Flexibility is a growing employee expectation. But this doesn’t just mean better schedules and work/life balance. Employees are increasingly looking to take control of their entire working experience which, for many people, means employment is not a full-time, long-term proposition. At the same time, organizations are shifting their staffing models to become more agile and responsive to changes in demand. As Mary Meeker showcased in her 2018 Internet Trends Report, freelance work, from ride sharing to seasonal assignments, is exploding around the world. In fact, according to a recent Forbes article, by 2027, freelancers are expected to become workforce majority based on the current growth rate, due to factors such as automation, freedom, flexibility and the ability to earn extra money.
A new workforce demands an adaptive training approach
This expanding gig economy has a direct impact on how companies support their employees. Traditional training strategies are built to take a new employee from zero to 100 over an extended career path. But the emerging definition of “career” isn’t a path with one company. Rather, it’s a collection of brief but meaningful relationships between employers and employees that meet each other’s needs at a given time. This requires a new strategy that will help an organization support a continuous influx of temporary workers, many of whom come to their roles with existing expertise. And adaptive microlearning is the perfect approach.
In order to understand why the principles of adaptive microlearning work so well for the gig economy, let’s explore the working experience of an average freelancer–we’ll call her Susan.
Susan joins an organization in a freelance role and has considerable experience. So she doesn’t need a full onboarding experience. Rather, she just needs to close a few specific gaps related to her new company, such as org-specific processes. An adaptive microlearning approach takes Susan’s existing knowledge into account and assesses her capabilities through questioning and practice scenarios. Her training is personalized right away to focus on just what she needs to get started quickly and confidently. The most important topics are covered up front, while additional information is introduced along the way through daily, 5-minute online microlearning sessions.
As part of a microlearning strategy, Susan is provided with on-demand resources to help her solve problems as they come up. This includes the ability to reach out for help from her community when she can’t find an answer on her own. This helps Susan become productive and focused on her work quickly, rather than wasting time in training that she either doesn’t need or will quickly forget anyway.
Learning that keeps pace with behavior changes
Microlearning is a data-driven strategy. As Susan does her work, her knowledge is continuously assessed during her daily microlearning sessions. Her manager is also observing her work and capturing data to identify potential behavior gaps. Finally, her performance is continuously measured using business KPIs (key performance indicators). This data is all pulled together to shape Susan’s microlearning profile. This profile continuously adapts and personalizes her learning experience to focus on the topics most important to her at that time.
Of course, Susan isn’t the only freelancer in the company. This data-driven microlearning strategy can scale personalized support across the organization to freelancers and full-time employees alike. Meanwhile, administrators can evaluate the data generated through microlearning to better target their training efforts. They can also identify gaps in freelancer knowledge to inform the recruiting and hiring experience.
Traditional training fails to meet the needs of a modern business, and these shortcomings will only be magnified by the realities of the gig economy. Microlearning has grown in popularity because it enables organizational agility.
- It meets the employee where they are rather than wasting time in extra training
- It provides just-in-time support to enable continuous learning
- It uses data to personalize and adapt the learning experience
- It scales personalized learning across the organization
All of this will be a critical for companies that hope to thrive with a freelance workforce.