denotes premium content | Jun 19 2013 Feature
posted 1 Jun 1999 in Volume 2 Issue 9
Business Intelligence versus Knowledge
Management
This article is an academic argument designed to stimulate
thought and provoke wider debate around the role and function of Business
Intelligence in relation to Knowledge Management. It approaches Knowledge Management
and Business Intelligence from the perspective that both activities have a
common objective - the persistence and prosperity of the organization. Shaun McCarthy
explores the means to which this is achieved through generating and applying
Intellectual Capital.
The principle is as old as mankind itself. Man requires knowledge before
he can act sensibly. Human understanding is required for making sense out of
information and for applying knowledge.1
Before man can act, he needs to have some sort of basic idea about what it is
that he wants to do or achieve. Therefore identifying strategic objectives is an
activity that precedes information gathering. The next logical step is obtaining
the necessary knowledge in order to achieve those objectives. Knowledge
Management is essentially a management philosophy that is a means to an end and
should not be confused as the end in itself.
Fundamentally,
Business Intelligence and Knowledge Management have the same objective - to focus on
improving business performance. The purpose of Knowledge Management is to achieve
the maximum degree of understanding of one's operating environment and
relevant circumstances that can advance or retard progress toward an objective.
However, the same rationale applies to the concept of Business Intelligence. If we
agree that Business Intelligence is comprised of Customer, Competitor and
Market Intelligence and that the purpose of conducting Business Intelligence is
to support strategic decision-making, grow the business and monitor
the organisation's competitors, then we recognise that there are
definite similarities between Knowledge Management and Business Intelligence. While
both concepts share a common high level objective, there are some
fundamental differences. These differences are to be found in the manner in which they
are applied towards achieving that goal. The value of Business Intelligence and
its product, opportunity analysis, is found in its usefulness as a decision
making tool; the value of Knowledge Management lies in the ability of the
organisation to identify, capture and reuse knowledge and in particular best practices
in such a manner that it saves the organisation time, effort and resources
-translated and measured in cost.
Opportunity
analysis
Intelligence for its own sake is of little business value
unless it can provide actionable value. By this it is meant that opportunity
analysis should be the objective we strive for within Business Intelligence.
Opportunity
analysis is an intelligence assessment relating directly to the vulnerabilities
and opportunities of the organisation as they arise from circumstances within
the operating environment. The key element of opportunity analysis is the
intelligence production unit's understanding of the organisation's objectives.
Being able to relate to the knowledge on hand and to interpret that within the
context of the organisation's strategic objectives - in effect by pointing out
the opportunities and vulnerabilities that decision-makers and marketing
personnel can exploit to advance the organisation and to improve customer
relationships is crucial. The standard is to provide actionable analysis without
prescribing general guidelines.
Opportunity analysis depends upon two
fundamental principles.2The first
holds that opportunity analysis starts with the effective tasking by
intelligence consumers - in most organisations the consumers are the users of
intelligence. The consumers are responsible for identifying the relevant
intelligence priorities. The second principle postulates that in order to
satisfy the needs of the consumers, the intelligence producers must provide
analytical assessments that deliver a high order of understanding and insight
that can support sound decision-making, customer relationship building and
strategy planning. This implies that intelligence adheres to a distinct process.
The
Intelligence Process
For analysis to be effective in business it
needs to add tangible value to the organisation. This is usually difficult to
measure in any currency and therefore analysis is best measured in some other
form of value in relation to the organisation's persistence and prosperity. This
value is created in the form of Opportunity Analysis. In consulting companies
however, business intelligence must be combined with expertise and knowledge
from within the organisation's centres of excellence to create solutions-based
consulting products.
One of the most difficult stages in the intelligence cycle is the
analysis process. The challenge lies in the intelligence producers' ability to
weigh information about the external operating environment and to integrate that
information with the internal knowledge of the organisation. The objective is to
identify patterns, trends and tendencies and to formulate a range of scenarios
predicting probable future outcomes and to be able to discern potential
opportunities and barriers against achieving them. With the exception of Daily
Intelligence Briefings, Opportunity Analysis is an intelligence quality that
should be incorporated within all analysis efforts and reflected in intelligence
products.
The Shared dilemma of interpretation and value
recognition
For the purposes of this discussion when we talk of
knowledge, we are referring to knowledge in the following context:
Knowledge is a fluid
mix of framed experiences, values, contextual information, and expert insight
that provides a framework for evaluating and incorporating new experiences and
information. It originates and is applied in the minds of knowers. In
organisations, it often becomes embedded not only in documents or repositories
but also in organisational routines, processes, and norms3
In addition, Gartner Group defines
Knowledge Management as:
"Knowledge Management is a discipline that promotes an integrated
approach to identifying, managing and sharing all of an enterprise's information
assets. It is the discipline applied to manage intellectual capital."4
It can be
said that Knowledge Management is a system that includes a process to identify,
understand and use knowledge in a creative manner to add value. It is a process
to facilitate the efficient flow of knowledge to the right people in a timely
manner. A Knowledge Management System therefore includes strategies, tactics,
processes and enabling technologies that facilitate and support the creation,
capture, process, organisation, delivery and leverage of knowledge within an
organisation. Implicit in this definition is the need to encourage the use of
knowledge to achieve leverage. For Knowledge Management makes no sense unless it
contributes to improving performance through savings in time, effort and
resources. 'A company's choice of Knowledge Management strategy is not
arbitrary 'it must be driven by the company's competitive strategy.'
In the search for knowledge the first
logical step or place to start is at home. In other words, to start by searching
for the information or expertise that is required from within the organisation.
After having explored or searched for the information within the organisation
the next logical place to look would be outside sources. Having collected the
information internally and externally the next step is bringing all the relevant
pieces of information together for analysis that includes the essential step of
interpretation. For it is in the act of interpretation that information becomes
knowledge from a Knowledge Management perspective and intelligence from a
Business Intelligence perspective. The end product or outcome generates
Intellectual Capital for the organisation. It is really at this juncture where
Business Intelligence and Knowledge Management meet.
This is not the only similarity in the
Knowledge Management and Intelligence processes. The kernel of similarity
however, is found in the conversion process of data to information to knowledge.
This transformation is similar to the conversion of information to intelligence
through the analysis process of evaluation, verification and interpretation. In
both processes the end product is knowledge. The intelligence process does not
end there however, and is extended when that knowledge is recognised as
Intellectual Capital and awarded varying levels of classification in accordance
with its sensitivity, value and the need to protect its source and method.
One of the key
issues around Knowledge Management and Business Intelligence is the point at
which information is recognised for its knowledge worth. By this we mean at what
stage in the process of converting information to intelligence and knowledge
does the analyst or manager of that knowledge perceive its value to the
organisation? While we may not be able to actually pinpoint the exact stage in
the conversion process, what is evident however, is the need for the analyst or
knowledge manager to command an in-depth understanding of the strategic
objectives or direction of the organisation. This principle of Knowledge
Management and Business Intelligence reinforces the need to understand the
relationship between producers and consumers of intelligence and knowledge.It
emphasises the significance of the producer-consumer relationship and the
necessity for an appropriate business mechanism to manage and sustain the
linkage and communication between them.
The key to the success of both
intelligence and knowledge within the business environment and in terms of
deriving value therefrom is dependent upon the following criteria:
1. The recognition by
the content owner of the relevant association between the knowledge or the
intelligence information and the strategic objectives of the organisation
2. The degree of
understanding where that knowledge or intelligence information can be applied
towards achieving an advantage.
To date one of
Knowledge Management's biggest challenges is to identify a process or methodology whereby the
owners of information are able to apply associations of value to that
information and convert information to knowledge and ultimately intellectual
capital. One approach is to introduce a process within the organisation's
project management discipline whereby project managers, using a template, capture key
learnings at the end of all completed projects. A sort of After Action Review
(AAR) process. This knowledge then contributes towards the capture and use of 'best
practices' and replication - a process that can help organisations shorten learning curves
and reduce costs through leveraging previously invested resources, time and
money. Without the above criteria, the whole exercise becomes nothing more than
organising information. The Holy Grail of Knowledge Management therefore is to
apply knowledge towards gaining a competitive advantage. In todays highly
competitive environment it is the time to market that an organisation takes
between innovation and product or service maturity that will enable it to gain
an advantage.
Business intelligence as a component of knowledge
management?
If we approach this question from the perspective that
the end product of Business Intelligence is Opportunity Analysis and that
Opportunity Analysis, once classified, becomes an organisation's Intellectual
Capital, then the concept of defining Business Intelligence as Knowledge would
appear to be a logical inference. This deduction is reinforced by the
interpretation of Intellectual Capital. Thomas Stewart defines Intellectual
Capital as:
"Intellectual capital is the sum of everything everybody in a company
knows that gives it a competitive edge.5
If we apply Stewart's
rationale of Intellectual Capital to Knowledge Management and Business Intelligence
we cannot fail to recognise the common goal - competitive advantage. Therefore it
is difficult to argue against the notion that Knowledge Management and
Business Intelligence are one and the same activities. Yet there are those who
would argue that there is a fundamental difference between the two. One argument
finds its roots in the principle of knowledge sharing. As a former
intelligence officer, the concept of Knowledge Management and the principle of
sharing knowledge is in direct contradiction with the rule of applying the 'need to know
basis' that intelligence managers have traditionally applied to the sharing of
intelligence. This is a factor that some competitor intelligence specialists may
refer to when defending the need to uphold Competitor Intelligence as a
profession apart from that of Knowledge Management. But this argument is surely
not sufficient grounds for making the case. What then are the factors that
differentiate KM from BI while recognising that both activities strive for
identical goals?
Conclusion
I can offer
the following concluding perspective. Classification is one area that
could distinguish Business Intelligence from Knowledge Management. Intelligence analysis,
once produced, is generally classified according to its strategic value and in
order to protect collection methods and information sources - a scarce and treasured
asset. A contradictory argument, however, is that in the knowledge
based economy, intelligence sources abound. A plethora of sources and electronic vendors
are to be found on the Internet. In fact, many CI professionals are
touting the Internet as the 'golden highway' to intelligence information and are
offering courses on how to exploit this goldmine. This abundance of information on
the Internet however, has the potential to swamp the consumers, causing
information overload. The information era and the Internet is indeed having a
profound impact upon the traditional methods of intelligence. This is
particularly relevant when we consider its influence on the intelligence
producer-consumer relationship. Enjoying direct access to the wellsprings of
information, consumers are now 'doing it for themselves' and engaging in their own analysis
instead of relying on trained and professional analysts who verify, evaluate and
interpret information on the consumers' behalf. The long-term effects of this
still remain to be seen. Intelligence may very well be replaced and indeed
mistaken for instantaneous information. No matter what level of classification
ends up being applied to intelligence, the end product that retains value is
also Knowledge and Intellectual Capital. The answer may be that while we
acknowledge that some knowledge found in a manner where the methods and sources
of contributing data and information need to be safeguarded, then those
associated activities and the end product need to be called Business
Intelligence.
Shaun McCarthy is Regional Leader for the Americas within Shell
International. He can be contacted at: spmccarthy@shellus.com
