Managers must account for all the investments made in a competitive business environment that changes rapidly, and it is becoming increasingly important that they carefully evaluate IT investments before making them. Moreover, while managers can evaluate the probable impacts of individual IT projects, they find it difficult to predict the overall effect of two or more of them.Most IT projects exceed their budgets and do not perform as well as expected. And after considering the risks of development delay and budget overruns, managers need to think about assigning an IT project a priority level that maximizes its effect while keeping its cost within the budget. Because the IT measure must be considered in light of the prevailing business challenges, all the while taking account of various constraint condition and risks, there is a pressing need to develop a method for determining the priority of an IT investment.A schedule chart showing the order of introducing each measure (called a "road map") will help managers make decisions about investing in two or more IT measures. Here, a greater effect might be obtained by introducing two or more measures at the same time. On the other hand, the effect of two measures might not be significant even if they are introduced at the same time. That is, there is a synergy effect when two or more measures are introduced. What's more, while some measures need to be introduced and others do not, there has been no method for drawing up a road map that takes these various factors into account.The way in which the road map is drawn up is based on the business challenge level and the constraint conditions are set. The solution is calculated in such a way that maximizes the evaluation value of the road map as a whole. We have the following two kinds of frames:(1) Two-axis frames with time and budget axes.(2) Two-axis frames with time and staff axes. When drawing up the road map, we need to build the constraint condition of the entire road map into each these two kinds of frames for each measure.It is impossible to calculate the evaluation value of the whole road map all cases because the computational complexity is expected to be O(n!) when the number of measures is n. We therefore propose a method for drawing up the road map by dividing its calculation into two steps, one calculating the initial solution and the other calculating an optimization solution.Firstly, to maximize the overall effect of the road map, the initial solution of the road map is calculated as one in which measures are introduced sequentially in descending order of business challenge level. Next, the road map is corrected to consider the synergy effect. An example of this correction procedure is shown in Fig. 1. When the synergy effect is considered, those measures are actually replaced if the business challenge level of the entire road map is high before the measure is replaced.We applied the proposed method to the fictitious constraint condition data simpler that actual problem data. When the synergy effect is co...
Abstract:System utilization was investigated with the aim of selecting appropriate service parameters for defining the quality of information systems such as SLA (service level agreement). This investigation is based on the hypothesis that parameters having a strong influence on user satisfaction depend on how the system is used. Accordingly, the parameters for availability and responsiveness, which are known as the two major factors in SLA, were investigated. First, it is explained that parameters having a strong impact on user satisfaction are not common among information systems. Next, three parameters for availability (mean time between halt, mean time to restore, and both of them) and ones for responsiveness (mean time, maximum time, and variance) were introduced. To analyze the relation between these service parameters and system utilization, a questionnaire about system utilization was designed and administered to several experienced system engineers. Quantification theory type II was applied to the results of this questionnaire, and the validity of the hypothesis was demonstrated. The results also classified information systems into six groups in terms of availability and responsiveness. The characteristics of each system group were also clarified.
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