Estimating Risks Related to Extended Enterprise Systems (EES)

Estimating Risks Related to Extended Enterprise Systems (EES)

Jasleen Kaur (Chandigarh University, India) and Rajinder Kaur (Chandigarh University, India)
DOI: 10.4018/978-1-5225-6029-6.ch008
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This chapter describes how risks are inherent in all systems. Risk is the ability of losing or gaining something of value. Values, like social status, financial wealth, or physical health, may be won or lost while taking threat as a result of a given movement. Risks also can be termed as the intentional interaction with ambiguity or uncertainty. Uncertainty is a capability, unpredictable, and uncontrollable final results; risk is an effect of action taken regardless of uncertainty. Extended Enterprise Systems (EESs) are defined as a complex structure of unique but interdependent and distributed organizational systems which are related in an autonomic manner to acquire goals beyond the reaching capacities of each. The purpose of this chapter is to estimate a set of critical risks that come across in proper logistics and the functioning of EESs. Identifying, analyzing and managing the risk in the EESs will result in an increase in the overall effectiveness and efficiency of the system. So, estimating risk could serve as the most important and powerful weapon in the hands of a decision maker of an EES.
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The term system is described as a collection or set of elements and method. Element includes products like software, hardware and peoples where processes include equipment, procedures, facilities and materials which might be associated and whose behavior satisfies functional and customer desires. Similarly, enterprise is defined as a goal-oriented complex system of resources like human, statistics, monetary, physical and activities, commonly trouble, risk, and time period (Rouse, 2005).

However, the necessities of trendy marketplace governed by means of excessive opposition, battles and globalizations amongst supply chains, have modified the focal point on how an agency conducts its commercial enterprise. Enterprises are steadily transferring on from working as a stand-on my own entity to producing goods and offerings via network of semi-independent or independent groups (Huang et al., 2008).

As an end result, enterprises have become prolonged organisms based on network capable of working in extraordinarily complicated environments (Mansouri et al., 2009). In order to seize the dynamic nature of such entities, present procedures may be combined to introduce an Extended Enterprise System. EES is defined as a complex structure of unique but interdependent and distributed organizational systems which are related in an autonomic manner to acquire goals beyond reaching capacities of each (Mansouri & Mostashari, 2010).

The form of relationship and interactions among constituent systems of any such community is probably defined primarily based on coordination, collaboration, hierarchy, or a combinatorial form. Regardless of the interconnectivity forms and policies that effects in a multiplied adaptability and flexibility without being vulnerable to sudden, unexpected vulnerability that could place it in a great threat through astronomical financial losses and a gradient fall in its normal market share, thereby result to the loss in its competitive advantage. Since introducing a “riskfree” method that enables the “best” functioning of an EES is nearly impossible inside the presently triumphing business environment, having a clear information about the crucial risks related to the functioning of an EES is genuinely important for its sustenance and growth inside the enterprise environment.

Furthermore, the bounds for evaluation and control of risks related to an EES are inherited from an abundance of inter- as well as intra-organizational relationships (Sutton et al., 2007; Sutton, 2006) that stretches properly beyond those related to its enterprise-centric counterparts, and therefore warrants a first-rate deal of interest from decision-makers as a part of designing a well-established risk mitigation approach. However, regardless of the rapidly developing reputation of EES amongst practitioners, there is nevertheless an enormous void within the open literature on comparing the critical risks related to an EES, something that the current studies is attempting to shed a few light on.

The objective of this is to assess a set of crucial risks that would stand in the manner of proper functioning and logistics of an EES. Starting with a review of the literatures on risk management and EES, this is going directly to identify a set of critical risks that could make an EES susceptible in nature, thereby leading to losses, both market share as well as financial.

The risks that are identified are then accordingly prioritized with a view to verify their relative criticality. This enables decision-makers of any EES to determine the relative criticality of the established and identified risks and in turn develop suitable risk mitigation techniques, thereby minimizing its economic losses and growing its competitive favor. Conclusions have been drawn and suggestions provided based totally on the findings of the research in conjunction with suggesting possible guidelines of future research. The contributions inside the domain of EES and systems engineering is two-fold. First, this identifies and explores the essential risks, which, if not addressed, can doubtlessly amplify the exposure of an EES in the industry. Secondly on the base of proposed model, policy-makers can use the estimated and identified risks along with their subsequent ranking to decide their associated criticality for making risk mitigation techniques for EEs.

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