Measuring Learning Impact in Pharma (Part 3)

In Part 1, we explored why most pharmaceutical L&D teams rely on completion rates and satisfaction scores and why those metrics are nearly meaningless. In Part 2, we considered what you should measure at each Kirkpatrick level and overcoming the genuine challenges involved.

Now for the practical question: How do you actually implement meaningful evaluation without unlimited budgets or resources?

Here are 8 ways you can stop wasting energy on vanity metrics and improve the quality of evaluation data you provide to stakeholders.

A practical approach to evaluation for pharmaceutical L&D

1. Start with the end in mind

Before designing and developing the training program, ask: “What specific business outcome are we trying to influence?” Shift the focus from “what do people need to know?” to “what do we need them to do differently, and why does that matter?”

If you can’t articulate a clear business outcome, you need to question whether training is even the right intervention.

2. Choose your battles

The healthcare professionals in our customer base cannot do all possible investigations for every diagnosis they make. They triage cases and make reasonable and responsible choices about the efficient use of the tools available to them. In the same way, you cannot (and should not) invest in comprehensive Level 1-4 evaluation for every training initiative. It’s reasonable to reserve a rigorous evaluation for:

• High-stakes training (product launches, major change initiatives)
• Expensive investments (major eLearning development, external programs)
• Programs with sceptical stakeholders who need convincing
• Pilots of new approaches where you’re testing effectiveness

For routine training, simpler evaluation is perfectly acceptable.

3. Build evaluation into the design

The completion of the program is too late to be thinking about evaluation. Design assessment and measurement approaches before you develop content, then develop the program to make the difference you want to see.

For significant training initiatives, determine:

• What business outcomes are we targeting? (Level 4)
• What behaviours need to change to achieve that outcome? (Level 3)
• What knowledge or skills enable those behaviours? (Level 2)
• How will we make the training engaging and relevant? (Level 1)

Work backwards from business results to design.

4. Treat level 2 as a non-negotiable

Every pharmaceutical training program should include meaningful assessment of knowledge or skill. This is realistic, affordable, and valuable. Don’t settle for true/false quizzes with painfully obvious answers. Not only does this rob you of useful data, it can decrease engagement with the training and reduce level 1 satisfaction scores. Learners would be justified in asking why they were assigned content that was clearly not needed to pass the assessment. They will be even more likely to take a ‘just click next’ approach to future training. Instead, build scenario-based assessments that require application of knowledge.

Examples:

• Present a realistic customer interaction and ask learners to identify appropriate approaches
• Give technical employees a scenario where practice deviates from the expected, and have them walk through correct response procedures
• Give MSLs an ambiguous off-label question and ask them to craft an appropriate response

If learners can pass your assessment without engaging with the training content, your assessment is worthless.

5. Use level 3 strategically

You can’t observe every learner in every situation. Be selective.

Approaches that work:

• Sample observation: Observe or collect data on a representative sample of learners, not everyone. (This is in the context of program evaluation, not learner assessment!)
• Use existing data: Your organisation likely already tracks call metrics, quality data, and customer feedback. Partner with the teams that own this data
• Involve managers: Train front-line managers on what to observe and how to provide feedback. They’re in-field anyway, so give them a structured way to report what they see
• Self-reporting (with verification): Survey learners about changes to their in-field behaviour, then verify with a representative sample

Example: When deploying training for a new sales model in a pharmaceutical organisation (a major investment across multiple business units), my team and I partnered with the business analytics function to:

• Compare average call duration and target-customer call frequency before and after training using existing CRM data
• Compare third-party customer survey data for call usefulness and message recall for the periods before and after training

We also provided managers with a set of easy-to-use job aids that clearly described “what good looks like” for each skill trained in the program. This improved their confidence to provide in-field feedback and allowed them to report their observations in a structured and consistent way.

Credible level 3 evaluation is feasible without a massive resource investment.

6. Be honest about level 4

Level 4 evaluation is valuable when it’s realistic. Often though, it isn’t feasible and pretending otherwise damages your credibility.

Level 4 makes sense when:

• Training is the primary intervention targeting a particular outcome
• The time since training allows results to materialise
• You can control for other variables
• You can access the necessary business data
• Stakeholders recognise and understand the limitations around causality

Skip Level 4 when:

• Training is just one factor among many that influence the outcome
• The time between training and measurement is too long to maintain focus
• Organisational complexity makes attribution of causality difficult or impossible
• The cost of collecting and analysing data outweighs the value of the information

It’s better to do great level 2/3 evaluation than questionable level 4 evaluation that lacks credibility.

7. The truth, the whole truth, and…

When you report your evaluation results, be clear about what you measured and what it means.

Don’t report that “training increased sales by 12%” when all you really know is that “among representatives who completed training, sales increased 12% over six months, though we can’t isolate the contribution of training from the changes to marketing strategy that occurred during the same time period.”

The second version is more accurate. It might feel like hedging, it might be less satisfying to stakeholders who want a clear success story, but it’s honest. And honest reporting builds credibility that inflated claims destroy. This is a hill on which I choose to die.

8. Measure what you control

You control the design and delivery of training. You drive the immediate learning outcomes. You don’t control whether the business provides ongoing support, whether managers reinforce learning, or whether external factors help or hinder application.

Focus your measurement on what training directly influences: knowledge, skill development, and confidence. Be realistic about the number of factors beyond training that also contribute to business results.

An uncomfortable truth

Most training doesn’t fail because it’s poorly measured. It fails because training was the wrong solution to a problem that required management intervention, process change, or system improvement.

Better measurement won’t fix bad training. But it will help identify when training isn’t working so you can try something else. And it will demonstrate value when training does work.

Stop celebrating completion rates. Stop hiding behind satisfaction scores. Start measuring whether people learned, whether they’re applying it, and when feasible, whether it made a difference to the bottom line.

Your stakeholders might not ask you for better metrics, but they deserve them. And so do their team members whose performance you’re trying to improve, and ultimately, the patients depending on effective, compliant, safe pharmaceutical practices.

The Bottom Line

Evaluation isn’t about proving training works. It’s about understanding whether training works, so you can continually improve its effectiveness and cease providing interventions that are ineffective.

Level 1 (reaction) is necessary but not sufficient. By all means measure it, but don’t mistake satisfaction for success. Level 2 (learning) is realistic in just about every pharmaceutical training scenario. Build meaningful assessments that require application, not just recall.

Level 3 (behaviour) is difficult but achievable with a well-planned approach. Think about sampling, leveraging existing data, and partnering with managers and other functions. Level 4 (results) is valuable when it’s feasible and impossible when it’s not. Be honest about attribution challenges and focus on Level 3 when Level 4 isn’t realistic.

Most importantly: measure what matters, not what’s easy. Your credibility as a learning professional depends on it.