Cost datasets often do not have quantity information, because that would be meaningless. Therefore you cannot analyze "price" variance. The tool provides useful insights also in this case.

In this example, the 200k row dataset of the budget of NYC, there is no quantity column, but just the amount spent. This means that we cannot distinguish price variance from volume variance. We also cannot get mix variance information because this also requires a quantity metric.

Let's load the the New York City budget dataset (type NYC in the "choose sample dataset" widget) and run a "fix dimension" bridge.

To show higher values in red, change the color palette parameter.


The first year expense is 271,597,447,185$. The change between the two years is about 5%, 14,191,868,822$.

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If we run a "a variable dimension" bridge with standard parameters, we get this. Notice that the most important items is "N/A" as Responsibility Center Name. The field seems to be often empty.

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Lets drop the responsibility center name column from our analysis


Here is the new output.

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We are showing this chart with the initial and final totals.


You can also see it without.

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We want to understand better that first "Department of education" row so we drill down


The app now also returns a more detailed report.

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To distinguish the "new", "maintained" and "dropped" expenses set "Show variance as" to "price, new, lost, volume & mix".

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