning activity metrics, which include:

  • Logins
  • Time spent in course or on platform
  • Course accesses
  • Course completions
  • Volume of asynchronous content accessed
  • Content completions
  • Course satisfaction ratings
  • Instructor ratings
  • Learning effectiveness surveys
  • Quiz and assessment metrics
  • Cost metrics
  •  Number of discussion forum posts
  •  Badges earned
  • Volume of shared content
  •  Content “likes” or “dislikes”
  • Grades

You can, of course, choose which of these measurements are important to you, like the use of social media, completion rates,  etc. These numbers will tell you how your learning program is faring at the user coal face.

Performance metrics will reveal if your training goals are hitting their targets. These numbers include thresholds for satisfactory completion of objectives. These thresholds may include business metrics that often involve percentages. For example, if you want to increase sales by 5% per month, then you should measure those outcomes.  Or you  may want to increase the number of follow-up phone calls to prospects by x-percent. A good CRM (Customer Relationship Management)  system can help you consolidate these numbers.

Business metrics work hand in glove with performance metrics and may also include x-percentage increase in volume of sales opportunities and improving sales margins by up selling.

Demographic metrics also give you valuable insights into which region may be outperforming another and you can drill down and find out why, using indicators such as office location, job roles and tenure.

The best way to consolidate these metrics is by creating an impact map.  This is basically a flow chart that gives you a quick look into what your data measurements are. Once you have decided on your metrics, collating them into a readable format usually calls for a data audit. Although data collection is usually an automatic process that involves sourcing information from a number of platforms, that data is rarely exportable as is.

Some tips for cleaning up your data:

Consistency is key to accurate measurements, like making sure your customers don’t appear in two places at once. Make sure fields are consistent. There are many Business Intelligence software apps available to crunch your numbers for you once you decide which data to export.

If you need more help in decided how analytical learning tools can help your organisation, please contact My Learning Space.

 

 

 

 

 

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