Evaluating the effectiveness of the training delivered is part of the role of Learning & Development professionals and critical to demonstrating adding value to the business. This has been done in the past by using test scores and upward/downward trend analysis e.g. beginning with a pre-test and ending with a post-test, and maybe an aggregation of a volume of participants over time. Then there is the survey or ‘smiley sheet’ to evaluate the learning experiences across programs to monitor a program or an aggregated trend.
Some might say that we are already making ‘data-driven decisions in training functions. However, this holds true only if you analyse the data, draw conclusions from it and take data-based actions. Data is being collected, but how often is it really being used?
Data leads to insights; business owners and managers can turn those insights into decisions and actions that improve the business. This is the power of data. [Bernard Marr, Forbes.com, 2016]
Training or any particular learning solution is often hard to isolate as having business impact. However, data can now be collected during the learning experiences. But an organisation trying to stay relevant and ahead of the skills gap curve in today’s environment will need to be making data-driven decisions to maximise resources and opportunities. Careful planning and design, based on actual data, can help training be a better-targeted experience and relevant results achieved.
Inspired by the10 step process outlined by business leader, Bernard Marr, [Forbes, 2016], here is how it might work with learning:
You are probably already collecting some data from your learning activities, such as participant feedback; however, if the data is sitting on different platforms and therefore in different databases, it may not be easily accessed or used. The utopia is to get the data into one place in a reusable format and use a visualisation tool to interpret it. This is the same ambition the commercial functions have to conduct cross channel analytics. ‘Good data’ needs to be quick and easy to access. ‘Numbers that matter’ are based on picking relevant, actionable metrics.
Both qualitative and quantitative data can be useful in the pursuit of insights into learning needs and priorities.
Basic data which is often available include:
There are several ways Big Data analytics, which often combines different sources and AI or machine learning, can provide new insights:
Data-driven decisions are proven to drive increased productivity and effectiveness. Data-driven decision-making is an approach to making decisions using data to back them up. The quality of the data is a critical success factor of course - bad data informs bad decisions! The ability to analyse data and draw valuable insights may in itself be a required area for skills building in your organisation.
Implementing data-driven decisions in a learning environment means collecting and using data to identify learning solutions needed, and how to best design and deliver those solutions. Training or any particular learning solution is often hard to isolate as having a business impact, but the collection of new types of data, combined with improved analytical and decision-making skills, offers new opportunities to really understand the learners, customise learning solutions and also to demonstrate real business impact.
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The Actando Consulting Team