This morning, Axonify announced that it has reached the “holy grail of corporate learning”: connecting training to business results. Proving the value of training is, indeed, often considered the ultimate goal – and ultimate challenge – of learning leaders. Recent research by LEO and Watershed found that 70 percent of L&D leaders say measuring business impact is a top priority, but learning leaders also say it’s a top challenge.

Measuring impact is so difficult because of limited data and the many confounding variables that contribute to improved performance. For example, if a sales rep increased her sales goals last year, do you know if she did so because of the training she received, because she received better content from marketing or because she has a new sales coach? Axonify believes it’s found the answer with Axonify Impact, a “learning attribution engine” that uses big data and machine learning to connect employee knowledge acquisition with business results.

“Big data” is a term used to describe large, complex data sets that require advanced analytics tools to sift through and identify patterns and relationships. Machine learning is one of those tools – a type of artificial intelligence (AI) that automates data analysis using algorithms. For example, Netflix uses machine learning algorithms to make movie or series recommendations based on behavior – what the viewer has watched previously. In the case of Impact, machine learning takes Axonify learner data as well as client business data to identify patterns like the varying levels of product knowledge based on sales rep success. “We ingested the sales data of [a customer’s] product, and then went back and looked at who was selling the most of that product, and what was their performance on Axonify,” Carol Leaman, CEO of Axonify, explains. “What we were able to do was to pinpoint exactly who was going to sell more of the product based on their knowledge and, not only that, which topic areas had the most impact on driving the outcome.”

This granularity, Leaman says, means that not only will training managers be able to demonstrate clear impact on business results, but they will also be able to identify what types of training they should focus on and what types of training are not actually needed. “Instead of guessing at what the training is delivering and what behavior it might be changing, we can tell [training managers] specifically what to focus on that is going to have the biggest impact on the business.” That ability, in turn, makes learning leaders true “strategic partners” with other business leaders, giving them the proverbial seat at the table.

Connecting Training and Business Results

“An often ignored issue,” write Jack and Patti Phillips and Kylie McLeod of the ROI Institute, “is communicating the results to the key stakeholders.” Once you’ve collected data and made those connections between training and business results, make sure your stakeholders know about it. Demonstrating impact is the best way to obtain more resources for training (another common challenge for learning leaders).

It’s also important to use that information internally to improve training. “Once you decompose what those business outcomes are that are the most important priorities,” Leaman says, “then you can go back and start to look at, ‘Now what do we need people to know? What is the knowledge that is going to drive the correct behavior to achieve the business outcome?’” Then, make sure learners are actually applying that knowledge. Fredrik Schuller and Kevin Bronk of BTS call this reinforcement “the missing step for measuring ROI.”

As technology continues to evolve, and our ability to efficiently analyze large amounts of data improves, it will become easier for L&D to prove business impact. It’s been a long and difficult quest, but the holy grail will be a true game-changer for the industry.

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