Let’s talk about knowledge management success. In an earlier article, I wrote about the wealth of benefits available from knowledge management. It should be a win-win for everyone involved. However, for a variety of reasons (let’s call them barriers and mistakes), IT service management (ITSM) organizations and their IT service desks still struggle to get knowledge management right.
The common barriers (to knowledge management success) can be split into different groupings. For instance:
- Start-up barriers – the things that prevent knowledge-sharing initiatives from delivering a workable ecosystem and/or making an initial impact
- Day-to-day operational barriers – the things that prevent people from actively using or sharing knowledge and delivering knowledge management success.
This article looks at both of these barriers to knowledge management success, offering help, plus covering the knowledge management success issues related to people, process, technology, and scale.
The start-up barriers to knowledge management success
Good examples of knowledge management success start-up barriers include:
- Not having a shared understanding of what knowledge management is and entails – as with many IT and organizational “disciplines,” it’s all too easy for different people to have different views on what needs to be involved with knowledge sharing.
- Focusing on the ease of knowledge capture over the ease of knowledge use – but the bottom line is that an organization can have the best knowledge capture, organization, and management capabilities in the world, but it will amount to little if people can’t and/or don’t use (and reuse) the available knowledge.
- Not appreciating how hard knowledge management can be – as with any other organizational change that involves people, organizational change management (OCM) tools and techniques are needed to help transform both cultural aspects and the ways of working. But the act of knowledge “extraction,” i.e. capturing what people know, is also complicated, as described in the next subsection.
These three barriers need addressing for knowledge management success, with a good place to start being the following good practices.
5 must-dos for starting your organization’s knowledge journey right
So, what should your IT support organization do when starting out with, or trying to improve, its knowledge-sharing capabilities and knowledge management success?
It needs to address the three knowledge management success barriers outlined above as a minimum. This can be achieved through the following five knowledge management “must-dos”:
- Get people on the same page. As already mentioned, different people will have different views as to what knowledge management is (and isn’t). For instance, while ITIL v3 offers knowledge management as a discrete ITSM process, people need to appreciate that it’s really an organizational capability built from people, processes, and technology.
- Focus on knowledge exploitation over management. While “knowledge management” is the accepted term for what’s needed (for successful knowledge sharing), there’s also the need to ensure that the real focus is on exploiting knowledge rather than simply on its collection, storage, and management.
- Make your knowledge management initiative about people change. Knowledge management requires a change in mindsets and behaviors. The introduction of new (knowledge management) technology alone won’t bring about the changes required for successful knowledge sharing. Sadly, this has been proven time and time again – so focus on the required people change first.
- Don’t do half a job with OCM (or, even worse, neglect it). Your knowledge-sharing initiative will most likely fail without a suitable investment in people/organizational change management. In particular, in the removal of the resistance that results from the common barriers to change – including the fear of the unknown. So, invest in “bringing people along” – selling the change (including the “What’s in it for me?”), communicating key activities and milestones, and the necessary levels of education and training.
- Understand the complexities of accurately capturing knowledge. So, taking the “tacit” knowledge that’s in our heads and “creating” explicit knowledge – the documented version of it. Research into real-world knowledge management achievements has concluded that this is complicated and, in particular, that:
- People always know more than they can say, and they will always say more than they can write down
- The way people know things is not the way they report they know things
- People only know what they know when they need to know it, and
- Knowledge can only be volunteered it cannot be conscripted.
Exploiting existing and potential knowledge for knowledge management success
The insight and advice offered above will only get your organization so far in terms of creating the right environment for knowledge management success. It allows the foundations for knowledge management success to be created but there’s much more that needs to be addressed to ensure that knowledge is successfully shared (and used) on an ongoing basis.
There are both day-to-day and “growth” barriers related to knowledge management success:
- People and process, and
- Technology and scale.
Dealing with People and Process Issues
So, your organization has done everything possible to ensure knowledge management success and people have so far bought into a new, knowledge-sharing, way of working. But things can still go wrong from a people and process perspective. For example, that:
- Knowledge management is treated as a separate process or activity (relative to day-to-day operations) – with it potentially seen as something that’s done in addition to the “real” work. This will inhibit both the capture of new knowledge and the automatic use of existing knowledge.
- Traditional employee performance measures don’t reflect the new ways of working – and, as a result, knowledge sharing is held back by the organizational encouragement of “the wrong types of employee behavior.”
- Knowledge articles are “too much” – with their authors providing everything they know (related to a subject) rather than just what the reader needs to quickly get to the required resolution. Ultimately, long – and potentially bloated – knowledge articles are just not helpful to knowledge-seekers and are a surefire way of preventing knowledge management success.
Thankfully, each of these knowledge management success issues can be addressed through the application of knowledge-sharing good practices, including:
- Embedding knowledge sharing into business-as-usual activities. If this isn’t done, the required knowledge-sharing activities will be delayed or dropped. Knowledge access (and use) will be something that’s done as a secondary or tertiary activity, rather than primary. And activities such as knowledge article creation will be “saved for later” in the day and potentially lost to “more important work.” This can be a knowledge management success killer.
- Revising employee performance management frameworks to drive knowledge-sharing behaviors. Your organization’s people management frameworks need to reflect the importance of knowledge-sharing to each of individual, team, and business success. So, ensure that the revised set of metrics drive the right staff behaviors – and not the wrong ones.
- Focusing on brief articles, or answers, not overly-long knowledge dumps. Understanding that sometimes “less is more” – especially from the reader’s perspective. They just want a quick solution to their immediate need. Think of this more as “answer management” than knowledge management. And that the positive outcome of knowledge management success is not the creation of “War and Peace”-length articles but the use and reuse of focused, and thus easy to consume, pieces of help.
- Appreciating that knowledge sharing might be people, rather than text, based. While it’s great to capture and share text-based knowledge articles, it’s not always the best way to help people with their needs. Sometimes people are best pointed to other people (who can quickly help). For example, highlighting an available subject matter expert (SME) rather than requiring the searcher to trawl through thousands of captured words (in a knowledge article). This is now something that’s aided by AI and the creation of people “knowledge profiles” based on the work they undertake. So, this is what people actually know rather than what they think they know (and people might be SMEs without even realizing it). It also becomes more relevant as organizations grow and personal-relationship “spheres” become relatively smaller.
Dealing with technology and scale issues
There are also knowledge-sharing issues and barriers related to the scope and suitability of knowledge-sharing technology. Plus, the added complexity of change over time – whether this is related to the continued relevance of existing knowledge articles, the changing habits of employees, or organizational growth. These include that:
- ITSM tools offer knowledge bases rather than fit-for-purpose knowledge-sharing capabilities – and while the traditional ITSM-based technology definitely helps, a managed data repository (MDR)-approach will only deliver part of the required, and optimal, organizational knowledge-sharing capabilities.
- Traditional knowledge management capabilities have required end users to “do the leg work” – i.e. employees must seek out the help/knowledge they require, with it often only available in a single place (a self-service portal). Thus, accessing knowledge is a deliberate employee act that requires a focused effort.
- ITSM tool knowledge-sharing capabilities aren’t evolving to match consumer-world innovations – employees now expect corporate IT and services to match their personal-life experiences and expectations. Consumer-world mobile apps, social networks, self-service/help, live chat, chatbots, and other consumer-world capabilities all drive employee expectations of knowledge sharing.
- Knowledge bases can become the place where corporate knowledge “goes to die” – and it’s something that’s compounded when organizations overly focus on knowledge capture and neglect knowledge use (and thus its real value).
- Organizations that continue to struggle with knowledge sharing will also struggle with AI exploitation – the evolution of knowledge sharing is in its third phase. Progressing from the sharing of knowledge between IT support peers (Phase 1), through the availability of knowledge via self-service/help mechanisms (Phase 2), to the need for knowledge, information, and data to fuel AI capabilities (Phase 3).
Each of these knowledge management success issues can be addressed through the application of knowledge-sharing good practices and new approaches, including:
- Appreciating that there’s a need to supplement native ITSM tool capabilities. It’s not a decision that needs to be taken as a leap of faith. Instead, organizations that understand the value of knowledge – in particular how its use, and reuse, creates value (as well as saving costs) – can show the positive return on investment (ROI) of such an approach.
- Introducing additional ways to offer knowledge to employees as and when they need it. There has traditionally been two employee access points to (formally documented) knowledge. Firstly, MDRs – the knowledge base(s) – that were initially made available to IT staff and then extended, usually with different articles, to end users via self-service portals. Secondly, ITSM tools introduced in-ticket (and in-portal) knowledge features to automatically provide relevant knowledge as the employee types the need. From an end-user perspective, this still requires them to “go somewhere” to seek help (and knowledge) rather than having the knowledge come to them. With the latter mirroring what employees are now increasingly experiencing, and expecting, in their personal lives.
- Augmenting “basic” knowledge management technology with additional capabilities. Existing ITSM tools might already have some features that do this. For example, read-counters, end-user feedback mechanisms (such as “thumbs up/down” or “this is out of date,” and date-driven update flags). But technology can also do so much more to help – in particular, using AI and machine learning. From identifying knowledge gaps to the automatic creation of new knowledge. And the technology not only increases the volume of knowledge articles, but it will also help to ensure that knowledge stays relevant (and thus useful).
- Taking a consumer, rather than supplier, based approach. This is understanding that “size (or volume) isn’t everything.” Not just in providing easy-to-consume answers over potentially-bloated knowledge articles but also in applying the “Pareto Principle.” This is “that, for many events, roughly 80% of the effects come from 20% of the causes,” with 80% of end-user issues potentially covered by just 20% of the knowledge articles. This 20% should thus be the focus of early, and ongoing, knowledge efforts.
- Finally tackling organizational issues related to knowledge sharing. It’s something that will pay dividends now, but it’s also a must-do for the future. As already mentioned, AI technology will need knowledge, information, and data to work effectively.
So, all this hopefully gets you to where your IT organization needs to be for knowledge management success. But what about the future and the growing importance of knowledge management? What do you need to do to prepare for this? To help, you can read a paper I wrote for Kaleo Software: “Prepare Your IT Service Desk for Its Knowledge-Powered Future Now.” This is available on the Kaleo website now.
This 2018 knowledge management success article was updated in 2023. If you would like to read more about ITSM and ITIL, the following ITSM.tools articles might be helpful…
Principal Analyst and Content Director at the ITSM-focused industry analyst firm ITSM.tools. Also an independent IT and IT service management marketing content creator, and a frequent blogger, writer, and presenter on the challenges and opportunities for IT service management professionals.
Previously held positions in IT research and analysis (at IT industry analyst firms Ovum and Forrester and the UK Post Office), IT service management consultancy, enterprise IT service desk and IT service management, IT asset management, innovation and creativity facilitation, project management, finance consultancy, internal audit, and product marketing for a SaaS IT service management technology vendor.