Whether implementing a new Knowledge Management initiative or maintaining Knowledge Management in BAU, customer service organisations need to consider the following roles for a Knowledge Team. 

All organisations are different, so the size and scale of the team may vary, and you may have individuals performing multiple roles simultaneously. 

KM Exec Sponsor – This person represents the highest position in the organisation for Knowledge Management. This person supports the ongoing strategy of Knowledge Management and represents Knowledge Management at the highest level.

Knowledge Manager – The Knowledge Manager is the most critical role for KM success. They are accountable for Knowledge Management within an organisation. They work with the KM Exec sponsor to set a KM vision and strategy and provide leadership to the rest of the team to manage knowledge effectively. A Knowledge Manager needs to ensure they deliver continuous value to customers and frontline staff and share the value across all relevant stakeholder groups.

Knowledge Workers (Knowledge Analysts / Knowledge Engineers / Knowledge Editors / Content Editors) – These will likely be the most numerous role in the KM Team. They manage new and updated knowledge for customers and the frontline across the content lifecycle. In addition, they drive ongoing end-user adoption and engagement. They continuously improve customer and end users' knowledge experience using metrics and insights. 

Knowledge Architect – This role will depend on the organisation and the systems in place. However, they are responsible for the underlying taxonomy of a Knowledge base. They usually represent the technical requirements of the wider Knowledge Management team and work closely with the Knowledge Systems manager.

KM Champions – These frontline users work together to promote Knowledge Management best practices amongst the frontline and represent the end user's voice to the broader knowledge management team.

Knowledge Systems Manager – If you use an out-of-the-box vendor solution, you won't necessarily need this role. It depends on the system you are using, but this could be an IT, Developer or UX person responsible for the ongoing upkeep and maintenance of the Knowledge Management platform.

Agile – If your organisation follows Agile, you may need a KM Product owner and Scrum Master to help facilitate Agile methodology.

After finishing one of my previous blogs on user engagement with customer facing staff, I couldn't help but reflect on how brilliant the brain of a call centre agent is. When a call comes into a contact centre and is received by a top-performing call centre agent, amazing things happen in the agent's brain.

The Real AI (Agent Intelligence) 

Before the customer comes through on the phone, agents analyse what the customer might need based on the context of what is shown on the screen. As the customer starts talking, the agent deciphers which systems to use and knows how to answer the customer's question best without navigating the knowledge base. They get to the answer far better than any AI system would (at this moment, March 2023), and the customer is delighted.

Even when they don't have the answer, they know exactly where to look and what to do to get the information they need.

They end the call, and 10 seconds later, they do it again and again for 50+ calls in a day.

How does the agent do this? I'm full of admiration for customer-facing frontline staff.

Why should KM Professionals care?

"I've created content with the legal and compliance teams and agents just need to follow it. I know best!!" No No No hypothetical KM professional, that won't do.

I've always been a firm believer that KM professionals should be engaging with the frontline staff constantly. In customer service, agents are the ultimate "Customer" of Knowledge Management, and as such, Knowledge professionals should be asking how they can continuously offer more value from a KM perspective.

Agents' brains contain brilliant information; if KM professionals can utilise it correctly, everyone benefits.

• The gap between the worst and best-performing agents will reduce.
• Agents are happy to get the proper knowledge at the speed of conversation.
• New starters are not overwhelmed by jargon and can be more productive sooner.
• Tenured agents feel valued and offer more to the business than just answering calls.
• Customers get excellent service more consistently.
• Leadership teams achieve their intended benefits. 
• Knowledge Professionals get direct access to users' brains, so they don't need to guess what will work.
• Agent feedback could benefit customers across all customer channels.

What are the practical ways of doing this? 

Well, this is documented one of my previous blogs 17 Ways to Engage Customer-Facing Staff in Knowledge Management. But to summarise:-

• Involve users when kicking off a KM initiative
• Pilot with users
• Let them name the new tool
• Launch party with users
• Give out branded items to celebrate.
• Get users to help write content.
• Involve Rogue agents.
• Use secondments.
• Observe frontline staff in action.
• KM staff could take calls or chats.
• Ensure a robust feedback process.
• Set KM sharing objectives.
• Make Knowledge Management fun.
• Regular Roundtable sessions with users.
• Create a community of frontline users for KM.
• Knowledge Champions.
• Locate KM workers with the frontline.

Agents are brilliant and when Knowledge Management professionals show agents they are valued, great things happen!

So you've successfully launched a new Knowledge Management initiative; however, several years later, it is deemed a failure!
What happened?

Here are my top 6 reasons Knowledge Management initiatives fail,
the underlying causes, and the best way to mitigate them.

1 - Lack of Senior Management Engagement

Sometimes KM is treated as a one-off launch, with lots of excitement initially; however, BAU lacks focus. Therefore, you must actively engage Senior Managers in KM and show its benefits to the business on an ongoing basis. It's crucial that if organisational restructuring or role changes occur and new Senior stakeholders arrive on the scene, they see the constant value of KM. Without Senior Leadership support, funding and resources for Knowledge Management are likely to reduce.

2 - Content Quality

If the quality of content that customers and frontline staff access is poor, end-user engagement will suffer. 

Quality issues typically occur when you don't have enough people with the right skills to manage the content lifecycle. Quality drops when content authors are under pressure to deliver content quickly. Quality also drops if the frontline is not actively engaged through continuous feedback, so keeping an ongoing dialogue with the frontline and customers is essential. 

Poor content quality will impact: Findability, Readability, Accuracy and the Reliability of the Knowledge Management solution. Trust will erode with the end users.

3 - Lack of Frontline Staff and Customer Engagement

As well as content quality, if there are no ongoing adoption and engagement activities with the frontline and customers, then Knowledge Management will not meet the user's needs on an ongoing basis.

Users will stop relying on it and find other means to get what they need, for example, asking a colleague or team manager or putting their notes on the desktop—leading to inconsistent experiences, upset customers, increases in complaints, escalations and quality issues. Frontline staff will lose faith in knowledge management, which could cause a high attrition rate. 

4 - Lack of responsibility / accountability for Knowledge Management

This could be caused by a lack of clarity on roles and responsibilities. For Knowledge Management to remain successful in BAU, it needs:-

Ongoing Knowledge Management vision. 
Ongoing Governance, with roles, responsibilities and accountability for Knowledge      management, clearly defined. 
Knowledge management practices embedded into everyday processes. 

5 - Technology Issues

These can come in several forms: -

Knowledge Management is delivered as a Technology solution rather than a Business or Cultural solution.
The KM solution is over-customised or integrated into other systems without      consideration of the technical debt or the end-user experience.
The gap in expectations between technical teams and business users. 
Lack of ongoing technology roadmap for continuous improvement and innovation.
Technology outages, slowness, and features needing to be fixed.
Finger-pointing and apportioning blame between different technical teams or vendors rather than working together and collaborating.
Technology teams driving KM can lose focus on the end user. Instead, KM should be business-led with support from Tech.

6 - Lack of Obvious Value to the Business

Without a clear vision and a clear way of measuring and delivering value, people will not be aware of the ongoing benefits of Knowledge management and its progress. Negative perception (rightly or wrongly apportioned) is a killer concerning knowledge management and is challenging to change further down the line.

How to stop this from happening? 

The Knowledge Management Team and Knowledge Manager roles are vital in managing the above. They should consistently show the value Knowledge Management brings, working with end users and Senior Leadership to keep them engaged. Ensuring the Tech, processes, culture, governance metrics, and content quality are all in place and continuously improving for the business in line with the broader Knowledge Management vision.

These guys are the gatekeepers for excellent Knowledge management. 

Data’s impact on a company’s success is undeniable. Through it, you can learn how to serve customers and employees better, build professional partnerships, and create systems that fuel productivity.

A less-talked-about use of data is in knowledge management. If you’re unfamiliar, knowledge management is the act of collecting, sharing, and managing information and knowledge within a company and ensuring it’s accessible to everyone. 

You can use data to improve knowledge management within a project. But it starts with collecting the most valuable data for this purpose.

Collect the Most Useful Data

To use data to find areas of improvement in knowledge management for projects, you must first collect data that will help you do this. In other words, what kind of data will be most helpful in helping you better your knowledge management?

Data that gives insight into how your team uses your knowledge management system is a great starting point. You’ll gain insight into how each person navigates the knowledge management system for various projects. You’ll also see the information they use most when completing projects.

Armed with this information, you can conclude where more training is needed regarding using the knowledge management system. You’ll also learn which information is most essential to input to complete a project successfully.

Think about the customer, employee, and business data most helpful in improving knowledge management and focus on collecting it in abundance.

How To Best Collect This Data

Project managers can collect data in various ways. But the best approach is combining data collection tools with team feedback.

You should analyze every channel your customers interact with. Likewise, analyze the apps, software, and devices your employees use. Don’t forget about your company systems — data analytics tools are a must on those as well.

Project managers must also be intentional about collecting feedback from their teams. What are they saying about knowledge management? What do they think about it in terms of using it for projects? What are their suggestions for improvement?

Analytics tools and actual feedback are the best ways to collect data that aid the improvement of knowledge management in projects.

How To Use it to Improve Knowledge Management Within a Project

If you’re still unsure about data’s role in improving knowledge management for the sake of each project’s success, these specific examples should get you over the hump.

Identify weaknesses

Data, generally, is monumental in identifying weaknesses. You can use it to identify weaknesses in knowledge management and those in specific projects.

For example, let’s say your team is working on a recession-proof marketing campaign. In this case, you can use customer data to identify weak points in your content that don’t resonate with their needs or who they are in a recession.

In addition, you can look at the customer information you’ve input into your knowledge management system and see if it’s enough to support you in completing the marketing campaign. You may find that you’re missing critical customer data and can then add it to improve your system and project.

Data is instrumental in determining what’s lacking in a project or your knowledge management system.

Streamline communication and collaboration efforts

Two of the most critical factors in completing a project successfully are team communication and collaboration. Without both, completing a project and maintaining its quality is challenging. Knowledge management keeps teams on the same page, pulling from a single source of truth that streamlines communication and collaboration efforts.

You can use data to create a personalized intranet for your team within your knowledge management system. When it has all things company, customer, and project-related in it, working conditions get better, improving team and individual efficiency in the process.

When you know you’re striving for a knowledge management system that acts as a personalized intranet for your employees, you can document what that looks like. Then, you can weigh your intranet vision against your current knowledge management system to determine what you must do to get closer to your vision.

Putting the right data into your knowledge management system sets the foundation for a personalized intranet, streamlining communication and collaboration on every project.

Determine training opportunities

Much of using knowledge management effectively depends on how well-versed your team is in the system you’re using. If they can’t navigate it seamlessly, find the information they’re looking for, or find value in knowledge management, they won’t ever be able to use it to its full advantage.

On the contrary, the benefits are tremendous if your team knows how to navigate your knowledge management system, can find what they need for every project, and deem knowledge management useful.

The key is finding out where your team needs the most help regarding your knowledge management system — data can help you determine that.

Collect data on how your employees use your knowledge management system. Find out how they navigate it. Study how accessible the system is for each team member. Understand how easy it is for them to find information and what info is missing that would move projects forward faster.

All of this data can give you insight into what your team needs training on when it comes to knowledge management.

Conclusion

Knowledge management is one of the best tools a business can have. It ensures you collect, organize, and manage crucial organizational information appropriately and that it’s accessible to every employee. Make an effort to continuously improve your knowledge management system with the help of data. Your team and business will thank you.
 

Resilience isn't something we normally talk about with knowledge management. We talk about document repositories, collaboration, artificial intelligence (AI), help desks and knowledge centered support, communities of practice, lessons learned and continuous learning, all kinds of things, really. But we don't often talk about resilience when it comes to knowledge management.

And yet, resilience is very important to knowledge workers and thus knowledge management. It helps us get up when we fall. It helps us to keep going, keep asking questions, iterating, and coming up with new solutions, problem solving. It drives us forward and if knowledge management is about (continuous) learning and about helping people to have the knowledge they need to do their jobs, then resilience is probably something we should be talking about.

Knowledge workers are human, after-all. We are not robots; we need to find ways to bounce back when things don’t go as expected. If we as knowledge managers are trying to make the lives of our colleagues, fellow knowledge workers better, then resilience should figure into that.

So as Knowledge Managers where does resilience come in?

Resilience comes in, in trying to help people to have the courage to ask the questions, to find different ways of looking at things, especially when they have failed, or things have not gone the way that they expected them to.

Historically, a lot of knowledge management and knowledge work has focused on the analytical processes of writing things down, of capturing knowledge and putting it in a technology platform to find and reuse later. However, as we enter the mid 2020’s, the question of what knowledge management practitioners need to do to enable knowledge workers in the age of AI, constantly changing technology, relentlessly evolving knowledge, rears its head and is increasingly up for debate.

Do we give them another technology to help them find and summarize documented knowledge? Do we help them communicate and share information, opening-up spaces for conversations? Do we help them tap into their inner artists and learn resilience, curiosity, the courage to iterate, share, and to trust?

Yes.

Knowledge is human, trust is human. My vote is on the human side, tapping into our inner artists and reactivating the creativity that has been educated out of us.

Conversation is certainly part of that. The art of conversation, the art of dialogue, the art of sharing information and knowledge so that people can understand it, that's human. The art of critical thinking so that people know what's real and what's not. What's to be trusted and what's not. That’s what Knowledge Managers need to support in their programs. The tools and the processes are only part of the answer. Helping the humans be better humans, to be resilient, that's the real solution to knowledge management.

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