New PDF release: Advances in Neural Information Procesing Systems 4

By John E. Moody, Steven J. Hanson, Richard P. Lippmann (Editors)

ISBN-10: 1558602224

ISBN-13: 9781558602229

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Extra info for Advances in Neural Information Procesing Systems 4

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This technique can be used simply for risk identification, prior to risk analysis, or it may be used right through risk analysis to risk response and fed directly into the project risk register. 1). It is usual for the participants to select the elements as representative, in this case of projects within their experience, and to generate the constructs by a process of comparison of three elements (triads) at a time (Cassell and Walsh, 2004). 1) and the third one different (D) and give it a label.

This is why it is advisable for organizations that experience this type of project on a frequent basis to spend time building up a knowledge base and using a predetermined set of risks for BDP-type projects in assessing the level of risk of each such opportunity. 1 were found in the main case study in a large logistics business for BDP projects, using a combination of the nominal group technique and the repertory grid technique (see Chapter 2). 1 Project risk attributes for business development projects Project Risk Attributes Brief definition (see full glossary in appendix) CORPORATE FACTORS: Strategic fit Expertise Impact Potential contribution to strategy Level of expertise available compared to need Potential impact on company/brand reputation PROJECT OPPORTUNITY: Size Complexity Planning timescale Quality of customer/supplier Scale of investment, time and volume of work Number of and association between assumptions Time available to develop proposal pre-decision Credit checking, etc.

Interpret the score along with financial appraisal measures (matrix). project risk appraisal techniques 23 Step 1. Identify sources of project risk The example used here is taken from research in a large logistics company, where 12 project risk attributes were found. The last two are not included here, as they are more specific to the logistics sector, and 10 is sufficient to illustrate the technique. Each attribute should ideally be broken down into several subcategories and discussed at length, but the aim is to establish a cost-effective decision-support technique which focuses managers’ attention on key risk areas.

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Advances in Neural Information Procesing Systems 4 by John E. Moody, Steven J. Hanson, Richard P. Lippmann (Editors)

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