denotes premium content | May 19 2013 Feature
posted 1 Apr 1999 in Volume 2 Issue 7
Exploring Knowledge Frontiers:
From information
to innovation
Knowledge management must be more than just a glorified filing
cabinet to lead to innovation. Knowledge is the essential link between
information and innovation; capturing knowledge lies in the relationships forged
from new connections. In this article, Patterson Shafer brings together the
thoughts of knowledge management professionals who recently spoke at a
benchmarking presentation in the IBM Watson research Centre, New
York.
What is your definition of knowledge management? All too
often, it is defined as something like 'capturing, categorising and
re-using the knowledge assets of the organisation.' The emphasis is on
increasing efficiencies and reducing redundancy by reusing work products such as
reports, proposals and presentations. And the organisation's Knowledge
Management system becomes nothing more than a glorified filing cabinet, enabled
though powerful, 'intelligent' search capability.
Many organisations are unwilling to devote the personnel or
financial resources to evaluate these 'knowledge assets'. The result is
potential replication of worst practices, or at best, mediocre practices. The
solution lies in the realisation that Knowledge Management is not about
technology. It's about people, culture, and the ability to distinguish between
good and bad, the relevant and the irrelevant. Developing a culture of knowledge
creation and sharing will have a far bigger impact than throwing technology at a
problem.
This article is about
the advancements that leading knowledge organisations have made, based on the
realisation that understanding and nurturing human behaviour is the key to
growing competitive advantage. The information in this article is based upon our
work with these organisations, and IBM's generous benchmarking of their
Knowledge Management technologies and practices.
Diverging
approaches
David Snowden is Director of
Knowledge and Differentiation at IBM. He has described two schools of thought
around Knowledge Management: The first is a mechanistic view characterised by
bringing all the knowledge to the surface (the filing cabinet/search engine
approach). A purely technological approach leaves the motivation to share and
leverage knowledge assets unaddressed.
The other is the biological view characterised by managing
the ecology or knowledge culture of an organisation. Far less energy is
expended, at far less expense. Technology addresses neither the incentives, nor
the attitudes that promote a 'knowledge organisation'. Success lies in
creating the culture for sharing, and then enabling with technology.
Case study: culture triumphs over technology
Like many organisations responding to modern competitive
and regulatory pressures, a municipal water company was looking to increase
efficiencies and reduce costs. Its management invited in some highly-paid
consultants, who observed that the field engineers spent a good thirty minutes
each morning conversing at the supply depot before heading out to the field. So
the decision was made to abolish the depot, outfit the engineers with PDA's and
cell phones, and have them go directly to their first assignments. Armed with
technology, the managers expected databases filled with field data, and the cell
phone to serve as an information lifeline. A new knowledge management system was
developed - but not in the form expected.IBM's David Snowden set about to
observe field engineers responsible for maintaining the municipal water system.
After gaining their acceptance (getting his hands dirty) he came to learn about
who they were and what they did.
Having lost their morning rendezvous, the engineers started
gathering at lunchtime - always in the same pub. Some came early in the day,
others later. But they all came to the same place. David shared this curious
observation with the pub owner, only after slowly gaining his confidence (and
friendship). The patron presented a substantial, well-worn diary. In it were the
daily notes of each of the engineers. For example: '3/mar - The valve at
Bond Street was leaking badly - replaced packing - should last a month before
more serious repairs needed.' Or, '6/mar - Found a new way to crack the
heads off the pressure valves using the #4 wrench.'
And so the collective knowledge was aggregated and passed
from engineer to engineer; A mixture of notes, observations, demonstrations and
stories became totally out of reach of the technology designed to capture it!
New ways to look at
knowledge
Knowledge Continuum
Knowledge can be viewed as procedural (explicit) and
natural (tacit). Explicit knowledge lends itself well to codification. This can
include step-by-step instructions, or processes that are easily captured.
Explicit knowledge is generally tied to organisational structures and repetitive
or linear systems as found in product-oriented or manufacturing environments.
Tacit knowledge, represented on the vertical axis in Figure 1 is not easily
codified, and is more likely the province of a co-dependent community (a bunch
of consultants). Knowledge workers share information intimately because they
recognise the benefit to the group. While many systems try to capture and
replicate tacit knowledge by translating it into codified information (analog to
digital) and allowing technology-based access (through user navigation, search
or push approaches), they often fall far short. The outcome is usually
a 'community of competence', an organisation of semi-experts performing
sub-optimal work.
Figure 1
The
exception is the task force. A task force is pre-meditated co-dependence.
Individuals are directed towards a specific, urgent task. Each individual's
success rests with the outcome of the group effort. Motivation is high. And this
may be a key to successful knowledge management.
Tacit -
explicit - tacit:
Something lost in translation
Why do technology-based systems
fail when information is less easily codified? Too much of the nuance can get
lost when we digitise. When we try to reconstitute an experience, we need to add
back the context, nuance and emotion that represent most of our face-to-face
communication. Through filtering information into the virtual dimension,
technology takes out the tacit colour and tone which supports and gives meaning
to that information. What is left barely describes the concept.
This leads to the conclusion that
some knowledge should be stored in the form of audio or video, capturing the
subtleties of the original communication. Or, taken to the extreme, knowledge
systems should provide the intimacy or 'social proxy' of a face-to-face
encounter.
Technology approaches
Where Technology Falls
Short
The goal, according to John
Richards of IBM's Thomas J. Watson Research Center, is to make technology
disappear, to move the paradigm from people, process and technology to people
process and relationships (see Figure 2). Technology strips away our cultural
peripheral vision. Up till now, we had 'conversational' tools (such as chat
rooms) that didn't support conversation. Some of IBM's current research is
experimenting with ways to represent social proxy, and enable persistent
conversations. An application called 'Babble' is attempting to re-establish some
of the realities of face-to-face conversation, including:
Figure 2
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Social and work talk |
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Opportunistic interactions |
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Group awareness |
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Conversation genres |
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Socially shaped behaviour |
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Private offices |
The interface
Babble's interface is designed to support small work groups of up to 24 people. The simulated interface at the right shows three 'navigational' boxes at the top of the page shown in figure 3. The coloured circles on the left indicate who's around, and where they are (at their desk, at home, on the road etc.) The tree on the right portrays the topic or 'discussion room' hierarchy. And, the 'cookie' in the middle shows social proximity.
Figure 3
If members are on-line,
and in the room you're in, their 'avatars' are in the grey area. If
individuals are actively engaged, they are clustered around the centre. If they
haven't participated recently, or if they're active in another application, they
drift from the centre. If members are on-line, but in another room, their avatar
moves to outside the gray area of the cookie.
The threaded discussions, displayed in the text box at the
bottom of the interface, are searchable by text, time and date. Additional
features, such as context combined with greeking of text, allow users to spot
patterns in their discussions. Generalisations can be made regarding the most
productive time of day, or the amount of time spent 'on-subject'
vs. 'off-subject'.
Boundaries
Another concept John Richards
explored was that of the 'boundaries of cognition'. Our nervous systems are
attuned to boundaries. We have limited resources. With all the sensory
information we receive, it is only the change in information that alerts us. How
can we exploit this phenomenon? We've all seen websites and applications that
flag new content - or even entire areas marked 'what's new'. More advanced
databases signal change through e-mail notification and pushed alerts that
notify users of change that is relevant to their work.
Another technique
that leverages our ability to notice change is animated or kinetic text.
Although this paper-based article can't demonstrate kinetic text, readers can
refer to Carnegie Mellon University's site:
http://www.cmu.edu/cfa/design/kdg/kt/index.html
and MIT's site:
http://acg.media.mit.edu/projects/kinetext/
for
examples. Duke University's Instructional Technologies Web site also has
information on kinetic text. The address is
http://aaswebsv.aas.duke.edu/focus/it/visual/text.htm
Enabling
knowledge management
Investment in Knowledge
Management
David Snowden has indicated that
IBM devotes approximately 5% of revenues to Knowledge Management; no small
amount. That figure represents the systems (design, hardware, software and
direct support) and their use (allocation of professional's time spent using the
system). Why must the commitment be so great?
Key enablers
What are the factors that need to
be addressed to make knowledge management work? Design impacts the usability of
the system, and includes elements of speed, ease of use and the layout graphical
user interface. Features include technologies such as Babble's indication of
social proxy, and push mechanisms such as web-based alerts, voice-mail and
e-mail notification. Structure describes the information architecture, including
strategies for capture, codification, archiving and distribution. But most of
all, it's about culture. It must be in the organisation's nature to share
information?
Examples
One Big 5 consultancy implemented a Knowledge Management
system and reported early use statistics of 13%. Only after supporting a
cultural transformation, through incentives, training, and a top down mandate,
did use gradually climb to 68%.
After speaking with the research and development group of a
pharmaceutical company, we found that scientists were rewarded for hoarding
knowledge. Their recognition came in the form of being published, or receiving
patents; sharing information was an anathema. They have not yet resolved this
impediment, but they know they have lost substantial revenues by keeping
break-through information away from their marketing department.
Cultural Change
How do you break down these cultural barriers? Knowledge
Management at IBM Global Services is achieved through a partnership with Human
Resources. Evaluations and performance reviews incorporate a measure of
contribution to, and use of the Intellectual Capital Management asset pool.
Individuals' are evaluated at every level, from their performance on specific
projects, to their contribution to the organisation as a whole.
Innovation in knowledge management
The Human
Factor
Earlier in this article, we
claimed that Knowledge Management is not about technology. While technology
certainly is an enabler, knowledge leaders are going beyond the electronic
filing cabinet solution, and placing practice experts in the information value
chain (See figures 4 & 5).
Figure 4
This allows information and
practices to be evaluated before they are replicated. At the very least,
organisations should dedicate resources to a structure that weeds out
sub-optimal work products. Only those documents and processes that represent the
organisation's best thinking should be available for distribution. This is what
separates knowledge management from knowledge sharing.
Figure 5
Not invented here
Many
organisations are extending Knowledge Management beyond their walls. Their
Business Intelligence systems capture information from information subscriptions
such as Hoovers, from their employees in the field, from their customers, from
their competitors' Web sites, even from their employees who worked for their
competitors. In Europe, Juran Institute
1 established a blind benchmarking club for
the oil and gas industry. Competitors would submit production quality and
throughput data to a blind database to measure their 'best practices'
against that of their entire industry.
Counter Intuitive
Should Knowledge Management
systems even try to capture everything
in bits and bytes? Or would the system be more productive by bringing
communities together FACE-TO-FACE?
What happens to those promises of reduced
travel costs, more time at the workstation, increased productivity? Let
s look back at the success criteria of any Knowledge Management effort. If
cost-cutting is the goal, then promoting face-to-face collaboration works
contrary to plan.
If more strategic efforts such as competitive
advantage, improved customer service or replication of best practices are the
primary goals, then the organisation must decide whether the benefits of
increased face-to-face communications and knowledge transfer outweigh the costs.
One service company is looking beyond best practices to develop
world-class services and methodologies. This strategy includes:
a). Looking outside the organisation for benchmarks and best
practices
b). Pursuit of better-than-best solutions
c). Bringing
people face-to-face, in addition to connecting them with technology.
The organisation
solicits all forms of intellectual assets (speeches, presentations, proposals,
reports, etc.) and quickly evaluates them for further consideration. Strict
metrics are then applied to determine whether or not an idea or document is
elevated to a status of "worthy of improvement" .
The best ideas are then floated to experts both within and
outside the organisation. These can include consultants, academics, customers
and others who can bring a broader perspective to the issues. Only after a
rigorous process of review and improvement is a document, idea or methodology
labelled as "world-class" and worthy of distribution across the organisation.
Conclusions
To contribute value, Knowledge
Management systems must go beyond merely capturing information for eventual
distribution. Advances in technology can facilitate and enable improving the
quality and effectiveness of knowledge assets. But true advances come only with
a substantial commitment of human resources. This commitment is represented in
the form of content evaluation and improvement, in terms of evaluation, reward
and recognition, and in terms of placing the value of culture and interaction
above the technologies that are designed to support them.
Acknowledgments
This report is a summary of a one-day Knowledge Management
presentation sponsored by Ark Group of London, and hosted and presented by KM
professionals at IBM's Watson Research Centre. Our presenters included:
Ko-Yang Wang - IBM Global Services. Principal
- Knowledge Management and Asset Reuse
John Thomas. Manager, Knowledge Socialisation
David Snowden. Director of Knowledge and
Differentiation
John Richards. Thomas J. Watson Research
Center
Patterson Shafer is Senior Vice President of e-business at
Bell and Partners. He can be contacted at:
pshafer@bellandpartners.com
