Author: Brian Johnson
1. Information and technology
Information is the DNA of the enterprise, how it is recorded, secured, retrieved, changed, etcetera. And IT is, for the most part the engine for those actions. But there is also a school of thought stating that information strategies are part of IT technology strategies. Try telling your CEO that. Information is processed through a lifecycle no different to anything else, the issue is that the Information Lifecycle is the reason technology was created to facilitate the management of data---not the other way round!
Information Management is not concerned only with Information Technology. Information is the business of the traditional experts such as librarians, records managers, information scientists, database administrators, systems analysts and programmers and so on. And although the majority of information is now transmitted using IT rather than on pieces of paper (the majority does not mean all....), the principles of document management still apply. The records are electronic documents and if anything the ‘old fashioned’ principles of managing records are more important than ever.
The proper administration of information (or lack of it) by IT has been the cause of many scandals lately, loss of information, failure to secure data, and privacy controversy, all are high on the list of CEO headaches. Information and data management (IDM) is both a policy matter for senior managers and a practical management task for information services professionals and practitioners who have responsibility for its implementation. Information and knowledge management also should be on the agenda---but often is not.
Information is the product of factual data processed and presented to meet a business requirement. An enterprise information service and systems define the context within which data is used to derive information. As technology enables an increasing amount of data to be collected and used to support information requirements, the definition, collection, maintenance, use and disposal of this data has to be managed in support of effective information management.
Without proper Information and Data Management there is no basis for proper Document and Records Information Management (DRIM). It is simply fundamental to good governance of
information assets. IT is responsible for the majority of information assets because of the way information is stored in the modern day; DRIM is not, therefore, something only for the business to be concerned about, it is probably the most important concept for IT; security and privacy issues are becoming more newsworthy (and more embarrassing) with each passing month.
We begin by clarifying a few definitions;. In this section data is defined as the raw material collected from disparate sources, both structured and unstructured; information is the structuring of that data into meaningful, useful elements; knowledge is the ability to put the information into context so that it has value.
Some important questions to consider include:
• Does the enterprise know what knowledge, information and data is needed to achieve its information services strategies?
• Are the knowledge, information and data assets easily found by those that need them?
• Does a collaborative community thrive that ensures valid, useful and timely knowledge and information is available to those that need it in an effective manner?
• Are enterprise information services (for example, service desks or electronic or paper document repositories and/or libraries) based on good-practice principles that support the storage and retrieval of information, data and knowledge assets in a way that optimally serves the business?
• Are the risks of being unable to access information in the event of a major IT failure understood? Are all information assets – electronic and paper – under proper and effective control?
• Is “proper and effective control” defined, understood audited and monitored?
• Is the relationship between knowledge, information and data fully understood?
• Has knowledge management become a technology issue and become divorced from business information oversight?
If your answer to the last question is ‘yes’ then knowledge, information, data and the responsibilities for each of these, are not being properly addressed by information services professionals.
3. Data, Information and Knowledge
“Data”, “information” and “knowledge” are often, incorrectly used interchangeably; it is not pedantic to be certain that everyone knows the definitions and the differences. Schools of thought vary, though it is generally accepted that information is data that has been organized; knowledge is using that information for a specific and successful purpose. For instance, mining many names and addresses from the database for some purpose transforms the data into information. Putting that to a specific purpose requires knowledge.
Without context, information has little or no value. People tend to think about and evaluate the things they do because they can place them in context – either because of experience or education. For example, outside of a catwalk, the average person looks at the latest JP Gaultier creation and laughs. Well, they may also laugh when they see it on the catwalk but let’s not get too pedantic.
4. Knowledge Management
Knowledge management has been described as many things – from managing ignorance to managing intellectual property. The University of East Anglia once commissioned a book about Ignorance Management from this author and a colleague (Paul Wilkinson co-owner of GamingWorks).
Ultimately, KM is a set of guidelines, principles, usually supported by technology because of the sheer volume of information, with the underlying structure of providing information in context.
What is the objective of knowledge management? Having knowledge is critical to the continued operations of any enterprise. “Business decisions” are made based on the available knowledge and its application to the current circumstances. If we collect and maintain enterprise databases stuffed with ‘knowledge’, that is not enough.
KM has challenges:
• Does the data exist, or is it an assumption?
• Where is data held?
• How long will it take to locate the data?
• Have information services been defined in such a way that the data is consistent, available and up to date?
• Who can I contact if the data needed is unusable or inaccurate, or non-existent?
KM is similar to BIM in that the good practice implementation is not the goal; it is the means to an end. Technology solutions provide the ability to trawl masses of data using a taxonomy but rarely do more than provide the haystack in which the needle might be found. Or more likely the country in which the meadow exists in which might be found the haystack.
Information services are the precursor to maintaining and using data properly and encouraging the principles of KM.
5. Why is knowledge management an enterprise issue?
Can an enormous international coalition of intelligence agencies gather appropriate contextual data to inform strategic government decisions? How will governments manage information flow to the public in the light of the Freedom of Information Act, the Data Protection Act, and other records management and privacy regulations? As the mobile workforce moves jobs more frequently how will business continuity, values and culture be maintained? Does anyone care?
Understanding where knowledge and information flows is key to success. Search engines can mine numerous databases to establish patterns and throw up information that a human could never find. The most advanced artificial intelligence is still, however, no substitute for what has been described in many publications as ‘the human glue’ that provides context and allows inferences to be accurately (or even more often, inaccurately) made.
Libraries are traditional information repositories. However, the principles of managing that repository are as valid today as they ever were. Who is better equipped to understand the need to organize, index and maintain enormous data repositories than librarians? Long term productivity depends on both investment and the growth of knowledge assets. Joining up information flows, identifying and eradicating duplication of effort, streamlining data collection and distribution – all
these things are crucial to managing an efficient productive enterprise, and all are enabled by managing knowledge as an asset.
The fundamental business requirement for most enterprises is compliance with whatever regulations exist that must be satisfied. Information services must be designed to ensure that any data being collected or stored is properly managed. Your business is obliged to be compliant to data regulations or else suffer severe penalties.
Everyone likes a checklist so here is one that you can use to help keep BIM and KM in step:
• Build a framework to help people think about data/information need and value, strategic alignment, the risks of failing to manage key assets and measurements, things that will justify KM as a benefit and that can be understood at executive level
• Identify knowledge management KPIs and CSFs
• Keep privacy and regulation at the top of the agenda
• Maintain a summarized background of information management in the enterprise
• Ascribe responsibility for information rights management
• Build a KM team, and/or community, including management and users
• Understand and communicate where knowledge management and data management fit in the wider context of the enterprise
• Communicate KM quick wins and long term goals
• Build KM criteria into the initial service design architecture of a proposed new or improved service
• Track the use of information and data assets in enterprise documentation at executive level, BUT, keep it simple
• Identify cost savings and economies that can be attributed to KM
• Encourage BIM professionals to undertake KM training.
Title: BiSL® Next
Author: Brian Johnson, Gerard Wijers, Lucille van der Hagen
Price: € 42.35