Accelerating Time-to-Productivity with In-Flow Learning

When you hire, are your new employees pillars of productivity, or are they sat en masse, waiting for training programmes to help guide the way? Time-to-productivity could be make-or-break for profitability, and Fuse is proving pivotal in accelerating onboarding with in-flow learning.

Common L&D Challenges in Onboarding and Time-to- Productivity

• Slow onboarding, training and upskilling of new employees in fast-growth environments
• No visibility in measuring how well employees are onboarded, and how well they perform
• Reliance on face-to-face training
• Getting product information to people quickly enough

How Fuse Can Help

We’re helping the productivity predicament across many industries, and retail is a great example. Our customer Seasalt provides a compelling and successful in-flow learning use case. With Fuse, the company shifted much of its knowledge to be available in the flow of work. We call it ‘in-flow learning,’ and it’s the opposite of ‘out-of-flow learning,’ which is usually formal and course-led. 

• Learning shifted from face-to-face training to online knowledge delivered at the point of need, in the flow of work. The onboarding process became less formal, and more an everyday part of work, moving from slow and variable to quick and consistent. 
• It also meant that onboarding could be combined with upskilling, which has been crucial, particularly for companies in light of the pandemic. 
• Ultimately, Fuse helped Seasalt to accelerate onboarding with in-flow learning, which also demonstrably accelerated time-to-productivity. In turn, this reduced time to performance, which is a great underlier of profitability driven by L&D. 

It’s where all companies should be aiming, and luckily for us, it’s the norm for Fuse customers. 

How Machine Learning is Taking Productivity to New Levels in Learning and Knowledge Development 

In 2019, Josh Bersin and Marc Zao Sanders ran a survey with Linkedin to find out more about the ‘flow of work’ surrounding knowledge workers. It turned out that 19% of the worker’s time was spent gathering information (searching for data.) That’s one day a week, or one-fifth of their salary!

Rest assured, there’s help at hand. Delivering relevant, personalised knowledge in search results is where Machine Learning can introduce demonstrable productivity improvements for L&D. 

We’re using Machine Learning to build real-time learner experience layers for our customers, which are providing the easiest and most relevant content, research and recommendations. 

Fuse looks at structured knowledge and unstructured knowledge together, learning from both to improve its understanding and accuracy to pinpoint the best answers and knowledge to serve up in response to queries. 

From a practical point of view, it means that learners can search for and successfully find the best answers they need to complete tasks within the flow of work, saving time for more useful endeavours, and boosting productivity to boot. 

Download a PDF version of this use case here. 

If you’d like a demo of how Fuse can help your company boost productivity and performance with in-flow learning, get in touch today.