In this presentation, Galdamez and Cross will go into an in-depth explanation of Knowledge Portals, their value to organizations, the technical components that make up these solutions, lessons learned from their implementation across multiple clients in different industries, how and when to make the case to get started on a Knowledge Portal design and implementation effort, and how these solutions can become a catalyst for a knowledge transformation within organizations.

Find out more about the event and register at the conference website.

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The Challenge

In support of the KM strategy, the organization had identified several core needs that offered opportunities for better alignment with the full network and a more streamlined process for content and system management. They sought to more clearly communicate the value and purpose of two of their major platforms to the broader network: a content management system/intranet and a learning management system (LMS). The organization’s network members did not always understand the value of these systems, the purpose of each, and where they should go to find certain types of information. In addition, the organization wanted to update their platforms’ terminology and structure to be more intuitive to employees in the larger network, as they often use different nomenclature than the organization’s staff members.

To do so, the organization was now seeking a comprehensive information architecture (IA) strategy to: 

• Define purpose statements and strategy for the intranet and LMS, providing clarification for end users on the specific uses for each platform; 

• Develop an IA site map for the intranet to support discoverability, usability, and design of content within the site, integrating functional areas with related services; and

• Create a scalable IA plan that outlines the steps needed to implement and configure the defined intranet site map, ensuring it can effectively accommodate future growth and evolving user needs.

The Solution

EK worked with the organization to develop an IA strategy that provided clarification for users on where to find different information between the intranet and their LMS platform through System Purpose Statements and issued High-Level Information Architecture recommendations for the findability of, accessibility to, and navigation through information in the intranet. EK also worked with the organization to develop a taxonomy and metadata to support the proposed site map, clickable Site Prototypes to visualize what changes would look like, and an IA Plan for Scale to help the organization understand the next steps on a long-term implementation roadmap.

EK leveraged a top-down and bottom-up discovery approach during the first 4-6 weeks of the project to ensure that all recommendations were rooted in user-centered design. Before beginning work, EK conducted a persona refinement session to better understand the organization’s user groups, detailed walkthroughs of the systems and prioritized sites, and three focus groups with representatives from across the network. Once the initial recommendations were delivered, EK facilitated four validation sessions with end users and content owners to collect feedback and make updates accordingly.

The EK Difference

Throughout the project, EK emphasized user-focused research, engaging in constant review and iteration. EK incorporated changes based on discovery work and asynchronous feedback received via multiple facilitation tools such as visual boards. This iterative process ensured that the solutions developed were aligned with the organization’s user needs and expectations. By leveraging insights from the former KM Strategy engagement that EK conducted with the organization, the EK team crafted detailed system purpose statements and developed a scalable plan, ensuring a robust framework for future growth.

EK facilitated a crucial conversation with the organization’s IT and intranet stakeholders to ensure alignment and smooth implementation. To meet the organization’s needs, EK conducted comprehensive technology research focusing on its intranet functionality and its integration with existing systems. EK provided detailed recommendations for future technology considerations, ensuring the organization could make informed decisions as their needs evolved.

EK’s work with the core team was tailored to the organization’s current capabilities, providing a comprehensive how-to guide for validating prototypes through click testing, along with sharing sample questions for conducting these validation sessions. This guidance was shared to ensure the organization could continue to successfully validate prototypes and further work on this project independently.

The Results

As a result of this engagement, the organization received an IA site map for its intranet, which will significantly enhance discoverability, usability, and content design. Common nomenclature was suggested to improve findability for all users, accompanied by guidance on updating, managing, and maintaining IA governance to ensure long-term consistency.

Validated Purpose Statements for the LMS and Intranet were defined, clarifying the type of content that was appropriate for each system. The purpose statements were short vision statements for each system that differentiated it from the others and co-created with the organization’s team. These will help minimize user confusion about where to contribute and find information. Specific strategies were also provided to communicate the purpose of each system to users, fostering a common understanding. 

To support ease of navigation and findability, clickable prototypes were designed, showcasing the necessary framework and metadata aligned with a new IA. These interactive prototypes helped the organization visualize the suggested changes and encourage buy-in for the redesign of the intranet. By demonstrating clear pathways and organized content, the prototypes illustrate how the new IA will enhance the user’s experience. This tangible representation allows stakeholders to see the practical benefits and improvements firsthand, facilitating a smoother transition and greater support for the redesign initiative. 

Finally, a scalable plan was developed for implementing additional site design changes following the delivered site map. This roadmap included actionable steps across short-term, mid-term, and long-term timelines, addressing technical and content recommendations to improve efficiency and user experience. The plan ensures that the IA recommendations are effectively integrated, setting a solid foundation for ongoing improvement and scalability within the intranet and LMS.

 

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At EK, we’ve worked tirelessly over the last decade to ensure KM is understood for the business value it offers and considered in terms of practical solutions and measurable results. We’ve found that defining use cases is one of the best ways to help organizations understand this value, and moreover, prioritize what really matters for them, their mission, and their stakeholders.

There is a lot of writing about KM outcomes, or features, but there is a surprising dearth of writing regarding Knowledge Management Use Cases. In this article, I’ve captured the top ten use cases for KM Transformations. It’s important to note that these aren’t enabling features or software like search or online discussions, nor are they expected outcomes or results like improved findability, knowledge sharing, or knowledge retention. Rather, these are the actual use cases, the reasons why people do KM and what it actually means to the organization’s operations and people.

Of the top ten Knowledge Management use cases, six are what I’d consider “classics,” in that they’ve been present as the leading use cases for much of the short history of KM. The other four are the cool new ones, which are presently driving the industry and will be top organizational priorities for the near future as well.

The following six are the “classic” KM use cases. They hold as much value today, if not more, as they always have. The solutions and technologies we can apply against these use cases have changed over the years, though the use cases themselves remain largely the same.

Use Case #1: Knowledge Sharing and Retention

Perhaps no use case is more central to KM than Knowledge Sharing and Retention. Organizations have consistently sought to retain the knowledge and expertise held within the minds of their employees. This tacit knowledge walks out the door with employees if not properly shared with others or transferred into an explicit format that may be captured and managed. KM for Knowledge Sharing and Retention will counteract this “brain drain,” ensuring that information is shared, used, and reused, thereby improving the collective knowledge of the organization and saving countless hours that otherwise would have been spent re-creating lost knowledge (or worse yet, repeating mistakes already made).

Real World Example:

We recently led a “Knowledge Transfer Menu” effort with a global development bank, which was concerned with their increasing attrition at all levels, recognizing their expertise and associated experience was walking out the door. Given the wide number of potential knowledge transfer and sharing techniques, we worked with them to develop a menu of different techniques, allowing them to quickly test a selection of each, ranging in scale, type, and complexity (none, limited, or high technology) to determine what would be most natural to their unique business and employees—to facilitate knowledge sharing either one-to-one, one-to-many, or as a larger community. As a result, the organization adopted a subset of the Knowledge Transfer techniques to establish enterprise wide, and we helped them implement a simple knowledge base to ensure this new knowledge would be managed and easily findable. 

Use Case #2: Onboarding and Learning

To be fair, onboarding and learning could easily be considered two separate use cases, but both are solved by many of the same solutions and tend to produce similar outcomes. The Onboarding and Learning use cases are all about providing the employee with everything they need to perform, from day one of their job through the entire employee journey. This is much more than employee self-service. The Onboarding and Learning use cases cover the delivery of knowledge at the point of need, connecting learners with teachers or experts, and guiding a learner to develop and extend their knowledge. Effective Onboarding and Learning will result in employee satisfaction, which further leads to higher employee retention.

Real World Example:

A large public agency was seeking to transform from a traditional to modern learning environment. With a highly distributed workforce, the agency needed an innovative means of helping their employees of all levels and tenures connect and learn from each other. We designed and implemented an advanced learning platform for them that integrated all elements of their learning and performance ecosystem so that any employee could intuitively find and discover classes, self-serve learning content, experts, and cohorts with which to engage. The result was a single place for employees to craft their learning journey and managers to track and manage these journeys, while also capturing new knowledge through communities of practice and learning cohorts.

Use Case #3: Customer Support

The Customer Support use case covers call centers, help desks, and the associated knowledge bases responding agents use to deliver concise, complete, and consistent customer service. This use case addresses common customer complaints that they were “bounced around” from person to person, given inconsistent guidance, had to repeat themselves, and were stuck in “on hold” purgatory. Just as the Onboarding and Learning use case results in employee satisfaction and retention, the Customer Support use case results in customer satisfaction and retention. Moreover, appropriate customer support can yield higher revenues and faster deal close times, depending on the industry.

Real World Example:

One of the largest insurance companies in the United States found that nearly half of their help desk calls were unresolved, requiring escalation or follow-up. Not surprisingly, less than 30% of their customers were satisfied with overall customer support. We helped to reengineer their customer support systems by designing a new tagging structure and taxonomy for their knowledge base, implementing new content governance for their knowledge base content, and creating new incentives and measurements for their agents to identify and improve lower-end knowledge base content. As a result, their Tier 1 call resolution improved to nearly 80%, with similar trends for overall customer satisfaction.

Use Case #4: Self-Service

This use case connects to the two preceding, in that it may be either employee self-service or customer self-service. As the name states, this use case is creating easy and intuitive mechanisms to get the right people the information they need, without having to make a call, send an email, or otherwise rely on others. Generationally, end users are increasingly wanting to get their questions answered or complete their desired action via self-service. This use case delivers the right knowledge, information, and data at the point of need, and when delivered properly, does so quickly and intuitively. Self-service can be a major cost saver for an organization, while also improving user satisfaction and delivering a more complete and more customized “answer.”

Real World Example:

One of the world’s largest employers recognized their host of employees was struggling to get fast answers to simple HR and payroll questions. As part of a 360-Degree Employee Satisfaction effort, we helped them redesign their employee self-service system, including the ability for employees to crowd-source questions and answers to a variety of questions, up-vote ideas and priorities for management, and independently track and complete simple changes to their benefits and employee data.

Use Case #5: Idea Generation and Innovation

In an increasingly distributed world, the opportunity for water cooler meetings and moments of professional kismet are waning. The Idea Generation and Innovation use case counteracts those trends, creating KM-driven opportunities to share knowledge, ideas, problems, and challenges, invoking the collective expertise of individuals to help. This use case isn’t just about coming up with the next “Flamin’ Hot Cheetos” scale of idea, but also about day-to-day problem solving, small ideas, and incremental wins that can collectively make a big difference for an organization and its performance.

Real World Example:

A leading software company dramatically shifted to a largely remote work environment following the pandemic. However, they recognized that this sudden and permanent shift would eliminate many of the natural opportunities for the “water cooler talk,” moments of happenstance collaboration, and whiteboard innovation that had previously helped them to thrive. We helped them envision and execute a complete menu of techniques to help them transition to remote work while continuing to collaborate and innovate. This included new traditions like virtual brown bags and topic-based online meetups, new tools for synchronous and asynchronous collaboration, and new processes to capture knowledge at the point of generation and deliver it at the point of need.

Use Case #6: Regulatory Compliance and Preparedness

This use case isn’t about addressing the lack of knowledge, information, or data within an organization; rather, it’s about addressing the proliferation of bad knowledge, information, and data. Many organizations have a poor handle on their content, maintaining years of old, obsolete, and incorrect legacy content, which exposes them to undue risk. For some organizations, this presents a regulatory risk, which if unaddressed can result in millions of dollars of fines, lawsuits, and accidents. Successfully implementing this use case not only addresses these types of risks and costs, but it also vastly improves the findability and manageability of content by removing all the potential wrong answers and dead ends.

Real World Example:

During an audit, a global manufacturing company in a highly regulated industry identified a major risk to their operations, finding scores of obsolete, outdated, and incorrect information hosted on their servers. We helped them engineer a content audit and cleanup process to confront this risk, which included a blend of system analytics, automated semantic analysis, and targeted expert reviews to eliminate their “bad” content and also enhance and promote “good” content to new systems so that it could be better leveraged. This process not only removed or archived over 80% of their total content, it also highlighted hidden gems of lessons learned and thought pieces that helped the organization maintain their expertise.

The final four KM use cases are the cool new ones, which have gained great traction only recently and promise high value and organizational prioritization for years to come. These are the ones that are getting the largest budgets and most attention today.

Use Case #7: Getting the Most out of a Digital Transformation

The previous decade was marked by massive investments in digital transformations, with organizations seeking to fundamentally update their processes and systems with streamlined technologies and more “online” modes of work. Millions were invested in these transformations, but few organizations reported the results they were expecting. The missing piece for many was KM. Though systems and processes had been updated, insufficient attention was paid to the core content and means of harnessing organizational expertise. This use case focuses on ameliorating those omissions by helping the state of an organization’s knowledge, information, and data “catch up” with the digital transformation.

Real World Example:

A global pharmaceutical company invested millions of dollars in a digital transformation—modernizing, consolidating, and integrating their assorted document, content, and data management systems and implementing a leading enterprise search product. As the multi-year transformation was well underway, however, the organization was not realizing the return on investment they’d anticipated. We conducted an assessment of the organization and helped them pinpoint the critical points of knowledge, information, and data management that would help them realize true business value. These included design and implementation of taxonomy/ontology with auto-tagging of content, improved knowledge capture workflows, design and implementation of search hit types, and a knowledge retention measurement plan. Within six months, they were capturing the returns they’d initially expected from the overall digital transformation.

Use Case #8: Measurement and Efficacy

Keying off of previous use cases, with millions invested in digital transformations, more advanced delivery systems and interfaces, and greater customization, organizations are asking whether they’re getting the promised returns and desired impacts to their business. Though always an important question for a business to answer, in the face of a recession, this becomes all the more critical. This use case seeks to answer that question by delivering detailed insights into how people are using an organization’s content and what they’re doing as a result. Are people learning as they should? Are they taking the appropriate actions as a result? This use case delivers a comprehensive view not just into usage, but impacts, allowing organizations to make the right decisions as a result.

Real World Example:

A global financial organization had invested heavily in the creation of an array of new multichannel learning and performance content, as well as improved analytics to track its usage. They had the new content and data, but they lacked the insights to understand it and make decisions as a result of it. We worked with them to go beyond measurement of usage to measurement of efficacy, plotting out the desired impacts and outcomes of each learning topic, then creating measures of performance for each. In cases where the outcomes weren’t reached, we developed processes to engage internal stakeholders and external subject matter experts to help address the underlying issues with the learning content, creating a consistent and positive learning loop to help the organization’s learning environment evolve. We also identified opportunities to use this same process to identify gaps in organizational knowledge and leveraged the same approach to proactively fill those gaps.

Use Case #9: Content Assembly and Customization

The Content Assembly and Customization use case addresses one of the long-standing issues with many organizations’ content. Too frequently, organizations that have focused on systems and processes have overlooked the reengineering of their content to be more consistent, readable, and customized to the user. This use case focuses on deconstructing content into more structured components that may then be reassembled in more intuitive and personalized ways. There are many potential applications and audiences for this, but the binding concept is that every individual will get just that which applies to them in a clear and concise way.

Real World Example:

A big box retailer with highly complex logistics and a massive fluctuation of employees was constantly struggling to keep key documents like employee handbooks, required safety documents, learning materials, and store-specific guidelines up to date. We worked with the organization to deconstruct this content and then build a content assembly engine to automatically create customized documents for each individual based on their home store, geography, role, and dozens of other factors. This drastically reduced human error and administrative burden while delivering a more customized experience to the individual stakeholders.

Use Case #10: Powering AI

The hottest new use case is no doubt around AI. Most every conversation seems to involve an organization’s vision for their own Chat GPT, bespoke large language models, and organizational Artificial Intelligence. The questions tend to be the same in many of these organizations. How do we make AI happen? This use case is the enabler for organizational AI, creating the structured content, knowledge maps and ontologies, and integrated systems that will truly make AI real for these organizations in their production environments across the enterprise.

Real World Example:

For many years, we’ve worked with a global development bank to progress towards Knowledge Management maturity. Over the years, we helped them clean up their content, design and apply an enterprise taxonomy, improve their knowledge capture techniques (for consistency and completeness), and implement more consistent information architectures. Each of these KM initiatives yielded its own value for the organization, but the culmination of the work was the creation of a knowledge graph powered by an ontology and connected to the key content and data stores across 12 different applications. This solution allowed them to realize an array of Artificial Intelligence capabilities, including an intelligent chatbot, a recommendation engine, and an application to identify at-risk knowledge topics in the organization, triggering prioritized knowledge transfer and capture techniques.

At this moment, the organizational understanding of KM continues to increase, executives show a growing willingness to support and invest in it, and the associated technologies continue to progress to help KM Transformations become a reality. These use cases can all be faster, easier, better, and more tangible than in the past, making the overall opportunity for meaningful KM Transformations as high as it has ever been.

For more details and use cases visit Enterprise Knowledge.

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One way we do this at EK is by defining a series of pilots, which are limited-scope efforts, focused on quickly demonstrating value to organizational stakeholders by solving targeted issues and exploring new technologies and practices. Each pilot is intended to validate that the KM Strategy approach we’ve developed will work for the organization and to determine how that pilot can be scaled. These pilots also serve to drive incremental change and excitement for “what could be.” This exercise in defining pilots begs the question though, “How do we know where to get started?” 

Here are 6 questions that help us determine the best approach for an organization to start their KM transformation. 

1. Where is the low-hanging fruit?

A commonly used metaphor, what I mean by “low-hanging fruit” is that we’re looking to identify the simplest activity to implement within an organization that will produce immediate, tangible value. What this means from a practical standpoint  is that the pilot has a low-level of complexity. There are a few ways to judge this:

• The pilot is able to be conducted using solely the internal expertise and experience of the organization’s staff. In this scenario, no external subject matter expertise or consultancy is required. The organization can get started today with the skills and competencies they have in house.
• The pilot involves one department (or business area) or up to two closely-aligned departments. Scoping the pilot to one or two departments allows an organization to test a methodology or process within a specific function before it’s adapted and scaled for the enterprise’s benefit. 
• The pilot is building off and enhancing a pre-existing technology or practice. We’re always looking for examples of “good KM” when we’re conducting our Current State Assessments because we know that there are strengths that can be leveraged. Some of our pilots do just that – they improve something that is already in place that has the potential to be transformative if modified or if the right incentives are in place to increase adoption.

2. What does the organization care about, and what would get them excited?

At the onset of a KM Strategy project, we ask staff at different levels of the organization, “If you had easier access to the people and information you need to effectively execute your daily tasks and responsibilities, what would that mean for you? How would that help you be successful?” Ultimately, we’re trying to understand the downstream effects and business value of KM for the organization. 

In every organization, the downstream impacts and business value of KM can vary depending on the teams and departments whose insights are being solicited. For those in Sales roles, for example, it could be access to accurate, current, and competitive market information that is going to help them pursue and close sales deals. For those in Customer Service positions, it could be having the ability to find customer and account information to provide the right level of service to customers based on what the organization has done for them in the past. For other organizations, it’s ensuring continuity of operations by ensuring that knowledge does not walk out the door when their employees leave or retire. 

It’s these value statements that help us think through what pilots can serve to further these goals:

• Does the organization need a pilot around content clean-up to ensure that when people do come across information, they have confidence that it’s up-to-date and accurate, and they can use it to take action or make a decision?
• Could we come up with a pilot that helps to define what customer-facing staff would want to see when searching for past information on customers and accounts? 
• Do we need to consider a pilot around experimenting with knowledge transfer techniques to support colleagues in sharing what they know throughout their tenure with an organization?

My colleague, Mary Little, discusses the importance of aligning KM with your organization’s strategic goals and this can start as early as the pilot definition phase. 

3. Who is interested in being an early adopter of KM, or is equipped with the capabilities and resources to support a pilot immediately?

If we’re conducting an KM Strategy project at the enterprise level, we always ask to speak with staff who represent different functions and departments with the organization. We do this for a variety of reasons, one being that it helps us understand those pockets within the organization that are acutely experiencing a KM challenge and who are eager to see change. This approach not only helps us brainstorm options for what recommendations and pilots we will define for the organization, but it also helps us identify who might want to be a part of a pilot. Identifying early adopters in the form of a department, group, or team helps the organization drive interest in and momentum for its KM initiatives. This is critical for the long-term adoption and sustainability of a holistic KM program, which will be focused on solving different challenges over time and necessitate changes in how people work. 

Another angle to consider is whether there is a department or group who has the capabilities and resources needed to support a pilot immediately. Part of this involves exploring what skill sets will be needed to perform associated responsibilities and whether the organization can draw on current employees with specific expertise to support the implementation of a pilot. Conversely, it is also important to gain an understanding of an organization’s internal processes around approving funding for projects. It can be beneficial to have these conversations to determine whether departments have their own pool of funding to use at their discretion or whether projects have to go through a more formal review process that happens at different intervals throughout the year.  

4. Is there an existing organizational initiative that we can align a KM pilot to?

In developing a KM Strategy, we look at five different dimensions within an organization: People, Process, Content, Culture, and Technology. Because we’re looking across these dimensions, we often hear about other initiatives that are going on in the organization. We love to hear about these because they can be tangential to what we’re doing and there are opportunities for alignment. In the past, these tangential initiatives have taken the form of:

• Data inventory and governance efforts.
• Enterprise search projects.
• Process improvement efforts.
• Initiatives to consolidate content management or customer relationship management systems.  
• Records management implementations.
• Selection and implementation of a learning management system. 
• Sunsetting legacy knowledge repositories and related content migration efforts.

Just as it can be easier to secure support for a pilot if it’s tied to an organization’s strategic objective, it can be easier to secure support for a pilot if you can communicate how it will support the success of another initiative. By aligning a KM pilot to another relevant initiative, you’re helping to ensure the maximal effectiveness of both.

5. How many people will the proposed pilot impact?

In considering what pilots we recommend prioritizing as part of a KM transformation, we’re thinking about what is going to drive the biggest return on investment. Part of that has to do with how many people will be affected by the proposed change. Early on in our KM Strategy engagements, we request an overview of our client’s organizational structure, their departments, and which departments have interdependencies. This gives us a sense of how big the departments are in relation to each other and which work closely with one another. In return, as we conduct interviews, focus groups, and workshops, we start to understand the degree to which staff are experiencing similar KM challenges regardless of where they sit in the organization, and which KM challenges are most pressing. Armed with this information, we can think through how to prioritize our pilots based on how many people it will impact positively. These pilots often end up being holistic efforts that will benefit all departments over time, as they are scaled. 

6. How foundational is the pilot?

When developing pilots and recommendations, we are also outlining a roadmap across which these can take place. Our roadmaps span different timeframes based on an organization’s needs and resources, but they can include both “foundational” and “advanced” pilots. A foundational pilot is one that helps establish the success of subsequent efforts in the roadmap. This could include, for example, developing metrics to monitor the success of KM pilots, enable alignment across different initiatives, and allow the organization to make data-driving decisions on how to adapt its KM Strategy, as needed. We may also include, if the organization is ready, advanced pilots that lay the groundwork for AI applications – for example, developing a knowledge graph to connect and show meaningful relationships between data regardless of where it is located. While the advanced pilots can sometimes be more “exciting” work, we want to ensure an organization is laying the foundation to explore advanced AI capabilities in the right way and in a way that will be scalable and sustainable. Prioritizing foundational pilots on your organization’s KM Strategy Roadmap is essential to building that infrastructure.

Closing

Regardless of how big your company is, how many millions of documents your organization might maintain, or how widely disparate the processes are between staff to capture critical information, we know it can be overwhelming to contemplate the question “Where do we start?” But it doesn’t have to be. We’re here to help! Contact Us at Enterprise Knowledge to navigate this ambiguity and jump start your KM transformation.  

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