The current business focus on skill, digital disruption and employee engagement requires great learning and development (L&D) professionals who know how to help others be equipped and ready for the future ahead.

Whilst L&D has the potential to contribute significant value to pressing business issues, the profession is also facing hurdles. Increasing demands for training, limited resources and a deluge of new tools, technologies and data all contribute to the challenge.

Others process data on our behalf, assisting us make decisions about what to eat, what to wear, what to watch, where to go and how to get there. It can simplify our lives and help us make smarter decisions.

In L&D, we are also inundated with data. In theory the data available to us today could guide us to making smarter decisions to improve our offering but a lack of confidence in using data effectively doesn’t help. In fact, the pressures can make it difficult to see how data can be a useful tool rather than an additional burden.

Data Deluge

In theory, data can help us learn from the past, thrive in the present, and, sometimes, predict the future. Through the click of a button, we can find out how to collect, track, harness, analyze, visualize, communicate, explore and exploit it.

In L&D we have easy access to metrics like course completion rates, test scores, feedback ratings and engagement levels. In 2017, 96% of L&D professionals stated that analytics skills were a high priority L&D skill needed for the future, today 54% of L&D pro’s list analytic skills on their LinkedIn profile.

For many, the idea of leveraging data to improve learning can seem advanced, especially when we’re already stretched thin. But it is worth us revisiting.

In CIPD’s 2023 Learning at Work report, we explored the behaviors of L&D professionals who felt valued by their business leaders to those who did not: 70% of the learning practitioners who feel valued by their leaders were more likely to use evidence-informed principles to address performance issues, versus 41% of learning professionals who reported not feeling valued by leaders.

Also in the report, L&D professionals who are valued by leaders are more likely to recognize their contributions to the business, and have a commitment to evolving and innovating its practice, all of which are very important when implementing a data-driven approach in a competitive and fast-changing world of work.

The big question.

In the L&D context, data encompasses a wide range of information that can include learner activity and engagement metrics to stakeholder opinions, stories, business key performance indicators (KPIs) and industry benchmarks. When used effectively, data can help us make smarter decisions linked to:

• Improving strategy.
• Solving business problems.
• Personalizing learning experiences.
• Improving learning design.
• Demonstrating the impact of learning initiatives.

But the big question underpinning all of these decisions is “why?”

We all need to start with our own big question to provide focus and purpose before we can make sense of the data around us. Simply collecting or reporting single statistics without proper analysis and interpretation can lead to misguided conclusions or wasted efforts.

Evidence — turning data into insight, and insight into action.

While collecting data is important, the real value lies in using that data as evidence to inform decision-making around our specific big question. The use of evidence is irrevocably linked to the concept of proof. For many in L&D, data and evidence is automatically conflated with proving our value — the role of measurement and evaluation.

But evidence also has a role in improving our service offering and learning design, disproving the validity of outdated services or silver bullets or even approving a new approach.

The concept of proof can allow us to make smarter decisions. It requires us to turn our data into insight around our big questions, and ultimately, to open the door to action.

The Center for Evidence Based Management talks about quality decisions being based on a combination of critical thinking and the best available evidence.

The principles of evidence-based practice include four sources that should be considered when using data to make a business decision.

1. Scientific evidence: from academia and trusted sources.
2. Stakeholder perspectives: the values and concerns of those influenced by the decision.
3. Organizational data: from internal systems.
4. Experiential evidence: the experience and judgement of practitioners (that’s you!).

An evidence-based practice is about making informed decisions with explicit and judicious evidence from multiple sources by:

• Asking: translating a practical issue or problem into an answerable question.
• Acquiring: systematically searching for and retrieving evidence.
• Appraising: critically judging the trustworthiness and relevance of the evidence.
• Aggregating: weighing and pulling together the evidence.
• Applying: incorporating the evidence into the decision-making process.
• Assessing: evaluating the outcome of the decision taken.

In my experience, an evidence-based approach doesn’t have to be an onerous task as long as L&D professionals are curious and aware of the best available evidence. Focusing our decisions on a single scientific study or industry benchmark, without considering the data to inform our context is crazy. Also, decisions made on personal experience alone (this has worked or failed for me before) is equally foolhardy.

Asking smart questions and actively seeking multiple sources of data in the time available is the secret of our success.

Getting Started

To harness the power of data and evidence in improving learning, consider the following approach:

1. Ask the right questions.

Start by clearly defining what you want to achieve. Some key questions might include:

• How do we know that a learning problem exists in business?
• What specific business problems are we trying to solve through learning?
• What will success look like when individuals apply their learning in the workplace?
• What indicators of productivity improvement can we track?

2. Collect relevant data.

Ensure to do this from the best available combination of sources. Consider the chart below as an example.

3. Be curious: Explore patterns and relationship to look beyond surface-level metrics and understand deeper patterns.
4. Share the load: Work with data specialists or explore artificial intelligence (AI) to conduct detailed analysis of patterns and relationships in your data.
5. Communicate findings effectively: Use data visualization tools and dashboards to clearly communicate relevant insights to stakeholders. Data opens conversations in ways that opinions sometimes cannot.
6. Do something: Act on the decisions that you have made.

Making Smarter Decisions

Evidence-informed decisions matter because they allow us to:

1. Focus on outcomes rather than inputs.
2. Align learning initiatives with business goals.
3. Identify and address skills gaps more effectively.
4. Continuously improve our learning offerings.

By adopting an evidence-informed approach, even time-strapped L&D professionals can begin to harness the power of data to improve learning outcomes and demonstrate value to the organization.