Talk on knowledge management for NRM

Dear Friends,

You are cordially invited to attend a talk by Dr Jaishanker, Assistant Professor, Indian Institute of Information Technology and Management - Kerala.

Topic: Knowledge Management for Natural Resource Management.

Date: 6th Sep'07 (Thursday)

Time: 12.00 - 1.00 noon

Venue: ATREE terrace

Here's the Concept Note

This note advocates the application of Knowledge Management for sustainable management of natural resources. Knowledge Management for Natural Resources Management (KM4NRM) will constitute a new avenue of research to address the challenges of sustaining human life on Earth - sustainably.

Knowledge Management (KM) is the phrase used for the process through which business organizations generate value from their intellectual and knowledge-based assets. Being closely associated with and mostly confined to high-end business, KM is often misunderstood as a synonym of Information Technology (IT). While KM is facilitated by IT, IT by itself is not KM.
KM systems do not have to be computer systems. It is a process of finding, selecting, organizing, distilling and presenting information in a way that improves comprehension in a specific area of interest (http://presidentofindia.nic.in/scripts/sllatest1.jsp?id=282) and acquiring, storing and utilizing knowledge for such things as problem solving, strategic planning, decision making and dynamic learning. This involves the whole gamut of transforming data into knowledge, managing knowledge as well generating new knowledge.

Data, Information, Knowledge and Wisdom

Without reference to either space or time, data is just a meaningless point. It is like an event out of context. The key concept is being ‘out of context’ and hence it conveys little meaning. When we encounter a piece of data, our first action is usually to attempt to find a way to attribute meaning to it. We do this by associating it with other things. For example, the data 33, 26 alone conveys little meaning. When the same data is suffixed with 0 Celsius, it immediately makes sense. Similarly, a time reference can be associated with the data, this might be, ‘temperature of day’ ’temperature of night’, etc. The implications being; when there is no context, there is no meaning and more information (here context) increases certainty.

That a collection of data is not information implies that a collection of data for which there is no relation between the pieces is not information. The pieces of data may represent information, yet whether or not it is information, depends on the understanding of the one perceiving the data. Information is quite simply an understanding of the relationships between pieces of data, or between pieces of data and other information. [Neil Fleming, Coping with a Revolution: Will the Internet Change Learning? Lincoln University, Canterbury, New Zealand]

While information entails an understanding of the relations between data, it generally does not provide a foundation for why the data is what it is, nor an indication as to how the data is likely to change over time. Beyond relation there is pattern. When a pattern relation exists amidst the data and information, the pattern has the potential to represent knowledge. It only becomes knowledge, when one is able to realize and understand the patterns and their implications. Wisdom arises when one understands the foundational principles responsible for the patterns representing knowledge being what they are. The embedded figure depicts the transition of data to wisdom.

Value of KM

In an organizational context, data represents facts or values of results that have the capacity to represent information. Patterns of relations in data and information and other patterns have the capacity to represent knowledge. For the representation to be of any utility it must be understood, and when understood the representation is information or knowledge to the one that understands.

Traditional view of Knowledge Management treats knowledge in terms of prepackaged interpretation of information, residing in technological databases. This view works against generation of multiple and sometimes-contradictory views that are much needed to address the new challenges. Information residing in the technological databases as bits or pixels are distinct from knowledge. Knowledge resides in the user and not in the database.

Knowledge Management caters to the critical issue of organizational adaptation, survival and competence in the face of increasingly discontinuous environmental change. It embodies processes that seek synergistic combination of data and information-processing capacity and the creative and innovative capacity of human beings. [Malhotra, Y. Information Ecology and Knowledge Management: Towards Knowledge Ecology for Hyperturbulant Organizational Environments, Encyclopedia of Life Support Systems (EOLSS) 2002, UESCO/Eolss Publishers, Oxford, UK]

The value of Knowledge Management relates directly to the effectiveness with which the managed knowledge enables the members of the organization to deal with today's situations and effectively envision and create their future. In essence, KM tries to understand the situation and processes from a system perspective to arrive at a decision. From a business perspective, it tries to extract tacit knowledge of the employees and utilize it for decision-making. Explicit knowledge is everything that is written down or otherwise encoded. Tacit knowledge, by contrast, exists largely in employee's heads. Today managers are forced to look for ways to add value by taking advantage of uncertainty.

Although uncertainty is usually seen as negative, it can also increase performance if flexibility is incorporated into the system to capture upside opportunities, and reduce losses in case of downside events. Knowledge Management is this complex process that is becoming more and more important to organizational success.

KM for NRM
Natural systems and processes are either (i) too slow to observe and study in a lifetime (evolution) (ii) abrupt and hence not predictable yet (natural disaster – a misnomer)

(iii) too subtle to be taken note of (alterations/adaptations) or

(iv) too big to comprehend completely (hydrologic cycle). Our attempts to understand / quantify natural processes, as functions of space and time are based on generalizations and assumptions. The abstractions impede any blanket/ universal recommendation for specific natural resource management. Neither is it surprising to find any NRM decision not getting criticized.

The efficiency of NRM decision is limited by gaps in our understanding of the interdependencies of the individual processes. The challenge for the 21st century science is to understand Earth's bio-geo-physical processes and how it shapes the global environmental systems, on which all of life depends. This knowledge is critical to science and society for rational policy for managing natural systems, sustaining human health, maintaining economic stability, and improving the quality of human life.

Understanding the intricacies of global bio-geo-physical processes requires assiduously synchronized, global efforts. It is here that natural resource managers/ scientists need to learn from their corporate counterparts and look for ways to add value by taking advantage of uncertainty. NRM studies are based on observations, analysis, interpretation and implementation. As an environmental scientist/ ecologist you would now be able to appreciate how the data that you collect gets transformed into knowledge or wisdom. Contrary to business processes, which have limited personnel to pool knowledge from, KM for NRM can pool knowledge and wisdom from entire population and even from people across geographic or administrative boundaries.

It is surprisingly strange that, KM has confined itself mostly to business enterprises. The author foresees enormous potential of KM4NRM. However, the domain is too nascent to cite any academic/ research precedence. The note concludes with a request to streamline your thoughts and scan your noosphere to discover the potentials of knowledge management for natural resources management. The author is convinced that KM4NRM is pivotal to sustainable natural resource(s) management.

Acknowledgments
Dr. C.S.P. Iyer, IIITM-K
Dr. V. Sobha, University of Kerala
Dr. K. Srinivasan, IIITM-K
Dr. K.R. Srivathsan, IIITM-K

Contributed by Mrs Kalpana Prasanna, Human Reources Officer, ATREE