WO2003073323A1

WO2003073323A1 - Data visualisation system and method

Info

Publication number: WO2003073323A1
Application number: PCT/NZ2003/000036
Authority: WO
Inventors: Tom Beard
Original assignee: Compudigm International Limited
Priority date: 2002-02-27
Filing date: 2003-02-27
Publication date: 2003-09-04
Also published as: NZ534945A; AU2003206484A1

Abstract

The invention provides a data visualisation system comprising an interaction database of interaction data maintained in computer memory representing interactions between customers and merchants and a retrieval device configured to retrieve from the interaction database data representing interactions between customers and merchants. The invention further comprises a data constructor configured to construct a set of discrete data values from the retrieved data, an aggregator configured to construct a set of summary data values from two or more of the discrete data values, and a display configured to display a representation of the discrete data values and a representation of the summary data values. The invention further provides a related method of data visualisation.

Description

DATA VISUALISATION SYSTEM AND METHOD

FIELD OF INVENTION

The invention relates to a data visualisation system and method, particularly but not solely designed for representing sales performance in the wholesale and retail industries.

BACKGROUND TO INVENTION

The low cost of data storage hardware has led to the collection of large volumes of data. Merchants, for example, generate and collect large volumes of data during the course of their business. To complete effectively, it is necessary for a merchant to be able to identify and use information hidden in the collected data. This data could include wholesale and retail sales data for one or more organisations.

Visualising summaries of such large amounts of information can be problematic for large corporations and other organisations. Such consumers need simple visual summaries to assist with rapid global exception reporting and analysis of activities of an organisation.

SUMMARY OF INVENTION

In broad terms in one form the invention comprises a data visualisation system comprising an interaction database of interaction data maintained in computer memory representing interactions between customers and merchants; a retrieval device configured to retrieve from the interaction database data representing interactions between customers and merchants; a data constructor configured to construct a set of discrete data values from the retrieved data; an aggregator configured to construct a set of summary data values from two or more of the discrete data values; and a display configured to display a representation of the discrete data values and a representation of the summary data values. In broad terms in another form the invention comprises a method of data visualisation comprising the steps of maintaining, in computer memory, interaction data representing interactions between customers and merchants; retrieving from computer memory at least part of the interaction data; constructing a set of discrete data values from the retrieved data; constructing a set of summary data values from two or more of the discrete data values; and generating and displaying a representation of the discrete data values and a representation of the summary data values.

BRIEF DESCRIPTION OF THE FIGURES

Preferred forms of the data visualisation system and method will now be described with reference to the accompanying figures in which:

Figure 1 shows a block diagram of a system in which one form of the invention may be implemented;

Figure 2 shows the preferred system architecture of hardware on which the present invention may be implemented;

Figure 3 shows preferred form data structures in accordance with the invention;

Figure 4 is a flow chart of a preferred form of the invention;

Figure 5 is one representation generated in accordance with the invention; and

Figure 6 is a further representation generated in accordance with the invention. DETAILED DESCRIPTION OF PREFERRED FORMS

Figure 1 illustrates a block diagram of the preferred system 10 in which one form of the invention may be implemented. The system includes one or more clients 20, for example 20A, 20B and 20C, which each may comprise a personal computer or workstation described below.

One or more of the clients could be interfaced to a workstation 30 as shown in Figure 1 via a network or collection of networks 40. The networks could include a local area network, a wide area network, a WAP connection, the Internet, or any combination of the foregoing.

The preferred system 10 may include a data repository 50, for example a data warehouse maintained in computer memory. It is envisaged that the data repository may comprise a single database, a collection of databases, or a data mart. The preferred data repository 50 includes data from a variety of sources and may include for example interaction data 52 representing interactions between customers and merchants as will be more particularly described below. The interaction data typically represents wholesale and retail sales of products and commodities to consumers distributed throughout different countries.

The data repository 50 could also include data from sources such as census data 53, a customer database 54, a loyalty programme database 55 and/or promotion data 56.

The workstation 30 could include a data memory 32 and server 34 and preferably operates under the controls of appropriate operating and application software stored in running on data memory 32.

The system 10 includes a retrieval device or retrieval component 60 which in one form comprises a software-implemented query enabling retrieval of data from the data repository 50, the data memory 32 and/or a data memory forming part of a client 20. The retrieval device 60 could alternatively comprise a data memory on which such a query is installed and operating.

Data retrieved with the retrieval device 60 is processed with the server 34. A data constructor 70 is configured to construct a set of discrete data values from the data retrieved from the retrieval device 60. An aggregator 80 is configured to construct a set of summary data values from two or more of the discrete data values constructed from the data constructor 70. Both the data constructor 70 and aggregator 80 are preferably implemented as software routines or software programs and are further described below.

A display 90 in one form comprises a computer-implemented software program that is configured to generate a display of the data obtained from the retrieval device 60, data constructor 70 and/or aggregator 80 on a client workstation 20, as will be described below. The display could alternatively comprise a conventional display software module interfaced and operable to display data on the client 20.

It will be appreciated that the system of Figure 1 is conceptual in nature. In one form a client 20 could have installed on it interaction data 52, the retrieval device 60, the data constructor 70, the aggregator 80 and the display 90 and function independently of any other component in the system. Alternatively, some or all of the components could be installed and operating on the workstation 30 and the client access required information as necessary in a client server relationship.

Figure 2 shows the preferred system architecture of a client 20 or workstation 30. The computer system 200 typically comprises a central processor 202, a main memory 204, for example RAM, and an input/output controller 206. The computer system 200 may also comprise peripherals including a data entry device such as a keyboard 208, a pointing device 210 for example a mouse, track ball, touch ball or cursor key set, a display or screen device 212, a mass storage memory 214 for example a hard disk, floppy disk or optical disc, and an output device 216 for example a printer. The system 200 could also include a network interface card or controller 218 and/or a modem 220. The individual components of the system 200 could communicate through a system bus 222.

It is envisaged that the invention have a wide area of application and that the nature and format of the data stored in computer memory will be different for each application. Different applications of the invention are set out below. In one form, the invention is arranged to display data representing interactions between customers and merchants which is typically sales of consumer products to various global markets.

Figure 3 illustrates preferred form data structures generated in accordance with the invention. Typically, an organisation involved in sales will maintain interaction data representing such sales. Typical sales records could include a region indicator, for example ASIA/PACIFIC, EUROPE, LATIN AMERICA or NORTH AMERICA and could include a country indicator, for example CHINA, SPAIN, MEXICO or CANADA.

Each record could also include a product identifier, for example TEA-BASED BEVERAGE, PROFESSIONAL CLEANING, or LAUNDRY. Each of these products could in turn be grouped into a product group, for example FOOD, MISCELLANEOUS or HPC and these food groups could be stored either with each sales record or separately in another table linking individual product identifiers to product group identifiers.

Each sales record could also include a time/date indicator representing the date of the sale and also a sales quantity indicator which could include the quantity of products sold, the revenue obtained from the sale, and/or the profit obtained from the sale.

The interaction data could also include target values. These target values could represent desired sales volumes in a particular country or region for a product, or could include revenue targets and/or profit targets. It will be appreciated that interaction data of this nature represents a large data set and is therefore difficult to interpret.

The retrieval device in accordance with the invention is configured to retrieve from computer memory, for example the interaction database 52, data repository 50, data memory 32 and/or client 20, data representing interactions between customers and merchants. An example of such data is shown at 300. The retrieved data could be stored in a data table that includes region 302, product 304, country 306, sales 308 and target sales 310. It is envisaged that sales 308 could include actual sales but could also include the change in sales as a percentage increase or decrease when compared to an equivalent earlier time period. The target sales 310 are preferably compatible with sale 308. For example, where sales 308 are based on an actual volume, target sales 310 would be specified as a change in volume.

The retrieval device preferably stores the retrieved data 300 in computer memory for subsequent retrieval. The data constructor then constructs a set of discrete data values from the retrieved data 300.

One example of the resulting data is shown at 320. The data could include a region identifier 322, a product identifier 324 and a country identifier 326. The data also includes a set of discrete data values 328 constructed by the data constructor. One example of these discrete data values could be sales performance. Where the retrieved data 300 includes sales figures 308 and target sales figures 310, the sales performance 328 could comprise the difference between actual sales and target sales and could comprise a positive value where sales exceed target sales and comprise a negative value where sales have not met target sales. Alternatively sales performance 328 could be represented as a percentage increase or decrease when compared to an equivalent earlier time period.

The data constructor is preferably configured to store data 320 including the set of discrete data values 328 in computer memory ready for subsequent retrieval. The aggregator is configured to construct a set of summary data values from two or more of the discrete data values 328. Typical summary data values constructed by the aggregator are illustrated at 330. The summary data values could include for example a region indicator 332 and sales performance 334. The aggregator in one form is configured to sum all of the discrete data values 328 for an individual region and to create data set 330 with the aggregated sales performance data for each region.

As described above, each product could be grouped into a product group for example FOOD, MISCELLANEOUS or HPC, and these food groups could be stored either with each sales record or separately in another table linking individual product identifiers to product group identifiers. The resulting data 320 could include or be linked to these product groups and the resulting aggregated data 330 could aggregate discrete data values 328 for an individual region for an individual product group and create data set 330 with the aggregated sales performance data for each region for each product group.

Figure 4 illustrates one preferred method 400 of operation of the invention. As shown at 410, data is retrieved from computer memory using a suitable query initiated by the retrieval device. The retrieved data could include data interactions between customers and merchants.

A set of discrete data values is then constructed 420 from the retrieved data. This set of data values could include for example the sales performance of various products throughout different regions over a predefined period.

A set of summary data values is then constructed 430 from the set of data values. A representation of these discrete data values is then displayed 440 and a representation of the summary data values is also displayed 450. Figure 5 shows one preferred representation generated in accordance with the invention. The preferred form representation 500 is shown as a grid of individual representations of respective data values. The data representations could be divided into geographic regions 502 which in turn could be further divided into individual countries 504. The representations could also be divided into product groups 506 which in turn could be further divided into individual products 508.

Each individual representation is preferably positioned in substantial alignment with the country and product associated with that representation. For example, ice cream sales in Argentina could be displayed as representation 510 which is aligned with all other product groups in Argentina on one axis and all other country groups for ice cream on another axis.

It is envisaged that the colour of each individual data representation could indicate the comparison of that data value against a target value. In this example, the growth of ice cream sales in Argentina is below a target value which results in a negative sales performance data value.

In one preferred form the discrete data values are mapped to a sales performance colour value such as that shown at 512. Sales performance values of more than 9% are mapped to one colour value, sales performance values between 3% and 9% are mapped to another colour value, sales performance values between 1% to 3% are mapped to a further colour, sales performance values of -1 to -3 are mapped to a further colour, sales performance values of -3% to -9% are mapped to a further colour and sales performance values of less than 9% are mapped to another colour. A sales performance value of 0 preferably does not result in any representation being generated.

In Figure 5, sales performance of ice cream in Argentina is significantly below the corresponding target value and falls within the less than -9% and is displayed in the colour equivalent to this sales performance value. The invention is further configured to generate and display a representation of the summary data values. In the example, ice cream sales in Argentina are significantly below expectations but this is not true of other food products in Latin America. It is beneficial to present to a user representations of overall sales of food products in Latin America in close proximity to the representations of the individual data values.

One such representation of summary data values could include a border or frame 520 that provides a comparison between actual summary data values and target values. Each group of representations could be framed by a coloured border, the colour of the border functioning as a performance indicator. The same legend 512 could be used for different border colours in addition to discrete data representations.

Border 520 for example summarises sales of all of the food products sold in Latin America. The colour of the border indicates that as a whole this area is performing below a measured standard or threshold but not significantly below the threshold. Individual representations shown within the border 520 are shown to be performing above expectations, with the exception of ice cream sales in Argentina. The comparison between individual data record representations and grouped data record representations is readily apparent.

Figure 6 shows another preferred form representation, 600 generated by the invention. The representation 600 is configured to display wholesale and retail data involving four retail outlets, Ahold 602, Carrefour 604, Tesco 606 and Walmart 608. It will be appreciated that the interaction data comprises a merchant identifier sufficient to distinguish between each of merchants or outlets 602, 604, 606 and 608.

Representation 600 includes a plurality of representations similar to that shown in Figure 5 in that the representations comprise a grid of individual representations of respective data values and are framed with a representation of summary data values in close proximity to the representations of the individual data values, for example representation 609. The layout of each grid can include for example merchant or retail outlet 610 along one axis for example Ahold 612, Carrefour 614, Tesco 616 and Walmart 618. Along another axis could be positioned product groups 620 for example food 622, miscellaneous 624 and HPC 626.

Representation 609 represents product sales for each of the different merchants or outlets throughout the geographic region Europe. To make this feature clear to a user, the individual representations could be overlaid on a world map 630 and a link 640 drawn between representation 609 and the geographic area 642.

By clicking on one of the merchant indicators 602, 604, 606 or 608, the user could be presented with a display such as that shown in Figure 5 which shows a more detailed representation for a particular outlet or merchant.

As shown in both Figures 5 and 6, the representation of discrete data values could include contoured representations as is more particularly described in WO 00/77682 published 21 December 2000.

It is envisaged that the display could be configured to display data is more than two dimensions and could show a 3-dimensional cube of representations.

The invention presents to a user a series of summary visualisations with broad detail of each summary visualisation discernable from this view. The information summarised in this visualisation is such that viewers can identify which of the series of visualisations require closer examination.

It is envisaged that the invention is applicable to all industries. Information can be displayed using both still images and animated visual images or AVIs where these AVIs are a succession of consecutive still images visualising data over some specified time period. The foregoing describes the invention including preferred forms thereof. Alterations and modifications as will be obvious to those skilled in the art are intended to be incorporated within the scope hereof, as defined by the accompanying claims.

Claims

1. A data visualisation system comprising: an interaction database of interaction data maintained in computer memory representing interactions between customers and merchants; a retrieval device configured to retrieve from the interaction database data representing interactions between customers and merchants; a data constructor configured to construct a set of discrete data values from the retrieved data; an aggregator configured to construct a set of summary data values from two or more of the discrete data values; and a display configured to display a representation of the discrete data values and a representation of the summary data values.

2. A data visualisation system as claimed in claim 1 wherein at least one data value representing interactions between customers and merchants has a corresponding target value, the set of discrete data values constructed by the data constructor including differential data values representing the difference between respective data values and corresponding target values.

3. A data visualisation system as claimed in claim 2 wherein the aggregator is configured to construct the set of summary data values at least partially from two or more differential data values.

4. A data visualisation system as claimed in any one of the preceding claims wherein the display is configured to display a grid of individual representations of respective data values.

5. A data visualisation system as claimed in claim 4 wherein the display is configured to display a representation of the summary data values in close proximity to the representations of the data values.

6. A method of data visualisation comprising the steps of: maintaining, in computer memory, interaction data representing interactions between customers and merchants; retrieving from computer memory at least part of the interaction data; constructing a set of discrete data values from the retrieved data; constructing a set of summary data values from two or more of the discrete data values; and generating and displaying a representation of the discrete data values and a representation of the summary data values.

7. A method of data visualisation as claimed in claim 6 wherein at least one data value representing interactions between customers and merchants has a corresponding target value, the set of discrete data values including differential data values representing the difference between respective data values and corresponding target values.

8. A method of data visualisation as claimed in claim 7 further comprising the step of constructing the set of summary data values at least partially from two or more differential data values.

9. A method of data visualisation as claimed in any one of claims 6 to 8 further comprising the step of displaying a grid of individual representations of respective data values.

10. A method of data visualisation as claimed in claim 9 further comprising the step of displaying a representation of the summary data values in close proximity to the representations of the data values.