The Retirement Cliff and Its Implications

The “retirement cliff” refers to the impending wave of retirements as a significant portion of the workforce—particularly Baby Boomers—reaches retirement age. According to labor market trends, millions of experienced professionals are set to retire in the coming years, posing a critical challenge for organizations. The departure of seasoned employees risks the loss of institutional knowledge, technical expertise, and key relationships, leading to operational disruptions and costly efforts to regain lost expertise.

One of the most immediate financial consequences Enterprise Knowledge has seen on several of our engagements is the growing reliance on retirees returning as contractors to fill knowledge and capability gaps, often at significantly higher costs than their original salaries. While this can provide a short-term fix, it also creates a long-term liability. Research from Harvard Business Review and other labor market analyses shows that rehiring former employees without structured knowledge transfer can perpetuate a cycle of dependency, inflate workforce costs, and suppress the development of internal talent. Organizations may pay premium contract rates while still losing institutional knowledge over time, especially if critical expertise remains undocumented or siloed. Without proactive strategies, such as structured succession planning, mentoring, and systematic knowledge capture, organizations risk operational disruption, weakened continuity, and increased turnover-related costs that can amount to billions of dollars annually.

The Role of Knowledge Management in Succession Planning

Knowledge management plays a vital role in succession planning by implementing systems and practices that ensure critical expertise is systematically captured and transferred across generations of employees. Documenting key insights, best practices, and institutional knowledge is essential for mitigating the risk of knowledge loss. This process helps to strengthen organizational continuity and ensures that employees have the knowledge they need to perform their roles effectively and make informed decisions.

The Retirement Cliff: Challenges & Solutions

While the table highlights immediate challenges and corresponding solutions, organizations benefit from a deeper set of strategies that address both near-term risks and long-term sustainability. The following sections expand on these themes, outlining actionable approaches that help organizations capture critical knowledge today, while laying the foundation for resilient succession planning tomorrow.

Near-term Strategies: Mitigating Immediate Risk

Engage Employees in Knowledge Capture Efforts

Long-tenured employees approaching retirement have accumulated invaluable institutional knowledge, and their sustained tenure itself demonstrates their consistent value to the organization. When a retirement cliff is looming, organizations should take action to engage those employees in efforts that help to capture and transfer key institutional knowledge before it is lost.

Cast a Wide, Inclusive Net

Organizations often lack visibility into actual retirement timelines. Rather than making assumptions about who might retire or inadvertently pressuring employees to reveal their plans, frame knowledge transfer efforts as part of comprehensive KM practices. By positioning these initiatives as valuable for all long-tenured employees—not just potential retirees—organizations create an inclusive environment that captures critical knowledge. This broader approach not only prepares for potential retirement-related knowledge gaps but also establishes ongoing knowledge transfer as a standard organizational practice.

Acknowledge and Thank Employees

Explicitly acknowledge the expertise and contributions of key knowledge holders participating in efforts. By recognizing their professional legacy and expressing the organization’s desire to preserve and share their wisdom with others, leaders can create a foundation for meaningful participation in knowledge transfer activities. This approach validates key members’ career impact while positioning them as mentors and knowledge stewards for the next generation. Consider setting aside some time from their normal responsibilities to encourage participation.

Reward Knowledge Sharing

Employees are far more likely to engage in knowledge transfer when it is seen as both valuable and valued. In EK’s experience, organizations that successfully foster a culture of knowledge sharing often embed these behaviors into their core talent practices, such as performance evaluations and internal recognition programs. For example, EK has helped to incorporate KM contributions into annual review processes or introduce peer-nominated awards like “Knowledge Champion” to highlight and celebrate individuals who model strong knowledge-sharing behaviors.

Enable Employees to Capture Knowledge

Effective knowledge transfer begins with capturing critical institutional knowledge. This includes both explicit knowledge, such as processes and workflows, and tacit knowledge, such as decision-making frameworks, strategic insights, and the rationale behind past choices. To guide organizations in successful knowledge capture and transfer practices, EK recommends implementing a variety of strategies that help build confidence and make the process manageable.

Provide Documentation Training and Support

Organizations should consider offering dedicated support through roles and teams that naturally align with KM efforts, such as technical documentation, organizational learning and development, or quality assurance. These groups can help introduce employees to the practice and facilitate more effective capture. For example, many organizations focus solely on documenting step-by-step processes, overlooking the tacit knowledge that explains the “why” behind key decisions to provide future employees with critical context. In EK’s experience, preserving and transmitting knowledge of past actions and opinions has given teams the confidence to make more informed decisions and ensure coherence in guidance. This approach is especially valuable from a legal perspective, where understanding the rationale behind decisions is crucial for consistency and compliance.

Help Prioritize the Knowledge to Capture

Organizations can help focus knowledge capture efforts, without overwhelming employees, by prioritizing the types of knowledge to capture. If knowledge falls into one of these categories, it is ideal to prioritize:

1. 1. Mission-Critical Knowledge – High-impact expertise that is not widely known (e.g., decision-making rationales, specialized processes) is at greatest risk for loss. Encourage employees to prioritize this knowledge first.

1. 1. Operational Knowledge – Day-to-day processes that can be captured progressively over time. Suggest to employees that they take advantage of workflows and cycles as they are completed to document knowledge in real time from beginning to end.

1. 1. Contextual Knowledge – Broader insights from specific projects and initiatives are best captured in collective discussions or team reflections from various participants. Aim to make arrangements to put team members in conversation with one another and capture insights.

Embed Knowledge Capture into Workflows

Rather than treating documentation as a separate task, organizations should embed it into the existing processes and workflows where the knowledge is already being used. Integrating documentation creation and review into regular processes helps normalize knowledge capture as a routine part of work. In practice, this may look like employees updating Standard Operating Procedures (SOPs) during routine tasks, recording leadership reflections during key decisions, or incorporating “lessons learned” or retrospective activities into project cycles. Additionally, structured after-action reviews and reflective learning exercises can further strengthen this practice by documenting key takeaways from major projects and initiatives. Beyond improving project and knowledge transfer outcomes, these habits also build durable knowledge assets that support AI-readiness.

Design Succession-Focused Knowledge Sharing Programs

Cultural silos and resistance to sharing knowledge often undermine succession planning. Employees may hesitate to share what they know due to fears about losing job security, feeling undervalued, or simply lacking the time to do so. To overcome these challenges, organizations must implement intentional knowledge transfer programs, as outlined below, that aim to prevent a forthcoming retirement cliff from leaving large gaps.

Create Knowledge Transfer Interview Programs

Pairing long-tenured staff with successors ensures that critical institutional knowledge is passed on before key departures. Create thoughtful interview programming that takes the burden off the experienced staff from initiating or handling administrative efforts. EK recently partnered with a global automotive manufacturing company to design and facilitate structured knowledge capture and transfer plans for high-risk roles that were eligible for retirement, including walkthroughs of core responsibilities, stakeholder maps, decision-making criteria, and context around ongoing initiatives. These sessions were tracked and archived, enabling smoother transitions and reducing institutional memory loss. EK also supported a federal agency in implementing a leadership knowledge transfer interview series with retiring senior leaders to capture institutional knowledge and critical insights from their tenure. These conversations focused on navigating the agency’s operations, lessons for successors, and role-specific takeaways. EK distilled these into concise, topical summaries that were tagged for findability and reuse, laying the foundation for a repeatable, agency-wide approach to preserving institutional knowledge.

Foster Communities of Practice

Encourage cross-functional collaboration and socialize knowledge sharing across the organization by establishing communities of practice.  The programs provide opportunities for employees to gather regularly and discuss a common professional interest, to learn from each other through sharing ideas, experiences, and best practices. Involve long-tenured staff in these efforts and encourage them to develop topics around their expertise. EK has seen firsthand how these practices promote ongoing knowledge exchange, helping employees stay connected and informed across departments, even during leadership transitions.

Offer Formal Knowledge Exchange Programs

Knowledge Exchange Programs, like job shadowing, expert-led cohorts, and mentorship initiatives, create clear pathways for employees to share and document expertise before transitions occur. Long-tenured employees are often excellent candidates to take the leading role in these efforts because of the vast knowledge they hold.

Ultimately, effective succession planning is not just about capturing what people know—it is about creating a culture where knowledge transfer is expected, supported, and celebrated. By addressing resistance and embedding knowledge-sharing into the rhythm of daily work, organizations can reduce risk, improve continuity, and build long-term resilience.

Long-term Strategies: Building Sustainable Knowledge Flow

While short-term efforts can help reduce immediate risk, organizations also need long-term strategies that embed knowledge management into daily operations and ensure continuity across future workforce transitions. That is why EK believes Artificial Intelligence (AI) and Knowledge Intelligence (KI) are essential tools in capturing, contextualizing, and preserving knowledge in a way that supports sustainable transitions and continuity.

Below are long-term, technology-enabled strategies that organizations can adopt to complement near-term efforts and future-proof institutional knowledge.

Structure and Contextualize Knowledge with a Semantic Foundation

EK sees contextual understanding as central to KM and succession planning, as adding business context to knowledge helps to illuminate and interpret meaning for users. By breaking down content into dynamic, structured components and enriching it with semantic metadata, organizations can preserve not only the knowledge itself, but also the meaning, rationale, and relationships behind it. EK has supported clients in building semantic layers and structured knowledge models that tag and categorize lessons learned, decisions made, and guidance provided, enabling content to be reused, assembled, and delivered at the point of need. This approach helps ensure continuity through leadership transitions, reduces duplication of effort, and allows institutional knowledge to evolve without losing its foundational context.

Leverage Knowledge Graphs and Intelligent Portals

Traditional knowledge repositories, while well-intentioned, often become static libraries that users struggle to navigate. EK has helped organizations move from these repositories to dynamic knowledge ecosystems by implementing knowledge graphs and a semantic layer. These approaches connect once disparate data, creating relationships between concepts, decisions, and people.

To leverage the power of the knowledge graph and semantic layer, EK has designed and deployed knowledge portals for several clients, providing a means for users to engage with the semantic layer. These portals consolidate information from multiple existing systems into a streamlined, user-friendly landing page. Each portal is designed to serve as a central hub for enterprise knowledge, connecting users to the right information, experts, and insights they need to do their jobs, while also supporting smoother transitions when staff move on or new team members step in. With intuitive navigation and contextualized search, the portal helps staff quickly find complete, relevant answers across multiple systems, explore related content, and access expertise—all within a single experience.

Augment Search and Discovery with Artificial Intelligence

To reduce the friction of finding and applying knowledge, EK has helped clients enhance knowledge portals with AI capabilities, integrating features like context-aware search, intelligent recommendations, and predictive content delivery.  These features anticipate user intent, guide employees to relevant insights, and surface related content that might otherwise be missed. When paired with a strong semantic foundation, these enhancements transform a portal from a basic search tool into an intelligent instrument that supports real-time learning, decision-making, and collaboration across the enterprise.

Automate and Scale Tagging with AI-Assisted Curation

Manual tagging is often cited as one of the more time-consuming and inconsistent aspects of content management. To improve both the speed and quality of metadata, EK has helped clients implement AI-assisted tagging solutions that automatically classify content based on a shared taxonomy.

We recommend a human-in-the-loop model, where AI performs the initial tagging, and subject matter experts validate results to preserve nuance and apply expertise. This approach allows organizations to scale content organization efforts while maintaining accuracy and alignment.

For example, we partnered with a leading development bank to build an AI-powered knowledge platform that processed data from eight enterprise systems. Using a multilingual taxonomy of over 4,000 terms, the platform automatically tagged content and proactively delivered contextual content recommendations across the enterprise. The solution dramatically improved enterprise search, reduced time spent locating information, and earned recognition from leadership as one of the organization’s most impactful knowledge initiatives.

Integrate Technology, People, and Process Within Succession Planning

The most successful organizations do not treat knowledge technologies as standalone tools. Instead, they integrate them into broader KM and succession planning strategies, ensuring these solutions support, rather than replace, human collaboration and expertise.

In EK’s experience, when AI, knowledge graphs, and semantic metadata are used to enhance existing processes—like onboarding, leadership transitions, or project handovers—they become powerful enablers of continuity. These tools help protect institutional knowledge, reduce bottlenecks, and enable repeatable practices for knowledge transfer across roles, teams, and time.

As part of a long-term KM strategy, this allows organizations to evolve from reactive knowledge capture to proactive, ongoing knowledge flow.

Measuring Knowledge Transfer Impact

As we have provided the tools and advice for ensuring impactful knowledge captures and transfers, measuring the effectiveness of knowledge transfer initiatives is the essential next step to ensure that succession planning goals are being met and that knowledge transfer efforts are producing meaningful outcomes. Key performance indicators (KPIs) and metrics can help track the success of these initiatives and provide insights into their impact on the organization’s leadership pipeline.

Closing

Navigating the retirement cliff requires both immediate action and long-term planning. By addressing resistance, dismantling silos, embedding knowledge-sharing into daily work, and leveraging technology, organizations can reduce risk, preserve critical expertise, and build long-term resilience. Need help developing a strategy that supports both near-term needs and long-term success? Let’s connect to explore tailored solutions for your organization.

The post Navigating the Retirement Cliff: Challenges and Strategies for Knowledge Capture and Succession Planning appeared first on Enterprise Knowledge.

Enterprise Knowledge regularly hears from our clients that: 

• “We don’t have time for documentation with everything going on.”

• “We’re not sure how to capture knowledge in a way that is useful to others.”

• “People don’t know what they can or can’t share.”

These are real barriers, and this blog and accompanying infographic address them directly. It is not about doing more. It is about working smarter by embedding lightweight, effective knowledge-sharing habits into what you are already doing. Over time, these habits create durable knowledge assets that strengthen organizational memory and prepare your content and data for AI-readiness.

Integrate Knowledge Capture Into the Flow of Work

Small changes can make a big impact, especially when they reduce friction and feel like a natural part of the workday. Start by using familiar tools to ensure employees can document and share knowledge within the platforms they already use. This lowers barriers to participation and makes it easier to integrate knowledge sharing into the flow of work.

Standardized templates offer a simple, structured way to capture lessons learned, best practices, and key insights. The templates themselves serve as a guide, prompting employees on what details to capture and where those details belong. This reduces the cognitive load and guesswork that often gets in the way of documenting knowledge.

To reinforce the habit, build knowledge capture tasks into process and project checklists, or use workflow triggers that remind employees when it is time to reflect and share. Until knowledge-sharing practices are fully embedded, timely prompts help ensure action happens at the right moment.

Some moments naturally lend themselves to knowledge capture, such as project closeouts, after client interactions, during onboarding, or following major decisions. These are high-value opportunities where small, structured contributions can have an outsized impact. Our blog on High Value Moments of Content Capture expands on this by showing how to identify the right moments and implement simple practices to capture knowledge effectively when it matters most.

Automate Where You Can

Leverage automated and AI-powered processes to further enhance knowledge capture by minimizing manual effort and making information more accessible with low-effort, intelligent solutions such as:

• Automated meeting transcription and indexing capture discussions with minimal effort, converting conversations into structured content that is searchable and readily available for reference.
• AI-powered recommendations proactively surface relevant documentation within collaboration tools, reducing the need for employees to search for critical information manually.
• Auto-classification of content streamlines knowledge organization by automatically tagging and categorizing information, ensuring documents and insights are consistently structured and easy to retrieve.
• AI-driven named entity recognition (NER) automatically extracts and tags key information in real-time, transforming unstructured content into easily searchable and actionable knowledge.

Closing Thoughts

When knowledge capture is built into existing workflows, rather than treated as a separate activity, staff do not have to choose between sharing what they know and doing their job. The goal is not perfection; it is progress through building consistent, low-effort habits.

Whether your organization is just starting to explore knowledge capture or is ready to scale existing practices with automation, EK can help. Our approach is practical and tailored–we will meet you where you are and co-design right-sized solutions that fit your current capacity and goals. Contact us to learn more.

The post Capture as You Work: Embedding Knowledge Capture in Daily Work appeared first on Enterprise Knowledge.

Organizations can prevent the unnecessary loss of essential knowledge by having structured conversations with key personnel before they leave their organization. This is one example of a tacit knowledge transfer activity, capturing knowledge that resides in people’s heads. These conversations, also known as knowledge transfer interviews, can enable smoother transitions between leaders, ensure continuity in organizational performance, and reduce the risk of repeating past mistakes or missteps. 

Capturing knowledge is the first step in making the most out of tacit/institutional knowledge activities. The next step is taking that knowledge and making it findable, reusable, and machine-readable with semantics to add context and/or content structure for ease of application to add real value to an organization. Retaining knowledge in a findable, action-oriented, and/or AI-ready format will transform knowledge transfer interview outcomes from interesting tidbits into valuable, distributable knowledge assets for companies to benefit from. 

In the following sections, this blog will break down the steps to conducting successful knowledge transfer interviews so that anyone can employ this technique at their organization and retain critical knowledge from experienced personnel. It will conclude with a discussion about how to enhance the knowledge gathered so it can be applied in the future. In all, conducting knowledge transfer interviews and subsequently transforming interview outcomes into a machine-readable, reusable format is a crucial strategy organizations should seek to employ. 

Preparing For The Interview: Identifying Critical Knowledge for Retention

1. Define and Prioritize Outcomes

To prepare for the interview, determine clear outcomes to obtain from the conversations with the interviewee, such as ensuring continuity in leadership or mitigating risks associated with leadership turnover. Reflect on what this knowledge capture will enable or who it will benefit, and prioritize outcomes accordingly (i.e., “Given this interviewee’s position, these are the top 3 pieces of information to walk away from this conversation with”). A clear outcome will ensure that interview sessions are efficient, focused, and targeted. While determining interview outcomes, plan for how and where interview takeaways (“aha” moments, lessons learned, preventable mistakes) will be captured so the knowledge gathered can be leveraged by the organization and others who can benefit.

2. Set Up an Interview Schedule

In most cases, multiple interviews will be necessary to achieve all desired interview outcomes. A particular topic might spark anecdotes or branch off into different topics. These segways can lead to the interviewee sharing unexpected but relevant and critical takeaways (it is amazing what stories will surface given the right amount of time!) that might not otherwise surface in a one-time session. Having multiple meetings helps account for the unexpected. Similarly, allotting enough time per session can be the difference between an uncomfortable interviewee and someone who is ready to open up. Plan multiple sessions for no less than 45 minutes and no longer than 60 minutes each, giving the interviewee enough time to get comfortable with the format and to start digging deeper into their experiences and expertise. If possible, consider recording the interview sessions to ensure the knowledge shared is accurately captured. Be sure to ask for the consent of your interviewee before recording.

3. Prepare A Guide For the Interviewee

An interview guide is a document that outlines the major topic areas–not the questions themselves–that the interview session will cover. Create an interview guide as part of the interview invitation to allow participants to think through the chosen topics and organize their thoughts ahead of the interview. A prepared interviewee can get to the most important nuggets of their knowledge more readily, making the most out of the limited time together. In addition to being a valuable resource for the interviewee, the practice of creating the guide will aid the interviewer in developing focused, on-topic interview questions.

4. Develop the Interview Questions

It is important to align interview questions with prioritized interview outcomes to direct the conversation and ensure all topics are covered. The aforementioned interview guide will aid in the development of focused questions. Even with interview outcomes as the underlying logic for question creation, developed questions should not be viewed as a strict script for the interviewer to follow. Instead, use the interview questions and outcomes as a guide, leaving room for adjustments and the ability to be flexible as the conversation flows. 

To get started developing interview questions, consider the following helpful categories.

• Contextual Background – Consider the interviewee’s current role and associated responsibilities. Seek to understand the context for their transition out of their current role. This background information will help set the stage for lessons learned and takeaways for future leaders in their role. 
  
• Knowledge Specific to their Role – Determine the expectations for their position. Ask about key mission successes and what factors could contribute to the success of their successor. Find out about the surprises the interviewee faced in their role or expectations about their role, frustrations they dealt with, pressing challenges, and how they overcame or addressed them. These strategies could directly apply to a successor and prevent repeated missteps or mistakes. Consider asking questions about how the organization could have made fuller use of the interviewee’s capabilities and expertise. Explore the culture of the organization and the ways it might affect how the role is executed (internal politics, etc.).
  
• Task-Specific Information – Focus the interviewee on describing a specific, demanding task. Have them break down the steps of the task and address factors such as complexity, time, criticality, and knowledge needed to execute successfully. Honing in on one activity can assist the interviewee in digging deeper into their time in the role, rather than providing generalized, high-level descriptions or takeaways.
  
• Summary and Wrap-Up – Wrap up the interview by inquiring about things the interviewee wished they had known before starting the job, and any advice they would offer to a future team. The end of the interview also provides a great opportunity to reflect on the interview thus far, potentially prompting insights that the interviewee had not initially surfaced. Ask the interviewee to summarize the three most important things about the role and anything else the interview may not have covered.
  

Conducting The Interview: Capturing High-Value Knowledge For Future Use

Once you have prepared for the interviews (set your interview intentions, created and passed along an interview guide to your interviewee, and developed interview questions), it is time to conduct the interview. When carrying out the interview, keep in mind the following advice:

1. Step into the interview with an open mind, leaving bias and opinions at the door.

2. Build trust by establishing confidentiality. At a later stage, key messages will be identified and sent back to the interviewee for their agreement to publish.

3. Strike a balance between free-ranging conversation and digging into real stories by looking for specific answers.

4. Be alert to the focus of the interviewee’s energy, focus, and interests, following their lead to areas of interest or concern.

5. Develop the interviewee’s train of thought by asking follow-up questions.

6. Ensure the focus is on the interviewee by refraining from telling stories or drawing conclusions based on what was said.

7. Request any artifacts mentioned in the interview and plan to follow up on obtaining them.

Try to hit on the topics that will be most valuable to others, using interview questions as a guide, rather than a strict script to stick to.

After The Interview: Codifying and Distributing the Knowledge

Knowledge transfer is not complete until the knowledge is made accessible to others. Once the interview sessions have concluded, review what has been said, send copies of potentially useful quotes to the interviewee for approval,  and look for key learnings to include in a final knowledge asset. A knowledge asset is a shared resource within an organization that captures and codifies insights, lessons learned, know-how, guidance, and other useful knowledge to enable staff to better conduct their work and make informed decisions. A great first step for creating the final knowledge asset would be compiling written documentation divided into sections based on subject matter or topic, with key takeaways or interview quotes. 
To make the knowledge asset even more meaningful and reusable, consider taking steps to prepare the knowledge asset for future applications (such as an input for AI or large language models). Here are some other content-related tips to get the most out of a final knowledge asset:

1. Utilize a centralized authoring platform to manage content in one place, leverage content types to standardize the final knowledge asset, and break content into semantically meaningful sections so they can stand on their own apart from the asset as a whole. 

2. Apply metadata tagging or a dynamic content model as part of a semantic layer, for example, to structure and semantically enrich the knowledge asset. 

3. Beware, even the prettiest reports get lost in people’s inboxes! Make a plan for circulating the final knowledge asset to those who will benefit from it and store it in an accessible, searchable, and centralized location where future knowledge transfer interview outcomes can also live.

Knowledge transfer interviews can also prompt additional actions like updates to Standard Operating Procedures (SOPs) and policies. These actions can embed valuable knowledge into the organization’s day-to-day business–a significant knowledge management accomplishment. 

In addition to the creation of a knowledge asset, potential takeaways resulting from transition interview distillation and analysis can fall into two categories: (1) what was effective/what could be changed, and (2) strategic improvement opportunities. 

Closing

Knowledge transfer interviews with departing senior leadership can be a highly effective element of succession planning. The knowledge of the transitioning team member has immense value, which is especially relevant in roles where the team member has accumulated a significant amount of knowledge and personal connections. This practical guide can be a starting place for planning interview sessions, rather than waiting until it is too late to capture these invaluable insights. Adding in content and semantic strategies to prepare interview takeaways for AI can be the difference between knowledge simply captured and knowledge utilized and leveraged to benefit the organization, individuals, or business functions in the future. Effective knowledge capture and transfer results in knowledge that is findable, reusable, and AI-ready.  

Want to learn more about how EK can support knowledge capture and transfer efforts and transform your knowledge assets to be AI-ready? Contact us!

The post A Practical Guide To Knowledge Transfer Interviews appeared first on Enterprise Knowledge.

Enterprise Knowledge CEO Zach Wahl again speaks with Barry Byrne, Global Head of Knowledge Management at Novartis and founder and organizer of the Knowledge Summit Dublin conference.

In this conversation, Zach and Barry discuss Barry’s growing knowledge management team at Novartis, how to measure KM success, and best practices for conducting (and scaling!) knowledge capture before valuable team members leave an organization. They also share what they’re most excited about at Knowledge Summit Dublin this year, especially the “salmon of knowledge.”

For more information on Knowledge Summit Dublin, check it out here!

Click ⁠here⁠ to listen to Barry’s first Knowledge Cast episode.

If you would like to be a guest on Knowledge Cast, contact Enterprise Knowledge for more information.

The post Knowledge Cast – Barry Byrne at Novartis (pt. 2) appeared first on Enterprise Knowledge.

In Greek mythology, the character Sysiphus is condemned to spend eternity pushing a boulder up a hill, only for the boulder to roll back down as soon as he nears the top. 

When organizations lack capability to manage and preserve their institutional knowledge, in the form of documented procedures, expertise, and know-how, their staff may experience a similar sentiment: doomed to repeat tasks that have already been accomplished, and solve for issues that have already been solved for by others. This needless repetition of work results in wasted time and resources, and represents a tangible opportunity cost: teams become unable to dedicate their attention and efforts to improving and innovating. 

Conversely, organizations that harness innovation can edge out advantages over their competitors. Research has found evidence that “perceived innovativeness improves the attractiveness of firms to consumers” (Keiningham et al., 2023). The Norwegian Innovation Index furthermore argues that increased innovation correlates to increased customer loyalty (NII, 2021). The Drucker Institute goes a step further, explaining how innovative companies “deftly use data and technology to ferret out evolving customer wants and needs—and respond by devising new products and ways to deliver them” (Wartzman & Tang, 2021). 

In this blog article, we’ll discuss the opportunity cost to innovation represented by the loss of institutional knowledge, and what can be done to solve this challenge. 

Poor Knowledge Management as a Barrier to Innovation

A few years ago, we had the opportunity to partner with a Silicon Valley firm. They initially sought our help to establish consistent approaches to share knowledge more effectively. This engagement started with an assessment of their current Knowledge Management (KM) maturity. As our discovery efforts progressed, we uncovered a fundamental challenge facing the organization: limited innovation due to immature KM practices.

Periodic reductions in their workforce had exacerbated these problems. With these layoffs, the cracks in their foundational knowledge management practices illuminated additional burdens. Remaining employees not only had to pick up where their departing colleagues left off, but in many cases had to recreate their work altogether because it wasn’t properly captured in the first place.

Looking closer at the root causes of hampered innovation, we found:

1. Institutional knowledge was not being consistently captured. Teams lacked established approaches to capture knowledge across the flow of day-to-day work, diverged in how they documented that knowledge, and often stored it in different knowledge bases. 
2. Knowledge bases were poorly curated and hard to navigate – instead employees became the most reliable source of information.
3. Staff had limited access and visibility into the work that others were doing. Knowledge bases were siloed across the organization, and staff were unable to search for things across multiple repositories.
4. Staff had limited opportunities for cross-functional collaboration and exchange of ideas. While the organization had several Employee Resource Groups (ERGs), these weren’t geared towards sharing expertise and strengthening shared business capabilities. 

Maximizing Knowledge Management Capabilities to Unlock Innovation

Established knowledge management practices within an organization contribute to both promoting innovation and removing barriers to it. We can summarize this into three overarching outcomes: 

Ability to reuse institutional knowledge. When organizations are able to retain and reuse institutional knowledge, their people can dedicate their efforts towards bringing new ideas to life, enhancing existing products and services, and improving processes. While there are no single practices nor tools that guarantee this outcome, there are several things that organizations can do to encourage knowledge capture and reuse: having designated places for different types of knowledge, making the most of high-value moments of knowledge capture by collecting key documentation and lessons learned on projects, and enabling staff to search and discover knowledge resources that have been produced in the past. At a large Sovereign Wealth Fund, we successfully incorporated these concepts and practices to deliver a Knowledge Portal. This solution and supporting practices provided a 360-degree view of critical business processes, enabling staff and executives to identify synergies and opportunities for collaboration in their work. 

Ability to cross-pollinate ideas and increase awareness across traditional organizational silos. This capability can be enabled through a diverse set of practices and tools. Traditionally, Communities of Practice (CoPs), have been a common tool for organizations to create spaces to nurture knowledge sharing. Other approaches can include Knowledge Cafes, such as the one we instituted at the Green Climate Fund (GCF), providing a repeatable opportunity to bring together people from all areas of the organization to discuss topics relevant to their work and encourage them to learn from each other. 

Ability to deploy advanced KM technologies to accelerate innovation. The proper application of advanced technologies can enable organizations to leverage its institutional knowledge as a springboard to unlock and accelerate business capabilities. For instance, a Semantic Layer can unlock knowledge that has previously been siloed within individual systems and organizational units, enabling executives to make faster decisions using more complete data available throughout the organization. Similarly, a semantic layer can enable individual contributors to gain broader awareness of expertise throughout the organization, creating pathways to collaboration. AI applications can further increase the organization’s capabilities to create and share insights, and take faster action. 

Closing

Innovation is a key business capability. All too often though, we find that innovation efforts are hampered because staff spend a lot of time fixing issues that have been fixed in the past rather than on ensuring that the organization is evolving to continually be able to meet its objectives. 

Enterprise Knowledge brings a holistic set of solutions that involve human-centered approaches and cutting edge technology to enable organizations to accelerate their innovation processes. Contact us at info@enterprise-knowledge.com if you would like assistance in maximizing the ability to leverage your institutional knowledge for innovation.

Institutional knowledge is the sum of experiences, skills, and knowledge resources available to an organization’s employees. It includes the insights, best practices, know-how, know-why, and know-who that enable teams to perform. This knowledge is the life blood of work happening in modern organizations. However, not all organizations are capable of preserving, maintaining, and mobilizing their institutional knowledge—much to their detriment. This blog is one in a series of articles exploring the costs of lost institutional knowledge and different approaches to overcoming challenges faced by organizations in being able to mobilize their knowledge resources. 

References

Keiningham, T., Aksoy, L., Buoye, A., Yan, A., Morgeson, F. V., Woodall, G., & Larivière, B. (2023). Customer perceptions of firm Innovativeness and Market Performance: A Nation-level, longitudinal, cross-industry examination. Journal of Service Research, 27(4), 475–489. doi:10.1177/10946705231220463

NII (2021), Technical Description: The Norwegian Innovation Index Research Model. Norwegian School of Economics (NHH). Available at: https://www.nhh.no/en/norwegian-innovation-index/about-nii/technical-description/

Wartzman, R., & Tang, K. (2021). Which industry excels at innovation? you’ll be surprised; consumer-staples companies stand out in the management top 250 ranking. New York, N.Y.: Dow Jones & Company Inc. Retrieved from https://www.proquest.com/blogs-podcasts-websites/which-industry-excels-at-innovation-youll-be/docview/2490681747/se-2

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This infographic showcases practical strategies we’ve implemented to foster knowledge sharing, ensuring critical expertise is captured, collaboration flourishes, and teams are equipped for long-term success.

Organizations can improve collaboration, streamline workflows, and strengthen problem-solving by creating an environment that supports and rewards knowledge sharing. Investing in knowledge sharing today ensures a smarter, more connected workforce ready to tackle future challenges. EK can help your organization improve collaboration and knowledge sharing, contact us to learn more.

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Indeed, effective AI solutions, much like other technologies, require quality inputs. AI needs data embedded with rich context derived from an organization’s institutional knowledge. Institutional knowledge is the collection of experiences, skills, and knowledge resources that are available to an organization. It includes the insights, best practices, know-how, know-why, and know-who that enable teams to perform. It not only resides in documentation, but it can be part of processes, and it lives in people’s heads. Extracting this institutional knowledge and injecting it into data and content being fed to technology systems is key to achieving Knowledge Intelligence (KI). One of the biggest gaps that we have observed is that this rich contextual knowledge is missing or inaccessible, and therefore AI deployments will not easily live up to their promises. 

Vast Deposits of Knowledge, but Limited Capabilities to Extract and Apply It

A while back we had the opportunity to work with a storied research institution. This institution has been around for over a century, working on cutting-edge research in multiple fields. They boast a monumental library with thousands (if not millions) of carefully produced and peer-reviewed manuscripts going back through their whole existence. However, when they tried to use AI to answer questions about their past experience, AI was unable to deliver the value that the organization and its researchers expected.

As we performed our discovery we noticed a couple of things that were working against our client: first, while they had a tremendous amount of content in their library, it was not optimized for leveraging as an input for AI or other advanced technologies. It lacked a significant amount of institutional knowledge, as evidenced by the absence of rich metadata and a consistent structure that allows AI and Large language Models (LLMs) to produce optimal answers. Second, not all the answers people sought from AI were captured as part of the final manuscripts that made it to the library. A significant amount of institutional knowledge remained constrained to the research team, inaccessible to AI in the first place: failures and lessons learned, relationships with external entities, project roles and responsibilities, know-why’s, and other critical knowledge were never deliberately captured.

Achieving Knowledge Intelligence (KI) to Improve AI Performance

As EK’s CEO wrote, there are three main practices that advance knowledge intelligence, which could be applied to organizations facing similar challenges in rolling out their AI solutions:

Expert Knowledge Capture & Transfer 

This refers to encoding expert knowledge and business context in an organization’s knowledge assets and tools, identifying high-value moments of knowledge creation and transfer, and establishing procedures to capture the key information needed to answer the questions AI seeks to provide. For our client in the previous example, this translated to standardizing approaches to project start-up and project closeout to make sure that knowledge was intentionally handed over and made available to the rest of the organization and its supporting systems. 

Real-World Application: At an international development bank, EK captured and embedded expert knowledge onto a knowledge graph and different repositories to enable a chatbot to deliver accurate and context-rich institutional knowledge to its stakeholders. 

Business Context Embedding 

Taking the previous practice one step further, this ensures that business context is embedded into content and other knowledge assets through consistent, structured metadata. This includes representing business, technical, and operational context so that it is understandable by AI and human users alike. It is important to leverage taxonomies to consistently describe this context. In the case of our client above, this included making sure to capture information about the duration and cost of their research projects, the people involved, clients and providers, and the different methodologies and techniques employed as part of the project. 

Real-World Application: At a global investment firm, we applied a custom generative AI solution to be able to develop a taxonomy to describe and classify risks so that they could enable data-driven decision-making. The use of generative AI not only reduced the level of effort required to classify the risks, since it took experts many hours to read and understand the source content, but it also increased the consistency in their classification.

Knowledge Extraction

This makes sure that AI and other solutions have access to rich knowledge resources through connections and aggregation. A semantic layer can represent an ideal tool to ensure that AI systems have knowledge from around the organization easily available. 

Real-World Application: For example, we recently assisted a large pharmaceutical company in extracting critical knowledge from thousands of its research documents so that researchers, compliance teams, and advanced semantic and AI tools could better ‘understand’ the company’s research activities, experiments and methods, and their products. 

It is important to note that these three practices also need to be grounded in clearly defined and prioritized use cases. The knowledge that is captured, embedded, and extracted by AI systems needs to be determined by actual business needs and aligned with business objectives. It may sound redundant to say, but in our experience we find that teams within organizations are often capturing knowledge that only serves their immediate needs, or capturing knowledge that they assume others need, if at all. 

Closing

Organizations are increasingly turning to AI to gain advantages over their competitors and unlock previously inaccessible capabilities. To truly take advantage of this, organizations need to make their institutional knowledge available to human and machine users alike. 

Enterprise Knowledge’s multidisciplinary team of experts helps clients across the globe maximize the effectiveness of their AI deployments through optimizing the data, content, and other knowledge resources at their disposal. If your organization needs assistance in these areas, you can reach us at info@enterprise-knowledge.com.

Institutional knowledge is the sum of experiences, skills, and knowledge resources available to an organization’s employees. It includes the insights, best practices, know-how, know-why, and know-who that enable teams to perform. This knowledge is the lifeblood of work happening in modern organizations. However, not all organizations are capable of preserving, maintaining, and mobilizing their institutional knowledge—much to their detriment. This blog is one in a series of articles exploring the costs of lost institutional knowledge and different approaches to overcoming challenges faced by organizations in being able to mobilize their knowledge resources. 

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Throughout this hour-long conversation, panelists outline the current challenges that organizations face as they embark on the implementation of AI solutions to exploit their institutional knowledge. Panelists also share real-life examples of the practices they are helping cultivate across organizations in various industries and settings to facilitate the success and adoption of novel technologies.

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If your organization is seeking innovative ways to promote Knowledge Management among your employees and stakeholders, EK is here to guide you. With extensive expertise in crafting and deploying strategies that enhance company culture and promote candid knowledge sharing, we are ready to provide you with tailored, operational insights. Hear directly from the experts on their KM experiences on EK’s Knowledge Cast guests about their KM experiences!

For a customized consultation and to learn more about how we can assist you, check out our KM Strategy & Design  and contact us for more information! 

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• Review what KM ‘is’ and ‘isn’t’
• Understand the value of KM and the benefits of engaging 
• Define and reflect on your “what’s in it for me?”  
• Share actionable ways you can participate in Knowledge Capture & Transfer 

Upon review of a comprehensive list of Knowledge Capture & Transfer techniques, Taylor noted that the common denominator is the act of storytelling and listening. In addition to providing a definition and best practices, she outlines the benefits: 

• Shares the organizational knowledge, wisdom, and insight often missed during more formalized knowledge sharing processes
• Offers opportunity for real-time dialogue (Q&A) 
• May be facilitated or occur organically
• Nurtures existing and budding expertise 
• Builds trust and interconnectivity between participants

Participants engaged in a live poll to determine the frequency in which they currently engage in telling and listening to stories in the workplace. Taylor facilitated a healthy dialogue around the importance of frequency, structure, span, and the individual outcomes for participating in knowledge capture and transfer techniques, even if it’s through the simple act of storytelling. 

The presentation concluded with 15 minutes for participant questions and the shared sentiment to “Tell Your Stories” and “Learn from Each Other.”

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