Week 2 - Data — Information — Knowledge

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1. INTRODUCTION

A practical way of arriving at a definition of knowledge … is to differentiate it from what it is not. One of the most common distinctions in the current knowledge literature is between knowledge, information and data.

2. “MY PASSING THOUGHTS”

I have read numerous books on Information Technology (IT) and followed the discipline of information management on managing information as a resource; for that reason data and Information is something I understand well.

Knowledge is something I have not really thought about defining. To one it means analysing and understanding the information or data and acting upon it. Figure 1 shows what I think of the three terms:

3. BACKGROUND READING

3.1. Understanding the Terms

From previous reading of these three terms, it is not straightforward to find one concise definition. Moteleb & Bakry (2004) find the “lack of a definition that clearly distinguishes between the terms” and “the terms are usually used interchangeably in literature”. Consequently confusion occurs.

To understand these three terms, I have found some prominent scholars in Knowledge Management (KM) and also the everyday Cambridge dictionary; and listed their definitions in Table 1 to see the difference:

This table is not exhaustive (just limitations of constraints)…

As you can see from the above table, that there is no clear definition for each term, each scholar takes a different view from each other. This is supported by the work of Dick Stenmark (2002) who finds “many researchers use the terms very casually”. For example: information and knowledge, is sometimes used interchangeable in the earlier work of some scholars like Kogut and Zander (1992) who state that “knowledge as information” which they “mean knowledge which can be transmitted without loss of integrity”. Thus leading to confusion by indicating that information is a type of knowledge.

The earlier work on KM did not specify the clarity of knowledge and information, therefore the reason of perplexity about these terms (Stenmark, 2002, Lang, 2001, Hislop, 2004).

3.2. Understanding Knowledge

The meaning of data and information and the relationship between them is fairly straightforward, however defining knowledge is not that clear cut. Knowledge can be regarded as the next level of business value after the transformation from data to information (Chaffey & Wood, 2005; Lang, 2001).

Knowledge can be interchangeable to information and then data, it is not linear as thought out, Orna (1999) states “knowledge and information are separate but interacting entities, that transform one to another constantly” and agreed by scholars such as Moteleb & Bakry (2004) say “knowledge could be used to derive information, as well as to create data from information”, this is shown evidently in Figure 2:

For example: knowledge that is held inside an individual must be converted and communicated to others, either via verbal, written or visual information (Gurteen, 1998). Knowledge has a propensity to be less structured and is often transmitted informally, which it is less tangible than structured and formal information (Bellinger, 2004).

If you wish to read further on knowledge, view my other article ‘How to define Knowledge…?’

4. MY PERSONAL STAND POINT

Table 2 shows what I think of terms.

From experience I have seen data, information and knowledge valued in accordance to what the other side sees it as. For example: when I was working for certain company (won’t mention names, don’t want to be sued), when they wanted to leak some facts at price, they would explicitly say information and not data, because data is perceived as useless and information as quality.

Knowledge and information would some time be mixed up together to generate more value, because by saying knowledge it seems superior the information.

I do think it is important to distinguish between information and knowledge, as I originally thought it was not. This is because information is just processed data that can be reproduced quickly and cheaply, whilst knowledge is expensive but also something far harder to gain. Therefore understanding the difference helps the individual or organisation to achieve better efficiency.

5. IN PERSONAL CONTEXT

This example is not exhaustive, it just shows the process data, information and knowledge goes through the time in reading for a master degree.

6. THEORY IN PRACTICE

6.1. Tesco ClubCard

Tesco have been collecting data and information from customers for some time with there ClubCard. This is very popular with customers because of the incentive in reward points and discounts vouchers because of the loyalty the customer shows.

To have ClubCard; Tesco must first obtain personal information about you, so they can send your vouchers to you, for example: name, address, etc.

Tesco Clubcard is highly beneficial to the organisation. Data is captured at the point when a customer makes a purchase at the checkout. This is then sent and stored to a large database which allows them to forecast/manipulate and see what other products or services offered or suited to different types of customers.

This data becomes information when required, for example: Tomlinson & Evans (2005) state they are “mapping out their personality, travel habits, shopping preferences and even how charitable and eco-friendly you are”. This information is used by senior management to analysis and makes decisions to drive up sales by marketing products that suit the customer. In addition this is the knowledge gained by the senior management because they understand the retail market and intend to use this knowledge to make decisions that will add value to the organisation, for example: through sales, customer service, etc.

This knowledge does not stop here; it could be sold to different marketing firms that want to find out information about certain individuals

This is not all negative to the customer; it helps Tesco to stay competitive by offering better services to its customers.

6.2. Tesco Strategic Management Example

Figure 4 shows an example of strategic management using data, information and knowledge to make decision that will impact the organisation:

This example is not exhaustive, it just shows the process data, information and knowledge goes through making a decision at strategic level. There are many possibilities.

6.3. Metropolitan Police Service Definitions

The Metropolitan Police Service (MPS) is organisation with vast amounts of data, information and knowledge. Figure 5 shows the position of MPS with these terms:

For example:

Data would arrive in boxes containing police officers completed ‘stop and search’ slips. The slips would contain information about the subject that was stopped and searched. Processing of this data would happen manually if it was unreadable for the automotive optical character recognition (OCR) reader. OCR reader would capture the data and store it in a database. The data would become information when the annual statistic reports are published. This annual statistic report would be analysed by officials with experience of interpreting the information into knowledge to make an expert opinion of what actions can be taken. Thus information can be interpreted in anyway by anyone; however knowledge is far more valuable because it has expert opinion on what appropriate action to take.

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Reference(s)
	Web		Bellinger, G. (2004) Knowledge Management—Emerging Perspectives [Online]. Miami University - Systems Thinking: United Kingdom (UK), England, Lancashire, Manchester. [Accessed on: 2009-02-03]. [Available on: Issuu: https://issuu.com/raviii/docs/web-2004-bellinger-knowledge-management-emerging-p].
	Book		Chaffey, D. & Wood, S. (2004) Business Information Management: Improving Performance Using Information Systems. Financial Times Prentice Hall: United Kingdom (UK), England, Essex, Harlow. [ISBN: 9780273686552]. [Available on: Amazon: https://amzn.to/3yZ6vdF].
	Journal		Coulson-Thomas, C. J. (1997) The Future of the Organization: Selected Knowledge Management Issues. Journal of Knowledge Management, Volume: 1, Issue: 1, Page(s): 15-26. [doi: 10.1108/13673279710800691]. [Available on: Emerald: http://search.proquest.com/docview/28668233].
	Book		Davenport, T. H. & Prusak, L. (1998) Working Knowledge: How Organizations Manage What They Know. Harvard Business Publishing: United States of America (USA), Massachusetts (MA), Suffolk, Boston. [ISBN: 9781578513017]. [Available on: Amazon: https://amzn.to/3EZUXKZ].
	Journal		Gurteen, D. (1998) Knowledge, Creativity and Innovation. Journal of Knowledge Management, Volume: 2, Issue: 1, Page(s): 5-13. [doi: 10.1108/13673279810800744]. [Available on: Emerald: http://search.proquest.com/docview/28331016].
	Book		Hewings, M. (2005) Advanced Grammar in Use with Answers. 2nd Edition. Cambridge University Press: United Kingdom (UK), England, Cambridgeshire, Cambridge. [ISBN: 9780521532914]. [Available on: Amazon: https://amzn.to/3Sl878H].
	Book		Hislop, D. (2009) Knowledge Management in Organizations: A Critical Introduction. 2nd Edition. Oxford University Press: United Kingdom (UK), England, Oxfordshire, Oxford. [ISBN: 9780199534975]. [Available on: Amazon: https://amzn.to/3EUqwWK].
	Book		Ichijo, K. & Nonaka, I. (2006) Knowledge Creation and Management: New Challenges for Managers. Oxford University Press: United Kingdom (UK), England, Oxfordshire, Oxford. [ISBN: 9780195159622]. [Available on: Amazon: https://amzn.to/3DaXaRB].
	Journal		Kogut, B. & Zander, U. (1992) Knowledge of the Firm, Combinative Capabilities, and the Replication of Technology. Organization Science, Volume: 3, Issue: 3, Page(s): 383-397. [doi: 10.1287/ORSC.3.3.383]. [Available on: INFORMS: https://pubsonline.informs.org/doi/10.1287/orsc.3.3.383].
	Journal		Lang, J. C. (2001) Managerial Concerns in Knowledge Management. Journal of Knowledge Management, Volume: 5, Issue: 1, Page(s): 43-59. [doi: 10.1108/13673270110384392]. [Available on: Emerald: https://www.emerald.com/insight/content/doi/10.1108/13673270110384392/full/html].
	Conference		Moteleb, A. A. & Bakry, W. M. (2004) Polymorphic Nature of Knowledge: Towards a Knowledge Creation Model. In: Irani, Z. and Kamel, S., of editor(s) of the: Proceedings of the Conference on Information Science and Technology Management (CISTM 2004), 8th-9th July 2004. Information Institute Publishing: Egypt, Alexandria, Volume, Page(s): 1-12. [Available on: Issuu: https://issuu.com/raviii/docs/polymorphic-nature-of-knowledge-towards-a-knowledg].
	FoIR		MPS. (2006) Information Management Strategy 2006-2011 [Freedom of Information Request]. Page(s): 1-66. Metropolitan Police Service: United Kingdom (UK), England, London. [Accessed on: 2009-01-01]. [Available on: Issuu: https://issuu.com/raviii/docs/foir-2006-mps-information-management-strategy-2006].
	Book		Nonaka, I. & Takeuchi, H. (1995) The Knowledge-Creating Company: How Japanese Companies Create the Dynamics of Innovation. Oxford University Press: United Kingdom (UK), England, Oxfordshire, Oxford. [ISBN: 9780195092691]. [Available on: Amazon: https://amzn.to/3sg3y4W].
	Book		Orna, E. (1999) Practical Information Policies: How to Manage Information Flow in Organizations. 2nd Edition. Taylor & Francis - Ashgate Publishing - Gower Publishing: United States of America (USA), Vermont (VT), Orange, Brookfield. [ISBN: 9780566076930]. [Available on: Amazon: https://amzn.to/3sev9Du].
	Conference		Stenmark, D. (2002) Information vs. Knowledge: The Role of Intranets in Knowledge Management. In: Sprague, R. H., of editor(s) of the: Proceedings of the 35th Annual Hawaii International Conference on System Sciences (HICSS), 7th-10th January 2002. Institute of Electrical and Electronics Engineers: United States of America (USA), Hawaii (HI), Big Island, Volume: 35th, Page(s): 928-937. [doi: 10.1109/HICSS.2002.994043]. [Available on: IEEE: https://ieeexplore.ieee.org/document/994043].

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Reference (or cite) Article
	Kahlon, R. S. (2009) Week 2 - Data <—> Information <—> Knowledge [Online]. dkode: United Kingdom, England, London, Hendon. [Published on: 2009-01-27]. [Article ID: RSK666-0000005]. [Available on: dkode | Ravi - https://ravi.dkode.co/2009/01/week-1-orgnetcop.html].

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