Adaptive learning paths powered by verified skills data can significantly reduce learning time

• 4,923 completed skill assessments on the Workera platform
• 97% of learners who completed an assessment were certified in less than 90 days 
• 62% improvement in GenAI and ChatGPT skills after 2 weeks

How do you deliver engaging, personalized learning to a workforce of nearly 100,000 people?

That challenge became particularly important for Siemens Energy as the company developed a strategy for developing and integrating large language models (LLMs) and generative AI (GenAI) tools. The global energy company, based in Munich, employs nearly 100,000 people worldwide. 

Siemens Energy’s learning requirements span from subject matter experts responsible for designing and building cutting-edge products — and explaining them to others — to generalists who effectively use those solutions on a daily basis.

“One of our strategic priorities as a company is to increase technical domain knowledge when it comes to using innovative solutions like large language models,” said Jyotika Samjee, head of global transformation at Siemens Energy. “As a key step, we chose Workera to run a GenAI and ChatGPT learning challenge across our global workforce.”

Growing Need for Gen AI and LLM Knowledge

Before turning to Workera, Siemens Energy largely took a manual approach to learning and development (L&D). The company would conduct assessments of its employees, and business leaders would use those assessments to determine which employees should complete specific training modules. Siemens Energy works with many partner companies that provide learning materials. Still, a massive library of content can be time-consuming and overwhelming for both leaders and employees, ultimately not leading teams to the learning content they need most.

This manual approach to L&D could not scale given the growing size of the organization and resulted in a one-size-fits-all training plan that didn’t match the current skill levels or needs of individual employees. This mismatch often leads to dissatisfaction among employees. “People want to learn, but they also want to know what’s in it for them,” said Samjee. “They don’t want to start a two-week course and then realize they already know everything and just wasted their time.” 

The standard approach to enterprise upskilling would not meet the company’s needs for GenAI and LLMs. The company needed to provide highly specialized training for employees tasked with creating new AI applications and implementing Generative AI into existing applications. They also needed a different set of training materials to upskill those who would act as the consumers of the new AI-powered applications and services.

Personalized Learning Paths Accelerate Results

Siemens Energy partnered with Workera to gain a detailed understanding of the skill sets each employee needed for their role — and identify the skills they didn’t need. With Workera, two colleagues in the same role could finish an initial assessment and find that their learning paths are completely different; each being created for an individual’s verified skills and experience. 

Workera also enabled Siemens Energy to develop and deploy more trainers within their workforce. Instead of spending days or weeks completing lengthy training modules, Workera users could conduct an assessment, follow their individualized learning path, and then immediately begin deploying that knowledge by training others. In an organization with nearly 100,000 employees, this focus on “training the trainer” made it possible to rapidly multiply the impact of learning.

“We’re breaking down the learning units,” said Samjee. “You learn, and then you go back on the job and apply it. Once you’ve applied it, we then go further by teaching you how to train other colleagues who haven’t completed that training. We want a snowball effect.”

Workera also caused Siemens Energy to rethink the need for particular skills and knowledge bases. If the company previously focused on formal education and a detailed understanding of programming languages like Python, Workera demonstrated that employees could accomplish what they need with a simple understanding of APIs and precoded solutions. The Workera platform allows Siemens Energy employees to quickly learn the skills they need and begin applying them, saving them time on unnecessary topics and training.

Less Time Spent on Training = Happier Employees

Workera has led to noticeable improvements in two areas of L&D for Siemens Energy: more personalized skill building and a reduction in time needed to learn a new skill. What would previously require weeks spent learning a particular topic can now be accomplished in a few hours of targeted training. Learning paths are targeted to each employee’s existing ability level, ensuring they don’t waste any time studying what they’ve already mastered.

In addition to increasing the organization’s learning velocity, it’s also led to happier people. Every employee wants to know that they’ll be able to advance within the organization, but they don’t want to waste time on the things they find irrelevant. Workera threads the needle in providing the information each employee needs and then empowering them to apply it. “Now our employees gain access to the skills they need to learn and ignore everything they don’t need to worry about,” said Samjee. “They don’t need to sit for two weeks. They can spend a day and then get to work.”

Read the full story

Download the full Siemens Energy case study for free for to find out how Workera's Precision Upskilling solution enables teams to understand what specific skills they need to learn.