Here’s what you need, to “organise” serendipity and knowledge sharing
Your knowledge sharing ecosystem has two parts to it - tools and people. We've already discussed the capabilities your toolset needs.
- Start with a systems audit. Map your systems across two axes.
- Audiences and sources (known or unknown)
- Content/ questions/ insights (known or unknown)
- Aim to have coverage across all four quadrants of the above matrix and use that to drive decisions about investments in an improved toolset.
- In addition, staff your knowledge management team with community managers at the level of each community and curators at the organisational level.
A functioning collaboration and knowledge sharing system is essential for a distributed organisation. More so for companies and teams that want to work asynchronously. If you can’t trust your systems to help you find information and answers to your questions, you’ll default back to a meeting culture. So whether it’s explicit, stable knowledge that goes into your handbook, or tacit knowledge - the information needs to be easily available. This is the last of my posts about piecing together your knowledge and collaboration strategy and toolset. Here’s what we’ve already discussed.
First, I addressed the key consumer internet capabilities that your knowledge ecosystem needs.
Next, I explained why you need flows and weak ties, besides the traditional approach of creating knowledge stocks.
In this post, we’ll discuss how you can enhance your knowledge ecosystem by building on your existing collaboration stack. I’ll also go over how to create the right team of people to govern, curate and nurture that platform.
Audit your current systems
To simplify your system analysis, start with evaluating your existing toolset across two dimensions.
Audience and sources - How easy is it to identify your knowledge source and intended audience?
Content, questions and insights - How easy is it to define your content’s insights and/or questions you seek to answer?
Audit your collaboration and knowledge sharing systems
This analysis yields a 2 x 2 matrix like the one above. Let’s dive deep into each part of the matrix.
| Quadrant | Audience & sources | Content, questions & insights | Possible tools |
|---|---|---|---|
| 1 | Known | Known | This is the most addressed quadrant for modern enterprise software. You know what information you have or are seeking. You also know who you’re sharing it with or who you’re getting it from. Team collaboration tools like mailing lists, team sites, chat groups and collaborative documents are ideal for this combination of people and knowledge. e.g. Workspace by Google, Office 365, Notion, Basecamp. |
| 2 | Known | Unknown | On the internet, we follow people, blogs, social handles or websites without being able to predict exactly what value we’ll get. We find content creators who represent our interests and we bet that they’ll produce useful content for us. This is a two way street and just as we follow people, some of them follow us back and the interactions are richer for it. e.g. Workplace from Meta, Yammer, P2, Lumapps |
| 3 | Unknown | Unknown | This is where the age of intelligence has come alive on the internet. The internet knows us. A bit too much you may argue. Your social networks, digital assistants, news and entertainment apps make “intelligent” recommendations. I’d grudgingly admit that this does enrich our digital experience. There’s the concern about privacy, no doubt, and enterprise software needs to be doubly careful about this concern. Let’s not discount the role of “digital exhaust” here. When you come across interesting content, you follow the author and discover their, other, as-interesting content. One discovery leads to another, much like a trail of breadcrumbs. e.g. Workgrid, recommendation engines within your quadrant 1, 2 and 3 tools; custom recommendation engine; employee profiles on your enterprise social network. |
| 4 | Unknown | Known | Often you know what knowledge you’re looking for but don’t know where to look, and who could give you that information. Google comes to the rescue on the internet and at work, enterprise search comes to the rescue. E.g. Elastic, Glean |
Once you’ve completed this exercise, you’ll discover how you can improve your knowledge sharing infrastructure. The toolset should ideally have coverage across all four quadrants. This system audit can help you propose an investment roadmap to your company. It can also give executives the information they need to prioritise investments.
All systems need people
A truly democratic and free-form system allows everyone to contribute to the collective, just like Andrew McAfee said - free-form, without friction. The emergent part of McAfee’s universe, however, needs two levels of “sense making”:
People involved in your knowledge ecosystem
Community managers: This group should exist at every community, practice, centre of excellence or department level in your organisation. While the best content will bubble up, these people help add metadata and organisation - so it’s easy to access the “state-of-the-art” at a later point in time.
Curators/ Knowledge managers: These individuals help create an information architecture that mirrors the structure of your organisation. Their responsibility is to ensure that your knowledge ecosystem is “browsable and navigable”.
Think of this sense making structure as similar to that on Wikipedia. While each one of us can enrich the system with our contributions, dedicated editors help interlink pages, and to organise them in the right hierarchy. Editors also watch pages, so they can review changes when necessary.
Today, AI can handle many of the mundane tasks that a community manager or a curator would do - adding tags, updating metadata, creating newsletters and digests. In case you’re able to get to this level of sophistication, your community managers and curators can take charge of more human activities. Here are some indicative activities that your community managers and curators can take part in.
Being cheerleaders and creating opportunities for people to connect outside the system.
Building personal connections with and between valuable contributors across organisational boundaries.
Breaking silos where they may exist.
Fine tuning recommendations and search results.
Blurring the boundaries between work, knowledge sharing and learning by embedding the content creation process into work itself.
Enabling peer review and feedback mechanisms for content.
Helping people get answers to unanswered questions.
These sense-making roles are the building blocks for nurturing communities and knowledge sharing in a distributed workplace. Successful distributed organisations are “intentional” about everything they do, as you’ve noticed, with all the advice on this blog. Organisations that care about communities, knowledge sharing and serendipity, can’t leave this to chance alone.
“The real challenge of remote work isn’t that it somehow erases the mysterious serendipity of magical office collisions. The problem is that making connections digitally requires enrollment and effort. If we do it with intent, it actually works better.”
With the right systems and the right people in community management and curation roles, you can brew the perfect storm of “organised serendipity”. I daresay, that this can often work better than the proverbial watercooler meeting. I hope this series of articles helps you reimagine how knowledge sharing could work in a remote-first, asynchronous organisation.
Regardless of how you think about remote or hybrid work, this will eventually be a problem you need to address. I’m sure I’ve glossed over several complexities, so give me a shout if you’d like to talk about how to develop your knowledge system for this new decade. I’ll be happy to chat!