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KM as the Connector: Enabling Cross-Functional Business Transformation

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When organizations connect knowledge and technology in this way, they create a virtuous cycle of learning and improvement. Each project, decision, and interaction contributes knowledge that can be reused and refined across time. As that knowledge becomes more structured and accessible, both employees and AI systems can act on it more effectively, enabling transformation that fundamentally changes how work gets done.

Knowledge Continuity Requirements

Even with the right knowledge embedded in tools and workflows, organizations face another critical challenge: sustaining that knowledge across time. About half of all frontline workers older than 55 are expected to leave their jobs or retire in the next 5 years (reuters.com/press-releases/workforce-in-crisis-72-of-managers-fear-productivity-collapse-as-mass-retirement-strips-critical-skills-2025-03-17). If organizations don’t act to capture their knowledge and hard-earned expertise before they leave, it will walk out the door with them.

APQC research shows that many organizations are not acting with the urgency required to meet this challenge. Only 8% of surveyed organizations say they always capture knowledge from departing retirees; 41% report that they rarely or never do.

This creates a direct risk to sustaining transformation efforts across time. In many organizations, critical knowledge still resides primarily with individuals rather than in shared systems, processes, and practices. When experienced employees leave without transferring what they know, that knowledge is lost before it can be captured, shared, or embedded into how work gets done. This makes it much harder to build on past experience and sustain improvements for future generations.

KM Enables Structured Knowledge Transfer at Scale

KM helps organizations address the risk of critical knowledge loss by establishing structured, repeatable approaches for capturing and transferring knowledge (apqc.org/resource-library/resource/understanding-structured-knowledge-transfer-0).

In practice, this includes these actions:

♦ Targeted knowledge capture, such as structured interviews and knowledge capture sessions with experienced employees to document critical expertise
♦ Mentoring and peer-based learning, which enable the direct transfer of knowledge through observation, coaching, and on-the-job support
♦ Communities of practice, where employees share experiences, solve problems, and spread knowledge across teams and functions
♦ Reusable knowledge assets, including playbooks, guides, and templates that support onboarding, reskilling, and day-to-day work

These approaches help organizations go beyond preventing knowledge loss and create the conditions for continuous learning across the workforce. Employees gain access to institutional knowledge, learn from experts and their peers, and build capabilities more quickly across time. This not only supports onboarding and reskilling, but also strengthens an organization’s ability to adapt and prepare the workforce for what comes next.

Knowledge Is the Foundation of Enterprise Transformation

Successful transformation depends on an organization’s ability to manage and apply knowledge effectively. Whether the goal is digital transformation, workforce development, operational resilience, or innovation, organizations succeed when they can capture knowledge, embed it into daily work, and sustain it to improve how work gets done.

KM enables this by helping knowledge flow across people, processes, and systems. Effective knowledge flow, in turn, empowers organizations to break down silos, strengthen collaboration, and turn insight into action.

Put It Into Practice

Carry out these three actions to harness the power of KM for your transformation:

♦ Identify and Close Knowledge Gaps in High-Value Work: Start with one critical process and assess where employees lack the context, expertise, or guidance needed to perform effectively. Focus on making knowledge visible and reusable before investing in new tools.

♦ Put Knowledge Where Decisions Are Made: Choose a common decision employees make—for example, how to interpret a report, how to respond to an issue, or whether to approve a request. Identify what knowledge is needed to make that decision well, and embed it directly into the tools or workflows employees use.

♦ Capture Knowledge From One At-Risk Role: Identify one role where knowledge loss would significantly impact performance, such as a retiring expert or a critical operational position. Capture that knowledge by combining targeted methods such as job shadowing and interviews with AI-assisted analysis of existing work and content. Convert the results into simple, reusable assets such as checklists, guides, or short summaries.

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