Mapping and Measuring Knowledge Creation, Re-Use, and Flow
by Valdis Krebs
No one doubts that better management of knowledge
within the firm will lead to improved innovation and competitive
advantage. Everyone agrees on the goal -- better utilization of
internal and external knowledge. It is the approach to this goal
that is hotly debated. Many vendors and consultants push a technology-driven
approach. "Buy our state-of-art knowledge storage system and you
will never again lose knowledge that is vital to the company!",
they exclaim. Other consultants emphasize the soft-side of Knowledge
Management. "Create a learning culture, that rewards sharing, and
knowledge management will take care of itself!", they postulate.
There are no silver bullets. Not from the technologists. Not from
the culture prophets.
The effective utilization of knowledge and learning
requires both culture and technology. Explicit information
and data can be easily codified, written down, and stored in a data
base. For this type of business information we have the necessary
skills and more than adequate tools. Yet, simple data is frequently
not where competitive advantage is found. An organization's
real edge in the marketplace is often found in complex, context-sensitive,
knowledge which is difficult, if not often impossible to codify
and store in ones and zeroes. This core knowledge is found in individuals,
communities of interest and their connections. An organization's
data is found in its computer systems, but a company's intelligence
is found in its biological and social systems. Computer networks
must support the people networks in today's fluid and adaptive organizations
-- not the other way around.
Visualizing Knowledge Networks
The organization chart has been a staple in the Human
Resource [HR] department. It displays who works where and
who reports to whom. This was sufficient knowledge in a time
when organizations faced gradual change. These charts where tools
for control and planning. Today's fluid business environment
does not allow only static structures and does not reward those
that follow prescribed configurations in the face of rapid change.
The fast economy requires flexible, adaptive structures that self-organize
internally in response to changes externally. In this knowledge-critical
economy we need charts to show us who knows what and as a
complement who knows who. In addition to pictures of hierarchy
we need visualizations of the massive interconnectivity that occurs
in the learning systems that are our organizations.
Organizational Network Analysis [ONA] is a software
supported methodology that reveals the real workings of an organization.
It uses the rigor of systems analysis to reveal the behavior inside
and between organizations. Knowledge networks are mapped that uncover
interactions within and across the boundaries of the organization.
These visualizations are in effect business x-rays of how
things actually get done -- evidence of adaptation in the organization.
HR Managers and consultants use these revealing diagrams in the
same way that doctors use x-rays and CAT scans -- to see what is
normally invisible. ONA exhibits both how knowledge is shared in
emergent communities of practice, and how it is utilized in key
business processes. In short, it uncovers the hidden dynamics that
support learning and adaptation in the modern organization.
Not only can HR mangers and consultants now visualize
the connections that matter, they can also measure and benchmark
them. Based on recent research, an organization can now be benchmarked
in key dynamics such as adaptability, capacity to learn, openness
to the environment, ability to span boundaries, brittleness of its
structures, probability of project success, and efficiency of information
flow. This technology provides the ability to drill down into a
complex organizational system and find emergent experts, opinion
leaders, bottlenecks, breakdowns in communication and communities
of practice. The organization can be viewed and measured from the
system-wide level, to the group level, and down to the individual
-- you can see the forest and the trees... and how they are
ONA is an outgrowth of many knowledge disciplines
including social network theory, organizational behavior, interpersonal
communications, chaos theory, complex adaptive systems, artificial
intelligence-based search and pattern-matching, communities of practice
research and a branch of mathematics called Graph Theory. ONA is
basically an Object-Oriented model of an organization with objects
such as people, teams, and technologies interlinked sending messages
to each other and invoking their respective methods to accomplish
the goals of the firm.
The organizational example described below is a combination
of several knowledge management projects performed by the author.
A key business process will be mapped along with the knowledge exchanges
that support it. The organization will be viewed from several perspectives.
First, the company can be viewed via prescribed structures such
as hierarchy. This view reveals who is assigned where and who reports
to whom. Next, the company can also be viewed via emergent structures.
These views reveal what happens in the white space [between the
boxes] on the organization chart. The emergent views also show where
certain knowledge is clustered in the organization.
The model organization in Figure 1 below is divided
into four components:
- Corporate HR Office
- Compensation & Benefits
- HR Policy & Practice
- HR Research
- Strategic Business Unit [SBU] 1 HR Office
- SBU 2 HR Office
- SBU 3 HR Office
The Corporate HR office is divided into the 3 departments
that participate in a critical HR process. Five key knowledge areas
that contribute to this process where uncovered from interviews
with the client's employees. Employees names are replaced by numbers
to maintain privacy of the study participants.
Figure 1 - Organization Layout
The first question that employees where asked was:
"With whom do you exchange information, documents, and other
resources in order to perform your role in HR business process X?"
Below is a map of the work exchanges to execute this critical HR
business process. These are all confirmed two-way [give and receive]
interactions. The line thickness denotes intensity of relationship.
Figure 2 - Work Flow Network
Work Flow Network
The formal organization structure supports the work
flow for this business process -- most of the strong work relationships
are within the functional walls of the prescribed organization.
Compensation & Benefits and HR Policy are strongly interconnected
and appear to be working as one unit in this process. The SBU's
HR offices do not work with each other directly. Most of their interaction
is with the corporate HR office. This revelation alarmed the Executive
VP of Human Resources. All SBUs have similar missions and very similar
employee populations -- they should be talking to each other about
the changes in this key HR program. As a result of this finding
the most central node in each SBU was invited to process change
meetings together with the other SBUs so that knowledge and experience
sharing relationships would start to develop.
The knowledge exchanges around this business process
are mapped next. These links reveal who helps who learn and make
sense of what is happening in this business process. This is
a map of how expertise is shared. Nodes that are central in this
network are the experts that are sought out for critical information
and knowledge to complete this business process. Which nodes appear
to be 'in the thick of things' in the knowledge network in
Figure 3 below? How does the work flow
network compare with the knowledge exchange network?
Figure 3 - Knowledge Exchange Network
Knowledge Exchange Network
Figure 3 reveals more inter-group connections -- knowledge
necessary for this process is distributed throughout the organization.
A greater number of links between the SBUs are discovered. Yet,
corporate seems to hold most of the knowledge to execute this process.
R&D has fewer connections within the corporate office and is
now well connected to SBU 3 whose HR programs are holdovers from
its former parent company before it was acquired. They apparently
need more interaction to adapt to this new program.
A cluster discovery algorithm is applied to the network
data to see if this knowledge resides in emergent communities of
knowledge [aka communities of practice]. Communities naturally
self-organize naturally in companies around common problems, interests,
customers, and complex knowledge areas. It is within these communities
where core competencies of organizations are stored, shared, nurtured
and enhanced. Individual learning is enhanced by being a member
of one or more communities of practice.
Emergent communities have formed around the 5 knowledge
areas. They are mapped in Figure 4 below. To identify who is from
which organization the reader can refer back to Figure 3 to see
which node color corresponds to which business unit. Employees from
SBU 1 are connected to each other in Knowledge Community C and E
but are not tied to community members from other organizations.
Community fragmentation like this is found in both forming, and
dissolving, communities. The communities in this organization where
just forming in response to a changed environment and new direction
from the HR VP.
Figure 4 - Emergent Communities of Knowledge
Visualizations, like in Figures 1, 2, 3 and 4 above,
give insight into complex human systems not readily available by
other means. Even deeper insights can be gained from measuring these
complex human structures. Networks can be measured on the individual,
group, and system-wide basis. The focus here will be on individual
network centrality. This measure reveals which employees are
key in the flow of information and exchange of knowledge. A central
node is in the thick of things and has access to diverse
network resources such as knowledge, support, and other hidden assets
in the organization. Employees with high network centrality scores
have a greater capacity to get things done.
A common belief is that high network activity
brings increased network benefits. This is not necessarily true.
High network centrality does bring network benefits. Research
has shown that employees who are central in key networks learn faster,
perform better, and are more committed to the organization. These
employees are also less likely to turn over. On the other hand employees
with low centrality, those who are on the periphery, are much more
likely to leave the organization. Project teams also benefit from
being central in advice and expertise networks. Teams that are central
in the organization's knowledge networks complete their tasks quicker
than project teams who struggle to access the knowledge they need
to perform their work.
The secret to network benefits is in the pattern
of direct and indirect connections surrounding a node. It is
the pattern of relationships, that a node is embedded in, that either
constrain or enhance the ability to get things done in the organization.
The goal is to obtain wide network reach without having too many
direct ties. It is the indirect ties that provide network benefits.
Research has shown that both individuals and groups who are central
in organizational networks, yet are not overwhelmed by direct
ties, are very effective in getting things done. Those burdened
with too many direct ties are not as effective.
Opportunities in Networks
Innovation happens, within and between organizations,
at the intersection of diverse information flows and knowledge exchanges.
The network in Figure 4 above shows many opportunities to cross-fertilize
knowledge -- connect knowledge communities that are not yet connected.
These potential connections in networks are called structural
holes. It is across these holes in the network that the opportunity-seeking
player [individual, team, or organization] can establish a superior
position where diverse knowledge and ideas intersect. This position
is superior because it is unique -- these flows do not intersect
anywhere else in the network. The node that spans the right structural
holes receives a diverse combination of information and knowledge
available to no one else in the network. From this advantageous
position innovative products and services can be created. An organization
whose employees effectively span these internal holes of opportunity
creates a competitive advantage that can not be easily duplicated
by competitors. Even if competitors hire away a few employees in
the network they still cannot easily duplicate the knowledge
unique pattern of interconnections] that is in place in the other
Possible New Knowledge Exchanges
How should these knowledge communities be connected?
Use ties that already exist between groups -- the work ties that
currently exchange task resources but not knowledge and learning.
Find nodes that are not overloaded in the work network and assign
them the addition duty of knowledge exchange. The links in Figure
5 below reveal who has a work tie, but not a knowledge
exchange. It is these single purpose ties that can be expanded for
Figure 5 - New Knowledge Exchanges
Why did the HR VP look for possible connections in the
emergent organization? Why didn't she just assign various employees
to these boundary-spanning roles? She knew how emergent communities
work -- trying to formalize the informal, or trying to steer
an emergent process, just leads to resistance and then disappointment.
Knowledge-based organizations, through the people in them, attempt
to adapt to their environments. Exerting too much control over this
process hinders effective outcomes. Building emergent communities
and informal networks is a lot like gardening. The manager/gardener
must provide resources and remove obstacles/weeds so that the employees/plants
can follow goals/sunlight to self-organize and grow. Trying to exert
too much control over this emergent process will usually result
in a poor harvest.
Once the people networks are understood, the right
technology can be implemented to support these evolving entities.
Computer technology needs to be as flexible as the adaptive, self-organizing
human networks it supports. To meet this demand for adaptive technology
many organizations are utilizing the flexible technology and protocols
of the Internet inside the organization.
Tools to manage computer networks have been in existence
for a few years and are becoming more sophisticated. Tools for human
networks are just starting to emerge into general business use.
ONA tools such as InFlow [used in this article] are aimed at HR experts and management consultants.
ONA software has been utilized by early adopter firms since
the late 1980s and is now gaining interest in many industries.
Network Models: Tools for the Connected Economy
Today's fast and fluid business environment requires
HR mangers and consultants to understand the constantly changing
economic webs within and between organizations. Static, hierarchical
structures are no longer sufficient to function in the connected
economy. Adaptation and Learning are joining Control and Planning
in the executive suite of today's innovative corporations.
ONA has been used in many progressive firms including
Rubbermaid, TRW, IBM, and Lucent Technologies. These firms have
applied ONA to improving knowledge exchange, workforce diversity
analysis, post-merger integration, process improvement, and organizational
redesign. Consulting firms such as Ernst & Young LLP and the
IBM Consulting Group have, between them, utilized this technology
with hundreds of clients to support various projects such as product
development, computer system implementation, organizational design,
business transformation, retention analysis, business process reengineering,
knowledge management, strategic planning and other organization
effectiveness efforts. ONA has also been applied to understanding
the emergent dynamics in the network of alliances between firms
in the Internet industry.
A network view of the world is necessary to adapt
to the chaos and complexity of continuous change. In the past, HR
departments focused on the nodes [employees] in the network which
were often modeled as boxes on a hierarchical chart. In times of
reorganization the boxes and their formal connections where moved
around by management prescription.
In today's fluid economy, HR must also focus on the
ties [flows, relationships] in the network, and their ever-changing
patterns. Many adaptations to the rapidly changing environment today
are soft reorganizations -- knowledge exchanges and information
flows are created/strengthened/weakened, but the formal hierarchy
remains in place. This allows for more frequent and rapid adaptation.
Obviously technology must be adaptable with these frequent soft
reorganizations. Network models of how organizations get things
done are as necessary in the new economy as organizational charts
where in the industrial era.
Software and Training in social network analysis are available from the author.
Copyright © 1998, Valdis Krebs