The Technology Of Learning
Professional Learning Networks [Source: https://youtu.be/67ruX4AbZQc>
In the United States, nearly 10,000 people hit retirement age each day. Across the pond in the United Kingdom, about a third of the workforce is already over 50 years of age. Enterprises are holding a gun that's smoking from both ends - enough young workers, with the right skills, aren't walking in, even as older workers are walking out. Taking the cumulative knowledge, experience and relationships acquired over decades, along with them. It's a crisis whose proportions we are yet to grasp. But one study of the cost of employee turnover estimates that for high-level, experienced positions the replacement cost is about four times the annual salary of the exiting employee. Assuming, of course, that the company can actually find a replacement.
In reality, enterprises need to prepare to counter the challenge of a significant workforce gap. One way of doing that is through Knowledge Management.
As per the Information Technology Infrastructure Library (ITIL), "the purpose of Knowledge Management is to ensure that the right information is delivered to the appropriate place or competent person at the right time to enable informed decision making." The last bit is key. Knowledge Management, which involves storing, organizing and disseminating an organization's "worth saving" information, must finally translate into better employee performance. There are three components to that, namely, process, people and technology.
An electric linesman's knowledge of which roads to use in open terrain, could spell the difference between life and death. In California, where irate ranchers have been known to shoot at newbie linesmen straying down the wrong road, a prominent utility company is taking no chances. It has a robust knowledge management process in place to ensure that experienced workers pass on their tacit knowledge to the younger workforce before they retire. The company gets supervisors to conduct a knowledge transfer risk assessment of each retiring employee in their charge, and based on criticality, actions a knowledge transfer plan whereby the retiring employee records his knowledge in a way so that it can be easily accessed and used by others.
Mentoring is arguably the most important "people element" in knowledge management. Organizations should get senior employees to work with the younger generation early on as coaches and mentors or as project partners. When knowledge is transferred gradually and continuously, on a day-to-day basis, rather than rained down in a burst of "training", it has a much better chance of being imbibed and retained. However, it is hard to create a formal mentoring framework for transferring knowledge, which means it can never be fully documented or "replicated".
A variety of technology solutions can step in to fill such gaps. Enterprises can house a permanent digital repository of important knowledge on their intranet, accessible to employees at any time, for any length of time. They can deploy Learning Management Systems to enable both structured and informal learning. Employees can use the rich digital multimedia content on these systems to learn on their own, while trainers can leverage them as a valuable teaching aid in blended learning.
Social platforms are a great way to build employee knowledge and engagement. They also impart to the new workforce a sense of belonging. Senior employees should be encouraged - and assisted if need be - to use these platforms so they can share their personal experiences even outside official "mentoring hours". Companies can use bulletin boards for posting information that is relevant to a large number of employees.
But the best is yet to come. The emerging science of cognitive computing is the future of knowledge management. Combining a range of technologies, from artificial intelligence (AI) and machine learning to advanced analytics and natural language processing, cognitive computing can enable a near-human knowledge transfer experience. People can "teach" a cognitive computing solution what they know, after which it never forgets. Cognitive technologies can learn information, but more impressively, they can also "understand" intangibles, such as personal experience. And in doing so, they act pretty much like human experts.
It is exactly these intangibles - tacit information, experience, instinct, tribal knowledge, call it what you will - that enterprises hope to retain long after their employees have left the building. For a world staring at a serious talent crisis, the value that cognitive computing could bring to knowledge management is incalculable.