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A nal step in the analytical process of de ning where variances and defects are likely to occur is to once again question your initial assumptions. In so many quality projects, a team begins under the assumptions that a particular problem has to be xed, only to discover that in fact the problem originally de ned to create the project is not the problem at all. For example, let us say that your Six Sigma team is given the project to Find out why so many check requests arrive in the Accounting Department outside of normal match cycles. In other words, the team s job is to gure out how to get sales reps, other departments, and individuals to understand the accounting cycle and to time check requests accordingly. However, upon examination of the realities of the process, your team discovers that this is not a problem of people needing to comply with twice-monthly batch cycles; the real problem is that the Accounting Department does not run cycles often enough. We have previously mentioned the idea of having two major cycles per month timed for the second and fourth weeks, and then adding two minor cycles to occur in between. In this simpli ed example, the initial problem of noncompliance by everyone in the com-

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This discussion suggests the structure shown in Fig. 10.2, which employs an FIR filter with adjustable weights that is connected to the input and output signals { d ( i ) ,u ( i ) } of the channel. At each time instant i, the measured output of the channel, d ( i ) , is compared with the output of the adaptive filter, d ( i ) = uiwi-1, an error signal, e ( i ) = d ( i ) and uiwi-1, is generated. The error is then used to adjust the filter coefficients from wi-l to w according to (10.19). In steady-state, if the step-size p is suitably chosen to guarantee i filter convergence (usually, small step-sizes will do), then the error signal will assume small values, and the output d ( i ) = uiwi-1 of the adaptive filter will assume values close to d ( i ) . Consequently, from an inpuVoutput perspective, the (adaptive filter) mapping from u(i) to d ( i ) will behave similarly to the channel, which maps u(i) to d ( i ) . This construction assumes that the adaptive filter has at least as many taps as the channel itself; otherwise, performance degradation can occur due to under-modeling.

Include in that escape clause a provision that you will be paid some portion of your fee for work you perform to the point when the unforeseen events occur Consider using contingency pricing in a limited way with trusted clients If you are sure you can deliver the projected benefits to the client and are willing to take a set percentage of the benefits as your fee, contingency pricing might be your best bet Success Fees A variation on contingency pricing is to tie fees to an all-out guarantee: The consultant does not get paid if the client does not deem the project a success As clients have become more skeptical of the value that consultants provide, they want to base payment on the success achieved.

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The sentiment seems to be that if consultants are as good as they claim, they should be willing to put their fees on the line Under some formulas, only part of a consultant s fees is tied to success, and the rest is paid through a more standard pricing method Another possibility is that consultants can agree to allow clients to hold back partial fees For example, if a project calls for $500,000 in fees, the consultant might bill the client for $450,000 and let the client decide whether to pay the final $50,000 Some clients want to fund projects from the eventual project benefits Consultants have been known to bankroll projects provided the clients pay the deferred fees later when increased revenue or savings are realized from projects Such self-funding projects allow clients to hire consultants without increasing their budgets.

The two most common solutions offered to repair the NAT Traversal issue are:

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Freezing the Action . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 Faster Than a Speeding Bullet . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 211 Background Decisions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216

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