Role-Based Training Optimization A/B Testing Micro-Learning Vs. Traditional BIM-VDC Onboarding for Field Adoption - A Conceptual Framework

Over the last decade, many construction management organizations and the subcontractors have spent time buying different kinds of software that will streamline the process and communication using technology. A few of these common platforms include Autodesk Forma (previously Autodesk Construction Cloud), Revizto, Dronedeploy, and a bunch of adjacent platforms. While this software offers a great set of solutions, they do come with a requirement of having a human capability to use it, understand it, and then train it further. Every time a researcher has delivered a training to the project team there has been one lesson understanding that the same set of trainings and tools for the same software cannot be delivered to a large domain of audience that has personnel from different scope within the business, like the architects or the designers, field superintendents, project managers, QAQC personnel etc., across active job sites. This way of delivery may give initial boost to the usage of software but the observation shows that there has been decline in the use of right tool after two weeks of training where people go back to the physical drawings standard phone pictures (that are dated) and the text communication to resolve the issue. The technology was never the issue but the way it was implemented made the difference in the efficiency of trainings. Building on lessons from on-field training and notes captured during these sessions, this paper focuses on two major arguments. First, utilizing the actual job site examples across five different construction personas which will define and demonstrate how the Autodesk Forma, Drone deploy and Revizto implementation can create a value-based ecosystem for tech stacks depending on who is using them and how are they utilizing it. Second, it gives the parameters for the evaluation by proposing and specifying an experimental framework - A/B test comparing micro learning modules, simulating the actual job site condition in some cases and having a traditional office-led onboarding to move the data from just being in the "lessons learned" silo to a good implementation strategy that is not just a generic training agenda but turns training session into a successful outcome. This is based on the author’s observations and on-field training recommendations. The paper does not give the results from any of the actual experimental micro-learning performed but provides different methods in which it could be implemented.