8.1.1 A basic information management framework
Figure 4 Prioritising knowledge sources
The above figure highlights the dilemma confronting most individuals and organisations. How do you prioritise what information and knowledge your resources can justifiably obtain and hold, and which ones do you access as required? Assuming the requirements for the knowledge needed within the organisation are clearly defined, the two key parameters for setting priorities are the ease of access and the ‘value add’ of the knowledge. The ability to access and utilise information as actionable knowledge leads to a further important consideration. It triggers the design specification for the type of information system and technology required to manage knowledge.
Figure 5 Basic intranet knowledge management technology framework
An Intranet is concerned with optimising every employee’s access to knowledge in a timely manner. The aim is to ensure that all knowledge is managed and made available where it is required, irrespective of whether it may reside in different parts of the organisation or be used in different ways.
As depicted in the above figure, the building of any knowledge management or information technology framework has to consider three key design issues:
Capture – How to access information and data in a manner that is required, when it is required.
Storage – How will different forms of data and information be stored or technology designed to maximise access to stored data, documents, files, etc.
Retrieval – How do we make knowledge available to the user in a manner they can employ, irrespective of the data format or the technology.
Whether for an intranet or any information sharing framework, the three design features listed above enable information or data to be distributed in a manner whereby it can be actioned. Unlike the problems associated with accessing and using raw data or unprocessed information, knowledge frameworks can be designed to make sense of even the most extensive set of data and provide it to a user based on their individual needs.
Figure 6 Information and data access and use
The above systems reflect the need to build systems that meet the user’s knowledge requirements. If broad access to data is the aim, then the first model may suffice. However, the data warehouse-type of design brings together information and data across all specified activities and then presents that information to the user based on their needs and preferences. It has advantage over the point to point system in that the sum of the organisation’s knowledge can be tracked and the return on investment from the utilisation of that knowledge tied to the sum of each user and their requirements.
Effective Information Resource Management requires that some organisations manage multiple stockpiles of the same information (e.g. contacts, customer details, etc.). If this is not done problems can arise because there is no one consolidated and up-to-date version. Beside the efficiency costs of orchestrating information under one system, information needs to be managed as an organisational resource. For instance, consider the problems where customer information resides only with one employee and they leave. They could exit with “their own” customer list, and leave the organisational records with no information or knowledge of value in relation to those customers.
Dangers
Table 1 Top eight data management problems that restrict knowledge generation
Failure to track |
When data is captured (eg. customer feedback, sales receipts, etc.) it is not coded or identified in a manner that makes it able to be tracked or analysed |
Lack of currency |
Data and information lacks version control or any way of distinguishing if it is current or if it replaces earlier data |
Wrong data |
It measured and tracked, but the data or information gives an inaccurate, dated or incomplete picture |
Wrong time |
Right data and information, wrong time to collect it or project outcomes from data collected at that point in time |
Restricted access |
By its nature the data is not able to be readily accessed, it is secret, or not every one can access it as and when they require |
Over duplication |
Data or information is repeated, included from different sources or overused to the point where its validity and reliability become questionable |
Too Mobile |
Data that is easily accessed is either overused to the point where it holds little value or the reverse, it holds so much value it needs to be protected from migration to competitors |
Embedded relevance |
Data is so specific to a problem, context, location or such like it can not be extrapolated, accessed easily or translated into action |
Given the above problems the ideal for data management and the generation of actionable knowledge is depicted below.
Figure 7 Data that translates into knowledge able to be used
Yet even if we can build the system to code, track and enable access related to purpose, knowledge still comes in many forms and structures. We will now move on to examine this and test its implications for how we access and manage information and knowledge.
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