Geographical Analysis of hierarchical business structures by ...Document Transcript
Geographical Analysis of hierarchical business structures
by interactive drill down
Klaus Böhm Eva Daub
University of Applied Sciences University of Applied Sciences
Holzstrasse 36, D-55116 Holzstrasse 36, D-55116
ABSTRACT directly to the end users. The manufacture operates with the help
This paper deals with the geographical analysis and visualization of self-employed agents, who get commission for selling products
of network marketing. The aim of the study was to develop to the customers. Not only does the agent aim to sell products, but
interactive visual methods, which help to answer questions related also does he try to enlarge the Marketing Network by recruiting
to the analysis of network marketing structures. Those questions new agents. If he does this successfully, he participates in the
were the basis for the research and development performed. The profit scheme. The analysis of the complex business structures of
challenges tackled in the paper result from data analysis, which a corporation, which sells legal documents on a multilevel basis,
includes a combination of structural data and their geographical defined the initial challenges and led to the research study. From a
position. An approach utilizing interactive drill down was graph-theory perspective the structure of a Marketing network is
developed. The resulting prototype summarizes the findings and most likely a tree. In consequence this paper considers tree
allows the validation of the results. diagrams as the basic structuring element.
Part of the analytic process for the multilevel marketing structure
Categories and Subject Descriptors: was to find answers to the following questions:
H.5.3 [Information Interfaces And Presentation]: Group and 1. Which person in this network has recruited one particular
Organization Interfaces, member?
I.3.8 [Computer Graphics]: Applications, 2. How many new members did this specific member recruit?
H.5.1 [Information Interfaces And Presentation]: Multimedia 3. Who are those members?
Information Systems, 4. How are those members geographically distributed?
General Terms 5. Are there geographical clustering points/areas independent of
Human Factors, Economics, Experimentation, specific network relations?
Not only is the information to one particular person important for
Keywords a business analysis, but also information to the whole network.
Information Visualization; complex business structures, 6. How is the network geographically distributed? Are there
geographical analysis. any economic „hotspots“ or gaps?
7. Is the network hierarchy well balanced? In what proportion
1. INTRODUCTION are the different member types (e.g. trial, regular and
This paper describes the preliminary results of currently ongoing managing members) to each other?
research focusing on the analysis of hierarchical structures in
combination with their geospatial attributes. One field of interest 8. Are there any interrelations between business growth and
for combining those two components is the analysis of complex stops in the hierarchy and the respective geographical
multilevel marketing structures. Multilevel Marketing location?
incorporates the distribution of products from the manufacture Another area of interest is the business analysis regarding the time
Permission to make digital or hard copies of all or part of this work for 9. How did the network evolve over the past? This relates to the
personal or classroom use is granted without fee provided that copies are question, what prediction for the economical future is
not made or distributed for profit or commercial advantage and that possible.
copies bear this notice and the full citation on the first page. To copy This set of questions reflects the requirements from the
otherwise, or republish, to post on servers or to redistribute to lists,
requires prior specific permission and/or a fee.
application point of view. It is not yet comprehensive and could
ACM GIS ’08, November 5-7, 2008. Irvine, CA, USA be further complemented by other marketing related aspects.
(c) 2008 ACM ISBN 978-1-60558-323-5/08/11…$5.00.
When analysing those questions from a visualization point of in the presentation shown in Figure 2. This approach delivers
view, they can be divided into different categories: sufficient results for a well-structured network where the
hierarchical distribution of the network correlates to the
- Category I. Questions, which can be answered by visualizing
geographical distribution. In the map below (Figure 3) there is no
their structural information, for example as a tree diagram.
direct correlation between the hierarchy and the geographical
Those questions are: 1, 2 and 3.
distribution that leads to the unstructured arrangement.
- Category II. Questions, which can be answered by a
cartographic presentation of the data. For instance question
- Category III. Questions, which require an understanding of
both the hierarchical interrelation of the members and their
geographical position. For instance question 4, 6, 7 and 8.
One example, which combines geographical data with
structural information, is shown in Figure 1 demonstrating
some visualization of Internet traffic/connection.
Figure 2. This figure shows a structured diagram, in which
the hierarchy is geographically related. The root is marked by
the blue circle.
Figure 1. The figure shows a representation of internet traffic.
NSFNET T1 Backbone and Regional Networks, 1991 
- Category IV. Questions, which require special features in
order to provide the required understanding. An example
might be question 9.
2. STATE OF THE ART AND
Figure 3. The information in the map is very unstructured.
CHALLENGES The root is marked by the blue circle.
Information visualization has been a research topic for many
years. It remains an active field for investigations since the data The presentation in Figure 1 provides also good understanding, as
complexity increases and more demands for new visualization there is an easy structure on higher layer, which corresponds to
paradigms from applying domains are given, e.g. business the geographical position of the underlying notes. If the network
structures . Nowadays often used in this context is the term structure is not correlated with the geographical distribution
“visual analytics”, focusing on the analyzing aspect of (Figure 3), the limitations of this approach are obvious, as the
visualization in order to derive insights from massive and visualization does not provide any advantages for the analysis.
dynamic eventually ambiguous data . Instead of simplifying the analysis, the visualization confuses.
Digital cartography makes it easy to combine complex data with Improvements can be achieved by utilizing additional interactive
the geospatial information on maps to make the information more techniques such as a highlighting of the connecting lines in the
accessible to the reader . Peterson recently summarized an proximity of the mouse pointer after mouse movement. The
international perspective on maps used in internet applications connections of a particular member are therefore distinguishable,
. The term Business intelligence describes the collection, the however, the hierarchical network and the position of the member
processing and the visualization of business data often in in the network in the hierarchy does not become clear.
combination with geographic reference . These operations
serve the efficient analysis to find the right decisions in business 3. APPROACH – INTERACTIVE DRILL
It is obvious that the questions of the categories I and II ought to Our conceptual approach to overcome the deficiencies described
be answered by the means of standard information visualization above is to split the visualization of the structure and the
techniques and state of the art cartographic techniques. The geographical information. They are presented to the user as two
challenge is, however to find an appropriate solution for the different views of the same dataset.
questions of category III which require combination of structural
As we consider large structures (> 1000 nodes), first we need to
and spatial information. Combining the two representations into
reduce the information to be presented. The general approach for
one visualization result would be the logic attempt and is applied
this is the utilization of the “Visual Information Seeking Mantra” select a time in past and only the situation at this point in time
from Shneiderman: “Overview first, zoom and filter, details on may be shown. As far as the mapping is concerned, the approach
demand”  see also . For the tree diagram it means that a can be realized directly as only the respective nodes for a selected
permanent overview of the whole tree structure is given. Through time appear on the map. Regarding the tree visualization, different
navigation with a zoom window a section of the tree diagram is options had to be considered since adding and removing nodes
displayed in a second diagram enlarged (see Figure 4). This to/from a tree requires recalculation of layouts. This is of course
enables the analysis of particular substructures including the time consuming and for the user it requires a high cognitive work
whole proximity. to connect the different shapes when viewing the information
along the time. The solution chosen visualizes the structure with
all nodes but uses different visual attributes for those nodes,
which were not part of the system at the selected point in time.
Thus, this option does not change any layouts over the time, and
overcomes the deficiencies mentioned. Best results were achieved
by using different saturations of the colour (see also the
presentation of the tree in Figure 6: the transparent nodes were not
part of the structure at the selected time).
Figure 4. The left image shows the diagram with the overall
tree structure. The zoom window displays the enlarged 4. REALIZATION
version of the tree diagram. This section describes in brief some aspects of the actual
For the detailed analysis of a particular node we considered the implementation and shows the results. In Figure 6 the final
presentation of the direct proximity, in specific the father node, prototype is shown with the previously described features. On the
node of interest itself and all children. This information is also top of the left side the map properties are displayed, in which the
displayed in the map (Figure 5). By using different characteristics user can select which layers are shown on the map. Below is the
of labels in the map for the different node types (father, main search function, and at the bottom of the left side is the overview
node, children), an easy understandable presentation is generated. tree diagram. The main information is presented on the right
Trials showed that the connections between the labels are not containing the map on top and the tree diagram at the bottom,
even necessary for understanding the data on the map. separated by the timeline. For the layouting of the tree diagram,
the improved walker algorithm is utilized . As large data sets
are considered, performance is an issue. In order to support
performance, layouting is done in the preprocessing step.
Figure 5. The left image shows the detailed view of one node
including its father node and the children. The right image
shows corresponding nodes on the map. The different visual
characteristics of the labels represent the different layers in
the sub tree.
Interaction as an essential basis for drilling down the information
should be as intuitive as possible. Thus the user can navigate in
the tree structures by clicking on the nodes. By doing this the user
will navigate within the tree. In parallel the geographic position of
that member is shown in the map, together with its direct relations
i.e. father and child nodes. Alternatively the user can navigate in
the tree only by clicking on the labels in the map. In this case the
user might use the tree as the basic mental model, but the
geographic location of the members for drilling down. Of course
the display of the sub part of the tree is following the user’s Figure 6. Screenshot of the application. The application shows
navigation. This approach shall enable the user to answer the the statistical distribution of the different member categories
category III question defined in Chapter 1, as it enables the user in the states.
to understand the hierarchical interrelation of the nodes and their In order to allow the user to navigate in the tree structure, a
geographical position. The individual questions will be further moveable square (magnifier) is placed inside the overview tree
discussed in chapter 5. (Figure 4, 6.). Its movement is linked to the position of the
enlarged tree diagram. It is arranged in such a way, that the
In order to address question related to category IV – the time visible area of the enlarged diagram relates to the inside of the
associated questions – a timeline is integrated in the visualization magnifying square. The nodes are selectable. This might be used
approach, so the business structures can be visualised at different to drill down in the graph and observe only the direct proximity
points in time (see Figure 6). The relevant temporary information (Figure 5), together with its parent and child nodes. This diagram
is available in the data of the nodes. The user may interactively is recalculated each time, the user clicks on a node.
The timeline is generated according to the entry dates of the caused by a move of the member). With respect to question 9; the
members. Therefore the earliest and the latest entry dates are timeline approach described above provides a good mean to
determined, which are taken as the boundaries of the timeline. In understand the growth of the “structure”. It does not provide
a defined timeframe of one month, intermediate time intervals are special indication for future prediction and it does not replace
integrated through individual buttons. If a specific time is selected temporal analysis of the factual numbers. Good examples for this
the tree is traversed and it is checked if a particular person was are shown e.g. by Tableau Software .
already member at this time. If this is the case, the member node
remains visible in the map and in the tree diagrams. If this is not 6. OUTLOOK
the case, the node in the diagrams appears transparent, and Based on the results achieved so far, we see further work
becomes invisible in the map. Furthermore the statistics are necessary in three areas, first enhancing the layout for trees with
recalculated (see Figure 7 right). an extreme large amount of nodes especially if they are very
unbalanced or if they contain nodes with extreme large amount of
5. CONCLUSION children. Second, thorough usability testing shall be performed. It
The developed prototype is able to visualize the hierarchical was already detected that the usability and cognition can be
structures in a tree diagram as well as in a geographic map improved by including animated transitions between the different
simultaneously. It enables the interaction with map and tree visualizations when the user interactively navigates through the
diagram simultaneously. This gives the analyst an overview of the structure. Third, more tailored drill down techniques should be
whole network and details about smaller substructures or explored in order to better support e.g. answers to question 6.
individual members. The validation if the developed solution
fulfills the requirements given by the application might be done 7. REFERENCES
by reviewing whether the question stated in the beginning can be  Buchheim, C., Jünger, M., Leipert, S. 2002. Improving
answered sufficiently. Walker’s Algorithm to Run in Linear Time. Lecture Notes in
Computer Science, Heidelberg (2002)
 Cammarano, M., Dong, X., Chan, B., Klingner, J., Halevy,
A. and Hanrahan, P. 2007. Visualization of Heterogeneous
Data. IEEE Transactions on Visualization and Computer
Graphics 13, 6 (Nov. 2007), 1200-1207.
Figure 7. On the left unfiltered distribution of all members, on  Keim, D. A., Mansmann, F., Schneidewind, J., Thomas, J.
the right relative distribution of different categories. and Ziegler, H.:Visual Analytics: Scope and
Questions 1, 2 and 3 could be answered by a presentation given in Challenges, Visual Data Mining: Theory, Techniques and
Figure 5. The father-son relationship represents the recruiting Tools for Visual Analytics, Springer, 2008, Lecture Notes In
process. The details about a member can be displayed in a label Computer Science.
(see Figure 5 and Figure 6). Question 4 could be answered by the  Gonzales, M. 2005. Spatial Business Intelligence, The
combination of the presentations given in Figure 5. Both show the Spatial and Visual Components for Effective BI. Directions
same subset of members. In the right image the geographic Magazine (2005)
position is shown. The different colour and size of the bubbles  Hanrahan P., Stolte C., Jackinlay J. 2007. Visual analysis for
reflect the structural relation. Nevertheless, the information in the everyone, Whitepaper Tableau Software, 2007.
left image (including the position of the sub tree in the overall
structure, for instance Figure 4) provides the necessary insights to  IBM Press Room. 2007. http://www-
understand the members’ position in the structure. Question 5 03.ibm.com/press/us/en/pressrelease/23027.wss
could be answered by presentations given in Figure 7. Clustering  Miller, C. 2006. A Beast in the Field: The Google Maps
is clearly visible even on this presentation. However visualization Mashup as GIS/2, Cartographica: The International Journal
techniques, which merge the representation of members according for Geographic Information and Geovisualiyation University
to the map scale are to be integrated. Regarding question 6; the of Toronto Press (2006)
geographic distribution of the complete network is given as
 Perer, A., Shneiderman, B. (2008) Integrating Statistics and
described for question no. 5. For sub trees up to three layers the
Visualization: Case Studies of Gaining Clarity during
networks geographic distribution can be understood directly, see
Exploratory Data AnalysisProceedings of ACM CHI 2008,
comments to question 4. However, analysing the distribution of
sub trees larger than three layers has to be done by stepwise drill
down by the user. Here a more automatic solution would be  Peterson, M. 2008. International Perspectives on Maps and
necessary. To answer question 7; the overall structures in Figure 4 the Internet, v. 1 (Lecture Notes in Geoinformation and
provide an indication on the organic structure. Each inner node, of Cartography), Springer, 2008.
course, contributed to the further growth of the business. The  Shneiderman, B. 1996. The Eyes Have It: A Task by Data
detail analysis is conducted in the detailed view. Figure 7 in Type Taxonomy for Information Visualizations. In:
addition shows the distribution statistically. For question 8 the Proceedings IEEE Visual Languages 1996, pp. 336-343,
overview structure of Figure 4 helps to detect e.g. stops in growth Boulder, CO (1996)
at some part. Inspecting the concrete nodes including the
 University of Illinois, CyberOutreach and High-end
proximity leads to presentations shown in Figure 5 which would
show that some member could not expand further in a certain
geographical area while other areas are still growing (eventually