Information evaluation: empirical investigations in engineering organisations

The management of information in engineering organizations is facing a particular challenge due to the ever-increasing volume of information needs to be dealt with. It has been recognized that an effective methodology is required to evaluate information in order to avoid information overload and to retain the right information for reuse. By whatever approaches, information evaluation judgments are made in those engineering organizations in order to support businesses decisions. Investigating those practical methodologies would benefit the overall information evaluation research. This paper addresses this practical information evaluation issue firstly by briefly reviewing the idea of information evaluation, the definition of value, and related research work on the value of information in various areas. Then a series of industrial empirical investigation activities, based on interviews in engineering organizations, are introduced. The evaluation approaches in those organizations are analyzed and compared according to the nature of each of the organizations. The current practices are then summarized. Finally, several further issues including the impact of the newly developed information evaluation methodologies and the implementation issues associated with this evaluation assessment method are raised

Knowledge and information evaluation practice - an exploratory study in a construction firm

There are a number of challenges associated with managing knowledge and information in construction organizations delivering major capital assets. These include the ever-increasing volumes of information, losing people because of retirement or competitors, the continuously changing nature of information, lack of methods on eliciting useful knowledge, development of new information technologies and changes in management and innovation practices. Existing tools and methodologies for valuing intangible assets in fields such as engineering, project management and financial, accounting, do not address fully the issues associated with the valuation of information and knowledge. Information is rarely recorded in a way that a document can be valued, when either produced or subsequently retrieved and re-used. In addition, there is a wealth of tacit personal knowledge which, if codified into documentary information, may prove to be very valuable to operators of the finished asset or future designers. This paper addresses the problem of information overload and identifies the differences between data, information and knowledge. An exploratory study was conducted with a leading construction consultant examining three perspectives (business, project management and document management) by structured interviews and specifically how to value information in practical terms. Major challenges in information management are identified. An through-life Information Evaluation methodology (IEM) is presented to reduce information overload and to make the information more valuable in the future

Overload of information or lack of high value information: lessons learnt from construction

Information and knowledge are strategic assets, processed to attain objectives, perform actions and make decisions. However, technological innovations can change the format of information and often result in more complicated project information or knowledge management tools whilst this can provide information to an individual more easily and quickly. Current systems have little or no regard for the value of the information they contain. As projects draw to a close, some organisations are now asking what information is worth retaining and how might it be reused. This paper addresses the problems of information overload and value in the construction industry. Exploratory studies compared two major consultants in the UK from three perspectives (business, project management and document management). Major challenges in the current information evaluation practice in the industry were identified. Information overload does exist in the industry and is getting worse because of the heavy but often inappropriate use of search and collaborative technologies. Loss of high value information due to staff leaving is a major problem, but the companies are reluctant to evaluate recorded information (before or after storage) for future retrieval. From the strategic point of view, there is a lack of information evaluation tools that quantify the benefits and costs of performing information evaluation activities and the effects on storage. Based on these findings, a through-life Information Evaluation Methodology (IEM) has been proposed to allow high value information to be easily retrievable in the future in order to support through-life knowledge and information management (KIM) practice

Defining a framework for the evaluation of information

In any enterprise, principled decisions need be made during the entire life cycle of information about its acquisition, storage, creation, maintenance and disposal. Such information management requires some form of information evaluation to take place, yet little is understood about the process of information evaluation within enterprises. For evaluation support to be both effective and resource efficient, particularly where decisions are being made about the future of large quantities of information, it would be invaluable if some sort of automatic or semi-automatic methods were available for evaluation. Such a method would require an understanding of the diversity of the contexts in which evaluation takes place so that evaluation support can have the necessary context-sensitivity. This paper identifies the dimensions that influence the information evaluation process and defines the elements that characterize these dimensions, thus providing the foundations for a context-sensitive framework for information evaluation

High value information in engineering organizations

The management of information in engineering organizations is facing a particular challenge in the ever-increasing volume of information. It has been recognized that an effective methodology is required to evaluate information in order to avoid information overload and to retain the right information for reuse. By using, as a starting point, a number of the current tools and techniques which attempt to obtain ‘the value’ of information, it is proposed that an assessment or filter mechanism for information is needed to be developed. This paper addresses this issue firstly by briefly reviewing the information overload problem, the definition of value, and related research work on the value of information in various areas. Then a “characteristic” based framework of information evaluation is introduced using the key characteristics identified from related work as an example. A Bayesian Network diagram method is introduced to the framework to build the linkage between the characteristics and information value in order to quantitatively calculate the quality and value of information. The training and verification process for the model is then described using 60 real engineering documents as a sample. The model gives a reasonable accurate result and the differences between the model calculation and training judgments are summarized as the potential causes are discussed. Finally several further the issues including the challenge of the framework and the implementations of this evaluation assessment method are raised

An entropy-based financial decision support system (e-FDSS) for project analysis in construction SMEs

Uncertainty contributes a major part in the accuracy of a decision-making process while its inconsistency is always difficult to be solved by existing decision-making tools. Entropy has been proved to be useful to evaluate the inconsistency of uncertainty among different respondents. The study demonstrates an entropy-based financial decision support system called e-FDSS. This integrated system provides decision support to evaluate attributes (funding options and multiple risks) available in projects. Fuzzy logic theory is included in the system to deal with the qualitative aspect of these options and risks. An adaptive genetic algorithm (AGA) is also employed to solve the decision algorithm in the system in order to provide optimal and consistent rates to these attributes. Seven simplified and parallel projects from a Hong Kong construction small and medium enterprise (SME) were assessed to evaluate the system. The result shows that the system calculates risk adjusted discount rates (RADR) of projects in an objective way. These rates discount project cash flow impartially. Inconsistency of uncertainty is also successfully evaluated by the use of the entropy method. Finally, the system identifies the favourable funding options that are managed by a scheme called SME Loan Guarantee Scheme (SGS). Based on these results, resource allocation could then be optimized and the best time to start a new project could also be identified throughout the overall project life cycle