The benchmarking procedure begins by first breaking the population into benchmarking cells. Cells are formed by grouping units together that share common characteristics, for example, similar Y(k), yet anything can be used that enhances the accuracy of the final estimates. For each cell C, we let W(C) be the sum of all W(k), where the sum is taken over all sampled k in the cell C. For each cell C, we let T(C) be the auxiliary value for cell C, which is commonly called the "benchmark target" for cell C. Next, we compute a benchmark factor F(C) = T(C) / W(C). Then, we adjust all weights W(k) by multiplying it by its benchmark factor F(C), for its cell C. The net result is that the estimated W [formed by summing F(C) \cdot W(k)] will now equal the benchmark target total T. But the more important benefit is that the estimate of the total of Y [formed by summing F(C) \cdot F(k) \cdot Y(k)] will tend to be more accurate.
