In part one of a six-part series, Trish Uhl – Founder, Talent & Learning Analytics Leadership Forum – offers insight to L&D professionals on the components of a workplace learning analytics strategy and how to get started on your workplace learning analytics journey.

Workplace learning analytics is a specialised segment of the broader people analytics movement that involves applying business analytics to corporate training and organisational learning.

Learning practitioners to talent development executives are putting analytics into practice to better enable learning programmes and the learning function.

Why? Because many of us are eager to get the best use out of our data – to mine our learning technology systems to prove the effectiveness of our learning solutions, the value of our training programmes and the organisational impact of our learning function.

However, leveraging analytical capability in organisational learning doesn’t start with data, it starts with strategy. And strategy starts with looking at the ‘Why’.

• Why do you need to build analytical capability in your learning function?

• What is driving you to get your hands dirty with data?

• What do you intend to use analytics for?

Analytics means taking action

Analytics is not meant to be an academic exercise. It’s an action-oriented discipline used to drive improvement from benchmark to goal.  

Successful use of analytics as a practice means providing insights into past, present and anticipated future progress towards meeting organisational goals.

• What, then, are your organisation’s goals?

• What are your performance and quality targets?

• What are you aiming to achieve?

In other words, what will improve through investment in analytics?

Practical applications for workplace learning analytics

Some view analytics as a new take on traditional training measurement and evaluation. While analytics can be used for these, to only do so is narrow, limited in scope and not likely to produce a return that justifies the investment.  

The reason being that a roadmap and strategy that delivers on higher levels of maturity – advanced analytics – is, on average, a two year commitment. You need to make the outcomes worth the journey.

So is building a mature workplace learning analytics practice worth it?

Embedding analytics within our learning solutions allows us to provide timely, relevant, personalised, tailored feedback to delegates and managers.

A mature workplace learning analytics practice can move organisational learning beyond a reactive, tactical role to a proactive, strategic partnership in alignment with organisational outcomes. It also puts the learning function on par with how other business leaders manage their operational areas and business units.

There are two primary ways in which organisations can leverage workplace learning analytics to achieve this transformation. These include leveraging analytics to:

1. Improve decision quality related to the learning function, learning programmes, learning practice, learning participants, skills & capabilities enablement and people development

2. To provide tailored, personalised feedback that helps people contribute to the business in a way that makes the most of their skills and abilities.

Given your goals and strategic objectives, which one is right for you?

Leveraging workplace learning analytics for higher quality decisions

“Success comes from making a series of good decisions over time, while failure comes from making a series of bad decisions over time.”  – Jim Rohn

We make decisions, small and large, every day that impact how individual and organisational needs are assessed: which learning solutions are selected (and why); how learning programmes are implemented, tweaked, optimised or eliminated; how the learning team is developed over time (and which skills and tools are focused on); and how we provide support to our delegates and their managers before, during and after instructional events in a learning system.

These decisions are often made based on experience, expertise, subjective opinion, preference and even gut intuition.

Analytics can help us uncover unique insights about people in our organisations that could enable faster, more accurate and more confident decision making with regard to a wide variety of questions and challenges.

We don’t necessarily have to use analytical output to replace (data-driven) expertise or domain knowledge, we can use analytical output to augment (data-enable) our experience and expertise to improve successful outcomes.

Consider the decision making model in Figure 1 below.

This model illustrates how analytics can be embedded within the decision-making process where data is analysed using analytical tools and methods; analytical output (depending on the selected analytical approach) then provides actionable insights into what has happened (historical), what is happening (present) and even what will happen (future).

We can then use the analytical output as input into decisions and actions based on benchmarked measures and metrics.

Figure 2 (below) provides a visual flow for using analytics to monitor, measure and manage key performance indicators (KPIs) and metrics for continuous improvement.

This practice allows learning executives, practitioners and professionals to gauge what’s on/off track, troubleshoot bad performance, diagnose root cause and to take specific corrective action (as necessary).

Quality decisions based on data keeps learning in alignment with the expectations of the people we support and the businesses we serve, leading to:

• Improved learning system / learning program performance

• Improved quality of instruction (and other learning system components, such as communication)

• Improved cohort performance

• Improved individual delegate and/or manager performance

Further, embedding analytics within our learning solutions not only provides us with feedback, it allows us to provide timely, relevant, personalised, tailored feedback to delegates and managers as well.

Leveraging workplace learning analytics for fast feedback

Expanding our analytics capabilities gives us the ability to acquire real-time (or close to real-time) feedback, thereby enabling us to ‘listen’ – to ‘sense’ – and to be more responsive to human and organisational needs as those needs evolve and change.

This feedback loop can be multidirectional, allowing us to stay attuned to organisational and employee needs and to provide feedback to employees and the organisation that informs behaviour and performance.

This way, we can monitor, measure and manage – generate actionable insights – at multiple levels, including:

• Providing coaching feedback to individual delegates and managers

• Providing developmental feedback to individual delegates and managers

• Identifying who would benefit from performance support (and what specific support they need)

Industry analyst Josh Bersin calls this ability to sense and respond to employee and manager needs ‘fast feedback.’

Workplace learning analytics is a mechanism by which we can make this transition and transform the learning function.

In his 2015 Forbes article, ‘Feedback is the Killer App’, Bersin cites the ability of organisational learning to provide fast feedback as critical to our value proposition going forward as we transition from delivering instructional products to producing learning experiences.

Bersin notes: “Just as customer feedback has transformed the customer experience, employee feedback is transforming the employee experience.”

Bersin continues in his HR Technology Disruptions for 2018 report:

“You cannot really maintain employee experience without listening to your people on a continuous basis. To do so effectively, organizations need a set of tools to facilitate continuous listening; which goes well beyond annual surveys.

They [companies] want a system for multidirectional feedback that encompasses pulse surveys, developmental feedback, and coaching. They want agile, self-directed learning tools.”

Depending on your goals and strategic objectives for building analytical capability, this is an area where analytics can be of most benefit both to the learning function as well as to the organisations and people we serve.

Implementing agile, self-directed learning tools featuring fast feedback

Learning today can no longer be static and fixed. Learning experiences must be flexible, dynamic and versatile, moving at the speed of business with velocity and agility to address change and complexity, and adapting to evolving needs.

For many practitioners, implementing these feedback and response loops in their learning solutions is a BIG shift in mindset and practice from designing, developing and delivering a fixed instructional ‘product,’ regardless of whether that product is instructor-led classroom training, elearning, mobile learning, virtual instructor-led or microlearning.

Delivering the thing is no longer enough. Providing measurable value in the form of positive people impact and organisational outcomes now requires a focus on delivering results.

Workplace learning analytics is a mechanism by which we can make this transition and transform the learning function.

This means we need to adopt a mindset of continuous improvement. And think strategically.

Starting an analytics journey does not begin with the intent of using analytics to prove the effectiveness or value of our solutions or of the learning function. Instead analytics should be used for continuous improvement of the learning function so that our solutions are effective and on track for delivering value.

So craft your workplace learning analytics roadmap with a commitment to leveraging analytical insights to create responsive, agile learning systems. This will help you deliver measurable value to the people and organisations you serve who, in turn, can learn faster and achieve more.  

The substance of the articles in this series is derived from Workplace Learning Analytics: Moving from Strategy into Action (June 2018).