Managing Knowledge on Slack 2.0

SummarySlack Logo

The proliferation of Slack into the work place has been just amazing. While the jury is still out whether Slack can replace emails, however there is no questioning the important place it has come to occupy when it comes to communication and collaboration in several businesses. While Slack has many advantages as compared to previous enterprise messaging and collaboration tools, however managing knowledge on Slack is still a challenge. This article explores the importance of knowledge management on Slack, some of the challenges and why we need a tool that has been specifically built for Slack to actually enable knowledge management on Slack.


We are all in love with Slack. Slack has over 4 million users now and continues to grow at a rapid pace, turning the enterprise communication industry on its head. A survey conducted by Hiten Shah of CrazyEgg in 2015 reveals the reasons why people use Slack – the significant ones being reduction in email volume, better interface and lots of Integrations.

Slack wasn’t the first messenger service that entered the enterprise arena. Yammer, Lync, and HipChat are some of the other chat and messaging services for business and enterprise.

Slack User Growth

Slack has a few unusual features that make it perfectly suited for work, including automatic archiving of all your interactions, a good search engine and the ability to work across just about every device you use. Another reason is that Slack is fun to use. Part of this is the helpful Slackbot that guides users and provides assistance with a playful, yet helpful personality as well as the myriad of other bots that are available to add in. Besides Slack also brings a feeling of intimacy with co-workers on the other side of the country.

When email just started out it was still a luxury; not many organizations had email. Over time, it has become an indispensable means of communication. Team messaging is heading in the same direction, and as they take the center stage in business communication, other enterprise tools too need to adjust and build on the new workplace normal. One such tool is knowledge management: how we capture, organize and share knowledge within teams.

Should We Care About Knowledge Management in a Slack Setting?

As a recent report from the Society of Marketing Professionals (SMPS) notes, as we “transition from the Information Age to the Knowledge Era . . . continued training of both marketing and technical staff is vital to a firm’s longevity. So while ignorance may be bliss, knowledge is indeed power.”

Knowledge sharing is probably the most common type of interruption at any company. Team members frequently have to share their knowledge with other team members. This is where it can become quite costly, certainly in terms of employee productivity. A lot of companies don’t have a robust enough process and lose knowledge when employees move on or change roles. They lose their team’s deep smarts: the skills and know-how that have taken a lot of time and effort to cultivate. The cost of this loss is high.

Email, by design, has an inherent filter built into it. To put something down in an email and send it out to people (and have it stay in their inboxes), it had to be sufficiently important. By contrast, chat-based tools such as Slack simply do away with this filter. While this may result in more noise, but it also results in higher conversations, more sharing of data and files. With a more intimate team more conversations can happen in channels, which anyone on the team can join. Those conversations in Slack are what create that magical sense of “ambient awareness” of what’s happening, as well as an archive of organizational knowledge over time. Hence an increasing need to better capture, organize and share all this knowledge.

Challenges of managing knowledge in Slack

Slack uses a product architecture that is based on streams of data ordered by time. That means, by essence, things will get lost as new stuff comes up in an endless waterfall of information. For group chatting and social networking, this is extremely useful. But, for managing knowledge and making it accessible, could become a nightmare

Here are some of the reasons why managing knowledge on Slack can be a challenge:

Information Overload

New knowledge is organically created and shared everyday on Slack, but it quickly moves out of sight in the constant stream of new updates. This sometimes makes it challenging to find, record and share that fleeting knowledge.

Take one look at any team’s Slack channel, and you’ll find people having casual conversations, sharing everything that they would share in an email, including pieces of information that they want their co-workers to have easy access to (like in an email where you bolden or italicize parts that need their attention) – An important link, a piece of code that needs feedback, a file that needs to be viewed, a process document, an important topic that needs discussion. Since Slack is moving fast, most of these pieces of information or knowledge, are lost in the thread.

Users shouldn’t have to always be there just so that they don’t miss out on the important things shared. The chat history becomes way too big for users to mine all the important things they’ve missed out on.

Repetitive Questions

A challenge that several teams face with Slack is repetitive questions that clutter Slack channels. For team members, repetitive questions are annoying and reduce their productivity. Slack is great to preserve conversations but not so for finding answers.


Search in Slack is actually pretty good. Not only is Slack good at retrieving past messages and conversations, but anything that is linked to in Slack or attached as shared objects (text related or with text metadata) in Slack all become searchable. The challenge here is not the search engine itself but the fact since the platform generates so much conversation, getting to the right knowledge actually takes a lot of time. Also, finding related threads and discussions across channels can be cumbersome in search when different terms (synonyms / fungible technical terms) are being used, even if search is good.

There are also situations where you know a specific person uploaded a file but you can’t remember what it was called, or someone talked about a particular subject but you can’t remember who. This makes the information particularly hard to find using Slack’s existing search, and the information gets lost in the ‘noise’ of the channel. This problem is compounded by the high numbers of messages that Slack processes.

Slack Search


It’s often hard to find specific things (documents especially) and even harder to aggregate bits of information to make sense of what’s going on in the environment. Slack way to unlock what’s going on at a “higher level”, aggregating conversational data to find trends that would go unnoticed at a lower level and remain lost in the noise of the conversation.

An important feature of knowledge management is to elicit not just the explicit knowledge shared by people but also the tacit knowledge that can be built by analyzing user behavior and actions. This can be immensely beneficial for organizations to improve their productivity.

Knowledge Management framework

We can apply the model of knowledge activities based on Probst’s building blocks of knowledge management (Probst 2002) to understand how Slack plays a role with respect to a knowledge management framework.

Probst KM building blocks

Probst knowledge activities

If we focus on the application of knowledge within the activities of business process, we see that:

Knowledge generation

Knowledge generation can happen:

  • Internally i.e. knowledge is created within the organization by employees or
  • Externally i.e. knowledge is created together with partners or customers

And knowledge generation includes both creation of new knowledge as well as construction of existing knowledge. Slack does really well in generating knowledge, especially given the collaborative processes of knowledge building.

Knowledge transfer

Knowledge Transfer is basically sharing of knowledge which also happens on Slack but with its own limitations. E.g.  although knowledge in Slack channels can be searched but those in Direct Messages can get lost. Similarly sharing knowledge with external audience, e.g. with customers or channel partners, can be a challenge.

Knowledge organization

The organization of knowledge is building the relevant metadata and taxonomies so that its categorization and access can be improved and secured. The only knowledge organization we can do in Slack is associating it with different channels.

Knowledge Saving

Although Slack maintains a log of all conversations but the possibility to distribute this or refine or perform any intelligent operations on it is not possible.

Does this mean Knowledge Management Cannot Happen on Slack?

Absolutely not. Slack cannot do everything for everyone. And this is why they have created an app marketplace to allow others to build applications that plugs these gaps. Slack’s API’s are also very well documented and they actively support the community in developing helpful extensions to the Slack environment.

The early adopters of Slack were developers, and we can take some cue from them on how they managed their knowledge. The organization of conversation into channels combined with integration of tools such as Trello, GitHub, SVN etc. really helped to efficiently access the needed information and reduce redundancies.

These tools helped users to identify relevant or needed knowledge, follow the progress of a task or project and being aware of dependencies or responsibilities by providing notifications for the tool itself. In fact integration of these tools increased awareness about what the other is doing and what is expected from one, because there is more synchronization and each time for example a card moves in Trello, users get a notification. At KnoBis, we use Trello a lot and the Trello integration has been incredibly useful to us. It automatically posts to our #engineering channel every time a team member adds an update to product backlog board.

This way, Slack included the identification of knowledge, which was stored elsewhere. Slack is used as a central contact point to summarize knowledge that existed on other platforms.

As Slack extends usage to other cross functional teams, there becomes a need for a broader knowledge management system to enable similar knowledge sharing and capturing

Knowledge Management for Slack needs to be thought differently

Slack’s features and uniqueness, which of course makes it more popular, also means that knowledge management for Slack needs to be thought differently. Most existing knowledge base softwares were developed before the era of enterprise messaging and aren’t able to latch on to the uniqueness provided by these platforms, such as:

Conversations as Knowledge

More often than not, knowledge in Slack gets built as casual conversations and not necessarily long form rich text articles or documents. With conversations, the context and history is there to be seen and can be incredibly valuable for someone to understand the background. This is very different from traditional systems, which approached knowledge mostly as rich text articles.

Introduction of Bots

While bots have long lived in the quieter corners of the Internet, Slack is pushing it into the mainstream. Bots are great at making sense out of lots of different types of information (schedules, meeting notes, documents, notifications from other business applications), and making all of that data more useful by allowing people to interact with it like they would in a conversation with a person.

Slack bots range from the obvious—bots for recognizing good work, posting photos, translating text—to the utterly inane, like playing poker. Another tells you who’s talking too much, seemingly to shut them up. There’s one to notify you each time your startup is mentioned somewhere online, streamlining that whole wasting time on the Internet thing. They absolutely can save you time.

This of course presents a very exciting opportunity for knowledge management as a “knowledgeable bot” can answer a lot of questions for team members without them now needing to disturb their team mates.

Text Editor

Most traditional knowledge management systems tend to support WSYWIG editors that do not support Markdown, while Slack uses Markdown. This can create challenges when either capturing content from Slack or posting it to a Slack channel.

Slack APIs

Slack doesn’t allow integrations to create any custom views, instead limiting apps to plain or lightly formatted text. As a result, complex integrations generally have a pseudo-command-line interface, requiring one command to display information and yet another to act upon it. This can make it a bit of challenge for knowledge bases that often depend on a lot of multimedia and metadata for each knowledge content.


It is important to note that Slack doesn’t replace everything. Dave Teare, founder of Agile Bits (developers of 1Password), recently wrote that his company’s “Slack Addiction” led to “using it over all the other tools at our disposal,” which meant that employees posted support issues and development issues into Slack instead of ticketing systems and knowledge bases. This is a classic example of what happens when we try to substitute Slack for everything.

Slack does well to sit alongside those services for conversational interactions and sharing results out of them. It isn’t going to replace a social search or a document management service or a collective aggregation service like KnoBis. Slack not only integrates things into itself, but also can have what is in it as fodder to integrate out, so conversations and things shared in Slack can be honed and more deeply framed and considered in other services and then have results and outcomes of those considerations shared back into Slack. It is a good partner for it to add context and easily drop documents that are relevant from the service into Slack. But, Slack isn’t going to replace document management, even if its search is good, the versioning, permissions, and access controls for compliance and other valid needs aren’t there in Slack. Your document management service could become more pleasurable to use though. And therefore Slack users need a “Knowledge Network” – A place where Slack users can post things that others “need to know”, preferably integrated with Slack so that you can post-once-show-everywhere.

About Rajat

Rajat is the founder of KnoBis. KnoBis is a knowledge base software for Slack and Google Apps teams. Powered by a strong search, KnoBis makes it easy to capture and share knowledge in any format: conversations, rich text articles, multimedia documents etc. Use cases of KnoBis include sales enablement, customer support enablement, intranet/internal team knowledge base and self support module for customers.

Rajat has close to 12 years of experience in the computer software industry in engineering, product management and marketing roles. Rajat is a graduate from IIT BHU.

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Organisational Knowledge in a Machine Intelligence era

Artificial Intelligence

A preamble to the KIN Winter Workshop 2016, 7th December 2016.

According to Narrative Science, 62 per cent of organisations will be using Artificial Intelligence (AI) by 2018.

If you asked most people when they last encountered something that used artificial intelligence, they’d probably conjure up a mental image of robots, and might be hard pressed to think of something in everyday use. Machine intelligence and machine learning – the new synonyms for “artificial intelligence” – are on the rise and are going to be pervasive. Anyone using a smartphone is already using some sort of machine intelligence with Google Now’s suggestions, Siri’s voice recognition, or Windows Cortana personal assistant. We don’t call these “artificial intelligence”, because it’s a term that alarms some people and has earned some ridicule down the years. But it doesn’t matter what you call it; the ability to get computers to infer information that they aren’t directly supplied with, and to act on it, is already here.

But what does all this mean in a practical sense? Can – or should we –  rely on intelligent machines to do the heavy (physical and cognitive) lifting for us, and if so, what does the future hold for knowledge and information professionals?

The rise of the chatbot

It’s taken about 10 years, but social media has finally been accepted as a business tool, rather than just a means for people to waste time. If you look at any contemporary enterprise collaboration system, you’ll find social media features borrowed from Facebook or Twitter embedded into the functionality. Organisations have (finally) learnt that the goal of social technology within the workplace is not simply to maximize engagement or to facilitate collaboration, but rather to support work activities without getting in the way. Having said that, we still can’t extract ourselves from email as the primary tool for doing business. Email is dead, long live email!

Some progress then. But technology never stands still, and there’s more disruption on the way, led as usual by the consumer society. Early in 2016, we saw the introduction of the first wave of artificial intelligence technology in the form of chatbots and virtual assistants. This is being heralded as a new era in technology that some analysts have referred to as the “conversation interface”. It’s an interface that won’t require a screen or a mouse to use. There will be no need to click, swipe or type. This is an era when a screen for a device will be considered antiquated, and we won’t have to struggle with UX design. This interface will be completely conversational, and those conversations will be indistinguishable from the conversations we have with work colleagues, friends and family.

Virtual Assistants are personalised cross-platform devices that work with third-party services to respond instantly to users requests which could include online searching, purchasing, monitoring and controlling connected devices and facilitating professional tasks and interactions.

Will it be another 10 years before we see this technology accepted as a business tool? I think not, because the benefits are so apparent.  For example, given the choice of convenience and accessibility, would we still use email to get things done, or would we have a real-time conversation? Rather than force workers to stop what they’re doing and open a new application, chatbots and virtual assistants inject themselves into the places where people are already communicating. Instead of switching from a spreadsheet to bring up a calendar, the worker can schedule a meeting without disrupting the flow of their current conversations.

Companies like Amazon and Google are already exploring these technologies in the consumer space, with the Amazon Echo and Google Home products; these are screenless devices that connect to Wi-Fi and then carry out services.  This seamless experience puts services in reach of the many people who wouldn’t bother to visit an App Store, or would have difficulty in using a screen and keyboard, such as the visually impaired.

We’ll be looking at some examples of how chatbots and virtual assistants are being used to streamline business processes and interface with customers at the workshop.

Machine Learning

It is worth clarifying here what we normally mean by learning in AI: a machine learns when it changes its behaviour based on experience. It sounds almost human-like, but in reality the process is quite mechanical. Machine learning began to gain traction when the concept of data mining took off in the 1990’s. Data mining uses algorithms to look for patterns in a given set of information. Machine learning does the same thing, but then goes one step further – it changes its program’s behaviour based on what it learns.

One application of machine learning that has become very popular is image recognition. These applications first must be trained – in other words, humans have to look at a bunch of pictures and tell the system what is in the picture. After thousands and thousands of repetitions, the software learns which patterns of pixels are generally associated with dogs, cats, flowers, trees, etc., and it can make a pretty good guess about the content of images.

This approach has delivered language translation, handwriting recognition, face recognition and more. Contrary to the assumptions of early research into AI, we don’t need to precisely describe a feature of intelligence for a machine to simulate it.

Thanks to machine learning and the availability of vast data sets, AI has finally been able to produce usable vision, speech, translation and question-answering systems. Integrated into larger systems, those can power products and services ranging from Siri and Amazon to the Google car.

The interesting – or worrying, dependent on your perspective – aspect of machine learning, is that we don’t know precisely how the machine arrives at any particular solution. Can we trust the algorithms that the machine has developed for itself? There is so much that can affect accuracy, e.g. data quality, interpretation and biased data. This is just one facet of a broader discussion we will be exploring at the KIN Winter Workshop, and specifically those deployments of machine learning for decision making and decision support.

Jobs and Skills

The one issue that gets most people agitated about AI is the impact on jobs and skills. A recent survey by Deloitte suggested 35% of UK jobs would be affected by automation over the next two decades. However, many counter this by saying the idea is to free up people’s time to take on more customer-focused, complex roles that cannot be done by machines.

I think this video from McKinsey puts the arguments into perspective by differentiating between activities and jobs. Machines have a proven track record of being able to automate repetitive, rule driven or routine tasks. That’s not the same as replacing jobs, where routine processes are only part of a wider job function.  According to McKinsey, taking a cross section of all jobs, 45% of activities can be automated, and we’re not just talking about predominantly manual labour. They go on to say that up to a third of a CEO’s time could be automated.

Other research by the Pew Research Centre has said 53% of experts think that AI will actually create more jobs.

The question we need to be asking ourselves is what knowledge and skills do we need to develop now in order to make the most of this technology revolution happening around us and ensure we remain relevant. If organisations don’t find out more about these technologies and how they can be used to improve efficiency or productivity, they can be sure their competitors are!

If you haven’t yet registered for the KIN Winter Workshop (KIN Member’s Link) – “Knowledge Organisation in the ‘Machine Intelligence’ era, do so soon! If you’re not currently being affected by AI technology, you soon will be. Make sure you’re ready!

Steve Dale
KIN Facilitator


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30 ways to fail on Twitter

Twitter Logo FailCulled and curated from a few of my archived blog posts, a few tips on Twitter protocol that might enhance your social media credibility and encourage real people (not Bots) to follow you.

However, to conform with the (slightly misleading) title of this blog post, which you’ve probably guessed was crafted to attract attention, just do the opposite of the items in this list!

  • Don’t auto-reply to follows with a link to your free (but crap) ebook.
  • Don’t provide an obscure description of who you are and what you do.
  • Don’t have a completely blank bio.
  • Don’t refer to yourself as an “expert”.  That’s for others to judge.
  • Don’t have a profile photo or an image that only makes sense to you and your imaginary friends.
  • Always add a link to a great resource you’ve cited.
  • Show you care by customising your background.
  • Don’t have big gaps (e.g. days) between posts.
  • Don’t follow over 1000 people in a 2-hour period.
  • Don’t write about the cat/hamster/holiday over and over again.
  • Don’t swear and expect business people to take you seriously.
  • Don’t over-abbreviate.
  • Don’t tell people on the public timeline that someone else is on vacation.
  • Don’t reply on the public timeline when you meant to DM (or when it should be a DM…).
  • Don’t retweet EVERYTHING!
  • Don’t follow everyone and everything – even those with zero tweets.
  • Don’t auto DM spam.
  • Don’t be stupid (this one is a bit of a challenge for politicians, elected councillors and footballers!)
  • Don’t assume that Twitter is a marketing plan.
  • Don’t get into an argument with an idiot – they will always win!
  • Don’t take credit for tweets that did not originate from you.
  • Don’t report on every piece of news you can get your hands on.
  • Don’t tweet about your need for coffee in the mornings.
  • Don’t tweet emotional rants!
  • Don’t worry about your follower count. The content of your tweets is far more important.
  • Don’t pay for followers (most of them will be bots anyway) – quality trumps quantity.
  • Don’t let spammers into your feed.
  • Use hashtags (and if possible, ones that are already in use) to categorise information.
  • Don’t overuse hashtags (e.g. several in one post).
  • Don’t post a picture of yourself holding a knife, gun or other weapon.

You can probably think of more – if so let me know at @stephendale and I’ll post an updated list.

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Making The Case For Enterprise Social Networks

Why is it that so many organisations still struggle to (a) understand what an Enterprise Social Network (ESN) is and (b) how it might benefit their business. Despite the fact that social networking technology has been around for over 10 years, there is still a general lack of social business maturity on the part of many organizations, who appear to lack the culture to be able to understand, appreciate, and leverage ESN’s.

Gartner have reported that over 80% of Social Business efforts will not achieve intended benefits by 2015. At least part of the problem is that where ESN’s have been implemented, they have been treated as technology deployments with a focus on adoption and usage. A different way to think about this is that ESNs represent a new way to communicate and form relationships — and because of that, can bridge gaps that exist in terms of information sharing and decision-making processes.

For anyone yet to be convinced of the benefits of social collaboration within the workplace, here are a few points to add to your business case:

Enterprise Social Networks:-

  1. let employees become happier at work: by allowing all facets of their personalities to be expressed.
  2. connect employees with each other: thus forming deep, long lasting and more meaningful relationships.
  3. encourage every employee to believe they can make a difference.
  4. promote innovation, creativity and change within an organisation. This is achieved through the network culture of communication and collaboration that is created and encouraged by use of Social Media tools. This is opposed to the traditional top down way of management and communication, which is acceptable for some forms of official control and communication in the enterprise. This however is not good for fostering creativity at work and deters innovation from flourishing within the organisation.
  5. avoid the problem of duplication of work in the enterprise by giving much more visibility to what other people are doing. This can be achieved through the use of wikis and open collaborative platforms that encourage sharing and dissemination of ideas and thought processes.
  6. put people with similar interests and skills together and make it easier to search for someone with the skills you are looking for. This allows cross-departmental efforts to be exchanged more seamlessly and organically because the relationships are based on skills and interests rather than the traditional departmental or project base relationship.

Point 4 is perhaps better illustrated below, showing the relationship between traditional command and control structures vs. social networks.

Hierarchies & Networks

It’s also about time organisations got over the mental barrier of making sure that the content on their ESN is strictly about work. They fear that personal discussion will result in less productivity or inappropriate private content. If anything, the organization should encourage “personal” postings because social networks are a representation of who you already are. If you are an unproductive, time-wasting team member, your activities (or lack of) will be plainly visible to everyone. I can think of many other less productive activities,  such as sitting in meetings that have no purpose!

I know it’s been said before, but I’ll repeat it here, because I still see the same old approaches to ESN deployments – focus on behaviours and relationships, and less on the technology.  That way you are more likely to think about value creation rather than tools and features. It’s only through investment in behaviours and relationships that value can be created through:

  • Knowledge sharing
  • Knowledge capture
  • Improved decision-making
  • Employee empowerment

Otherwise Gartner’s predicted 80% failure rate will become reality!


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Bullish on digital: McKinsey Global Survey results | McKinsey & Company

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CEOs and other senior executives are increasingly engaged as their companies step up efforts to build digital enterprises. A McKinsey & Company article.

The latest report from McKinsey on the state of digital enterprise (Social Business) offers some interesting insight on trends, as follows:

56 percent of businesses survey say digital engagement of customers is at least a top-ten company priority, and on the whole respondents report notable progress since 2012 in deploying practices related to this trend.

Companies have been slower to adopt digital approaches to engaging their own employees, suppliers, and external partners. Executives say their companies most often use online tools for employee evaluations and feedback or knowledge management; smaller proportion report more advanced uses, such as collaborative product design or knowledge sharing across the supply chain.

Significant growth in the company-wide use of big data and advanced analytics, used to improve decision making, R&D processes, and budgeting and forecasting.

40 percent of respondents say their companies are either incorporating digital technology into existing products or improving their technology operating models (for instance, using cloud computing).

31 percent say their CEOs personally sponsor digital initiatives, up from 23 percent in 2012.

30 percent have a chief digital officer (CDO) on their companies’ executive teams, a sign of the widespread awareness that these initiatives are important.

Respondents said that success (or failure) of digital implementations ultimately relies on organization and leadership, rather than technology considerations. The absence of senior-management interest is the factor respondents most often identify as contributing to an initiative’s failure. [No surprises here then!]

Organizational issues hinder companies’ efforts to meet goals and see real impact from digital. Misaligned organizational structures and difficulty finding functional talent (such as data scientists or digital marketers) are cited as the biggest issues.

57 percent say their companies are up to one-quarter of the way toward realizing their end-state visions for their digital programs, and just 40 percent say their organizations’ digital efforts have yielded a measurable business impact thus far.

Looking ahead, the report concludes:

  1. Find the right digital leaders. Leadership is the most decisive factor for a digital program’s success or failure.
  2. Manage expectations. Setting the right agenda and maintaining an aspirational vision while addressing organizational, technical, and cultural challenges. Prioritize talent. Concerns about finding the talent their companies need to realize their digital goals.
  3. Technical, functional, and business skills are all critical for digital programs. Finding and hiring talent is only part of the solution; no matter where the talent comes from, development and retention are equally important in a sellers’ market.

The full report is available from McKinsey.


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A Glimpse into the Future of Learning

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Stephen Dale‘s insight:

I thought this was a great illustration of how learning and the application of knowledge is evolving – as it must – to meet the challenges of an increasingly complex and rapidly changing social ecosystem. The key point here is how we must take control of our learning, and the increasing opportunities to do so. Personalisation is fundamental to the future of learning, and learning has to be a life-long activity in order to ensure knowledge adapts to change. All of this is at the heart of "Personal Knowledge Management’. #pkm

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Connect with Social Media Influencers

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There are ways to slowly break into the world of the experts. Learn how to connect with social media influencers in your industry using G+ Ripples and other social tools and techniques.

Stephen Dale‘s insight:

I must admit I had forgotten about Google’s Ripples feature until I read this.  Well worth dipping a toe in the water! #google

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Social Collaboration: it’s the people not the technology, stupid!

Regardless of what labels we give to collaboration technology, the one constant feature is the people, i.e. the staff, the workers, the users. The continuing paradox is that, despite all the evidence of poor adoption rates; the accepted wisdom that “build it and they will come” doesn’t really work, and the oft’ repeated mantra that “it’s not the technology, it’s the people that count”, most collaboration strategies are treated as technology projects and not organisational change management projects.

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The workers production lineI was recently reflecting on my personal experience as a knowledge management consultant in deploying enterprise and business collaborations solutions over the past several years. I’ve seen various buzz-words and labels come and go, and witnessed the morphing of Enterprise Content, Document and Records Management Systems (ECM’s, EDM’s, ERM’s) into varieties of Enterprise 2.0, social CRM, Social Intranets and – more recently – Enterprise Social Media and Social Business solutions.

But regardless of what labels we give to the technology, the one constant feature is the people, i.e. the staff, the workers, the users. The continuing paradox is that, despite all the evidence of poor adoption rates; the accepted wisdom that “build it and they will come” doesn’t really work, and the oft’ repeated mantra that “it’s not the technology, it’s the people that count”, most collaboration strategies are treated as technology projects and not organisational development (OD) projects.  Putting in a shiny new enterprise collaboration system is unlikely to change behaviours that have been conditioned by corporate culture, and less likely to be successful if it’s not integrated with the business processes – and yes, that includes email! Becoming “social” and sharing knowledge is not something that is solved by technology; it’s something that is solved by addressing behaviours. Sure, technology can be an enabler, but it has to be part of a wider and more holistic change programme.

This was certainly the case when I was asked to deliver a strategy for more effective learning and sharing across local government in 2005, which resulted in the delivery of an award-winning community of practice platform that ultimately supported over 120,000 users and more than 1000 communities by 2011. The technology was only one (fairly small) component of the project. Most of the effort went into winning hearts and minds in local authorities that this was the right thing to do, and encouraging staff to narrate their work and share good practice. It was also underpinned by training, coaching and mentoring on how to manage and facilitate on-line communities – activities that don’t often feature in technology-driven projects.

So, with the benefit of some hindsight and experience, coupled with a more contemporary view of emerging trends, the following sums up what I think are the key factors in the emergent social collaboration ecosystem:

  1. Collaboration is about people and behaviours; technology is an enabler, not a solution.
  2. Engagement with and adoption of social collaboration technologies should be part of a wider organisational change programme. HR should be as much involved as IT.
  3. Seek out, support and encourage your ‘network weavers’ and collaboration advocates as part of your social collaboration strategy. Every organisation has them but, dependent on culture, they may be considered disruptive (but social technology is, by its very nature, disruptive). These are your “Trojan mice” who will stimulate those parts of the organisation that you can’t reach.
  4. Knowledge repositories are places where knowledge goes to die. They may still be relevant to researchers but are places of last resort for knowledge workers. Knowledge workers want instant access to expertise, information and knowledge, and increasingly rely on social networks and search engines to find it.
  5. It’s never been easier to connect with people with same/similar interests, or to find answers from “experts”. Anyone who is not yet fully engaged with the social web is at a distinct disadvantage.
  6. ‘Buy’ is trumping ‘build’, but systems integrators are key. Collaboration technology is increasingly powerful and flexible and can be adapted to all but the most specialised needs. However, integration with legacy systems and business processes still requires specialist knowledge.
  7. There is a growing call for products and services that help us manage the information torrent. All of the leading collaboration technology vendors now provide aggregation, filtering, trending, and personalisation capabilities. Look for features available in web products/services such as Bottlenose,, Prismatic, Twylah etc. in Enterprise solutions.
  8. There’s no such thing as privacy on the web – get over it!
  9. The web has been with us for almost 20 years, social media and social networks for over 10 years. Any workers (managers, supervisors, staff) who still claim to be digital technophobes in 2012 are a lost cause. Focus effort on those who see the benefits of on-line interaction.
  10. The future is mobile and ‘appified’. More and more work is being done on the move; the growth of BYOD and COPE initiatives are weakening the ties and dependencies on the ‘lobotomised’ corporate PC in the corporate workplace. Any enterprise collaboration solution must support agile and mobile working.

If I were a CEO deploying a social collaboration strategy, I would be looking for something far more expansive than a technology solution.  The 80:20 rule would seem to be appropriate; if the technology accounts for 20% of budget, 80% should be devoted to organisational development. I wonder how many more failed collaboration projects it will take before this philosophy takes hold?

What do you think?

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The ART Of Collaboration (Collaborative Behaviours)

If people are given the right tools and the right environment, will they spontaneously collaborate and share knowledge? Why do some people find it difficult to share and collaborate? Would incentives and rewards make a difference? This post explores answers to these and other questions about Collaborative Behaviours.

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I was recently asked to present at the Knowledge and Innovation Network (KIN) summer workshop on the topic of “Collaborative Behaviours”. The slides I used have been posted to Slideshare and embedded at the end of this blog post. This post is a summary of the key points I made during my session.


“Knowledge can only be volunteered, it can’t be conscripted”. A quote from the redoubtable Dave Snowden. But is the same true for collaboration? If people are given the right tools and the right environment, will they spontaneously collaborate and share knowledge? Why do some people find it difficult to share and collaborate? Would incentives and rewards make a difference?

What is “collaboration”?

According to dictionary definitions, collaboration means:

  1. The act of working with another or others on a joint project
  2. Something created by working jointly with another or others
  3. The act of cooperating as a traitor, especially with an enemy occupying one’s own country.

I think we can discount point 3 from this discussion, but it is worth testing all three of these definitions with the behaviours described later in this blog post to determine whether there are consistent characteristics that can be applied to all three.

For the purpose of having one single, all-embracing definition, I prefer to use the following:

Collaboration is when individuals or groups work together, combining their strengths and negating weaknesses to accomplish a set of goals.

I think the important point about this definition is that the outcomes are more likely to be amplified when working together as opposed to individually.

Types of Collaboration

It might help our comprehension about what we mean by “collaboration” by looking at various collaborative models.

Peer to Peer Production

Not to be confused with P2P file sharing, such as BitTorrent. P2P production is defined as “any coordinated, (chiefly) internet-based effort whereby volunteers contribute project components, and there exists some process to combine them to produce a unified intellectual work”. Source: Wikipedia.

The process is one-step, meaning the user accesses some or part of an original file from a P2P community website, modifies or enhances the file in some way, and then submits the modified file back into the community.

Probably the best-known examples of peer-to-peer production networks are the Apache Foundation Network and the Linux network (8000 developers from 800 countries). Other collaborative networks include ccMixter, a community music site featuring remixes licensed under Creative Commons where you can listen to, sample, mash-up, or interact with music and Remix The Video, and Scratch, for creating interactive stories, animations, games, music, and art for sharing on the web.

As part of my research for this presentation I attended a lecture at City University London, given by Dr Stephen Clulow, who described the motivators for peer-to-peer collaboration as:

  • Competence
  • Autonomy
  • Relatedness (knowing what you are doing is appreciated by others).

I’ll come back to motivators later in this post.

The Digital Workplace

Collaboration in the workplace is now high on the priority list of many organisations seeking to leverage social technologies to free-up knowledge and provide opportunities for co-creation, co-production and innovation.

I particularly liked this diagram and explanation from Jane McConnell at Net Strategy (reproduced below):

Digital Workplace


  • The managed dimension includes business applications and validated, authoritative, reference content. It is primarily internal but extends partially into the client-partner sphere for inter-enterprise projects and processes.
  • The structured collaborative dimension involves teamwork on projects with specific goals, deliverables and timelines. It overlaps with both social collaboration and the managed dimension.
  • The social collaborative dimension is self-organizing. It includes social networking, micro blogging, community building and other social features such as user-generated content. This dimension stretches the furthest into the public world and is deliberately drawn off the chart because it is the biggest unknown today and triggers the most apprehension in management.

David Gauntlet has defined the motivators for collaboration in the digital workplace in his book “Making Is Connecting” as:

  • Pleasure
  • To feel an active participation
  • A wish to be recognised.

I’ll come back to motivators later in this post.

Barriers to collaboration

Understanding the barriers and obstacles is the first step to identifying potential solutions. Individuals acting alone may not be empowered to make the desired changes, but if there is a real desire to collaborate and share knowledge, most if not all of these obstacles can be overcome or circumvented.

In no particular order:

Knowledge is power

Knowledge and information hoarders exist in every organisation. However, their knowledge is likely to be one-dimensional and limited to their own small network. This can’t compare to the wealth of knowledge in social networks. A case of “none of us is smarter than all of us”.

Fear of change

There is no doubting that we live in far more uncertain times, where change and complexity is all around us. Holding back change is a bit like King Canute – with same outcome!

Can’t teach an old dog new tricks

Some people will never change. Accept it and move on.

Command and control

We don’t collaborate because there’s a real or perceived hierarchy in the workplace. Over the years, the leadership has developed a culture that appears to value one person or group over another.


What’s in it for me? It’s reasonable to seek value in what you do; otherwise you’ll consider your actions as being a waste of time.

Lack of time

The research report “Why Businesses Don’t Collaborate” cites the management of email and attending meetings as the biggest consumers of staff time. These points probably deserve more time and space than I’m giving them here, but the underlying issues here are (a) deciding what is important and (b) having some control of, or input to, meeting agendas.

Lack of support from the top

Bottom-up initiatives will fail to take hold unless there is some support from senior managers and directors. Collaboration initiatives need to be aligned with business or service goals.

Sceptical middle management

What I call the “marzipan layer”. You may have support from the top (the icing), and bottom-up encouragement (the cake). But middle management is more likely to understand the detailed processes that provide the foundations for how the organisation operates. They will be potentially risk-averse, since any change may have unpredictable consequences, and for which they may be accountable.

No tools/poor tools/too many tools

To be effective, collaboration has to be made simple. Intuitive tools accelerate user acceptance and can maximise the outcomes. However, tools need to be relevant and optimised to the task(s) to be completed. Too many choices result in cognitive dissonance (confusion on what to use for each task). No tools – no comment!

Inadequate education/support strategies

Collaboration needs to be recognised as a key workplace skill, and included in personal learning & development plans.  It’s not something that can be taught in a pedagogical sense, but can be encouraged through coaching and mentoring.

Information overload

Usually associated with management of email. Not the best environment for collaboration, or finding what is relevant from the torrent that hits your email inbox each day. Requires discipline on what is shared – does everyone need to know this snippet of information?


Once assigned a task or objective by a manager, most knowledge workers will just want to get on with it, with a degree of autonomy on how they go about it.  Some managers or supervisors feel the need to oversee every small detail, which discourages initiative and dis-incentivises the worker.


It happens when bosses tell people they want everyone to collaborate. But at the same time, they assign tasks, targets and goals to various individuals and teams. Agendas that vary greatly and can range from complementary to conflicting.

Too-Rigid job descriptions

Tightly written and prescriptive job descriptions will that create real or perceived boundaries that inhibit initiatives and taking on new responsibilities.


Collaboration is always going to be difficult if the parties cannot make themselves understood.


Not every culture is open and transparent. Need to be aware of rules and protocols that define collaboration with other cultures.


The layout of your workplace can help or hurt collaboration. The greater the distance between colleagues, the greater the chance of flawed communication.

Not just over-reliance on e-mail when face-to-face conversation is needed, but genuine “out of sight, out of mind” lapses that keep smart people out of the brainstorming, decision making or socialising that leads to positive outcomes.

Fear of rejection

You have something to contribute, but previous experience leads you to believe that your opinion is not valued. Typically seen in hierarchical networks.

Legal, Compliance, Security

It’s not always possible, or even desirable to have open and transparent discussion. Closed groups or communities can be used in some circumstances, but we have to accept that sometimes wider collaboration is not possible.

Digital Divide

Hopefully less of an issue than it used to be, but there is no doubt that anyone not able to connect to the Internet is likely to be at a disadvantage for knowledge and information sharing.

Incentives and Rewards

Speaking personally, incentives and rewards have never made any difference to me in terms of making me want to collaborate more than I do at present. But there is evidence that incentives do work for some (albeit artificial) scenarios, such as Macon Money.  This “serious game” explored how diverse people within a community could be brought together using real-world incentives (in this case, players holding half of a “play bond” tried to find the local citizen bearing the other half, then turned in their play money for real cash).

It’s clear that gaming concepts can draw people into taking interest and becoming part of something bigger than themselves, e.g. earning badges in FourSquare. But we’re also starting to see game technology being used in serious professional networks, as in the recent release of the Jive Gamification Module.

I was hoping to collect some hard evidence of how incentives and rewards might be influencing collaborative behaviours by posting this question on Quora:

Is there any evidence that rewards and incentives improve team-working and collaboration?

There has been little response, but whether this is because there is little or no evidence, or because the question didn’t really excite the community I’m not sure.

So for me, the jury is still out on this one, at least until I see some better evidence than in the Macon Money example mentioned previously.

The ART of collaboration

Admittedly I haven’t read every book, white paper or blog that purports to reveal the secrets of good collaborative behaviour. However, I have done sufficient research to realise that this is a very complex topic. I must admit that I’ve not been wholly convinced by what I have read, heard or seen and I don’t think anyone has really identified the key characteristics of good collaborator. So I’ve fallen back on my own experience (over many more years than I care to mention), and identified the characteristics that I think are most important for online collaboration.

1. Authenticity

This is not just ‘identity’, in terms of an on-line profile. It means, “are you who you say you are”? Are you truthful, genuine and sincere? Do you provide relevant attributions to your sources? Do you cite the origins of your content? Are you indeed a human being? Not to be confused with a Bot or a clever Artificial Intelligence application (don’t laugh even experts can be fooled. See the Turing Test).

2. Recognition (or Reward)

One thing that academics do appear to agree on is that a key influencer for good collaborative behaviour is recognition or reward. This does not have to be monetary reward, or gaining power and influence though promotion. In many cases it is simply being recognised as someone who has demonstrated knowledge or expertise on a particular topic. For the truly networked individual, to be acknowledged as an “expert” by your peers carries far more weight than some transient, short-term financial reward. I would go so far as to argue that collaborative behaviour that is driven mostly or entirely by financial reward will only be very superficial and is not sustainable in the long term.

3. Trust

To my mind, the most important characteristic, and the most ephemeral, since it’s not something that can be easily measured or evaluated. Trust relies on believing that a person will behave reasonably and will do what he or she says.

We establish trust with the people we engage with by the way we behave and how they reciprocate. Feelings of empathy with another person may also play a part. Establishing trust with people in an online network is more difficult than for face-to-face encounters, where we can tap into emotional signals and evaluate body language. However, trust, once established, can be just as strong for on-line engagement as it is for real-life. In fact, there are many people in my on-line networks that I’ve never met; yet I trust them more than some of the people I meet from day to day.

4. Passion

Enthusiasm, commitment, devotion to a cause or belief – all of these define ‘passion’. These are strong, emotional characteristics that provide the motivation for collaboration.  Having passion for something (or someone?) gives a meaning to our actions and, in the context of collaboration, connects the authenticity, recognition and trust characteristics. Long before there were social networks, hobbyists would gather to share their passion, whether it is photography, model making, knitting or gardening.  Such clubs and organisations are founded on the principles of sharing of ideas and techniques to support learning and improvement.  But the other (and arguably more significant) factor is that members of these gatherings also crave recognition for something they have achieved. This is not dissimilar to the recognition we wish to achieve through online collaboration, where knowledge or expertise can be recognised by our peers.

The diagram below shows how all of these characteristics combine together to form what I believe is the ideal model for collaborative behaviour. My only surprise from the research I undertook for this topic (admittedly not exhaustive) was how few references there were to “Trust”, and no references at all to “Authenticity”. Two of my key characteristics. However, we all seem to agree on ‘Recognition” as one of the fundamental characteristics.

ART of Collaboration

To conclude: I’ve emphasised the acronym ART in this post and in the diagram above because I do feel that effective collaboration is an “art” in the true sense of the word, i.e. a skill that is learnt through practice. I wonder….are you practising this ART enough?

Useful References.

Collaborative behaviours

View more presentations from Collabor8now Ltd
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Knowledge Hub: A response.

The Knowledge Hub community of practice facilities were meant to be a step on the way, and not an end in itself, which is what I think the Knowledge Hub has become. The unfortunate conjunction of original concepts and vastly cut-down capabilities (per the original specification) has resulted in a just-about-adequate user interface (UI), but a fairly hostile user experience (UX).

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My colleague Dave Briggs has posted an interesting challenge about the Knowledge Hub – the new community platform for local government – questioning whether it is reaching the parts that the legacy platform used to reach and particularly its relative lack of activity and fairly laboured user experience.

I wasn’t too sure whether or not I should contribute to the discussion, given that I probably have more insight on the history of this project than most people, and as the lead consultant and architect for the project over two years until October 2011, I’m party to some information that I can’t (or shouldn’t) make public.

However, in the light of the comments and feedback I’ve seen on Dave’s original post, I feel compelled to correct a few assumptions.

The original thinking and concept for the Knowledge Hub, which I articulated in a Knowledge Management Strategy paper I was commissioned to produce in 2008 for the Improvement & Development Agency (IDeA, now part of the LGA), was to leverage emerging social web technologies to provide better opportunities for collaboration across local government, encourage innovation and break down the silo’d working practices that were becoming prevalent on the legacy CoP platform.

The fundamental design concept was to map every user’s social graph (people and relationships) against their interest graph (the topics and themes they followed, e.g. housing, environment, planning etc.). I wasn’t to know it at the time, but this is precisely the thinking behind Google+ and specifically Google+ Circles.

Of course, each person’s social and information graph could span both internal (to Knowledge Hub) and external (the web) environments. Consequently the design incorporated facilities to link to conversations happening on Facebook, Twitter and other social networks, together with external blogs and RSS feeds. The aggregated feeds would be stitched together using a ‘filterable’ activity stream that included internal (Knowledge Hub) conversations. The user would then see relevant information (i.e. people and topics they had chosen to follow) coming to them rather than having to go out and find it.

Since all content would be tagged (some automatically), aggregated streams would show topics that were trending (similar to what Twitter has recently released as Tailored Trends), thereby helping to manage the information torrent. The system would also support powerful semantic search across all of this content.

The original specification also included support for the development of mobile and web apps, using tools that would enable non-technical users to create these apps, similar to the facilities provided by iBuildApp, but specific to local government data and services.

I noted that one comment referred to local government still being wedded to long and confusing email chains. This was also a consideration in the original design specification, and a feature was included to enable blogging direct from email, i.e. the user didn’t have to learn to use any new tools to create a blog post – they could do it all from their email account.

An important point to note was that the community of practice facilities (as currently being debated on Dave Briggs’ blog) were meant to be a step on the way, and not an end in itself, which is what I think the Knowledge Hub has become. The unfortunate conjunction of original concepts and vastly cut-down capabilities (per the original specification) has resulted in a just-about-adequate user interface (UI), but a fairly hostile user experience (UX). If you’re not sure about the difference between UI and UX, check this blog I posted a while back.

To my mind, this is proving to be the biggest drag on user engagement and activity. Knowledge Hub is a complex system, but a good UX design will ensure this complexity is hidden, and that navigation and actions become intuitive. This can be achieved by being aware at all times about what a user is trying to achieve (e.g. filing a document, writing a blog) and ensuring that:

  • links and sign-posting are contextually relevant
  • each process has a logical flow
  • there are no dead ends
  • action links are defined by verbs (e.g. write a blog, file a document)

If experienced social network/social media users like me, or Dave Briggs, find the environment a little confusing, I can only sympathise with users who are only just starting to embrace the world of the social web.

Since I doubt there will be any major changes made to the UI or UX, the effort falls on the Knowledge Hub support team and community facilitators to ensure that users understand how to get the best out of the system. And this will be hard work.

Going forward, I would encourage the LGA think about re-convening the Knowledge Hub Advisory Group. These were highly experienced knowledge, information and data professionals who helped me to shape the original specification and acted as critical friends throughout the procurement, architecture and design stages. They were disbanded when I left the project and all subsequent strategic design decisions were folded into a small in-house project team. A case of  “none of us are as smart as all of us” perhaps!

I hope I’ve gone some way to setting the record straight on what Knowledge Hub was meant to be. Community of practice facilities were just a small part of a much bigger idea, sadly not realised.

Other blogs in this sequence:






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