●
◗ Data
The dictionary definition of data is ‘known facts or things used as a basis of inference or reckoning’. Let’s try to unravel this multifaceted term and show that a definition of data depends on context. We acquire data from the external world through our senses and try to make sense of these signals through our experience. This external data becomes internal fact. The assumption about facts is that they are true. But our senses can play
Chapter 1 / Introduction to knowledge management 17 games with us. An example is the optical illusions contained in Escher’s drawings, which can be seen in two different ways. Escher made an art of creating impossible figures, such as people ascending and descending stairs at the same time, that were clearly con- tradictory. We can also exclude data in a number of ways that can affect our inference or reckoning of it. The first is by not focusing on the data, such as with the ‘cocktail party’
effect where we are bombarded with lots of data but are able to ignore most of it (back- ground noise) and concentrate on the data of the person speaking to us. We also exclude data when our senses are not able to respond to signals such as ultraviolet light or ultra- sound, and we may exclude data voluntarily by putting on a blindfold or inserting ear plugs (Meadows 2001) or involuntarily through data overload.
So far we have explored data from the perspective of the receiver of the signal. In this context, a signal is a set of data transmitted to our senses. What about the source of the signal and the channel or medium through which it is transmitted? Each one of these can contain a distortion and this can affect the nature of data coming to us. The traditional game of ‘Chinese whispers’ at the dinner table shows how an initial message can become totally distorted by the time it has gone around the table.
There are differences between quantitative and qualitative data. For example, the numbers 72 and 83 per cent are pieces of data that can have multiple meanings and are highly context dependent. They may refer to mean examination scores or the perform- ance of a new carburettor undergoing trials, so the data is meaningless when taken out of context and requires an association with something else. Qualitative data is much more troublesome as it depends on the perceptions of the transmitter and receiver of the data. Ten participants in a meeting are likely to provide ten totally different accounts depending on their perspective and their selective inclusion or exclusion of data. In this sense data is also value laden. An example of this is two artists, one European and the other Chinese, who painted ‘faithful representations’ of the same landscape in the English Lake district (Gombrich 1960). To European eyes, the paint- ing by the Chinese artist was typical of a Chinese painting. This example shows the
‘conceptually saturated’ character of observation and data where it is difficult to distin- guish between what is observable (empirical) and what is unobservable (theoretical or conceptual). We may have ‘sensations’ in our eyes without concepts, but we have no perception of data without concepts (O’Connor and Carr 1982).
●
◗ Information
The dictionary definition of information is ‘something told’ or ‘the act of informing or telling’. However, this doesn’t help us distinguish between data and information.
Information could be considered as ‘systematically organised data’ (Meadows 2001).
The notion of ‘systematic’ implies the ability to predict or make inferences from the data assuming it is based on some system. If we are given a sequence of odd num- bers such as 7, 9, 11, 13, we can predict from the information that the next number in the sequence will be 15. To inform, the data needs to be organised. This may be done through some form of classification scheme set up to provide a framework for our thinking. For example, libraries classify their books using a bibliographic classifica- tion scheme. A common one is the Dewey Decimal Classification which is based on
dividing all of knowledge into ten fields ranging from 0–999. Dewey has essentially fol- lowed a Darwinian model in which different aspects and parts of knowledge are related to each other either by direct descent or by collateral kinship. All knowledge is divided into genera and species using a similar approach to Darwin’s. The ten encompassing classes (000, 100 … 900) are subdivided, first into 401, 402 …, then 410, 411, and then by adding further numbers after the decimal point that are related to numbers which can also appear before the point (an example is that the number after the decimal point is the same for certain periods covered in related subject domains such as English history and English literature).
Another conception of information is data that are endowed with meaning, rele- vance and purpose. This does not have to have a scientific meaning such as the Dewey classification system but may have a subjective meaning given by the receiver of the data or message. Information gives shape to the data and makes a difference to the outlook or insight of the receiver of the data. In this sense, it is the receiver of the data that determines whether a message is data or information. A consultancy report may be written to inform senior managers of critical issues but may be judged as ramblings and noise by the recipients (Davenport and Prusak 1998). Meaning in data often occurs through some form of association with experience or relationships with other data.
●
◗ Knowledge
In a practical sense, knowledge could be considered as ‘actionable information’, as shown in the hierarchy of data, information and knowledge in Figure 1.4. Actionable information allows us to make better decisions and provide an effective input to dia- logue and creativity in organisations. This occurs by providing information at the right place, at the right time and in the appropriate format (Tiwana 2000). Knowledge allows us to act more effectively than information or data and equips us with a greater ability to predict future outcomes.
However, knowledge is much more complex than this simplistic notion. We have devoted the whole of the next chapter to exploring how over the past two millennia western philosophers have grappled with the question of what knowledge is. There is still no consensus on the nature of knowledge except that it is based on perceptions that can provide rational justifications for it. Such perceptions are based on our onto- logical and epistemological assumptions of reality. Put simply, we all wear ‘different coloured glasses’ whether we are aware of it or not. These ‘glasses’ contain assumptions about reality, such as whether it is subjective or objective (ontology) and assumptions about what we can know (epistemology). Continuing this analogy, the knowledge of a certain phenomenon is likely to be different if one individual wears ‘pink’ glasses and
Critical thinking and reflection
From your experiences, can you describe situations where you have made decisions with wrong data or information? How do you guard against this? What strategies do you adopt to evaluate a situation with conflicting information or data? How do you manage ‘noise’ or irrelevant data or information related to a particular problem? How do you manage too much data or the problem of ‘information overload’?
Chapter 1 / Introduction to knowledge management 19
another wears ‘blue’ ones. Hence, for example, it is no surprise that the knowledge of costs and benefits of organisational restructuring is often viewed very differently by the workforce and by senior management. The interpretation of the same data and information will vary significantly depending on these perceptions and the original knowledge base of the individual.
The most common notion of knowledge in the current KM literature has its roots in the ideas of logical behaviourism based on the writings of Gilbert Ryle and Michael Polanyi. From this perspective, knowledge exists along a continuum between tacit knowledge (know-how) and explicit knowledge (know what) (Polanyi 1967; Ryle 1949).
(See Chapter 2 for more in-depth coverage of knowledge frameworks and typologies.) One of the major challenges in knowledge management is exploring creative ways to convert the tacit knowledge base in organisations into explicit knowledge (Nonaka 1994). Organisational routines, practices and norms can also act as part of this tacit knowledge base. Despite the logical behaviourist perspective of tacit and explicit knowledge being dominant at present, there are numerous alternative perspectives on the nature of knowledge. As the literature gains in maturity, it is likely that other per- spectives such as postmodernism, critical theory and realism may provide new insights and advances in this field.
●
◗ Wisdom
Wisdom and truth have been shown to have higher qualities than knowledge in the hierarchy of Figure 1.4. These terms are even more elusive than knowledge. Wisdom is the ability to act critically or practically in a given situation. It is based on ethical judgement related to an individual’s belief system. Wisdom is often captured in famous quotes, proverbs and sayings. Some examples of proverbs from around the world include the following:
●
● Children have more need of models than of critics (French).
●
● You can’t see the whole sky through a bamboo tube (Japanese).
Truth Wisdom Knowledge Information
Data
Truth Wisdom Knowledge Information
Data PURPOSEFUL ACTION
Figure 1.4 Data, information, knowledge and purposeful action
●
● There is plenty of sound in an empty barrel (Russian).
●
● Trust in Allah, but tie your camel (Muslim).
●
● Wonder is the beginning of wisdom (Greek).
Truth is even more problematic, since there is a growing realisation that social phenomena are theory laden, as illustrated in the above example of the Chinese and European artists. Theory-neutral observations do not exist, as our tacit theories or con- ceptions of the world affect our observations. The notions of ‘truth’ and ‘objectivity’
can appear meaningless if the social world can be understood only through particu- lar ways of seeing. This implies that there are multiple truths rather than one absolute truth of social phenomena. A pessimistic outlook on information, knowledge and wisdom has been captured in the well-known lines from T.S. Eliot in the ‘Choruses’
from The Rock:
Where is the life we have lost in living?
Where is the wisdom we have lost in knowledge?
Where is the knowledge we have lost in information?