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Originally published 9 June 2011
I don't know about you, but I deal with a lot of people trying to sell me things. Over the years I have been the recipient of a lot of marketing that has claimed in one way or another to be able improve some aspect of "knowledge" in the enterprises where I have worked. Yet, on reflection, I found that I did not have a good understanding of what knowledge is. The problem with this is that words evoke emotional responses as much as they convey meaningful content. Good marketers grasp this, and I have nothing against them crafting the best message they can. But I also have a duty to myself to look past any emotional reaction and figure out if marketers actually mean anything substantial when they talk about "knowledge.” One particularly bothersome practice occurs when "knowledge" is simply illustrated as a bubble, or a slice though a pyramid, sandwiched between "information" and "wisdom," as if this somehow explains the whole thing. Visual metaphors are not definitions; but, unfortunately, if they are pretty enough, a lot of people accept them as such.
"Knowledge" generally has two major meanings: (a) to be acquainted with someone or something; and (b) to know a fact. In English, both are covered by the verb "to know," but in other languages two verbs identify the concepts separately (e.g., in German, kennen and wissen, respectively). I am certain that no marketer of IT products and services is using "knowledge" to mean "acquainted with," as in "I know my neighbor" or "I know downtown Manhattan.”
So if marketers are not offering to introduce me to people, places, or things, they must mean knowing a fact. But there are problems here too. "Knowing," in this sense, means knowing about something that really exists, being assured that this knowledge is correct, and understanding that this level of assurance cannot apply to statements that are not true. Here I am paraphrasing the entry for "knowledge" in Baldwin's Dictionary of Philosophy and Psychology. Is this really what we are concerned with in data management? It does not seem very satisfying to me.
It is true that data vendors, such as those who sell data on corporations, individuals, financial instruments, etc., might claim to be selling knowledge. In my experience, they do not. Rather they claim that what they are selling is data, and it is up to their customers to turn it into knowledge. However, there are vendors of software products and services who do make claims about knowledge. They are most certainly not selling data, which might be regarded as the raw material of knowledge. Rather they are selling tools and techniques that they claim can produce knowledge or better manage it. Again, what is "knowledge" in this context?
There is different traditional way of dividing (subtyping) knowledge, which is (a) immediate; and (b) mediate knowledge. Immediate knowledge is when we cannot deny a fact. If you, dear reader, see me robbing a 7-11, you know that I did it and a court of law will accept your testimony as evidence. Mediate knowledge, however, is knowledge that we acquire that has some kind of guarantee behind it. So if my neighbor tells you that I robbed a 7-11, your testimony will not be accepted from you in a court, because it is hearsay – it is mediate knowledge. Ultimately, however, we have to rely on mediate knowledge to a large extent. So if I am convicted of robbing the 7-11, and you have faith in the judicial process, then you can say that you know I did it. You have the guarantee you need.
I do not see how vendors can make any claims about immediate knowledge because immediate knowledge involves someone and the object of knowledge, and nothing more. But mediate knowledge has everything to do with data. Data is a medium in which supposed facts can be conveyed to us, and we can accept those facts as knowledge. But what can vendors claim about it? Well, they might have more reliable ways by which facts end up as data. The data that comes from sensors that measure manufacturing processes or geographical locations seems to be like this. In this case, better software can result in more and improved knowledge.
But in the enterprises I work in, data is entered by humans, purchased from vendors, or is simply a starting point for knowledge. Is knowledge just the collection of facts that are stored in such environments? If so, then knowledge and data are the same. If this is , then knowledge management and data management are the same. This seems very unsatisfactory – instinctively we expect knowledge and data to be different. But how? We do not seem to be getting much help from traditional definitions of "knowledge," so it might be more helpful to consider this in the specific context of data management.
One of the promises of using data as a corporate asset is that a set of data can be used to produce new facts, that these can be facts that nobody knew before, and thus these facts can be regarded as new knowledge. This is very easy to see in business intelligence (BI) environments. For instance, an enterprise can accumulate data on individual customers and then calculate metrics, such as customer lifetime value. This is not something that an enterprise can simply go out and measure, like taking someone's temperature. It is certainly something that was not known prior to accumulation and analysis of data. Data mining can provide even more astonishing examples, often revealing golden nuggets of information the enterprise can react to (e.g., buying patterns).
Another clue to what knowledge in data management might be comes from a definition by the Victorian philosopher Bernard Bosanquet – knowledge is "the representation of reality.” Again, mere representation is data, but I think that we can kick this definition up a notch to be more helpful and suggest that knowledge is, in part, a model of a specific domain of human experience or subject area. Such a model (some might call it an "ontology") consists of concepts – their relations, rules about their behavior, and taxonomies that organize these concepts. Such a mental model is our knowledge of how things work in a particular domain of interest, and we put data into it to get results aligned to our purposes. This can include planning for the future, or understanding how a particular situation has come about. It enables us to successfully manipulate a representation of reality in our minds, rather than having to deal with only the real world. Anything that contributes to building or managing such models contributes to knowledge. And running such models generates knowledge.
Another aspect of knowledge in the context of data management is the need to successfully use a data resource to fuel the models that give us understanding of customers, business processes, etc. To do this we need to find the appropriate data in an enterprise data resource, understand what it means, determine if it is appropriate for the models (ontologies) that we want to run, and so on. Also, we need to know if the data at hand is such that it contains facts that will oblige us to modify these models. Products and services will be valuable if they help us go from data to knowledge by mapping general enterprise data to the specific models that are our understanding of little pieces of the enterprise and its activities. To some extent, this may be part of what is meant by "knowledge management."
There is a lot more to a definition of knowledge than is provided here, but for me personally it is enough to minimally satisfy my use case of judging the relevance of a vendor who has an offering that claims to support or improve knowledge. If such an offering enables new data to be produced from old data, facilitates the construction of reliable models of specific domains of interest to the enterprise, or assists in fueling these models with appropriate data from the overall data resource, then I am interested. But if the word "knowledge" is simply being used to elicit an emotional response from me, and is only an inflated term that really points to a simpler concept, such as data, then I am going to be cautious.
Finally, I realize this is a difficult topic, and that readers may have genuinely different viewpoints on it. I welcome any feedback, and if I get enough I will try to represent it fairly in a follow-up article, even if it is critical of what I have written here.
SOURCE: What Is Knowledge?
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