Measuring Learning Impact Through Business Results
One major challenge we in Learning and Development (L&D) often find ourselves dealing with is how to demonstrate the impact of our learning solutions. Frequently, we rely on surveys, conversations with managers and learners, and completion data. In many instances, we’ve observed more confident co-workers embracing new practices in their daily work. They act as ambassadors for these practices, such as leveraging data analysis projects, within their teams and actively seek out opportunities for personal and collective development. Overall, this positive impact builds upon the solid foundations our training programs provide.
Measuring Learning Impact By Using Data Analysis Projects
However, quantifying this impact in monetary terms still remains a taboo. It goes beyond completion numbers and experience ratings for a particular solution. Recently, I had the privilege of leading a pretty big data analysis upskilling initiative. This topic had been on our agenda for quite some time, and we finally took a significant step forward by designing and delivering an intensive boot camp focused on data analysis.
Data analysis consistently ranks among the top five essential skills for various job roles. Reading and understanding data, analyzing and interpreting it, deriving meaningful insights, and effectively communicating findings through visualization and storytelling—all of these are considered fundamental tasks for roles where handling data is a daily norm. We took the chance to use this upskilling initiative to test a new way to measure impact. And what better opportunity to analyze this, if not through a data analysis program?
1. Apply Data Analysis To A Case Study/Project
To start, as part of the application process for this initiative, we requested all applicants to submit a case study/project proposal. A case study/project involves tackling a real business problem using the data analysis skills and techniques learned during the program.
In a capstone project, participants demonstrate their ability to apply data analysis techniques to practical problems. This encompasses the typical steps of data analysis: identifying relevant data sources, cleaning and preparing the data, conducting exploratory data analysis, and developing models to address the problem.
The goal of each project was to provide a comprehensive view of the entire data analysis process, from data collection to data presentation and storytelling, and to support the business in solving the identified challenge. It’s a great way to apply the learnings in a real-world context!
2. Outline How To Measure Project Impact
In addition to having a well-crafted project proposal, we asked all participants during the application phase to outline how they would measure the impact of their projects. In other words, we wanted to understand how the learning initiative influenced both the learners and their projects, ultimately moving the needle within the business.
This approach laid the foundations for a compelling narrative: thanks to the program, we now have a group of co-workers who have acquired practical knowledge. This knowledge has empowered them to tackle a variety of different projects and run specific experiments within the business. These endeavors yield returns in the form of profit or opportunities (such as cost and time savings).
The nature of these experiments allowed us to obtain results swiftly. It created accountability for the learner to deliver something meaningful to show that all their efforts were actually leading to something good and worth exploring further.
3. Explore Ways To Scale Up By Sharing The Narratives
Consequently, we had the opportunity to share our findings with the broader community and explore ways to scale up these projects. The participants were asked to participate in internal forums where they could present their work and the results of the tests they ran to measure the effectiveness. Additionally, they were asked to write an article to share on our internal channels where anyone in the company could read the whole story of each project, from the identification of the problem to the solution.
This internal marketing of the solutions generated, in turn, interest to replicate the experiments in similar contexts. By doing this, we continue to uncover even more results and fine-tune the projects, making them increasingly scalable and relevant for others in their respective contexts.
During this phase of scaling up projects, the learners were still held accountable for reporting back the results to the core case study. This enabled us to continuously measure the impact of the overall initiative by getting all the results from each project summed up.
Conclusion
In conclusion, although not perfect, this could be a good method to generate a figure that would demonstrate the impact of the learning solution you’re working on. The narrative behind a story like this one might help you in getting the stakeholders’ engagement needed to scale up the program while helping your learners to grow their competence and acquire a great level of confidence in the topic in focus.
