Users want to find the closest match of ready to consume content that is trustworthy and most importantly something that fills the wireframe that they have put together through their own research. With the rise of the digital age and advancement in technology, users are made aware of Content Relevancy - a key metric to consume content. Users are therefore expecting High-Value Content to be delivered at their fingertips, and here is where the folly lies as most organizations charter KM teams to meet this expectation.

Take for example an IT company which has many employees, some are new entrants into the workforce, others lateral experienced hires, managers, group managers, vice presidents / business heads and so forth. If you now see clearly you are not talking about creating content for an abstract audience, but a well-defined persona of users who rate the content based on how easy is it to consume to enable them to become successful. 

Hence, it’s important we familiarize ourselves with the process of Content Curation, which is defined as Collecting, Organizing, Selecting, Packaging and Promoting the best content that is tailored for an audience (users).  So what are some of those practices that can help us develop better collections addressed towards these personas of users?

Identify trigger points to deliver content to the group

Once we have zeroed down on a user group we need to ensure we are aware of pushing the content to them and enabling them through this medium to get hooked on to accessing our content and pulling them closer to becoming brand ambassadors of our content. Hence it’s important we focus understanding their unmet needs that should be addressed through our content.

Creating Fresh Content  V/s Curate the Content

As a Knowledge worker you come across leaders, champions and a host of networks. Its important you follow some of their best work whether it a thought paper, research article, knowledge nugget, webinars or other credible content. Take for example a newsletter weekly edition every good curator has a weekly planner of how he wants to schedule this content and while the supporting pieces can be curated from various sources it helps to manage the central piece and create fresh content so the story progresses with each new edition.  I guess we all are familiar with the Pareto Principle where it’s your 20% fresh content that delivers 80% of the hits.

Don’t limit yourself as the only Brand Ambassador of your Content

Content is no good if it cannot be marketed. And many a time as KMers we forget that it’s not just our job to make sure our best content gets delivered out there. So how do we ensure we identify which content can be marketed by our leaders, peers and gets noticed. It’s important to have a watch on the competition yes as many marketers are in need of content and pretty much are the brand ambassadors that Knowledge Managers should credit for ensuring higher touchpoints of the content we curate. Yes, making our knowledge systems accessible through blog posts, webinars and the likes ensures some of our experts get noticed by marketers and their content gets externally published making our work shine.  So don’t limit yourself to only managing your content strategy alone. Like they say don’t lose the trees for the forest always have an eye on the bigger picture and how your content is credit worthy to other communities.

Sharing credit can make you 'content searchable'

There is a plethora of good content out there and many times although we design our content well in advance and define the sources to gather them from we notice that the piece has already got posted most often by the author. So how does this handicap our content delivery process does it make our viewers lose interest even before we want them to find the content? What could be the solution? Well it’s important to ensure we reward our contributors before others do and publish them in our hall of fame ensuring they feel valued with providing us a steady stream of content that is well researched, timely and ensures they reach us as a first choice.

CTRL-R Managing your Content and keeping it up-to-date

The same old problem of governance where Knowledge Managers are chartered with archiving content that is dated a year back. We see less viewership and no this signals lesser number of hits and hence call for action to archive the content by triggering a few reminders. What instead if we take the same piece and work on it adding a few relevant links, headlines re-packaging it and sharing it with the author for the final proof read? There is a high chance it goes to the leaders and they take notice and on publishing the content post it on their private handle or tweet it highlighting their POV for an industry topic that they follow.  This could be the silver bullet and differentiates good curators. Content Curation is as much about the presentation of good content and sometimes enabling our audience with re-packaging their content ensures we develop better collections that are up-t0-date based on our own expertise managing topic based content over time.

Invest time to discover new content and be bold to critique it

CoPs are a great place to notice someone’s point of view and credit them. As a Community Manager we are also chartered with ensuring we respond to every post and at times critics play a big role in leading us to the right content. It’s important to not play silent spectator at all times and sometimes engage in a interaction to challenge a viewpoint as it helps us to learn more about the SME and in-time develop some of their content to build on our existing collection.

In-Summary

In this digital world where content relevance is measured by how practical, credit worthy and ready content is to be consumed it’s important we ensure we understand the importance of curation. While we are designing our content strategy it’s also important we are open to understanding our user persona’s and investing in defining the right trigger points to deliver high-value content to them. As Knowledge Managers it’s also our call to action to hone our content writing skills and contribute to enriching existing content through our deep industry research skills and ensure we expand our network of content creators crediting them. Over time we are all called to play critic and engage and identify SME’s some of whom we can co-partner with to sustain our collections of content and invest our time in becoming experts in our own industry or topics a curators.

With the rapidly changing landscape of how offices and organizations approach work, knowledge management (KM) is more crucial than ever. Due to the overflow of information within organizations, the ways in which this information is stored and archived change according to the need, time, and purpose. 

As with everything else, the field of KM in technology has its seasons of trends. However, some trends are here to stay. Why should some trends outstay others, you may ask?

Well, simply because they improve the user experience for the better.

With the changing composition of the workforce, traditional methods of disseminating information are replaced with more agile methods. Let us look at the top five knowledge management trends in 2022.

1. AI is here to stay 

Anyone who is active on the web has watched the trajectory of growth in Artificial Intelligence (AI). Within just a few years, AI has grown tremendously and is predicted to take over many sectors in the future.

Intrinsically, AI and KM deal with knowledge, information and learning. Recent developments in the field of AI can be implemented in the way knowledge management systems work. AI is mostly used in KM to store and retrieve explicit data. AI can dig deep into various channels of content, decipher relevant topics and present useful information when required.  

For example, companies have now started applying deep machine learning in AI-powered chatbots to relay the desired information when and where needed. This knowledge management trend is here to stay with many companies integrating chatbots in their websites for easy communication and problem solving.

2. Easy-to-use collaboration tools 

In 2022, especially with the growth of hybrid work culture, the rise of easy-to-use collaboration tools has grown exponentially. The key idea is to provide a seamless communication flow among employees.

Using the best enterprise knowledge management platform will allow for this collaboration through the integration of multiple apps. According to a research paper by Peter Clark and Maggie Cooper, the rise in collaboration is proportional to the increased possibility of communication through IT.  

Some spaces that now demand collaboration are task management, information sharing, co-editing, and case studies to name a few. This is why tools that encourage collaboration for ideating, working, communicating, and editing will inevitably be a popular knowledge management trend. 

3. Mobile-friendly user experience

According to Google, more than 50 percent of search queries now happen through mobile phones. Mobile users are only going to increase, and so will the search volume through phones. Hence, it is key to optimize your website for mobile. This brings us to a crucial part of knowledge management - mobile apps, as one of the biggest knowledge management trends to stay for good. 

For instance, the increasing use of mobiles has initiated M-learning or Mobile Learning opportunities. In order to make the learning process better for the user, knowledge management processes integrate M-learning apps increasing choice and convenience. 

Even with websites, optimizing your website in order to make it mobile-friendly is crucial nowadays. Google prefers sites that have a good user experience both on desktops and mobile devices.

4. Round-the-clock support 

For any kind of business, the common denominator is customer satisfaction and revenue generation. This makes it obvious that for a business to succeed, providing a seamless customer experience is not negotiable. In fact, customer support is one of the pillars of a business that can determine how successful your business eventually becomes.

Other than collaboration and knowledge-sharing, top-notch knowledge management can improve customer support, and therefore, customer experience tremendously. 

Businesses today can leverage this tool for internal and external business purposes. This would include providing insider business information to support agents that would help them solve customer problems faster and improve their KPIs like average handle time & first call resolution. Hence, there is quicker dissemination of information to customers to educate and inform them about the company’s offers, services, and so on.

5. More media-focused content 

Traditional forms of knowledge base management systems like Confluence knowledge base, Sharepoint knowledge base, etc are composed of really lengthy guides and manuals that make the employees dread reading them.

Humans, in general, focus on getting a job done in the easiest way possible. Whether an employee or a customer, no one would like to overcomplicate or have tedious systems.

Well, worry not! Today’s knowledge management systems are not only new and improved but they are genuinely geared towards improving both the agent’s and the customer’s experience. Another knowledge management trend is the use of media such as images, visuals, and videos to make the interaction more engaging and enriching. 

For the visual-inclined human mind, adding visuals to a text makes it easier for the person to grasp the concept and implement it. So goodbye to the long and boring formats, hello to cool and engaging relevant media. 

Conclusion 

With the emergence of new technologies and changing work cultures, it has now become essential for businesses to adopt efficient knowledge management systems. Besides having access to information, it is crucial to be able to access this information when needed. 

The above-mentioned knowledge management trends focus on enhancing both the business and its employees, and their customers.

Using a knowledge management system is one of the best ways to ensure that employees are not only productive but more importantly, satisfied in their job roles. 

Furthermore, efficient and readily available customer service ensures a good customer experience. And happy customers mean increasing sales and more revenue.

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What are Knowledge Management solutions?

Peter Drucker, famous for declaring, "Information only becomes knowledge in the hands of someone who knows what to do with it," coined the term "knowledge management" in the 1950s. 

Knowledge management has since become a specialized emphasis area for larger companies.

There have been numerous discussions about how knowledge management solutions can be implemented since the subject was created in 1991. 

One of the most popular is using a knowledge management software solution to support customer service and technical support operations such as contact/call centers, shared service centers, web self-service functions, and help desks, including ITSM (IT Service Management) operations approaches in businesses. 

Evolution of Knowledge Management solutions

Many attempts at internal systems have been made, ranging from internal "shared drives" to massive databases with intricate hyperlinks and meta-data. 

The accumulation of big data has made it increasingly difficult to find the exact information needed without a lengthy search or an intimate understanding of where the data is stored. 

In addition to offering an internal content management function and reports to assess knowledge base usage and knowledge gaps, the best software for Knowledge Management simply indexes a wide range of information resources before filtering and prioritizing relevant knowledge.

#1 - Central repository (Knowledge base systems)

Many information sources are accessible from a single location.

The system indexes all required content from all relevant sources without requiring any information to be moved to a single location and uses a natural language search function to allow users to quickly and easily retrieve the information.

This enables quick and easy solution deployment without the need to reformat or repurpose vast amounts of legacy data.

#2 - Guiding customers to answers (Content relationship Management systems) 

Users frequently know how to articulate their problem but are unsure how the answer will be phrased or communicated. 

Staff, partners, and customers can describe the issue, pain, or query in their own words and enter the term immediately into a search using the best software for knowledge management. 

The ai knowledge base solution will find and display solutions known to handle similar issues in order of importance.

#3 - NLP (AI – powered solutions)

Users can utilize natural language search instead of typing in keywords to ask inquiries. 

Documents are frequently prepared in informal language that differs from the language used to ask questions. 

Natural language search functionality is currently a significant element of the best software for knowledge management.

It allows the system to grasp the context of the query rather than just the keywords required for a successful search result.

This is especially significant in industries that employ industry jargon, such as finance, where a direct debit is commonly referred to as DD. 

Natural language capabilities can permit the use of the organization's common words.

#4 - Self-learning (Decision support systems) 

A self-learning capacity in a knowledge management solution captures the continually changing flow of information. 

This keeps the index up to date with the actual phrase used in inquiries. 

New content can be added to the content repositories that are already in use after the initial implementation.

Self-learning also includes users determining the quality of the solutions offered, so the most useful options are presented first.

#5 - Single source of truth (Document management systems) 

A knowledge management solution can also help with a push strategy, which allows specific content to be 'pushed' to a specified user group. 

This guarantees that new information reaches the right individuals at the right time.

The system keeps track of who read the material and when.

This allows administrative users to see who needs to be updated on new information.

The system may also manage user profiles across an organization, allowing each user profile to have specific access to pertinent information. 

This allows knowledge to be transmitted both within and outside of the company while maintaining control.

#6 - Identifying and closing knowledge gaps (Learning Management Systems)

A new age knowledge management solution can also identify knowledge gaps and refer unanswered concerns and queries to content specialists unlike old DMS like Sharepoint, who can react to the inquiry by updating the system with new information. 

This eliminates the need to elevate the same investigation to relevant experts numerous times. 

Tracking and responding to knowledge gaps also removes the guesswork involved in determining where knowledge gaps may exist before developing new solutions. 

#7 - Social communication systems

Knowledge is created and shared whenever your teams interact with one another.

It's critical, then, to analyze how your organization's communication and collaboration technologies relate to your knowledge management goals.

You want to know, in particular, that:

· In the first place, your teams can easily share knowledge and information.

· This information can be shared in a variety of ways.

· At all times, engagements are recorded, and knowledge is saved.

#8 – Decision support systems 

Decision support systems are technologies that assist people in making informed business decisions by analyzing large amounts of data. 

While DSSs can be used to collect and handle any form of data, the most frequent data types involved are:

· Performance in marketing and sales

· Services of assistance

· Internal operations

The idea is to use data to find the paths that will lead to the maximum development for your company, whether that growth is financial, productivity, or something else.

Conclusion

When implemented correctly, a knowledge management system can help your company raise customer happiness, lower customer care expenses, and boost overall customer success ROI.

While the tactical features of knowledge management systems may differ, the goal remains the same: to educate your consumers to effectively use and interact with your products or services.

You may accomplish this by using a combination of knowledge base FAQs, tutorials, academies, how-to articles, and forums.

Any aspect of a knowledge management system should contribute to addressing and educating consumers and gathering information about your products or services.

Data analytics and knowledge management (KM) are two integral elements of modern business. We depend on big data to inform our business practices and customer needs, and we need KM to cultivate an environment of transparency and insights. By using the best of evolving data strategies, you can streamline knowledge management to produce actionable information that improves business efficiency.

However, managing knowledge with data effectively isn’t always simple. The more data analysis strategies advance, the more complicated they can get. Start by exploring these changes and their impacts, then integrate these evolved strategies into your KM system.

Evolving Data Strategies and Their Impact

Knowledge management never stays the same. The amount of information you need to juggle and make visible to your organization is influenced by rapidly changing digital platforms and data sources. Without a comprehensive understanding of the latest data trends, you’ll run into problems deciphering solutions for operational efficiency.

This is especially the case when dealing with an overabundance of data. These days, massive amounts of data are collected and cycled through data processing software or stored as raw data on internal networks, never to be utilized to their full potential. To maximize the effectiveness of the data you assemble, you need to apply modern data management strategies.

Data management, as opposed to knowledge management, focuses specifically on the administrative challenge of organizing and controlling data resources. This is only one aspect of a larger KM strategy, but an essential one since most of the knowledge you store will likely revolve around data utilization. Evolving strategies in data storage can complicate matters.

Here are some of the modern data developments that are impacting the world of KM:

●      Data storage is moving to cloud systems and even blockchain technology.

●      Visualization of data through augmented and virtual reality (AR and VR).

●      Artificial intelligence tools for data monitoring, storage, and safekeeping.

These evolutions in data management all carry significant implications for any business’s knowledge approach. For example, AI is streamlining KM by enabling cognitive computing functions that explore huge data sets and connect patterns through powerful deep learning and neural network functions. The result is a living knowledge system that can improve itself.

As data processing methods like these improve, so too will the benefits that knowledge managers can bring to their business. But integrating new data strategies will take work.

Integrating New Data Strategies in Knowledge Management

You can build in the effective use of evolving data strategies into your own KM. The process involves striking a balance between your architecture, analytics, and communication tools, but by streamlining your process with modern features you’ll set yourself and your users up for greater success.

Start with your information architecture and its role in your analytics process. With the right data structure, you can integrate new tools easily and successfully. From there, it’s a matter of getting used to new systems across your organization.

Here are a few tips to help you integrate new data strategies in your KM system:

   1. Centralize your knowledge base on a cloud service. There are good reasons cloud-based data management services are gaining in popularity. With all your information in a single place, you can more easily apply the data service innovations of the modern era.

   2. Find the right knowledge tools. All kinds of comprehensive knowledge base software are out there. Modern offerings include AI-built hubs of information, containing graphics, personalized knowledge article recommendations, and more. Exploring these tools can be an effective way to streamline your own KM.

   3. Implement new visualization experiences. Understanding business data and procedure instructions can be difficult. It helps to have visualization tools. These days, AR and VR technologies are fueling new ways of looking at data and transforming the workplace as a result. Look for ways you can integrate these experiences into your own KM.

   4. Use AI. Far from being the frightening, job-ending technology you might imagine, AI can actually help streamline KM by allowing users to find information through voice, visual, and data searches. The evolution of AI features like Natural Language Processing (NLP) means your users can navigate knowledge with unprecedented convenience.

   5. Involve your whole team. Managing knowledge is a big job. The more voices and perspectives you bring into the process, the better you’ll be able to bring in evolving tech to streamline the experience. Engage your team with discussions and brainstorming sessions to help implement an effective plan.

Streamlining KM through evolving data strategies can make for a simpler and more impactful experience. Such a system can bridge understanding and connect users with better results, building a more transparent and effective business. However, you’ll need a comprehensive view of the tools and features available to you.

After thorough research and a team-generated solution, you’ll be able to apply new data tech to create all new experiences for your knowledge-seeking users. From cloud services to AI functionality, these tools in KM mean better communication, more transparent business, and more actionable insights when it comes to improving your processes.

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Knowledge management as applied in modern organizations is both a simple concept and a wide-ranging one. Definitionally, it can be boiled down to the effort to manage information and resources to improve the organization’s efficiency. But this effort can of course be applied to any number of specific issues or aspects of an organization.

In this piece, we’re going to explore the use of knowledge management for the navigation of an overabundance of information within a business.

Can There Be Too Much Data?

Any discussion on this topic needs to start with the logical question, which is whether or not there’s any such thing as an overabundance of information. Or, putting it another way, is there such a thing as having too much data for a modern company?

A lot of people might be inclined to impulsively answer in the negative. In our increasingly digital world, we’re perpetually inundated with discussions about the importance of data in business. We understand that robust data operations yield invaluable insights, and we hardly think to question whether there might be an upper limit on how much information is actually useful. The general perception is that the more data a company can produce, the deeper its insight will be — and the deeper the insight, the greater the opportunity to enhance efficiency and improve operations.

There’s a certain logical sense to this, but the truth is that there is such a thing as generating too much information, to the point that it becomes an inefficiency unto itself. As one discussion on data saturation put it, it’s actually a problem that is “everywhere” in modern business. This is because “the rapid rise in our ability to collect data hasn’t been matched by our ability to support, filter, and manage the data.” These comments were made with specific regard to marketing departments, but they do a nice job of summing up the problem more broadly. Companies that focus too much on gathering data in large quantities wind up with more than they know how to make sense of, and thus struggle to find meaningful insights.

How Knowledge Management Can Help

The most fundamental way to think about how knowledge management can be applied to this problem is to slightly tweak the definition provided above. As stated, KM is typically about the effort to manage information to improve efficiency. In this case, however, we might think of it more as the effort to make the management of information more efficient in the first place, so as to improve the quality of business insights. It’s a subtle distinction, but one that establishes a helpful way of thinking: a focus on turning the scattershot collection of information into a more targeted and productive effort.

This is something that’s easier to theorize about than to put into practice. It is actually easier, at this point, for organizations to simply cast a wide net and gather all possible information that might pertain to company performance — from internet activity, social media, internal performance, and so on. Where KM comes into play, however, is actually in narrowing that collection process to focus only on what is relevant, pertinent, and ultimately useful. It is essentially a filtration process that narrows the parameters of data collection in ways aimed at generating only the most helpful information, and avoiding excess clutter.

Naturally this is not an exact or flawless process. Some excess data without particular utility will trickle through. But by making the actual collection process more efficient, an organization can effectively apply KM as a solution to this problem.

How to Implement Knowledge Management

As mentioned, this sort of solution is easier to develop as a theory than to implement as practice. However, there are simple and strategic ways to go about the application of KM.

One is to turn to an employee or team specifically trained to handle data-related needs. For some companies, this might mean hiring data and/or analytics experts from the outside. Others, however, may find it more efficient to train internal administrators for the task at hand. Today, this sort of training is accessible via online business administration degree programs that make it easier for working professionals to study and learn new skills without having to quit their jobs. These programs prepare students for a number of different business tasks, but operations management, data research analysis, and marketing coordination are among them. Any of these specialties can help a company employee to gain expertise in data-related practices, and thus prepare said employee to direct a KM effort.

The other, similar but perhaps simpler option is to establish and train people in what are sometimes referred to as gatekeeper roles. Beyond the general definition that inspires the term, the gatekeeper concept is one more commonly associated with product development. Basically, the idea is that someone in a gatekeeper role controls the flow of information between stakeholders and project development teams, so that there isn’t excessive information or pressure moving one way or the other. And the same concept can be applied to data operations as a form of KM. Essentially, an organization can train gatekeepers to recognize what is pertinent and what is not in data collection, and thus — with relative ease — cut down on the clutter. This in turn makes an entire data operation more efficient.

In the end, the effort can be more complicated than how it is presented here. Particularly where larger organizations are concerned, data operations tend to be vast and multi-faceted. Applying KM across the board takes a thorough, effective strategy. The foundation for this strategy, however, is understanding the problem and the ways in which knowledge management can be implemented to solve it.

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Article specially written for kminstitute.org