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Why is a learning measurement strategy important?

Big data and smart learning analytics platforms are giving Learning and Development (L&D) departments the potential to make a compelling case when it comes to measuring business impact, as well as demonstrating the value of training programmes across an entire business.

A photo of an elearning professional looking at a measuring business impact strategy

Gaining a deeper understanding of the effect of of your organisation’s learning is important. With a vast amount of data often available, establishing and tweaking a well thought-out strategy for making those measurements is key.

Choosing data and condensing it into convincing reports can seem daunting at first, but there are some simple initial steps – highlighted in our insight, ‘How to define your business impact measurement strategy’ – that you can take to ensure your approach to gathering and using information remains clear.

Win over the board

One way of envisioning the reports you might produce is to imagine presenting your findings to board members, many of whom have extremely busy schedules and require succinct summaries.

Ultimately, your ambition should be to provide a single figure demonstrating the current capabilities of the organisation against business targets and KPIs – this means that identifying your targets and indicators at an early stage is important.

For these, consider broad organisational objectives that could be focused on during a specified period. Selecting data which will link learning statistics to improvements as part of an agreed business performance drive should win the attention of senior management.

Work out what data you want

Decide what type of data you’re going to focus on at an early stage: you might begin by using basic charts – known as descriptive analytics – to look at your baseline data as a starting point. As a step further, exploratory and inferential analytics can bring in other piecess of data, such as business performance or KPI metrics. You can then examine the relationships between the data sets to try to work out why things happened in a certain way.

You could focus on a combination of quantitative points, such as figures from a sales system, and qualitative measurements, including interviews with learners or quality assurance reports/transcripts of call centre conversations.

Bear in mind, though, that qualitative data, such as conversations, cannot be analysed with traditional statistical techniques, and therefore needs to be gathered and broken down in a judicious manner. LEO Learning’s partner company, Watershed, has built a prototype to collect qualitative data using Amazon’s voice technology, with the potential to generate analytics about discussions in observations and one-to-one sessions. You can read Watershed’s five-step model for getting started with learning analytics here.

Pick the data insights that matter

With the right techniques and approaches, you’ll quickly be able to quickly quickly draw meaningful insights. Our solutions allow you to find correlations and decide how much importance to place on the findings by highlighting the quality of separate pieces of analysis.

For example, some businesses have benefited from a scatter graph showing a clear positive correlation between the final assessment score in an elearning module and customer satisfaction.

This can be used to great effect, so it’s best if you engage with experts at an early stage or when designing in-depth evaluations. Its rewards in terms of measuring business impact are impressive – some organisations have created charts, for example, showing improved KPI, the best performers and the learners who improved most and least after the completion of a training programme. They have then generated an average percentage point score to show how much the learning programme improved the KPIs they decided upon.

Look ahead with confidence

Once you’ve scrutinised the current impact of learning, you can look to the future with a set of analytical methods known as predictive and prescriptive analytics.

These measurements draw on previous events to forecast what will happen if you carry out certain sequential actions, such as identifying a higher risk of workers dropping out of a learning programme based on the same actions as previous drop-outs. In this case, a business could take remedial action to reduce the potential of this happening.

Solid business impact measurement lets organisations make highly data-driven choices, judge which types of learning interventions will work best and tailor L&D programmes accordingly. Whatever size your business is, the right strategy will result in strong evidence with which you can make decisions confidently.

For more on big data approaches to learning analytics and setting your impact measurement strategy, make sure to get your free copy of the LEO Learning insight ‘How to define your business impact measurement strategy’.

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