We recently celebrated the ten year anniversary of Enterprise Knowledge (EK). As founders, this was very special for both Zach and I. I’ve been reflecting on the amazing people, clients, and projects we have been involved with and pondering all we’ve accomplished in a short ten years. I could spend hours talking about the incredible people that work for, and have worked at, EK (the EKers), and nearly the same amount of time talking about our wonderful clients. These EKers and our clients have partnered together to create a number of cutting-edge and impactful solutions, many of which offer great insight into the possibilities and future of knowledge management. In the spirit of Knowledge Sharing, I’d like to share some of these solutions with each of you.

Multichannel Customized Content Management

I always dreamed of building a content management system (CMS) that looked and worked like Google Docs for the authors. This tool would also componentize content automatically and enable authors to publish content in multiple formats. About four years ago, we got a chance to build this dream solution. 

Our client needed to make sure that critical information gathered at all hours of the day could be collaboratively captured and shared with key employees around the world. In addition, they wanted to store the information so that they could analyze trends about each of the alerts in their publications. For example, they might want to see all alerts about a specific subject so that they could identify problems or patterns of behavior that might be missed over time. Groups of people authored this content, so a collaborative editing solution like Google Docs was crucial.

The EK team developed a content management solution using a combination of open-source products like Drupal, ProseMirror, MongoDB, and MySQL. We used Drupal as the CMS for our clients to administer users, manage taxonomies, and add and publish content. ProseMirror was the collaborative editing library that allowed multiple users to edit a document at the same time. Each piece of content looked like a regular Word document with a title, headings, and bulleted lists; this was done without fields or forms to give the authors the feel of actually working in MS Word. Behind the scenes, the content was saved as JSON files in MongoDB so that the title, headers, bulleted items, and any metadata were stored separately and could be queried as needed. Finally, we developed a custom publishing process that combined the content into different formats and then delivered them across 10 different mediums.

The Result

Our client now has a tool that allows their teams to collaboratively develop content immediately and deliver it to people around the world in seconds. In addition, they have a repository of the structured content they have collected that can be queried to identify trends or related information.

AI for the Enterprise

This next solution was developed six years ago and is still in use today. It was one of the first Knowledge Graph solutions that we developed for an entire organization, cementing us as a global leader in designing and implementing Knowledge Graphs at scale.

Our client invests in and manages projects all over the world. As such, they have experts in different countries and different types of projects. These experts found that they were regularly being tripped up by the things they did not know, and they needed a tool that would proactively provide news about the country they were planning a project in, or updates on solutions similar to the one(s) they were discussing. A standard search solution would not solve this problem, because these experts often did not know that they even needed to search for information. Our client needed a solution that pushed the right information to people at the right time, even if they did not ask for it directly.

Our solution to their problem was a semantic hub based on a Knowledge Graph. This Knowledge Graph stored metadata about news and projects from over 12 different systems, and captured information about the areas of interest or responsibilities of all of their employees. The semantic hub used this information to automatically push content to people based on what they needed to know.

The first implementation of the semantic hub was integrated in Microsoft Exchange. As people scheduled meetings, they could add the semantic hub (or “brain”) as an invitee. The semantic hub read the meeting invitation and the people in it to select content that was relevant to the topic being discussed, which was then sent to the meeting organizer in advance of the meeting so that they were prepared with the latest information about the country or solution they were discussing.

This recommendation service was then used to power a chatbot, enhance search, and provide regular mailings on topics of interest to employees within the organization. This is a key point: a well-designed Knowledge Graph can be applied again and again to power different solutions.

The Result

The Semantic Hub gave our client a way to push the right information to people at the right time. As a result, our client’s people are more prepared and productive in their conversations with one another and with the people their organization works with.

A True Data Fabric

The next story is a more recent one, completed in the last few years. What I like about this one is that it solves some of the most challenging issues in business intelligence. KM has historically focused on documents and other unstructured or semi-structured information; however, structured data, often stored in data warehouses and data lakes, is just as important a source of knowledge for modern workers.

Our client had a 300-petabyte data lake with data sets from across 10 different business units. The data was available, but the data lake was so large that it was difficult for business users to find the information they needed. In addition, there were constant challenges with data quality. The size and complexity of this repository and the size of the data lake made it so that a data catalog could not easily solve all of these problems. We worked with our client to design an ontology for the key information assets in the data lake, and instantiated it as a Knowledge Graph (a data fabric) that mapped the critical entities of the organization to the data elements in each data set across the lake. 

For example, if the business users wanted to know when a customer started doing business with them, they had to search across each of the different data sets that represented each type of account that was opened. The name of the data element and the structure of each of these open dates were all different. This is a common problem that many of our data clients deal with. The Knowledge Graph solved this by mapping the entity Account Open Date to each of the tables and fields where that information was stored. Business users could now ask questions about the account open date to the Knowledge Graph and it would query all of the relevant tables automatically. As tables were added or changed, the mapping was updated and the user was able to ask business questions without having to know the structure of the data.

The amazing thing about this solution is not the technology we developed: the idea of using a Knowledge Graph as the middle layer between users and the data they need is one that Gartner has been pushing for a while. The amazing part of this solution is the impact it had on both business and IT. Business users could ask for information in a sensible fashion without having to rely on complex SQL statements or any deep knowledge of the data sets that they were querying.

The Result

Our client developed an ontology that not only maps key data entities to all of the data in their data lake, but also ensures that new data meets predetermined quality standards. As new data sets are submitted to the data lake, the data elements are mapped to the appropriate entities and the data is checked for compliance with the expected data values defined in the graph. Our client now has a higher-quality and more accessible data lake for their business users.

Knowledge Portal (A.K.A. Enterprise 360)

The ability to pull data of any structure from multiple systems and display it in a single screen has been a goal of every forward-thinking CIO that I have ever worked with. Knowledge Graphs finally give us the ability to do this by mapping information assets from across the enterprise to the entities that matter to the business. Customer 360 has been a hot term for a few years now, but Knowledge Portals, powered by graphs, allow business users to see more than just customers: they can see consolidated data about their people, products, projects, and anything of importance to running the business. We recently implemented a Knowledge Portal that serves as an Enterprise 360 solution for a large sovereign wealth fund.

Information about the deals our client was investigating was spread across 8 different systems, and investment information was spread across 12 systems. They also had very little ability to see information about what deals and investments their employees worked on, the companies they work with, the people in those companies, and the banks they worked alongside. We proposed a Knowledge Portal and have been implementing it for just over a year now.

The graph behind the portal maps key data to the most important pieces of information wherever that information resides. This information is then pulled together as part of a nightly feed, or dynamically, so that their employees can see all of the most important information about their deals and investments in a single application. We are working on future releases that will provide information about each employee and the deals and investments that they worked on, as well as information about the banks, companies, and executives that deals and investments were made with. When completed, our client will have a single place to see the information they need for all of their most important decisions: an Enterprise 360 knowledge system.

The Result

Our client has called this new system their most important investment in KM. They have rolled it out to all of the investors in their organization and are now providing rewards to the people that share the most information with one another. Our client has also started talking to others about the value this Knowledge Portal presents for all of their employees. This is a KM solution that impacts every area of their business, allowing people to make more informed decisions.

Enterprise-Wide Learning Ecosystem

The way in which people work and engage with their employers has changed a lot in the past few years. Between the hybrid working model and the impacts of the Great Resignation, companies are recognizing the critical importance of training. An effective learning strategy involves more than a series of courses, either taken one time or annually as part of a certification. The best organizations invest in learning solutions that provide multiple methods for learning, delivering knowledge and performance support at the point of need. We had a chance to develop one of these next-generation learning portals for one of our clients.

Our client was a federal agency with people working in remote areas around the country. Their employees are highly independent and passionate about their work, and our client needed a better way to disseminate information, improve collaboration, and lower the costs associated with in-person training. We designed, developed, and helped roll out a new kind of learning portal. This portal offered many different ways to learn, including:

• Structured learning in the form of online classes and links to in-person classes;
• Access to experts;
• Job aids, instructional videos, and interactive learning activities; and
• Communities of practice and discussion forums.

The new learning portal was built using common open-source tools like WordPress and Elasticsearch. The portal enables employees to learn from the organization and their peers through a front page with a Google-like search bar, making the act of finding information quick and easy. Users also have the option to navigate through topics of interest or discussion forums where employees can share thoughts with one another. We developed taxonomies to categorize learning content and make them more intuitively findable at the point of need.

In addition to making learning content more findable, the learning portal’s features enabled a modernized learning strategy, blending multiple facets of an andragogically-sound learning and performance ecosystem. The discussion forums included gamification features such as user ratings of documents and content shared in the communities. Users who frequently shared highly-rated content (as evaluated by their peers) earned badges which were incorporated into the user interface of the learning portal, rewarding users for their contributions. 

The agency’s learning technology stack already included a Learning Management System (LMS), existing structured learning from which was made findable within the context of the additional, diverse learning content. However, the learning portal itself became the content repository for the informal and social learning resources such as job aids and communities of practice. To track informal learning activity such as learners commenting in communities of practice or watching instructional videos, the learning portal also included a Learning Records Store (LRS) to store xAPI activity statements. This enabled powerful dashboards so that trainers and learners alike could evaluate the impact of informal and social learning on workplace performance.

The Result

This learning portal gave our client a new way to share information across their entire workforce. It was an immediate success, with users actively engaging in the portal and in the discussion forums where they could share their experiences with one another. This new tool lowered the overall cost of training by prioritizing in-person structured learning for the most critical workplace tasks and enabling asynchronous learning options for performance support of tasks that were less business critical. It was so successful, our client decided to make parts of the portal public so that volunteers and partner agencies could also access the learning content developed and shared by their employees.

Conclusion

Writing this article reminds me how much KM has changed over the years. Connecting the historically disparate fields of KM, information management, data management, and IT, we are now able to use cutting-edge technology solutions to break down information silos and deliver the right information to the right people at the right time. The impact of these systems is greater than ever before: these types of solutions are moving KM from a small back office service to an enterprise solution that allows our clients to be leaders in their industries. With new advancements in AI like ChatGPT and enhanced machine learning, I am more excited than ever to see what our team and our clients will come up with as the next generation of KM enablers.

The post EK at Ten: Looking Back on Our Greatest Knowledge Management Solutions appeared first on Enterprise Knowledge.

In conversation with Zach, Christianne discusses the role of technology for contact management and expertise finding, Getty’s enterprise Knowledge Management strategy, and the importance of setting KM goals.

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

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In conversation with Zach, Zsolt discusses the difference between memorizing and understanding information, draws comparisons between training and the middle finger, and provides his insight into how teams can combine learning and KM to collaborate more effectively.

Note: The views expressed by guests are their own, and do not necessarily reflect the views of their organization.

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

The post Knowledge Cast – Zsolt Olah of Amazon appeared first on Enterprise Knowledge.

It is helpful to revisit the definition from the first part of this series for explicit knowledge before continuing the conversation:

Knowledge that has been made visible by recording it, or embedding it, into a variety of formats: written documents, multimedia, and the design of processes, procedures, or tools. Explicit knowledge can be an overarching term to refer to ‘content’ and ‘information.’

Why is Capturing Explicit Knowledge Challenging?

Among the many challenges that organizations face in properly capturing their explicit knowledge are:

• Current repositories lack a clear purpose statement, and therefore staff use whatever they find most convenient for themselves or their team, making collaboration and coordination across teams harder.
• Staff rely on email inboxes as personal repositories, making the correct and latest versions of documents difficult to track down.
• Knowledge is not structured or tagged in a consistent, predictable way, so people spend undue effort making sense of what they find.
• Knowledge is distributed across many systems, and there is neither a centralized point of access to it nor a complete view of all the relevant content that a user may need.

A Holistic Approach to Capturing and Transferring Explicit Knowledge

At EK, we leverage our People-Process-Content-Culture-Technology framework to approach challenges from a holistic perspective. Below, I share best practices for capturing and transferring explicit knowledge based on this framework.

People

Individuals need training and guidance for storing their knowledge in the correct place and in the appropriate format. As knowledge managers, it is up to us to help teams understand the value of consistently managing their knowledge and helping them adopt best practices. A common issue we come across is that individuals will use their email inboxes as their personal knowledge base, locking away and burying helpful conversations and documents. This is usually because they don’t know any better. Once people are offered guidance and compelling reasons to move their documents to a document management system and their conversations to a platform like Slack or Teams, then this knowledge becomes available to more people within their organization.

Process

Knowledge capture should be embedded as much as possible in the everyday business processes that teams engage in. When helping our clients articulate their KM strategy, their most common request is “don’t make me do extra work.” Knowledge management should not be something extra that employees must do. If we are able to capture knowledge as part of people’s natural ways of working, then we will engender greater adoption. For instance, leveraging meaningful metadata default values and auto-tagging features in taxonomy management systems will minimize the need for users to manually assign metadata to their documents.

Content

Much of the content in an organization is unstructured, which means that it lacks the metadata to describe and categorize it, making it more difficult to identify and manage. When knowledge is captured, it should be structured and categorized in a way that will make it easier to find and use. Developing a taxonomy to consistently tag explicit knowledge goes a long way in making knowledge more usable and findable, as well as laying the foundation for more advanced knowledge management capabilities in the future. Creating navigational structures and information architecture that is intuitive will also help people within your organization browse and sort through volumes of documents more quickly.

Culture

As mentioned above, people often develop bad habits in capturing and managing their knowledge. As part of organizational culture, leadership should not only establish incentives for people to capture their knowledge correctly, they should also set expectations and accountabilities for doing so. Furthermore, there should also be indicators to assess the extent to which teams and individuals are adhering to best practices, enabling the organization to adapt approaches if they aren’t.

Technology

Technology again becomes a key enabler for knowledge capture. Knowledge repositories should be searchable, support taxonomies, and offer features that would make it easy for individuals to ‘do the right thing.’ Organizations will want to consider introducing technologies that support KM into their technology stack if they don’t already have them, such as content and document management systems, taxonomy management, and in more advanced cases, knowledge graphs to provide that rich contextual view of a piece of knowledge.

Closing

Organizations create volumes of explicit knowledge as part of their daily activities. Capturing it, storing it, and then sharing it in a way that makes work easy for your teams can be very challenging. However, we are experts in providing organizations with tailored, holistic approaches to managing their explicit knowledge. If your organization needs help wrangling their knowledge, please contact us.

The post Knowledge Capture and Transfer Series – Part 3: Capturing Explicit Knowledge appeared first on Enterprise Knowledge.

• A significant cohort of long-tenured employees reaching retirement age.
• High turnover and the constant re-learning that occurs with each new generation of employees prevents the organization from being able to grow and scale the way they want to.
• A key team member is either absent or unavailable, and a critical initiative subsequently fails.

Enterprise Knowledge is often brought in at this stage. However, it is important for knowledge managers to help their organizations be more proactive about capturing and disseminating tacit knowledge before it’s too late. This is your institutional knowledge—the knowledge that your staff have of your operations, processes, products, and services. Knowledge that if someone left, and it was not documented, could interrupt operational effectiveness. Before continuing the conversation, it is helpful to revisit the definition for tacit knowledge from the first part of this blog series:

Tacit knowledge is highly internalized knowledge that is difficult to articulate, record, and disseminate. It can only be acquired through experience in a relevant context.

Why is Capturing Tacit Knowledge Challenging?

If we think about tacit knowledge, its very nature makes it difficult to capture:

• It resides in people’s heads.
• Experts must volunteer the knowledge they hold.
• Even if experts are willing to share their knowledge, an expert may not be able (and it may not be practical) to elicit every single detail and context of what they know.
• People’s memories are not perfect, and if someone is trying to convey something about an activity or event that happened even mere weeks ago, they may not fully remember it.

A Holistic Approach to Capturing and Transferring Tacit Knowledge

At EK, we leverage our People-Process-Content-Culture-Technology framework to approach challenges from a holistic perspective. Below, I share best practices for capturing and transferring tacit knowledge based on this framework.

People

Because tacit knowledge resides in people’s heads, this factor of our framework is critical to consider. To capture their knowledge, you have to make sure that you first have the right experts and that you are asking questions that will elicit the outcomes you seek. Especially when seeking knowledge related to complex activities, it is important to obtain multiple perspectives in order to get a more complete view of the desired knowledge. For example, you are facilitating a retrospective on a large international conference; to get a better understanding of what went well and what can be improved, you would need to include more than just participants. You may want to talk to representatives from the event sponsors, speakers and panelists, supporting staff and volunteers, suppliers, and so on.

Process

From a Process perspective, we have to make sure that we are capturing knowledge at the right time. We have written before about high value moments of knowledge capture. These are generally inflection points along organizational activities, like the end of a project, the realization of a milestone, a colleague’s departure, the close of a fiscal year, and so on. It is important to strike a balance between capturing knowledge while it is still fresh, while also giving people enough time to ‘digest’ or process what they may have experienced so that they can form additional insights.

Content

Content is the result of capturing and codifying an organization’s knowledge. It is important that content is structured in such a way that prompts employees to capture the relevant and important ‘knowledge nuggets’ that we seek. For instance, if we are looking for lessons learned after a project, we shouldn’t just offer employees a form with a single field that prompts them for singular successes and failures with the project. Instead, structure the lessons into meaningful metadata that can be later sorted and found. For instance, the type of project, relevant partners, unexpected events, resources that the team lacked, or the elements that contributed to making the project a success.

Culture

As I mentioned above, people have to volunteer their tacit knowledge. It is easy for them to do so in an environment that promotes knowledge sharing and establishes a psychological safe space where they can discuss difficult topics without judgment or repercussions. Unfortunately, this is not the case in all organizations. In this blog, our founder Zach Wahl offers advice on how to create a knowledge-sharing culture, which includes the use of meaningful rewards and recognition, coaching leaders into exemplifying knowledge-sharing behaviors, and creating both spaces and opportunities for people to exchange ideas.

Technology

As usual, we leave technology last because technology is an enabler and not a centerpiece. This factor is closely related to content because ideally, you would store the resulting content in a repository where knowledge can be preserved and managed so it can benefit the rest of the organization. Beyond having a repository to store the knowledge, organizations should also consider a search tool that allows employees to retrieve this knowledge in an easy and intuitive way.

Closing

Capturing tacit knowledge so it can be leveraged across the organization can be a challenging task. However, with a disciplined, systematic, and holistic approach, it can be accomplished. If you need guidance on creating value by managing your tacit knowledge, please contact us.

The post Knowledge Capture and Transfer Series – Part 2: Capturing Tacit Knowledge appeared first on Enterprise Knowledge.

The first thing we must acknowledge is that generally, organizations are trying to leverage knowledge that currently exists in two main forms: tacit and explicit. This has deep implications in how we approach knowledge and how we capture and manage it. The diagram below offers definitions for both forms of knowledge.

The challenge in capturing knowledge in each of these forms is different precisely because of their nature. Tacit knowledge generally resides within people’s heads, and it hasn’t been effectively documented. Common challenges related to tacit knowledge are the time it takes to find the experts with the right knowledge or the colleagues with the right experience. Furthermore, if the experts are unavailable, busy or on vacation, or have left the organization, their knowledge becomes inaccessible. Explicit knowledge, although documented, is often not placed in a location where it is easily discoverable, managed, or shared. Common challenges people face include spending excessive time going from repository to repository gathering the information needed to answer common requests, waiting for access, or having to spend significant effort comparing and cross-referencing multiple versions of files.

The upcoming blogs in this series discuss these challenges in detail and provide approaches and considerations for enabling organizations to capture and use their knowledge in both tacit and explicit forms. The rest of the blog series will break down approaches using EK’s People-Process-Content-Culture-Technology framework to demonstrate how to solve these challenges in a holistic manner.

If you would like to discuss your knowledge capture and management challenges in more detail, we will be happy to have a conversation. Contact us to get started.

The post Knowledge Capture and Transfer Series – Part 1: Getting Knowledge Capture and Transfer Right appeared first on Enterprise Knowledge.

A metadata catalog is a central database of information about disparate content. Imagine having a single application to go to that allows the learning managers to search, view, and manage all of their content. This is what a metadata catalog can do. The catalog has a record of each content asset that points to the content where it sits. This record also stores descriptive information about the asset in the form of metadata. Some examples of the metadata we frequently capture for learning content includes:

• Course title
• Length of course
• Medium
• Status—Is the course complete or still being developed?
• Topic (typically from a defined taxonomy)
• Skills addressed
• Competencies
• Audience

Once a metadata catalog is in place, learning managers have a single place to go to manage all of their learning content no matter where it lives. Learning managers can search for their content using an Amazon-like faceted search and then click on the content to open it up in its source location.

The metadata catalog becomes the central hub of all learning content for the enterprise. It is the single place for finding information about any course in any system. As a result, it provides a great deal of value as the source of record for learning across the organization.

The most obvious use of the catalog is to enable rapid assembly of training content. Learning managers can assemble courses using content from multiple sources rather than recreate content each time they develop a new learning curriculum. Larger organizations tend to have multiple departments creating courses and training. As a result, different groups often recreate training built by another group. If their learning creators are able to easily find and pull training from other courses, they can quickly assemble courses that re-use the work of others. This course assembly can also be automated to support a more personalized approach to training. Learners don’t have to sit in event-based training as they can search on what they need when they need it to improve their performance on the job. Based on this information, courses can be assembled that align with those skills gaps. This personalized training not only makes employees more productive, it also keeps them happier because they are not forced to sit through courses on information that they already know.

In addition to streamlining the way in which courses are created, the metadata catalog gives learning managers better insight into what training exists. The legal department at one of our retail clients asked how much training was offered to employees about minimum wage laws. This request would have taken days as learning managers searched through 10 different systems and assembled a list of courses on that topic. Instead, the client ran a quick search and provided their response in minutes. Our client has greater confidence that they are meeting their obligations and their learning managers can focus on developing training and not researching answers for questions from the legal department.

One of the most exciting uses we are seeing with metadata catalogs has to do with badging or certifications. Certifications typically require a mapping of courses to skills and to the certification. There are LMS systems that do this mapping, but they cannot include courses or related learning information that is captured outside of the LMS. The metadata catalog provides a full list of learning material (irrespective of where it lives) as well as descriptive information about them. It is relatively easy to map this learning material to the certifications and integrate with products like Badgr to implement certifications across the organization.

If your organization is struggling to keep up with your learning needs, a metadata catalog could be the answer to getting control over your current learning and to creating better, more personalized learning offerings in the future. 

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What is Enterprise Learning?

Enterprise learning includes creating a set of learning principles and practices that allow employees, partners, clients, and customers to access knowledge and training at the time of need. In a world where content changes fast and the need to learn it even faster, access to information, training, and experts is critical to stay competitive and meet critical business goals.

There are many different ways that organizations approach learning and development. At EK, we’ve built upon the foundations of our concise definition of Knowledge Management to explain Enterprise Learning:

Enterprise Learning involves the people, process, culture, instructional content, and enabling technologies to deliver a holistic training strategy and maximize learning outcomes across the organization.

Why is Enterprise Learning Important?

When people can independently find learning content, they confidently engage in organic conversations and collaboration that drive knowledge proliferation. So how do you develop an environment that cultivates organic learning and skill-building across an enterprise?

Leading training organizations empower individuals and decentralize educational offerings. This strategy promotes a culture where learners can channel curiosity and connect to valuable resources, rather than be commanded by learning processes. Most organizations with whom we have worked have many Enterprise Learning components in place, but don’t have the staff or struggle to create a successful roadmap to transform from their training organization into a sophisticated Enterprise Learning Program.

Enterprise Learning Programs provide a clear roadmap that aligns training improvements with the organization’s priorities. Successful learning programs harness the power of Knowledge Management to look beyond training as an event and offer a human-centric learning experience. An Enterprise Learning Program extends the learning beyond the organization level and provides a clear channel for employees to access information and knowledge, consequently creating better alignment at the enterprise level. Successful programs also transcend company walls allowing partners, clients, and customers to stay informed and trained around products and services.

From an ROI perspective, the value of Enterprise Learning is clear. Individuals who feel supported by their organization, who see a path to develop and grow, and who feel they are being set up to succeed will stay with the organization and perform at consistently higher levels. Enterprise Learning will yield higher employee and customer satisfaction, in turn resulting in lower employee turnover and customer departures. Put simply, Enterprise Learning will save your organization money.

Key Tenants of Enterprise Learning

1. Transcend Training

Too often, learning and development professionals struggle to go beyond the proverbial training box. Traditional training is essential for teaching the basics of new knowledge and skills. Nevertheless, to be effective, it must be supplemented with microlearning that can be easily consumable by the learner rather than buried in lengthy manuals and overly complex multi-day course materials. Learning concepts can be mined from the larger training programs and used as performance support tools such as checklists and short instructional videos that are available at the point of need. Once the material has been mined, it can also be used to repeat the learning process over a period of time, creating a spaced learning offering to reinforce challenging concepts.

2. Collaborative and Social Learning

The best learning assets in most organizations are people. A robust Enterprise Learning Strategy will craft processes and develop technology platforms that support collaboration, problem-solving, and the co-creation of knowledge. This collaboration is often through communities of practice and discussion platforms like Slack or Microsoft Teams. Incentivizing active participation in learning communities is also essential to building a collaborative culture. In addition to collaborative discussion platforms that give all community members a voice, the development of Expert Finders can be incredibly impactful for larger and more siloed organizations – especially when there are hidden people in your organization who have niche expertise.

3. Data-Driven

Enterprise Learning strategy must generate data for analysis and iterative improvements to organizational learning outcomes. The key is to build data collection directly into technical systems. Traditionally data collection was in the exclusive domain of classroom rubrics and course summative assessments. This can be extended to include a robust system for tracking formative assessment data and social learning activity using the xAPI specification. When you expand what kinds of data you’re collecting, organizations must also ensure learning and development professionals are trained to craft valid and meaningful formative and summative assessments and analyze the data to improve learning assets incrementally.

4. Reusable Content

The need to create reusable content is not an old concept. L&D organizations struggling to define a process should start by looking beyond the traditional content development models where student manuals are the norm. Learning objects are vital to creating a reusable, self-serve content model. With various instructional delivery modalities available for today’s learning and development professional, training programs should leverage and Headless CMS approach to share instructional content in multiple learning contexts. Let’s say you’ve produced a two-minute video that explains how to publish a news article on your company’s intranet. That video could add value as a stand-alone content object in a knowledge base or a learning module within a more extensive communications course. Architecting content in such a way that it’s intuitively reusable is essential if we’re going to stop recreating the wheel and trying to keep multiple versions of similar learning assets up to date.

5. “Findability” of Learning Assets

Elevate findability by harnessing the power of KM through taxonomy, ontology, and a well-architected search system. A well-architected metadata strategy is essential when you expand your learning assets to include courses, webinars, job aids, performance support tools, communities of practice, and subject matter experts. Because of the diversity of learning aids, these assets likely exist across multiple systems, and that’s OK. As long as learning assets are contextualized and related with consistent metadata, they can still be findable. Moreover, if related using more advanced techniques like ontologies, a complete network of learning resources can be created in a way that can naturally be assembled and pushed in customized ways to each unique user.

Summary

Enterprise Learning can be transformative to an organization, offering significant business value, especially when considering the modern learner can quickly consume knowledge and information and immediately apply what they have learned. An Enterprise Learning Plan with a learner-centric approach results in better performance, more focused engagement, and a better user and customer experience.

Are you ready to channel curiosity rather than command and control? Empower individuals by giving them the autonomy to take the reins on their continuing education journey, and your Enterprise Learning Program will thrive. As a result, you’ll see increased engagement, enhanced workforce skills, and a modern learning culture instilled across your organization. Our instructional systems designers are here to help bring your Enterprise Learning program into the modern age; contact us to learn more.

The post What is Enterprise Learning and Why is it Important? appeared first on Enterprise Knowledge.

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Despite the improved learning outcomes which can be gained through the use of performance support tools, learning and development professionals often struggle to create them. As knowledge management and instructional systems designers, we can make the creation of performance support tools much more efficient by analyzing the commonalities between tasks and creating meaningful content types. Applying knowledge management best practices, such as effectively designed search results with action-oriented search can lessen the content creation burden on learning and development professionals.

Checklists

Often, a learner only needs a checklist to help them follow a policy or process correctly. An effective intranet or knowledge management portal will often include a checklist content type to make it easier for your subject matter experts and web content authors to create checklist content. Your content authors can quickly fill out a form like this one.

By leveraging a checklist content type in your intranet or KM portal, your subject matter experts will be able to efficiently create and publish checklist by simply filling out a form. When they publish the form, they will have created something that looks as professionally designed as this great checklist example from weddingwire.com.

Creating checklists via a specialized content type not only improves the efficiency of content creation, improving the content creation process in this manner has additional benefits. Those benefits include: improving visual design and creating consistency in the way checklists are presented in your system – reducing cognitive load and improving learning outcomes.

Quick Reference Guides

Quick-reference guides (or “cheat sheets”), are short tools which give the learner just enough to get the job done without having to read all of the instructions. Quick reference guides can be handled in multiple ways in a knowledge management portal.

Option 1: Quick Reference Guide Content Type

Quick Reference Guides can be a very simple content type in your knowledge management portal. When creating this content type, common fields might be:

• Task Name: Single-line text field which defines the name of the task the quick reference guide will support. Effectively the title of the content.
• Key Concepts: Character-limited richtext field which enforces the brevity of the text, but allows the content author to explain the most important concepts or steps to complete the task.
• Full Instructions: Field type is restricted to a link or a document upload and provides a way for the content author to provide a direct connection between the quick reference guide and the full set of instructions.

Option 2: Quick Reference Guide Search Results Type

Depending on the maturity of your system, it’s entirely possible that you do not need a specific content type to fill the need of a quick reference guide. Your search index could find simple things like the name of a task and a brief summary of the task from existing content – returning this existing information directly in your system’s search results page. You could even include action-oriented search buttons which would open the full set of instructions directly from the search results list – saving the learner one unnecessary click.

If you want to take things even further, your system could recognize your quick reference search result as a “best bet” and always give priority to this result as the most relevant content when a user of your system searches for a named task.

Summary

Learning and development, as well as knowledge management professionals are often extraordinarily busy  –  trying to meet more needs with less resources. By leveraging custom content types, EK consultants can help make their job much more efficient, allowing them to create polished looking content quickly and easily. In addition to content types, we can also provide them with the tools and knowledge to leverage well-designed search results to bypass the need for content creation at all. If you’d like an analysis of your existing web content and some custom content type and search design advice, contact us at Enterprise Knowledge.

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