posted 1 Jun 1999 in Volume 2 Issue 9
Business Intelligence versus Knowledge
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.
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?
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: email@example.com