Throughout my career, I’ve seen how the institutional knowledge someone holds can be regarded as key to their job security. It’s often considered an insurance policy of sorts, a reason to be kept around. This perception means that when it comes to documenting and reporting knowledge, people only share the bare minimum. And most of what they know leaves the organization when they do.

While this dynamic is particularly common in industries that thrive on proprietary intelligence—including financial services where I spent nearly two decades—institutional knowledge loss has immediate and long-term impacts in all industries. I witnessed consequences from lost clients to colossal recruitment expenditures, broken internal processes, and huge missed opportunities for innovation and new business.

Knowledge loss, long relegated to HR and people teams, is a sweeping leadership issue that deserves more attention from a company’s top executives and an upgraded approach that leverages newly available AI solutions.

UNDERSTANDING KNOWLEDGE LOSS

Corporations are exposed to knowledge loss of all kinds on a regular basis. Sugarwork, an AI-powered knowledge management platform, calculates that Fortune 500 companies lose $31.5B annually due to critical knowledge exiting their organizations. Mass layoffs across industries over the past few years have only heightened the urgency around the issue. Beyond layoffs, there are several other factors driving turnover and the widening knowledge gaps:

• Forty million baby boomers are expected to retire in the next 10 years, taking large swaths of knowledge with them that is undocumented.
• The pandemic upended the way we work and changed the nature of in-person collaboration for many companies, impeding opportunities for real-time knowledge-sharing.
• Companies are leaning heavily on independent contractors and freelancers to reduce expenses. Freelance talent inevitably takes knowledge with them when a contract ends.

The nature of the knowledge lost also varies widely, from hard data to qualitative insight, which is often where some of the widest gaps are. Upwards of 80% of company data is qualitative, and much of it is held by a company’s most experienced team members.

Combine this with the fact that only 15% to 20% of all knowledge in a company is documented at all, and the true cost and scope of the challenge quickly come into view. So while turnover is a major factor in driving knowledge loss writ large, major risks are also created by deeply rooted reporting gaps and a lack of a systematic approach to real-time knowledge transfer

A SWEEPING C-SUITE ISSUE

For leaders, poor knowledge management has a tangible business impact. In my work as an early-stage venture investor, I’ve heard numerous examples from entrepreneurs tackling this challenge, including Sugarwork’s Vanessa Liu. For example, they shared that a leading pharmaceutical company was managing the divestiture of assets by asking team members to share insights in individual Microsoft Word documents. A major airline tracked its expert network in multiple spreadsheets.

These situations have real consequences far beyond the general high cost of business inefficiency—the recent reports of increased near misses on airport runways come to mind. Top-level executives need to recognize the scale of potential reputational and economic impact on their company, team, and customers.

The good news is, the advent of AI-driven technology means that mitigating knowledge loss and synchronizing its transfer is more attainable for leaders than ever, just as the risks rise to new heights.

AI SOLUTIONS ARE WITHIN REACH

AI platforms can now leverage structured and unstructured data and automate most of the challenging processes involved in knowledge management. From creating organized, searchable records to powering knowledge transfer at key moments of business transition, a host of venture-backed startups are providing solutions to these issues.

On the organizational level, AI tools can ensure that knowledge is properly captured and retained at each stage of the employee life cycle. With virtual and hybrid meetings all common, AI can also aggregate business information and deliver intelligent, near real-time, and actionable insights to the C-suite in an easily digestible form, in certain ways preempting knowledge loss from accumulating.

Not only are knowledge loss solutions key to ensuring the overall strength of a business, but they can also empower leadership with the information needed to make key decisions, better allocate their time, and identify priorities. Of course, leaders need to proceed with reasonable caution—these tools aren’t flawless, so leaders and security teams need to be aware of how their proprietary data might be exposed.

Many still view knowledge loss as a risk to be handled by HR leaders. It is a strategic corporate priority due to its far-reaching implications for the bottom line. The responsibility for adopting a knowledge management strategy sits firmly at the executive level, with a company’s C-suite. And it’s not just a matter of leaders addressing knowledge loss during turnover or moments of organizational change, but of ongoing investment in technology tools that treat knowledge as a major organizational asset.