Thursday, December 01, 2022

Skills Building and Knowledge Management. Is there a connection?

I was reading something in my LinkedIn feed about the premium put on skills (vs. academic pedigree) in the current job market.  There is nothing new about the fact that employers want employees who know how to do things rather than employees with a lot of book knowledge and limited experience in how to apply that knowledge.  There is also something inevitable about new generations of employees lacking experience in applying knowledge and needing to acquire "know how" since most of that valuable knowledge is acquired through... experience.  Employers want some specific technical skills, but they also want everyone to have the necessary soft skills to operate effectively in the organization.  

This may be a case of hammer looking for nails, but what if we were to consider Knowledge Management as a possible solution?  Even if KM is not a direct solution to the skills issue, let's consider the connections.

What are the top soft skills required by employers and how are they connected to Knowledge Management?

  • Cognitive skills (critical thinking, analytical thinking, sense making):  Critical thinking is the process of analyzing a problem, situation or issue based on evidence and relevant information.  It is also about sense making, interpreting information to make better decisions.  A Knowledge Management initiative typically makes assumptions about employees' cognitive skills.  It would not hurt to revisit those assumptions.  When employees don't have time to think, they cannot engage in knowledge management. When knowledge management is prioritized, employees make time for thinking, whether through individual or team reflection activities for example. 

  • Interpersonal skills, teamwork and collaboration:  Whether through communities of practice (CoP) or task-based teams, employees need to develop the skills needed to interact with each other to get the job done.  A knowledge management program with a strong component focused on connecting people can support social learning, strengthening individual skills and contributing to a collaborative organizational culture. Many job-specific skills can be practiced in the safe environment provided by a CoP. 

  • Oral and written communications skills:  Having access to an endless flow of information in our modern digital workplaces makes it critical to develop the ability to understand, analyze and synthesize information to share and present in different ways. Managing information flows is critical.  The educational system teaches how to create summaries or books and other materials.  Synthesizing for action in a workplace context requires some adjustment.  Knowledge Management initiatives can help employees learn by doing, engaging employees (not just KM staff) in synthesizing activities, whether through oral presentations or in writing.  New communication channels (including internal enterprise social networks) provide great opportunities for everyone to practice writing succinct, yet powerful messages that can potentially influence many across an organization, helping to build internal thought leadership.

  • Agility:  Learning and growth mindset, adaptability, coping with uncertainty.  When knowledge management is understood as facilitating dynamic knowledge flows, it is well aligned with an agile organizational culture where expertise is valued but new knowledge is constantly emerging and innovation is perhaps valued more than the strict application of lessons learned from the past which may or may not be applicable in the present and future.  This leads back to the continued importance of critical thinking as THE skill that will always be needed... especially in a context where advanced in AI/ML are often presented as miracle solutions.   

It seems I am arguing that Knowledge Management programs can help build critical soft skills within organizations.  That sounds obvious but I'm not sure it has been argued this way before.  I've read many more papers and blogs about the skills needed for knowledge management implementation.  This is looking at skills via a different lens, suggesting that Knowledge Management helps develop the skills. 

Related paper:  Linking Critical Thinking and Knowledge Management:  A Conceptual Analysis, Sustainability, 2021, 13(3). February 2021. 

Tuesday, November 22, 2022

From "Yammer vs. Teams" to Yammer in Teams

I have managed an internal Enterprise Yammer network for the past three years.  It has been an interesting evolution, both in terms of the maturity of our network but also the constant "upgrades" brought on by Microsoft.  

Adaptability is becoming an ongoing theme.  There is no point in complaining about constant change.  Constant change is part of the new normal. Change has always been "normal".  The new normal involves more rapid change.  Three years of rapid change feels like an eternity.

We re-started in 2019 with an underutilized Yammer network. While Yammer was technically available to staff since 2016, it had been launched in a meaningful way.  The new corporate strategic plan launched in 2019 created new opportunities to leverage Yammer and engage our global workforce more effectively.

And yes, we immediately encountered the confusion and at time frustration that employees felt with the multiplication of tools for collaboration and communications.  In particular, it wasn't always clear why people should use Yammer when Teams seemed to be the way to collaborate.  By the time COVID-19 sent everyone to work from home, Teams was where people worked with their immediate colleagues, and Yammer became the place where you could share much more broadly and keep up with corporate events even if you were not in the office.  That was what I was saying to anyone who would listen but it took a while to sink in.

As of the end of 2022, there are still a few who think Yammer is a waste of their time and prefer to use other tools (beyond Teams). However, a number of factors have helped us get in the right direction in terms of finding the right balance between Yammer and Teams.

1. Leadership Support: Yammer has had strong support from the very top of the organization to move from corporate emails that went to everyone to Yammer announcements in the All Company community.  This has led to a significant reduction in corporate communications via email listservs and created more opportunities for staff to engage with leadership in Yammer.  Leadership engagement in Yammer is critical and it should be several layers deep.  

2. Communications and guidance around what to use for different purposes. When should you post in Yammer vs. in Teams.  In addition to general communications via internal blog posts and in Yammer, it became critical to control both the proliferation of Teams sites and Yammer communities.  Additional governance was put in place first to control the creation of Teams site, and later, the creation of Yammer communities.  The added burden on IT was well worth it because it created opportunities to redirect people to the appropriate platform when IT received requests for either of the tools.  This was also facilitated by the fact that with the exception of a few early communities that remained closed, the relaunch of Yammer in 2019 was based on the assumption that all new communities would be fully open.  There was no rationale for closed communities in Yammer.

There are still legacy instances of Teams sites that should have been created as Yammer communities.  In most cases, these were created by people who specifically wanted a closed group approach. However, it goes counter to the corporate approach of having open, accessible conversations to harness collective knowledge.

3. Integration of Yammer in Teams. Yammer communities in Teams (when it was still called the "communities" app) were not as functional as the Yammer app itself, but they provided another way to access Yammer without leaving Teams.  Once the Communities app was replaced by Viva Engage, it became clear that for most staff who did not already visit Yammer regularly, the Viva Engage app in Teams would be an opportunity to engage more often.  Only, several challenges emerged around the same time:
  • Notifications changed.  Announcements no longer automatically went to all community members' email inbox.  The community admins must specifically select "send to all" every time if they want to make sure all community members see the announcement as an email. 
  • Notifications in the Teams feed only cover announcements.  People need to understand the full set of notifications (in Yammer) to get the specific highlights they want either as email notifications or in a more limited manner, in Teams. 
  • Announcements became overused as the primary mechanism for getting "views" on messages and the great majority of posts became announcements.  These generated reactions, but very limited engagement in the form of comments or replies. The Yammer network was turning into just another channel for corporate communications, displacing email announcements via listservs but not really creating engagement.
Status update as of mid-November 2022:
  • We are seeing increased active engagement (posts) in the All Company community.  This is very encouraging because these posts come in two varieties:  1) engagement with polls and questions that are tied to corporate campaigns and posted by corporate leaders; 2) posts by project leaders describing project activities, progress, success stories.  It is particularly encouraging to see the number of views and level of engagement with posts in the All Company that are NOT posted as announcements.  
  • Smaller, topic-specific communities are not experiencing this increased engagement.  This is partly due to lack of active community management.
  • New Features:  I am still somewhat hesitant to launch Storylines and Stories.  There is no added cost but launching these two new functionalities in Viva Engage would create added complexity in terms of communications.  We need to rationalize these additional tools based on existing and emerging corporate strategic plans (and say "no" or delay as needed).  In addition, without being able to test/pilot with a smaller group, we will inevitably be very reactive in our communications, addressing questions and concerns as they are experienced.  We can also wait for other organizations to launch and look out for their immediate lessons.

    Caveat:  There is a broader layer of project communications that happens completely outside of my purview. Therefore I am only seeing a narrow slither of our internal communications.

Sunday, November 13, 2022

Some Thoughts about the Wisdom at the Top of the DIKW Hierarchy

The Data-Information-Knowledge-Wisdom hierarchy, sometimes called the DIKW pyramid, is a model originating in information science that is commonly used in Knowledge Management.  It has been critiqued before (1) and that is not my intent here.  I still find it relevant and useful as a trigger for deeper thinking and conversations. As a side note, the original model is a simple triangle, not a pyramid.  

In my recent adaptations of the DIKW hierarchy/triangle, which I have transformed into a more complex pyramid model with a base, edges and multiple faces representing different aspects of an organization's knowledge ecosystem (more about that in a future post, perhaps), I have dismissed wisdom and replaced it with innovation.  I had some reasons for doing that but I am now reconsidering and trying to find a way to re-inject some wisdom in the model.  

While attending this year's KMWorld conference, which is heavily focused on the data and information layers of the hierarchy or the bottom of the pyramid, I only heard the word wisdom once.  It was in the last keynote panel and not surprisingly (2), it was brought up by Larry Prusak who joined via a remote connection.  That is what brought me to reconsider my dismissal of wisdom.  

I would rather inject wisdom throughout the model than have wisdom as an outcome or ultimate level in the hierarchy. We certainly need wisdom to address the challenges of the data and information layers of this hierarchy.  Lots of people are becoming very knowledgeable about AI. Do they all have the wisdom necessary to apply AI?  Is there a mandatory course on the wisdom of AI in Data and Information Science academic programs?  Is there a course on wisdom in KM academic programs?  I have not addressed it in any substantive manner in my own teaching of KM (3) and that could be a gap to fill.  

If knowledge is the capacity for effective action, wisdom brings in the notion of sound judgment in the application of that knowledge.  For example, I may have knowledge of physical techniques to disable someone which I have learned in a self-defense class and that gives me the capacity for effective action.  If I have enough wisdom to accompany that knowledge, I should have enough good judgement to know when to run away and when to stand my grounds and fight (something like that).

If talking about knowledge in a way that clearly differentiates it from information is already a challenge in organizations, talking about wisdom further elevates the challenge, especially if conversations around profits and bottom lines are the dominant narrative.  However, I have also found that as long as the conversation provides some value and is perceived as insightful to the participants, all is not lost even if it doesn't immediately address a corporate challenge that is top of mind for corporate leaders. There is a time and place for these conversations. Serendipity also plays a role.

As a result, I am on a quest to find ways to inject wisdom into conversations or perhaps just to have conversations about the role of wisdom in organizations.  How can I seed conversations around wisdom? How do I connect these conversations to a sense of WIIFM (what's in it for me?) so that it's not an impractical philosophical discussion.  It could very well be that it connects to employee engagement and wellbeing, a sense of belonging to a community that cares beyond the bottom line.  Wisdom is about doing the right thing, working towards the greater good.

There is another term I am trying to use more:  collective intelligence. I'm wondering here if I'm not using the word "intelligence" in "collective intelligence" to mean the same thing as wisdom.   However, if I say "collective wisdom", I don't want it to be confused with the wisdom of the crowd. There is a place for the wisdom of the crowd but if the wisdom of the crowd is the folksonomy, collective intelligence is the ontology and I am more interested in the ontology.  And finally, here is an adjacent question:  Is there a difference between a smart organization and a wise organization?

One aspect of collective intelligence is that the whole is greater than the sum of the parts. As individual employees, we cannot know or do as much with our individual knowledge as we can as a collective.  The collective intelligence of John and Jane (John/Jane) is bigger than the the sum of John and Jane's knowledge (John + Jane).  When John and Jane collaborate, they unleash new capacities for collective action.  When John and Jane collaborate, do they also become wiser?  What's the connection between collaboration and wisdom or doing the right thing?

The leap or missing piece between the capacity for effective action and the wisdom to activate that capacity at the right time and in the right place seems to be "agency".  More about that in a future post perhaps. 

(1) Weinberger, D. (2010). The Problem with the Data-Information-Knowledge-Wisdom Hierarchy. Harvard Business Review.

(2) APQC (2015). Big Thinkers. Big Ideas:  Larry Prusak  -- practical wisdom.

(3) George Mason University, Organization Development and Knowledge Management Program, Knowledge Management and Collaborative Work.  Syllabus, Fall 2022

Tuesday, October 18, 2022

An Ecosystem Approach to Blend Learning and Systems

In the previous blog post, I touched on the need to blend systems and learning for a successful Knowledge Management program.  When I teach Knowledge Management, I talk a lot about methods, tools, approaches and the like, but in the real world of KM in organizations, there are very few people who speak that language, so the KM practitioner needs to work with practical examples, preferably focusing on processes that have an immediate and clear impact on the business' performance. 

Here is a task example:  

Jane is a relatively new employee. She is climbing the learning curve really fast, with some help.  She is working on a proposal team and she has been given the task of writing the past experience section.  She has never done this task before.  She needs to find information about relevant company past experience that can be used in the proposal. She has been given some general advice about where to look (past proposals, the repository of project documents, etc...) and the names of a couple of past projects and proposals she should look up because they are likely to be relevant.

This is not a simple task of retrieving some existing documents and doing a cut-and-paste job.  It requires some understanding of the proposal itself to transform existing information into an accurate, yet tailored rewriting to meet the specific needs of the proposal.

In the process of completing this task, Jane will gain valuable experience in at least three key areas:

  • Searching company databases
  • Combining/recombining information to create a new, tailored version of that information
  • Receiving and integrating feedback from proposal team members

Assuming well organized Knowledge Management systems, Jane will be able to spend a limited amount of time locating and retrieving relevant documents from the databases, and more time applying critical thinking to create the tailored version of the document.  

Assuming a learning-driven organization, Jane will optimize her learning by a) attending training for this  task (if available) and/or reviewing existing written guidance for this task as soon as he/she is given the task; b) receiving the support of a task-specific mentor throughout the process; c) reflecting in action; d) reflecting on action. 

Reflecting in action might mean that while Jane is search for a past proposal, she comes across another proposal that looks similar and might also be of interest. She pauses briefly and realizes that the proposal team lead who gave her the list of other proposals to look up may not be aware of this information she has come across.  She needs to decide whether to stick to what she has been asked to focus on or dig a little deeper into what she has come across.  Reflection in action may result in a quick insight that results in a slight change in direction, a decision made while she is completing the task.

Reflecting on action happens after the task has been completed and allows a look back to reflect on what has already happened and what could have been done differently.  In a learning-driven organization Jane will participate in the proposal team debrief of After Action Review (AAR), which will cover the entire proposal process. However, there is a lot that Jane can learn about her own task and how she handled it that will not necessarily be discussed in the team debrief. If Jane didn't realize that other projects might be relevant while she was gathering information (during the action), she might have that insight when she pauses to reflect after the action, perhaps in preparation for her participation in the team debrief.  

Assuming the proposal team debriefs are done consistently across the organization, the collection of debrief notes is a gold mine for analysis, to identify pain points and improve processes, existing guidance documents, and training, and continuously update information found in the "systems".  In most cases, systems are not self-sufficient and do not update themselves automatically with fresh information.  Jane, or someone on the proposal team, is going to be responsible for uploading the final version of the proposal and past experience section to the appropriate repository and add the necessary metadata according to a well-thought out taxonomy.  

Assuming Jane brings up her insight about other projects to the team debrief, it might be added as a good practice in the existing guidance.  It could be integrated as guidance to the proposal lead:  When guiding the past experience writer to specific projects and proposals, don't limit yourself to projects and proposals you know personally.  And it could be integrated as guidance for the past experience writer to "use best judgement when looking up information and don't limit yourself to the proposals and projects you have been told to look up."  

We want information to be available at the click of a button.  That gives us more time for processing that information, applying critical thinking and transforming information into actionable knowledge.  Most of the technology we use today to help organize our information so that it is easily accessible is helping with efficiency and speed in retrieval.  The technology does not do the thinking for us.  With AI and machine learning, some of that initial thinking, parsing and filtering of information sources will be more automated. 

Continuing with Jane's task example,  the proposal lead and others on the team may guide Jane towards specific existing proposals or projects that are likely to be relevant to the task.  These recommendations are based on one or two individuals' knowledge of prior projects and proposals.  In a larger organization, that could be very incomplete knowledge.  There is significant potential for missing out on relevant information.  Jane, during the search of the databases could encounter new information, but it would be totally dependent on her to engage in reflection in action and to pro-actively bring it up to the team.  That simple action will be dependent on the organizational culture and psychological safety the team.  Proposal teams can be high pressure, and even if the organizational culture promotes psychological safety, there can be subcultures that are more intimidating.

In the near future, the organization could use AI and Machine Learning to efficiently and automatically read the RFP, identify key components, then search the company's databases for all the relevant documents, and either spit out a list of all documents, sorted by relevance, or even draft a summary of the information that could serve as Jane's first draft.  Obviously, there is still need for a human applying critical thinking to decide how to adjust this first draft, but over time, assuming machine learning works as it should, the first drafts would become better and better.  The AI might even learn the organization's writing style if it is given training data based on the organization's existing materials.

Jane's task was relatively simple, yet exposed many connections between people and systems.  Expanding the task to the broader proposal process would expose hundreds of tasks and associated connections between systems and the people who maintain and use them.  And the proposal process is not totally isolated from the rest of the organization since as we saw from Jane's task, it is connected to past project experience and organizational knowledge. There is a broader, dynamic organization learning ecosystem.

All this requires a comprehensive framework for thinking through the tasks that Jane and other employees across the organization have to complete, establishing clear processes, defining roles and responsibilities, setting up user-friendly, integrated systems, and an overall governance that allows for seamless embedding of learning processes and systems.