For HR leaders, attracting and cultivating top talent is the highest priority. So it’s no surprise that investments in corporate training initiatives continue to increase. Last year, total U.S. training expenditures reached a whopping $70.65 billion last year - yet only 38% of learning & development professionals think they’re ready to support employee’s needs.
Why is there such a discrepancy? When you consider the digital transformation sweeping across organizations today and how it’s changing how people work, this is where the conflict arises - and why traditional training formats must adapt to be more effective.
The employee obstacle course
The classical approach to workplace learning is through structured, formal training. This includes dedicated workshops and coaching sessions, e-learning and instructor-led courses, and attendance at conferences and trade shows.
But here’s the irony - despite the upwards trend to invest in training programs, these are typically conducted in a passive and uniform manner regardless of each person’s skills and experience. In fact, research shows we're likely to forget 90% of what we learn within a year unless the skills are reinforced. And when new systems - or upgrades to existing tools - are introduced so frequently, conducting structured, one-off training sessions is unsustainable.
For the average employee, it’s a learning obstacle course fraught with pitfalls, fences and hurdles. Most people don’t feel that they have enough time to dedicate to formal training - and when they do take the time, there isn’t always adequate guidance or direction. Despite the volumes of resources available, employees also struggle to find the right information and engage with it.
Joining content with context
Most training programs are incredibly rich in content, but they fall short in their context, guidance, and engagement. Simply put, HR leaders need to scrutinize the application of the training program (how it is being conveyed), rather than the substance of what’s being learned (what is being communicated).
Fortunately, the latest technology advancements - particularly in big data analytics and machine learning - are creating a more dynamic format for how employees engage with existing systems and learn in real-time.
A simple analogy of how this works is a map versus a GPS system. Before GPS, to go from point A to B people spent time carefully plotting their journey on a map, factoring the pit stops and tolls along the way. But this opened up the chance to missing a landmark on the drive, leading the person to re-navigate the journey. The process takes a lot of time, money and emotional energy.
Using GPS technology, however, there’s a real-time guide for the entire trip. For every wrong turn, the system automatically redirects the driver, providing specific instructions. And there’s flexibility in the system, allowing the person to choose which route to take and what landmarks to see. It’s an effective means to the same outcome devoid of stress, achieved in a cost-effective way.
Contextual guidance is the new standard
Whether it’s a new employee coming on board, an existing worker learning a new process, or a team improving how they use a particular system, the latest innovations can effectively guide employees at every step.
By rolling out big data analytics, a business can gather information to identify the common obstacles to system adoption. Rather than simply providing FAQs or webinars, user data can show who is logging into a system, how long they are in the system, and where they get stuck. For instance, analytics may find that the main reason why people are not completing their performance reviews is because they struggle to create a SMART goal.
Based on such data, machine learning and artificial intelligence (AI) can contextually guide the user while they’re logged in to complete any given task. Using the same appraisal example, machine learning can leverage the insights to steer a user on how to create a SMART goal, to finish the task by deadline.
As a result, the notion of continuous performance improvement becomes a reality - and contextual guidance becomes the new standard. Taking advantage of existing resources and content, big data analytics and AI can bridge the gap in existing training programs to improve the quality of data in any given system, reduce support costs, and enhance the user experience.
Because the tools are accessible as an employee engages with a system or process, the business benefits from greater self-service adoption and ultimately, increased productivity. Through self-service, companies can make a paradigm shift from a system of engagement to one of productivity. If HR leaders capitalize on these solutions, not only will they see training spends decline dramatically, but they’ll be able to measure the true efforts in nurturing top talent. HR sits at a critical juncture to help users adopt, then adapt.
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