Analytics: the core to skills strategy

Dan Whelan explains why managers need analytics for insight into organisations’ skills gaps

 

Digital transformation demands that companies rapidly evolve, and employers need to provide their employees with learning opportunities to help them keep pace. Numerous microlearning, adaptive, AI-enabled, and virtual reality learning platforms are on the rise, gaining popularity and hype for their purported effectiveness, convenience, and overall innovative approach to learning. But new types of learning and ever-changing content require new ways of evaluating the effectiveness of training, upskilling, and reskilling.

Analytics as strategy
This should be no surprise, and it’s not a complicated formula. But it’s crucial for business leaders to view employee upskilling and reskilling data as part of their strategic plan. Better employee learning evaluation can’t be an afterthought. If the evaluation is insufficient, you can’t tell if the learning is effective. If the learning isn’t helping your employees excel, then you’ll find yourself at a competitive disadvantage in a fast-changing world.  

For business leaders, a lack of data and analytics on the performance of learning programmes and correlation to business outcomes can be costly. Business leaders need real-time data on their learning systems at both the individual and organisational level to make better decisions and course correct when necessary. The old ways of merely acquiring qualitative feedback and participation rates on employee learning won’t cut it – especially not at scale. 

Microlearning powered analytics
The right type of microlearning can help with the analytics problem. Well-designed microlearning platforms based on the principles of neuroscience employ scenario-based testing and spaced repetition, which provides learners with practical challenges that help them retain knowledge. The results of these types of tests can also provide a trove of data for HR, learning professionals, and managers alike.

It’s crucial for business leaders to view employee upskilling and reskilling data as part of their strategic plan

Another quality of good microlearning is providing individual employees customised and precision learning opportunities and evaluations – and that’s a strength for analytics, not a weakness. Personalised testing evinces personalised results. Therefore, if a particular employee struggles to complete the testing of a specific topic, it’s easy to measure what exactly they were missing and provide immediate coaching or additional, customised training. 

In the aggregate, that could show larger trends, too. If numerous employees across an organisation struggle with the same programme, themes or topics that may indicate that something larger than a single employee’s learning needs to be addressed.

Into the tech stack
The big question is how to go about capturing and using those analytics effectively. The key is automation and integration with your organisation’s larger tech stack. 

Microlearning and similar next generation learning platforms are not necessarily intended to replace current technology investments, but rather enhance, compliment, and extend existing apps and tools that workers use every day. Beyond the expected sorts of tools like communication platforms, microlearning should offer the ability to easily integrate with learning management systems (LMS), human capital management, work management, sales enablement and communication and collaboration platforms in an employee’s tech stack. This allows learning to be delivered in the flow of work as well as facilitate the flow of critical data for analytics and insights.

Too often, good data is stuck in the LMS, or within HR making sharing and the ability to combine data for analysis and surfacing of correlations and trends nearly impractical. At best, silos force teams to enter data manually across systems, which is agonisingly slow and introduces human error. 

When learning platforms are integrated into an organisations’ tech stack, business leaders have an elevated level of observability across all relevant systems, which helps them spot trends and identify problems in real-time so they can make more informed decisions about where intervention and remedial action is required.

Ironically, that brings us back to the important role of qualitative feedback in employee learning. Data is incredibly valuable, analytics provide unparalleled insights, and automation makes everything go faster and can close gaps quickly. But managers, trainers, and learning professionals can use all of those tools to augment what they do best, and what cannot be automated. They know their individual employees as people and can often read between the lines of test results. They can offer coaching or mentoring to individual employees or entire teams, combining the best of technology with the best of themselves. 

Moving forward
In the end, smart business leaders will keep their employees happy, engaged, and empowered. They’ll integrate the best of microlearning and the latest technology innovations to help their employees learn and retain knowledge, identify weaknesses and offer remedies so they can thrive, and generate analysis on resulting data – and then they’ll augment it all with the human touch.

By making analytics about the effectiveness of employee learning programmes part of their company’s strategy and culture, leaders will position their organisations for success in the immediate and far future. 

Dan Whelan is CEO of Qstream 

 

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