Systems and methods for a causality analyzer
DCFirst Claim
1. A causality analyzer implemented on a computer system, useful in association with price management systems, the causality analyzer comprising:
- a time period selector implemented on a computer system configurable to select a reference time period and a comparison time period;
a causality modeler implemented on a computer system configurable to receive transaction data and calculate change in total margin, percent margin and total revenue between the reference time period and the comparison time period using the transaction data; and
a causality attributor implemented on a computer system configurable to disaggregate each of the change in total margin, the percent margin and the total revenue by causality effects, wherein the causality effects include price effect, cost effect, quantity effect, product mix effect, customer mix effect, exchange rate effect, new and lost business, and an adjustment change, and further configurable to unbiase the causality effects where they interact using a finite difference approach, wherein the finite difference approach splits the shared effect according to proportionate percentage of the change attributed only to each effect.
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Abstract
A causality analyzer that provides attribution of causality effects for changes in revenue, margin and margin percentage is provided. The causality analyzer selects a reference time period and a comparison time period, and receives transaction data. Data cleansing and correction may be performed on the transaction data. The analyzer may then calculate change in total margin, percent margin and total revenue between the reference time period and the comparison time period using the transaction data. Each of the total margin, the percent margin and the total revenue may be disaggregated into one or more of a price effect, cost effect, quantity effect, product mix effect, customer mix effect, exchange rate effect, new and lost business, and an adjustment change. In this way the total margin, the percent margin and the total revenue are each defined as a summation of the individual causality effects. Causality effects may be disaggregated in such a way that the shared effects are allocated according to the proportion of percent change for each element, thereby unbiasing the effects to more accurately reflect actual causality.
120 Citations
19 Claims
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1. A causality analyzer implemented on a computer system, useful in association with price management systems, the causality analyzer comprising:
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a time period selector implemented on a computer system configurable to select a reference time period and a comparison time period; a causality modeler implemented on a computer system configurable to receive transaction data and calculate change in total margin, percent margin and total revenue between the reference time period and the comparison time period using the transaction data; and a causality attributor implemented on a computer system configurable to disaggregate each of the change in total margin, the percent margin and the total revenue by causality effects, wherein the causality effects include price effect, cost effect, quantity effect, product mix effect, customer mix effect, exchange rate effect, new and lost business, and an adjustment change, and further configurable to unbiase the causality effects where they interact using a finite difference approach, wherein the finite difference approach splits the shared effect according to proportionate percentage of the change attributed only to each effect. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A method for analyzing causality, useful in association with price management systems, the method comprising:
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selecting, using a computer, time periods, wherein the selection of the time periods includes selecting a reference time period and a comparison time period; receiving, using a computer, transaction data, wherein transaction data includes pricing data and volume data about products; calculating, using a computer, change in total margin, percent margin and total revenue between the reference time period and the comparison time period using the transaction data; disaggregating, using a computer, each of the total margin, the percent margin and the total revenue by price effect, cost effect, quantity effect, product mix effect, customer mix effect, exchange rate effect, new and lost business, and an adjustment change; unbiasing, using a computer, the causality effects where they interact using a finite difference approach, wherein the finite difference approach splits the shared effect according to proportionate percentage of the change attributed only to each effect; and outputting, using a computer, the disaggregated total margin, percent margin and total revenue. - View Dependent Claims (13, 14, 15, 16, 17, 18, 19)
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Specification