How do you use knowledge management software to support decision making and problem solving?

Knowledge management software is just software. By itself, it will not transform an organization into a knowledge sharing institution. This is only achieved with change management as knowledge sharing needs to be embedded in the company culture and rewarded. You should examine your knowledge needs through the lens of what business outcomes you want to achieve. Examples include more repeatable outcomes, transfer of knowledge due to an aging workforce, or the desire to leverage less skilled or less expensive resources for the same outcome.

Imagine your brain is a huge library with books scattered all over. Now, think about organizing those books so you can find them easily when needed. That’s what knowledge management software does—it helps you organize and access information effectively. For example, if you’re working on a project and need past data or solutions, this software helps you quickly find relevant info, like searching a well-organized library. It's like having a super-smart assistant for your digital knowledge!

I can't stress enough that a great search functionality is key to people using and leveraging the knowledge assets. One can create the best FAQ or how to guide; however, if no one can find, is it truly impactful and helping you accomplish your goals? Ideally, one should integrate this into an overall enterprise search strategy. Don't make people think about where they have to search.

In a KM project, using SharePoint helped our team by offering version control and robust search functions, making document retrieval 30% faster. This streamlined our decision-making process by ensuring we had the latest information at our fingertips. As I learned from another project, using Slack integrated with Confluence enhanced team communication. With tagging and notifications, we saw a 25% increase in real-time collaboration, making problem-solving more efficient and enjoyable.

In my experience search can make knowledge findable and usable. When there is a lot of knowledge content, the capabilities of the search make a big difference.

In my opinion, it is not enough just to deal with the need for knowledge. It is just as important to look at the software and the system landscape. If there are too many tools, the new knowledge database will not be accepted by employees. The software must serve people, i.e. be intuitive to use, fit into the work context, enable knowledge to be documented quickly and easily and, above all, not create any hurdles.

KM software comes with various features designed for different needs. For instance, if your team collaborates a lot, look for features like document sharing, real-time chat, and project tracking. These tools help everyone stay on the same page, just like sharing a toolbox ensures everyone has what they need for a project. So, pick software with tools that fit your team's workflow!

While I do love a good taxonomy, I think that relying on the document name to embed metadata such as year, month, topic, etc. creates more of a maintenance issue than what it solves. Ultimately, there are two types of end groups: people creating the content and people consuming the content. You want a balance between both roles. For example, you typically want low barriers to sharing knowledge; however you also want the knowledge to be accurate and original. On the other hand, a consumer of the knowledge will rarely drill down via a taxonomy. When was the last time you used categories to find information versus use of a search term?

I find taxonomy and metrics to be particularly helpful for learning and explaining knowledge content. For example if I'm going to tell you about cloud Policy as Code tools I should define the category (systems that use policy rules to check cloud configurations for security and compliance). I should also break the category down into major capabilities (static scanners for your infrastructure code before you deploy it, cloud platform policies, and live scanners that check live resources by using cloud service APIs). This makes the most sense if the terms I use are mutually exclusive, collectively exhaustive (MECE). But terms change so if I want the knowledge to make sense next year I need a way to relabel things: taxonomy and ontology.

Organizing your knowledge also requires understanding what types of knowledge article types there can be - and trying to format them accordingly. Besides that, a good taxonomy is important, not only to organize the content location, but also implement permissions properly, so only relevant users can see what they should

In a recent project with a financial institution, we used knowledge management software to support decision-making. For example, by organising data into categories like risk management and customer feedback, we enabled executives to swiftly access crucial insights, leading to a 20% reduction in decision-making time. In another KM project, we leveraged tagging and metadata in our knowledge base to streamline problem-solving. When a museum faced technical glitches with digital archives, the team quickly found solutions by searching relevant tags, resolving issues 30% faster than before.

I also recommend developing templates for different types of knowledge (content types). This gives employees structure and makes it easier for them to document knowledge in a structured and standardized way.

In a KM project, we used software to create a problem-solving portal at a tech company. This system, featuring a repository of past issues and solutions, reduced resolution time by 40%. Employees could search for similar problems and apply proven solutions, enhancing efficiency and collaboration across teams.

I would say this is the key element, KM is a strategy, an approach, and is largely about people. The software can be cool and helpful, but focus on the people using it through the user experience, and the change management, training and education that will allow them to use an software to its greatest potential.

The organization can support the exchange and documentation of knowledge by providing sufficient time for knowledge work, including documentation. Too often, knowledge is not properly documented due to a lack of time. Even a knowledge management tool will not be able to change this.

In a KM project, I found knowledge management software to be a game-changer for decision making and problem solving. Imagine it like having a digital Sherlock Holmes at your disposal :) :) Based on my experience, using software like SharePoint, we streamlined access to critical data, boosting decision-making speed by 30%.

Using different analytics would help you understand: - Overall usage - Most active users / inactive users and populations - Popular knowledge articles - Different actions, search, etc. These tools help the knowledge managers understand what works better, what might require improvements, and even more - get insight and learn gradually important best practices

I remember one of my favorite projects on the field with a contemporary museum: the knowledge management software was like having a brilliant assistant on hand. It provided instant access to past exhibit plans, expert insights, and visitor feedback. This made decision-making a breeze, like assembling a perfect puzzle with all available pieces. The software turned complex tasks into smooth and enjoyable experiences, making our work efficient and fun.

Make smart choices fast: Find the info you need quickly to make better decisions. Solve problems together: Learn from others and avoid repeating mistakes. Work as a team: Share knowledge and ideas to find better solutions.

One aspect often overlooked is the human element of KM. While tools are crucial, they're not a substitute for human interaction. Encourage team members to share insights during meetings or informal gatherings. For example, start a "Lessons Learned" segment in weekly meetings where team members discuss challenges faced and how they overcame them. This encourages collaboration and ensures tacit knowledge is shared, complementing what's captured in KM software.