IP Library Granted Patent US 10,586,359
Granted Patent B1
US 10,586,359 · App. 15/915,558 · Granted Mar 10, 2020

Methods and systems for creating waterfall charts

Inventors: Peter Long (Maroochydore, AU); Tim Berston (Leeming, AU); Kane Fasham (Queensland, AU); Mythili Gopalakrishnan (San Francisco, CA); Thomas Peff (Burlingame, CA)
Assignee: Workday, Inc.
G06T11/206G06Q40/12
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Quick Facts
Patent No.
US 10,586,359
App. No.
15/915,558
Granted
Mar 10, 2020
Kind
B1
Abstract

Disclosed is a method for creating a waterfall chart for data analysis. A waterfall chart enables a user to compare two different versions of a quantity and the underlying details for the differences between the two versions. The method comprises: 1) a data setting step including the setting of: a) an open value, b) a close value, c) a breakdown time and d) a breakdown dimension; 2) a data series definition step including defining: a) a reference data point, b) a comparison data point, c) a reference data breakdown series and d) a comparison data breakdown series; 3) a variance series computation step including: a) aligning the reference data breakdown series and the comparison data breakdown series, b) calculating a variance series, and c) creating a waterfall data series; and 4) a chart rendering step.

Claims (42)

1. A computer implemented method for creating waterfall charts, the method comprising:

a data setting step including setting a first plurality of data, wherein the first plurality of data comprises an open value, a close value, and a breakdown type, wherein the breakdown type is set to a first dimension associated with a first display format for a first value;

a data series definition step including defining a second plurality of data based on the first plurality of data, wherein the second plurality of data comprises a reference data point, a comparison data point, a reference data breakdown series, and a comparison data breakdown series;

a variance series computation step based on the second plurality of data, wherein the variance series computation step comprises calculating a variance series and creating a first waterfall data series based on the variance series;

a first chart rendering step comprising creating a first waterfall chart based on chart rendering data that comprise the first waterfall data series, wherein the first waterfall chart displays the first waterfall data series in the first display format for the first value;

resetting the breakdown type from the first dimension to a second dimension, wherein the second dimension is a child of the first dimension, wherein the second dimension is associated with a second display format for a second value, and wherein the first display format for the first value is different from the second display format for the second value; and

a second chart rendering step comprising creating a second waterfall chart based at least in part on the second dimension, wherein the first waterfall chart displays a second waterfall data series in the second display format for the second value.

2. The computer implemented method of claim 1 , further comprising determining a plurality of components for the waterfall chart based on the breakdown type.

3. The computer implemented method of claim 2 , wherein:

the reference data breakdown series includes an array of opening values for the plurality of components; and

the comparison data breakdown series includes an array of closing values for the plurality components.

4. The computer implemented method of claim 1 , wherein the second dimension is locations, subsidiaries, or geographical regions.

5. The computer implemented method of claim 1 , wherein the first plurality of data further comprises a maximum step count.

6. The computer implemented method of claim 1 , wherein defining the reference data point includes using the open value and defining the comparison data point includes using the close value.

7. The computer implemented method of claim 1 , wherein calculating the variance series compromises:

aligning the reference data breakdown series and the comparison data breakdown series; and

finding a plurality of differences between each member of the reference data breakdown series and a corresponding member the comparison data breakdown series as resulted from the aligning.

8. The computer implemented method of claim 1 , wherein the data setting step further comprises setting a sorting method.

9. The computer implemented method of claim 8 , wherein the variance series computation step further comprises sorting a plurality of members of the variance series according to the sorting method to create a sorted variance series.

10. The computer implemented method of claim 9 , wherein:

the method further comprises defining a concatenation method; and

the variance series computation step further comprises:

concatenating the sorted variance series based on the concatenation method to create a concatenated variance series and to calculate a reminder variance; and

adding the remainder variance in the sorted variance series to create a completed concatenated variance series.

11. The computer implemented method of claim 10 , wherein the first waterfall data series comprises the reference data point, the comparison data point, and one of the variance data series, the sorted variance series, concatenated variance series, and completed concatenated variance series.

12. The computer implemented method of claim 1 , further comprising enabling a time navigation, wherein the time navigation comprises:

receiving a first time period;

creating the first waterfall data series corresponding to the first time period;

creating the first waterfall chart based on the chart rendering data that comprise the first waterfall data series, wherein the chart rendering data is a first chart rendering data;

receiving a second time period;

creating a third waterfall data series corresponding to the second time period;

creating a third waterfall chart based on a second chart rendering data that comprise the third waterfall data series.

13. A computer implemented method for creating waterfall charts, the method comprising:

a data setting step including setting a plurality of data, wherein the plurality of data comprises an open value, a close value, and a breakdown type, wherein the breakdown type is set to a first dimension associated with a first display format for a first value;

a variance series computation step based on the plurality of data, wherein the variance series computation step comprises calculating a variance series and creating a first waterfall data series based on the variance series;

a first chart rendering step comprising creating a first waterfall chart based on chart rendering data that comprise the first waterfall data series, wherein the first waterfall chart displays the first waterfall data series in the first display format for the first value;

resetting the breakdown type from the first dimension to a second dimension, wherein the second dimension is a child of the first dimension, wherein the second dimension is associated with a second display format for a second value, and wherein the first display format for the first value is different from the second display format for the second value; and

a second chart rendering step comprising creating a second waterfall chart based at least in part on the second dimension, wherein the first waterfall chart displays a second waterfall data series in the second display format for the second value.

14. The computer implemented method of claim 13 , further comprising determining a plurality of components for the waterfall chart based on the breakdown type.

15. The computer implemented method of claim 13 , wherein the second dimension is locations, subsidiaries, or geographical regions.

16. The computer implemented method of claim 13 , wherein the data setting step further comprises setting a sorting method.

17. The computer implemented method of claim 16 , wherein the variance series computation step further comprises sorting a plurality of members of the variance series according to the sorting method to create a sorted variance series.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 6, 2019
From: ADAPTIVE INSIGHTS LLC
To: WORKDAY, INC.
Reel/Frame 050931/0879 →
CONVERSION Recorded Aug 1, 2019
From: ADAPTIVE INSIGHTS, INC.
To: ADAPTIVE INSIGHTS LLC
Reel/Frame 049938/0850 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 10, 2018
From: LONG, PETER; BERSTON, TIM; FASHAM, KANE; GOPALAKRISHNAN, MYTHILI; PEFF, THOMAS
To: ADAPTIVE INSIGHTS, INC.
Reel/Frame 045546/0665 →
Continuity (1)
Provisional Application 62469462 · Mar 9, 2017