We're all search engine junkies. How can we not be? In order to wade your way through the sheer volume of data on the Internet, the help of a search engine is pretty much a given. In fact, in the vast jungle that is the World Wide Web, a good search engine is like a machete, hacking its way through the overgrowth to clear a path for you to the treasure you seek.

Learning analytics is not unlike a search engine, getting you through the noise, focusing you on the relevant data, and presenting you with useful facts with a sometimes-startling clarity. It does this with a few tools, not the least of which is its dimensions of measurement. These dimensions serve as factors, parts of a whole that, through their specified information, give an even better understanding of the whole.

The End of Training Is Just the Beginning of Measurement

So you've gotten to this point. The training is done, students have participated, and your stakeholder is waiting for you to shed a light on the results--in short, to justify the expense of the initiative, both in time and in dollars. It's go time: the point at which learning analytics works its magic.

Using the search engine analogy is a basic, “sky level” comparison for the purpose of understanding how learning analytics allows you to drill down on your data and make use of it, not just view it. With best-of-breed analysis tools, you pre-define the criteria (like search engine keywords) through which your specific data is filtered. Just like a search engine, you can get more specific information or re-focus the information returned, by redefining your search parameters.

Dimensions of measurement work within those parameters. In many cases, dimensions ARE those parameters, acting as variables for sorting and parsing purposes, and rearranging the data according to the user and the request. According to Bersin & Associates, one-third of organizations surveyed cited “poor analysis tools” [within learning management systems] as one of the biggest challenges to effective training measurement. That’s where best-of-breed learning analytic tools come into play.

Learning analytic tools utilize a user-defined set of key measures. Key measures are metrics that combine and report results by specific dimensions across learning initiatives, allowing your company to measure actual values vs. targets and benchmarks, and trending those results over time. Key measures can be populated from widely different data sources.

Most key measures will come from learning systems, but different systems--such as financial systems, sales, customer service, and compliance--also have business metrics that correlate to training participation. Training and business metrics vary widely in their units of measurement--such as dollars, hours, ratios, accounts, etc. Regardless of unit type, the glue that binds the business key measures to the learning key measures is the dimensions and their common values. Dimensions are the characteristics of your world – your business units, departments, regions, managers, learning modalities, pay grades, course categories, and the like.

Unlike basic reporting tools, learning dashboards with built-in analytic tools are visual, allowing for a clear understanding of the key measure data in an intuitive format. The multi-dimensional information can be presented as gauges, bar graphs, pie charts, and so much more to show correlations, trends, and relationships between learning and the business metrics they intend to drive. Just like a search engine enables you to click on one of the result links for more detail, so does the dashboard based on cross sections of dimensions you’ve setup.

Defining the Nth Dimension

An important practice with measurement is that “less is more.” Having an unlimited number of variables produces too much data, resulting in analysis paralysis. Dimensions represent groupings and sub-groupings of your data, and dimension-level subsets help you drill down and focus your data analysis, providing you with both macro (aggregate) and micro (detail) views. If you don’t limit your dimensions, you’ll end up in measurement limbo…how low can you go? Experience tells us on average that six dimensions of data are sufficient. With up to six dimensions, your analysis tool can slice and dice by the dimensions based on what’s most important and then present the results in meaningful form.

Just as we measure length, width, and height to get depth and a much more intricate picture of an object, as well as increase our understanding of the object, so too do the dimensions of learning measurement help us unify multiple metrics to get a complete picture of progress on our learning initiatives. Dimensions can be hierarchical or simply interrelated. Nevertheless, they provide a clear picture to the highs and lows of your key measure data points so root cause analysis is quick and easy in determining where adjustments are needed in the work areas that inevitably influence those metrics.

Have you defined the Nth dimension of your learning measurement initiative? If not, you're most likely missing an important opportunity to succinctly align and measure your current training programs against your business plan and practices.