Forecasting effort: collecting facts about learning’s impact

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In a three-part series, L&D data detective Kevin M. Yates explores how to collect facts, evidence and data for learning’s impact on employee performance and organisational goals. Part two looks at how to assess the amount of effort required for obtaining evidence on the impact of any given learning solution.

Collecting facts for the impact of training, learning and professional development can feel vague, ambiguous and uncertain. But it’s not impossible.

When trying to measure the impact of L&D, we’re looking for facts that answer the question, ‘Did training work?’. We’re trying to find evidence and clues that reveal learning’s impact on behaviour, performance and organisational goals.

And while it may not be easy, we can manage our expectations and those of our stakeholders by forecasting the effort for collecting facts about learning’s impact on performance.

It’s not always easy but it’s possible

Some facts are easily discoverable, while other facts require deeper investigation. It’s just like Sherlock Holmes trying to solve a mystery, only our mystery is whether or not performance changed as a result of training.

When collecting facts about training’s impact, there’s a scale of effort that is based on the extent to which the training should impact performance levels. Higher levels of performance require higher levels of effort for collecting facts.

The effort scale

The effort scale for collecting facts about performance impact will help you to plan and prepare your investigation.

In particular, it will help to manage your expectations and those of your stakeholders about the extent of work involved with collecting relevant facts, clues and evidence. It will also help with evaluating the level of performance required to achieve the organisation’s goal.  

graph: effort scale for collating facts about performance impact

The vertical axis on the scale, easy to difficult, shows the level of effort that is required. The horizontal axis, routine to dynamic, shows the level of performance we expect the training or learning to have an impact on. As you can see, the level of effort for collecting facts about impact increases as the level of performance increases.

In this example, assembly line training on the scale of effort is easy. It’s easy because performance expectations are routine, repetitive and easily observed. This means that you can easily collect facts and evidence for how the training impacted assembly line workers’ ability to meet performance expectations.

On the same graph, training for call centre customer service representatives is higher on the scale of effort. Each customer interaction is different and requires the worker to respond uniquely to each call.

Therefore it’ll take a little more effort to collect facts about the training programme’s impact on behaviour and performance.  

Finally, client engagement training is placed at the highest level of effort. The training programme is for managers who have contact with customers with the goal of getting those customers to purchase additional services.

The performance expectation for managers to increase sales is influenced by many factors other than their engagement capability. And so collecting facts about the programme’s impact requires more effort, but is no less possible.  

Where would you place the effort?

graph: effort scale for collating facts about performance impact


Example 1

A power electric company identified an opportunity to reduce costs for operations by 65% if it replaces power grids in fifteen cities where it operates.

They implement a training programme for cable electricians that builds their skills for assessing residential readiness for the new system and the ability to install the new system in qualifying homes.

Where would you place the level of effort to collect facts about the impact of the training programme? Here’s a hint. Assessing readiness is unique to each home while installing the new system is routine.

Answer: If you selected B as the answer, you’d be right. Performance expectations require a mix of routine skills and dynamic capability, which means a medium level of effort is needed for collecting facts about the training’s impact.

Example 2

Carlotta was hired to work at a sandwich shop, which offers three specialty sandwiches. Each sandwich has its own unique ingredients.

Carlotta’s first week on the job is training, in which she’ll learn how to assemble the ingredients for each sandwich. Where would you place the level of effort it takes to collect facts about the impact of training?

Answer: If you selected A, you’d be right. We can easily observe Carlotta’s ability to make sandwiches and collect facts about the impact of training.

Example 3

Exit surveys for the Zebra Stripes company show that employees don’t feel supported by their managers. The company wants to reduce attrition by 5% by empowering managers with the capability to better engage, motivate and connect with people, so they offer a training programme for employee engagement.

Where would you place the level of effort to collect facts about the impact of the engagement training programme?

Answer: If you selected C, you’d be right. A manager’s ability to connect and engage with employees may be one reason employees stay, but there could be other reasons why employees leave.     

Forecast the effort and collect the facts

When you’ve identified the organisational goals and performance requirements to achieve those goals, you’ll have the facts you need to investigate the impact of training, learning and professional development.

In the next article, I'll describe how to collect facts and clues that forecast and predict the impact of training.

About Kevin M. Yates

Kevin M. Yates Picture

Kevin is a Learning & Development detective and just like Sherlock Holmes, he solves mysteries. The mystery he solves is, “Did training work?”. He uses facts, evidence and data to show training and learning’s impact on behavior, performance and goals.

His work is global and multi-industry. He’s served in a variety of roles across training, learning and talent development which guides and informs his perspective and actions. Kevin’s guiding principle is, “Find one thing about a person’s behavior or performance you can attribute to training or learning and let that lead to the facts about impact.”  

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