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Managers must prepare for the changes that are coming by understanding the factors that go into making a sound BPO decision In addition to the basic choice of whether to use BPO, a host of technological, business process, and HR issues follow in the wake of an affirmative decision The technological issues will range over the type of electronic infrastructure that will be required to communicate effectively with BPO partners to the integration of new technologies with legacy systems throughout the organization These difficult issues require the skillful assembly and management of a team of diversely talented individuals Because BPO is fundamentally a strategic issue, managers cannot simply call upon their firm s CIO or systems administrators to decide how to achieve an outsourcing relationship.

The web of relationships that make up successful BPO initiatives will be based on a range of managerial actions and skills that is unlikely to be present in any single manager or executive..

// allocate memory v=new NODE [N+1]; e=new LINK *[N+1]; alpha=new int **[N+1]; Path=new PATH [N+1]; for (i=0;i<=N;i++) { e[i]=new LINK [N+1]; alpha[i]=new int *[N+1]; for (j=0;j<=N;j++) alpha[i][j]=new int [N+1]; } // initialize variables time_t seed=time(NULL); srand((unsigned)seed); nLink=0; nPath=0; LineFlag=0; for (i=1;i<=N;i++) { e[i][i].Wt=99; for (j=i;j<=N;j++) { e[i][j].Wt=e[j][i].Wt=99; if (((j-i==1 && j-i!=Nx-1) || (j-i==Nx && j-i!=Nx*(Ny-1))) && !(j-i==1 && i%Nx==0) ) { e[i][j].Wt=e[j][i].Wt=1+rand()%9; nLink++; } } } for (i=1;i<=N;i++) for (j=1;j<=N;j++) { e[i][j].sd=e[i][j].Wt; for (k=1;k<=N;k++) alpha[i][j][k]=99; } // set fonts, colors, text and drawing area TextGap=50; TextHome=CPoint(70,520); DrawArea=CRect(10,20,900,350); TextArea=CRect(10,360,900,560);

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We call v0 the optimal reservation price. Note that it does not depend upon the number of bidders. For example, if valuations are uniformly distributed on [0; 1], then v0 D 1=2. This is consistent with the answers found for Cases 3 and 4 of Example 14.1. If bidders valuations are independent, but heterogenous in their distributions, then one can proceed similarly. Let pi .v/ be the probability that bidder i wins when his valuation is v. Let ei . p/ be the minimum expected amount he can pay if he wants to win with probability p. Suppose that bidder i does not participate if his valuation is less than v0i . Just as above, one can show that the seller s expected revenue is n n X XZ 1 1 Fi .v/ f i .v/ pi .v/ dv v E vi ei . pi .vi // D (14.4) f i .v/ i D1 i D1 vDv0i The term in square brackets can be interpreted as marginal revenue , in the sense that if a price p is offered to bidder i, he will accept it with probability xi . p/ D 1 Fi . p/, and so the expected revenue obtained by this offer is pxi . p/. Differentiating this with respect to xi , we de ne MR i . p/ D d d pxi . p/ D pxi . p/ dxi dp dxi Dp dp 1 Fi . p/ f i . p/

The project manager should frequently assess the current position of the project and see if the development schedule is on track and if the delivery dates can be achieved If the project is behind schedule, then the project manager should arrange for additional work-hours..

(11.22)

Failure to specify adequately the extent of uncertainty about a quantity may be due to a process of estimating uncertainty by making adjustments to an initial point estimate. The initial value may be suggested by the formation of a problem or by a partial computation. Unfortunately, subsequent estimates may be unduly in uenced by the initial value, so that they are typically insuf ciently different from the initial value. Moreover, for a single problem different starting points may lead to different nal estimates that are biased toward the starting values. This effect is known as anchoring (Tversky and Kahneman, 1974). Consider an estimator who is asked to estimate the probability distribution for a particular cost element. To select a highest possible cost H it is natural to begin by thinking of one s best estimate of the cost and to adjust this value upward, and to select the lowest possible cost L by adjusting the best estimate of cost downward. If these adjustments are insuf cient, then the range of possible costs will be too narrow and the assessed probability distribution too tight.

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