Systems and Methods for a Causality Analyzer

• US 20110251932A1
• Filed: 02/10/2011
• Published: 10/13/2011
• Est. Priority Date: 02/06/2008
• Status: Active Grant

• Current Assignee: Vendavo, Inc.
• Original Assignee: Vendavo, Inc.
• Inventors: Lai, Danny Cho-Liang, Early, John, Johnson, Jeffrey D.
• Granted Patent: US 8,412,598 B2
• Time in Patent Office: Days
• US Class Current: 705/30
• CPC Class Codes: G06Q 10/06 Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/12 Accounting

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.

Claims

1. A causality analyzer, useful in association with price management systems, the causality analyzer comprising:

a time period selector configurable to select a reference time period and a comparison time period;

a causality modeler 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 configurable to disaggregate 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.

2. The causality analyzer as recited in claim 1, wherein the transaction data includes reference revenue and comparison revenue, wherein reference revenue is revenue at the reference time period and comparison revenue is revenue at the comparison time period, and wherein by subtracting the reference revenue from the comparison revenue the change in total revenue is calculated.

3. The causality analyzer as recited in claim 2, wherein the transaction data includes reference cost and comparison cost, wherein reference cost is cost at the reference time period and comparison cost is cost at the comparison time period, and wherein by subtracting reference cost from reference revenue a reference margin is calculated, and by subtracting comparison cost from comparison revenue a comparison margin is calculated, and wherein by subtracting reference margin from comparison margin the change in total margin is calculated, and wherein by dividing the reference margin by reference revenue a reference percent margin is calculated, and by dividing the comparison margin by comparison revenue a comparison percent margin is calculated, and by subtracting the reference percent margin from the comparison percent margin the change in percent margin is calculated.

4. The causality analyzer as recited in claim 3, wherein the total margin, the percent margin and the total revenue are each defined as a summation of the price effect, the cost effect, the quantity effect, the product mix effect, the customer mix effect, the exchange rate effect, the new and lost business, and the adjustment change.

5. The causality analyzer as recited in claim 1, further comprising at least one of a missing data exchanger and data error corrector.

6. The causality analyzer as recited in claim 5, wherein the missing data exchanger is configurable to identify missing data and to determine if the missing data is price data or volume data;

and

if the missing data is volume data, then replacing the missing volume data with a value of zero;

if the missing data is exchange rate data, then replacing the missing exchange rate data with a weighted average used globally for currency and time period;

if the missing data is cost data, then determining if the missing cost data is from the reference time period or the comparison time period; and

if the missing cost data is from the reference time period, then replacing the missing cost data with cost data from the comparison time period; and

else, if the missing cost data is from the comparison time period, then replacing the missing cost data with price data from the reference time period;

else, if the missing data is price data, then determining if the missing price data is from the reference time period or the comparison time period; and

if the missing price data is from the reference time period, then replacing the missing price data with price data from the comparison time period; and

else, if the missing price data is from the comparison time period, then replacing the missing price data with price data from the reference time period.

7. The causality analyzer as recited in claim 3, wherein the transaction data includes at least one of an exchange rate at the reference time period, an exchange rate at the comparison time period, prices of the products at the reference time period in the currencies, prices of the products at the comparison time period in the currencies, volume of the products sold in the reference time period, volume of the products sold in the comparison time period, volume of each of the products sold in the reference time period in a currency, and volume of each of the products sold in the comparison time period in a currency.

8. The causality analyzer as recited in claim 7, wherein the price effect comprises:

subtracting the prices of products at the reference time period in the currencies from the prices of the products at the comparison time period in the currencies to calculate a change in price for the products at the currencies;

dividing the change in price for the products at the currencies by the exchange rate at the reference time period to calculate a relative change in price for the products at the currencies;

multiplying the relative change in price for the products at the currencies by the volume of the products sold in the comparison time period to calculate price only effect;

multiplying the relative change in price for the products at the currencies by the price to quantity split to calculate split price effect;

combining the split price effect with price only effect to generate revenues for the products at the currencies;

summing the revenues for the products at the currencies across the products to calculate revenues at the currencies; and

summing the revenues at the currencies across the currencies.

9. The causality analyzer as recited in claim 7, wherein the volume effect comprises:

multiplying the prices of the products at the reference time period in the currencies by the volume of the products sold in the reference time period to calculate revenue of the products for the reference time period in the currencies;

dividing the revenue of the products for the reference time period in the currencies by the exchange rate at the reference time period to calculate relative revenue of the products for the reference time period in the currencies;

summing the relative revenue of the products for the reference time period in the currencies across the products to calculate relative revenue for the reference time period in the currencies;

summing the relative revenue for the reference time period in the currencies across the currencies to calculate relative revenue for the reference time period;

dividing the relative revenue for the reference time period by the volume of the products sold in the reference time period to calculate revenue per product sold in the reference time period;

subtracting the volume of the products sold in the reference time period by the volume of the products sold in the comparison time period to calculate change in volume;

multiplying the change in volume by revenue per product sold in the reference time period to calculate the quantity only effect;

multiplying the change in volume by the price to quantity split to calculate split quantity effect; and

combining the split quantity effect with quantity only effect.

10. The causality analyzer as recited in claim 7, wherein the mix effect comprises:

dividing the volume of each product sold in the reference time period in a currency by the volume of the products sold in the reference time period to calculate a percent of sales volume for the products in the reference time period;

dividing the volume of each product sold in the comparison time period in a currency by the volume of the products sold in the comparison time period to calculate a percent of sales volume for the products in the comparison time period;

subtracting the percent of sales volume for the products in the reference time period from the percent of sales volume for the products in the comparison time period to calculate a change in percent of sales volume for the products;

dividing the price of the products in the reference time period in the currencies by the exchange rate at the reference time period to calculate a relative price of the products for the reference time in the currencies;

multiplying the relative price of the products for the reference time in the currencies by the change in percent of sales volume for the products to calculate a percent revenue change of the products in the currencies;

summing the percent revenue change of the products in the currencies across the products to calculate a percent revenue change in the currencies;

summing the percent revenue change in the currencies across the currencies to calculate a percent revenue change; and

multiplying the percent revenue change by the volume of products sold in the comparison time period.

11. The causality analyzer as recited in claim 7, wherein the exchange effect comprises:

dividing the price of the products in the comparison time period in the currencies by the exchange rate at the comparison time period to calculate relative prices of the products at the comparison time periods in the currency;

dividing the price of the products in the comparison time period in the currencies by the exchange rate at the reference time period to calculate prices of the products in the comparison time in the currencies at the exchange rate in the reference time period;

subtracting the price of the product in the comparison time in the currencies at the exchange rate in the reference time period from the relative prices of the products at the comparison time in the currencies to calculate changes in price for the products at the comparison time in the currencies due to exchange rate difference;

multiplying the changes in price for the products at the comparison time in the currencies due to exchange rate difference by the volume of sales of the products at the comparison time period to calculate changes in revenue for the products at the comparison time in the currencies due to exchange rate difference;

summing changes in revenue for the products at the comparison time in the currencies due to exchange rate difference across the products to calculate changes in revenue at the comparison time in the currencies due to exchange rate difference; and

summing changes in revenue at the comparison time in the currencies due to exchange rate difference across the currencies.

12. A method for analyzing causality, useful in association with price management systems, the method comprising:

selecting time periods, wherein the selection of the time periods includes selecting a reference time period and a comparison time period;

receiving transaction data, wherein transaction data includes pricing data and volume data about products;

calculating change in total margin, percent margin and total revenue between the reference time period and the comparison time period using the transaction data;

disaggregating 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; and

outputting the disaggregated total margin, percent margin and total revenue.

13. The method, as recited in claim 12, wherein the transaction data includes reference revenue and comparison revenue, wherein reference revenue is revenue at the reference time period and comparison revenue is revenue at the comparison time period, and wherein by subtracting the reference revenue from the comparison revenue a change in revenue is calculated.

14. The method, as recited in claim 13, wherein the transaction data includes reference cost and comparison cost, wherein reference cost is cost at the reference time period and comparison cost is cost at the comparison time period, and wherein by subtracting reference cost from reference revenue a reference margin is calculated, and by subtracting comparison cost from comparison revenue a comparison margin is calculated, and wherein by subtracting reference margin from comparison margin the change in total margin is calculated, and wherein by dividing the reference margin by reference revenue a reference percent margin is calculated, and by dividing the comparison margin by comparison revenue a comparison percent margin is calculated, and by subtracting the reference percent margin from the comparison percent margin the change in percent margin is calculated.

15. The method, as recited in claim 14, wherein the total margin, the percent margin and the total revenue are each defined as a summation of the price effect, the cost effect, the quantity effect, the product mix effect, the customer mix effect, the exchange rate effect, the new and lost business, and the adjustment change.

16. The method, as recited in claim 12, wherein the preparation of the transaction data includes at least one of replacing missing data and correcting data errors.

17. The method, as recited in claim 16, wherein the replacement of the missing data comprises:

identifying missing data;

if the missing data is volume data, then replacing the missing volume data with a value of zero;

if the missing data is exchange rate data, then replacing the missing exchange rate data with a weighted average used globally for currency and time period;

if the missing data is cost data, then determining if the missing cost data is from the reference time period or the comparison time period; and

if the missing cost data is from the reference time period, then replacing the missing cost data with cost data from the comparison time period; and

else, if the missing cost data is from the comparison time period, then replacing the missing cost data with price data from the reference time period;

else, if the missing data is price data, then determining if the missing price data is from the reference time period or the comparison time period; and

if the missing price data is from the reference time period, then replacing the missing price data with price data from the comparison time period; and

else, if the missing price data is from the comparison time period, then replacing the missing price data with price data from the reference time period.

18. The method, as recited in claim 14, wherein the price effect comprises:

subtracting the prices of products at the reference time period in the currencies from the prices of the products at the comparison time period in the currencies to calculate a change in price for the products at the currencies;

dividing the change in price for the products at the currencies by the exchange rate at the reference time period to calculate a relative change in price for the products at the currencies;

multiplying the relative change in price for the products at the currencies by the volume of the products sold in the comparison time period to calculate price only effect;

multiplying the relative change in price for the products at the currencies by the price to quantity split to calculate split price effect;

combining the split price effect with price only effect to generate revenues for the products at the currencies;

summing the revenues for the products at the currencies across the products to calculate revenues at the currencies; and

summing the revenues at the currencies across the currencies.

19. The method, as recited in claim 14, wherein the volume effect comprises:

multiplying the prices of the products at the reference time period in the currencies by the volume of the products sold in the reference time period to calculate revenue of the products for the reference time period in the currencies;

dividing the revenue of the products for the reference time period in the currencies by the exchange rate at the reference time period to calculate relative revenue of the products for the reference time period in the currencies;

summing the relative revenue of the products for the reference time period in the currencies across the products to calculate relative revenue for the reference time period in the currencies;

summing the relative revenue for the reference time period in the currencies across the currencies to calculate relative revenue for the reference time period;

dividing the relative revenue for the reference time period by the volume of the products sold in the reference time period to calculate revenue per product sold in the reference time period;

subtracting the volume of the products sold in the reference time period by the volume of the products sold in the comparison time period to calculate change in volume;

multiplying the change in volume by revenue per product sold in the reference time period to calculate the quantity only effect;

multiplying the change in volume by the price to quantity split to calculate split quantity effect; and

combining the split quantity effect with quantity only effect.