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3 Myths About Learning Measurement

Say the word “measurement” to learning professionals and you are likely to hear a number of responses: “We don’t have the data,” “Business leaders don’t care,” “We can’t afford a data scientist,” or all of the above. In fact, even though 90% of learning leaders want to measure business impact, only 26% believe they have the ability to do it.

But what if much of what you believe about measurement and the obstacles in your way isn’t true? We are about to debunk three myths that persist about learning measurement. And knowing the truth can set you free … and help you get the support you need to develop initiatives that:

  • Gain support from business leaders and stakeholders
  • Get the financial backing needed to create compelling content.
  • Lower risk and increase alignment with strategic goals.
  • Demonstrate that training moves the needle.

Myth #1: The business doesn’t care about measuring learning.

We have all been in this meeting—learning presents metrics as business executives’ eyes glaze over on the way to a lackluster response. But maybe, as solid as your data is, the way you are crunching it is wrong.

Let’s say you are presenting data for additional funding of a safety initiative in the organization. Your data says that 60% of the workforce has already been trained, and with the additional funding, you can knock out the remaining 40% by year’s end. Great. You are using data to back your request, but you haven’t told them why they should care.

Suppose instead, you tell them that their data shows that injury rates have dropped 6.5 points for every 10% of the workforce trained. That’s more compelling from a business standpoint, right? Because while executives may care about your completion progress to a degree, they care more about what that progress buys them in terms of the metrics they value.

Make your analysis relevant to the business and, suddenly, you’ll get their attention. Merge your learning data with their business data. Connect the dots between what they care about and how you are able to contribute. Over time, as you prove your value in a way that is business centric, you’ll see that the way the organization views learning will change. You’ll be speaking their language. Your learning measurement will now have real relevance.

We find it helps to create a Measurement Map® like the one below to build that causal chain of evidence between business goals and learning investments. Build one in collaboration with your business partners. Start at the right and work your way left.  By example, a sales organization naturally wants to increase market share and profitability.  How will you know if training is contributing to those goals?  Building out the Map, you would first need to grow sales volume and gross profits, and you’d get that through new, repeat, and referral customers.  How do you do that?  Through key sales skills such as prospecting, setting appointments and providing great customer service.  Now you know what needs to go into your sales training program.  And if, shortly after training, you can show evidence of increased customer contacts and appointments, both you and your business partner will feel confident that the training is already beginning to move the needle.

Once your Measurement Map is complete, you will have a picture of the causal chain of evidence, connecting your sales training program to business results executives care about—increased market share and profitability. Better yet, the executives have partnered with you in creating the Map, building alignment between learning and the business. They are invested and now better understand how learning supports their business goals.

Myth #2: Measurement is an exact science.

Measurement is a scientific endeavor, for sure. Interestingly, scientists view measurement as a way to reduce uncertainty, rather than a be-all, end-all exact answer.  Measurement is used to give us more information than we had before so we can make better decisions.  Consider clinical drug trials and political polls where nothing is 100% certain, but measures give us solid direction. 

This means that you can say goodbye to any perfection paralysis you may have when it comes to learning measurement. Think about the kinds of business questions you are using measurement to answer. You are not determining whether the seal on a rocket is the precise size and strength to hold pressurization in space. You are answering:

  • Is my program making a difference?
  • Is it “moving the needle”?
  • By about how much?
  • Is it more effective for some learners than for others?
  • Should we continue running it?
  • How can we make it better?

If you are 95% certain that your sales training program improved performance by an average of 4 units per person, plus or minus a unit, that is enough to know your program is a success. This means that, for the kinds of questions you are answering, close enough is good enough. The purpose of measurement is not to be exact. It is to reduce the uncertainty so you can make informed decisions.

Although this may seem a paradox, all exact science is based on the idea of approximation.

Bertrand Russell, mathematician and philosopher

Myth #3: I need a data scientist to do this right.

While a data scientist is a luxury, you certainly don’t need one to start improving your learning measurement. What you do need is someone who is good at looking at data and can leverage the power of spreadsheets —namely, a data analyst.

While most of the people on your learning team probably do better with people than with numbers, you are likely to have at least one closeted nerd who enjoys crunching data and finding patterns. If they have some business acumen, you’ve found a potential data analyst!

The news here is that you may not have to add anyone to your team to get yourself started with learning measurement. We recommend you look at the people you have and see how you can assemble a data analytics competency internally. Start simple. Start small. Before you know it, you’ll be dazzling executives with your understanding of their issues and how your solutions can make decision-making easier for them.

In summary, the industry has bought into many myths and fears over the years about measurement. This is probably because, for many of us, working with numbers is intimidating. But once you dispel these myths, you free yourself to embark on your measurement journey. In fact, measurement could be the thing that finally and truly gets learning aligned with the business, transforming your value forever.