Re: Model of an intelligent knowledge extraction in organizations #extraction #definition


Arthur Shelley
 

Hi John,

Welcome (and thanks for your question on the SIKM Leaders call recently too).

Your point is well made and relevant. To me it reinforces the validity of the concept of a Knowledge Continuum.

Lets explore a little, then come back to the connection…

 

Consider “white light”: our (normal) eyes see white light, but in reality it is a spectrum of a multitude of visible colours ranging from purple through to red. Close up, at any point on this spectrum we can “see” a particular colour. However, if we shift up or down the spectrum just a little the colour changes through the rainbow. Different people are more apt as seeing some colours than other colours (because we are different and we have preferences). If we step right back, we get the bigger picture of all the colours, which merge together to show as white. If we change the incident light on a white background, it interferes with what can be reflected back to us, so we only see a subset of the full “truth” we are looking at. The key point here is it is hard for anyone to fully understand the detailed perspective AND the bigger picture (without considerable investment of time, which most senior people cannot give to a knowledge manager).

 

Knowledge is like this. Our current knowledge (limitations), cultural norms and subconscious biases are like in the incident light. They filter out what we are capable of seeing/understanding, unless there is some sort of disruption that breaks out the flow into less entangled components. A disruption (a different way of viewing the situation) enables us to see individual elements of the “knowledge” (like water diffracting white light into a rainbow). The breakout of the signals we are now receiving can be interpreted for a deeper reflection and greater understanding. However, if we only see the different colours, we can miss the bigger picture (recombined as white light – or even in a slightly modified form).

The key point here is focus on the key knowledge component that impacts the sort term quick win to secure attention and support. Ensure you speak “business language” not KM dialect.

 

When we assess knowledge we sometimes focus in to see individual components, but mis the whole. OR we see the whole, but miss the components. It is important to assess situations from a range of perspectives, top down and bottom up and in between, to get a multifaceted understanding of the situation (systems perspective). I understand this can be challenging to get people who think convergently to understand. However, this is why complex approaches o resolving challenges work far better than trying to oversimplify the situation and “find THE answer” approaches. Reality is, “THE (existing) answer” may work to a degree, but is probably inadequate for the new challenges you face. The light metaphor will also probably not work on a senior business “leader”

He key point here is your stakeholders look to simplify the issue, not open it up to a range of possibilities – which makes them managers rather than leaders. If you can get them to change their focus  a little, you can open their minds to alternatives. Mindset is critical!

 

The messaging of how knowledge can assist a leader to enhance performance is heavily influenced by the target audience. Find a metaphor that works for them to connect to wat you are saying. Use this to build their understanding in a way that highlights which elements of the knowledge will directly help their most pressing issues. Trying to explain the complexities of knowledge up front will not work (I know I have tried this too). Building a trusted relationship with key stakeholders over time (based on a series of successful initiatives applying knowledge to create value) will enable you to build the knowledge maturity of the stakeholders and the organisation over time. This is why quick wins are important as it provides you the kudos and flexibility to address some bigger longer term challenges based on the proven value they generate.

 

How does this relate back to the knowledge continuum - because your success is constantly mixing the tangible benefits you generate with the intangible aspects of relationships, trust, collaboration and social sharing of insights. Harmonising this “balance” shifts up and down the continuum depending on the moment. Get this “tweaking” right more often than not, will generate new knowledge and drive commitment to ongoing capability development/knowledge maturity. Once you are in the flow it accelerates, but remember managers are always looking for short term benefits (often at the expense of longer term outcomes), so maintain the flow in a balanced way. I have found the biggest challenge is maintaining the “sponsor” stakeholders over time. Organisations are in constant flux and the key players/sponsors come and go quickly. It is critical to be working across a number of key senior stakeholders developing your relationships with them as potential future sponsors and clients. This is because it is inevitable that some will change during your initiative (before it fully matures).

My the knowledge gods be with you 😊 (and a bit of luck).

A

 

 

Regards

Arthur Shelley

Producer: Creative Melbourne

Author: KNOWledge SUCCESSion  Sustained performance and capability growth through knowledge projects

Earlier Books: The Organizational Zoo (2007) & Being a Successful Knowledge Leader (2009)

Principal: www.IntelligentAnswers.com.au 

Founder: Organizational Zoo Ambassadors Network

Mb. +61 413 047 408  Skype: Arthur.Shelley  Twitter: @Metaphorage

LinkedIn: https://www.linkedin.com/in/arthurshelley/

Free behavioural profiles: www.organizationalzoo.com

Blog: www.organizationalzoo.com/blog

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From: main@SIKM.groups.io <main@SIKM.groups.io> On Behalf Of John Carney
Sent: Saturday, 16 January 2021 9:38 PM
To: main@SIKM.groups.io
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

 

I have only recently joined this Forum - after a number of years absence in formally working in the KM field - but seeing a name I recognise on the post (Hi Nick ;-)) has motivated me to contribute.  Re the information vs (explicit) knowledge language debate it's an intractable issue for me and there will never be a right or wrong response, I think what's important is clarity of understanding in dealing with non expert 'clients' for want of a better term and speaking personally my observation is that the ambiguity is unhelpful. I have seen many strategy documents in Government that use the terms interchangeably that then confuses what folk are practically meant to do. I prefer to talk about IM and people/ social learning approaches - the latter being my predominant interest. I do accept that for most KM has now become synonymous with IM 

 

Recognising that having only just joined this party it feels a tad  disingenuous of me to challenge the very phrase that brings us together ;-) but I have always found the term Knowledge Management largely unhelpful to our cause - indeed I squirm with embarrassment when I have to introduce myself as KM Lead for Dstl as it doesn't really convey either what I think I am trying to do or what is attractive to the audience 

I think some of the early commentators like Peter Drucker got it right when they spoke about the importance of managing people . In my context ( I respect that others might be different) the KM challenge remains a leadership one IMO. 

 

I look forward to future interactions - in particular the peer assist discussion on learning lessons (thank you)  - another example where there are multiple interpretations of the phrase 

 

Kind Regards (and Happy New Year) John 

 


On 16 Jan 2021, at 09:21, Nick Milton <nick.milton@...> wrote:

In my view, codified knowledge can be seen as BOTH knowledge AND information as far as our management systems are concerned.

 

It is Information in as much as it is a document, video or other file which can be handled within information management systems, and which therefore falls underneath the umbrella of an information management system.

 

It is knowledge in as much as it can convey understanding, know-how and the ability to make effective decisions, from one person to another, and therefore falls underneath the umbrella of a knowledge management system (using the term “system” to mean “system of management” rather than IT system).

 

I know many people see “information” and “knowledge” as two mutual exclusive descriptors, but there is no reason why this should be the case. We are used to thinking this way, but there is no logical basis for it that I can see.

 

I would therefore submit that the category “codified knowledge” can be seen as a clear example of something that is both categories.

 

More on the idea here

http://www.nickmilton.com/2017/09/why-some-knowledge-is-also-information.html

http://www.nickmilton.com/2018/06/a-new-way-to-look-at-knowledge-and.html

 

Nick Milton
Knoco Ltd


 

 

From: main@SIKM.groups.io <main@SIKM.groups.io> On Behalf Of Murray Jennex via groups.io
Sent: 16 January 2021 01:36
To: fred@...; main@SIKM.groups.io
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

 

at the risk of sounding obnoxious, I have to ask why codified knowledge is information?  its still knowledge, just well understood knowledge.  For example, just because we well understand the knowledge of how fire works and causes burns does not make that information, it is still knowledge...murray


-----Original Message-----
From: Fred Nickols <fred@...>
To: main@SIKM.groups.io
Sent: Fri, Jan 15, 2021 12:24 pm
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

I agree, Chris.  Explicit knowledge is knowledge that has been codified.  It is indeed information.

 

Fred Nickols

 

From: main@SIKM.groups.io <main@SIKM.groups.io> On Behalf Of Chris Collison
Sent: Friday, January 15, 2021 3:03 PM
To: main@SIKM.groups.io
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

 

I’m with you Fred.

...and from my perspective (which not everyone shares!), I would add that explicit knowledge = information.

Cheers,

Chris

 


From: main@SIKM.groups.io <main@SIKM.groups.io> on behalf of bill@... <bill@...>
Sent: Friday, January 15, 2021 7:57:21 PM
To: main@SIKM.groups.io <main@SIKM.groups.io>
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

 

Hi Fred

 

I say the following knowing the risk with which I am placing myself 😊…never been a fan of “implicit” and so I am not a fan of Polanyi’s definition.  My point, based on years of practical consulting application, is that “tacit” knowledge can be elicited, harvested, captured and distilled to make it searchable, findable, accessible and usable/reusable. There is a skill and craft involved IMO. My definition of knowledge is based on the concept that it consists of information and experience = knowledge. For practical, not academic or theoretical application, this simple, practical definition I find has meaning in a business or operational environment.  This has been my experience.

 

Best

 

Bill

 

From: main@SIKM.groups.io <main@SIKM.groups.io> On Behalf Of Fred Nickols via groups.io
Sent: Friday, January 15, 2021 11:22
To: main@SIKM.groups.io
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

 

FWIW, in relation to Bill’s use of “explicit” and “tacit,” I find a third category useful; namely, “implicit.”  I define “implicit” as knowledge which hasn’t been articulated but can be.  Tacit, by Polanyi’s definition, can’t be articulated.  And explicit, of course is knowledge that has been articulated.

 

When it comes to capturing implicit knowledge, lots of folks have been doing that for many years.  You will find them in the training and human performance community.

 

For more, see a piece I wrote for the KM Yearbook (2000-2001).  https://www.nickols.us/knowledge_in_KM.pdf

 

Regards,

 

 

Fred Nickols, Consultant

 

My Objective is to Help You Achieve Yours

 

 

 

 

From: main@SIKM.groups.io <main@SIKM.groups.io> On Behalf Of bill@...
Sent: Friday, January 15, 2021 10:41 AM
To: main@SIKM.groups.io
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

 

Dear Colleagues

 

Been enjoying this timeless discussion on K capture and the extended inference about tacit knowledge and the subtleties of human language in the sharing in the context of the below thread.

 

Believe it is generally recognized that technology cannot yet get what is one person’s mind and transfer it to another person’s mind. At the heart of the issue, I believe, is the skill set that is required to capture or better said, to elicit what someone knows or can share, to distill and make sense of that knowledge whether it be explicit or tacit, and then to characterize it for reuse within an organization (fit for purpose and context relevant) and then to make is searchable, findable, downloadable, and usable/reusable.

I believe that this is a reasonable approach to as stated below “…to study KM processes, identify patterns and see if technology can address that in a narrow sense.” 

Best

 

Bill

 

 

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Learn more about the solutions and value we provide at www.workingknowledge-csp.com

 

 

 

 

From: main@SIKM.groups.io <main@SIKM.groups.io> On Behalf Of Sam Yip via groups.io
Sent: Thursday, January 14, 2021 21:41
To: main@SIKM.groups.io
Subject: Re: [SIKM] Model of an intelligent knowledge extraction in organizations

 

We are still very far from seeing any AI technology that can intelligently extract human knowledge in a broad sense. A main challenge is that of data, and in particular textual data.  Data has to be structured in a certain format to be consumed by an AI machine, but in the case of textual data, the number of permutation and subtleties in human language makes this task tremendously difficult. But perhaps the biggest challenge is the limitation of computation power. The most powerful computer today has roughly 1 billion neural connections/synapses, similar to the amount of synapses that a honey bee has vs 100-150 trillion synapses of a human brain. It has been suggested by computer scientists that we are actually just approaching bee-level intelligence, and we are not even there yet. 

That said, AI should be sophisticated enough for a focussed application, especially if it’s built around narrow use cases and trained for specific domains. e.g. the technology to recognise and extract names/entities from homogenous, unstructured text is fairly advanced, and so is the ability for a machine to auto-index/classify documents and textual data. Information extracted as such, combined with data visualisation techniques, will go a long way in enhancing the comprehension of what’s contained in an organization's textual data, and that is a possible KM angle you can look into. 

Instead of looking at broad ways “to extract automatically all types of knowledge in an organization” (I don't think this exists), it might be worthwhile to study KM processes, identify patterns and see if technology can address that in a narrow sense. 

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