U.S. patent application number 13/588711 was filed with the patent office on 2012-12-13 for forming a business relationship network.
This patent application is currently assigned to Accenture Global Services Limited. Invention is credited to Michael P. Miller, David R. Pendergraft.
Application Number | 20120316903 13/588711 |
Document ID | / |
Family ID | 39275677 |
Filed Date | 2012-12-13 |
United States Patent
Application |
20120316903 |
Kind Code |
A1 |
Pendergraft; David R. ; et
al. |
December 13, 2012 |
FORMING A BUSINESS RELATIONSHIP NETWORK
Abstract
A collective knowledge set of business relationship information
from a plurality of sources is generated. The collective knowledge
set is mapped as a plurality of navigable paths forming a business
relationship network between a source and a target. One or more of
the paths are identified as candidate paths most likely to lead to
a business relationship between the source and the target based on
evaluation criteria.
Inventors: |
Pendergraft; David R.;
(Mannasas, VA) ; Miller; Michael P.; (Alexandria,
VA) |
Assignee: |
Accenture Global Services
Limited
Dublin
IE
|
Family ID: |
39275677 |
Appl. No.: |
13/588711 |
Filed: |
August 17, 2012 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
11545753 |
Oct 10, 2006 |
8249903 |
|
|
13588711 |
|
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Current U.S.
Class: |
705/7.11 |
Current CPC
Class: |
G06Q 30/02 20130101;
G06Q 30/0201 20130101; G06Q 10/0637 20130101 |
Class at
Publication: |
705/7.11 |
International
Class: |
G06Q 10/00 20120101
G06Q010/00 |
Claims
1. A method of automatically determining and evaluating a business
relationship network for forming business relationships, the method
comprising: generating a collective knowledge set of business
relationship information from a plurality of sources; mapping the
collective knowledge set as a plurality of navigable paths forming
a business relationship network between a source and a target, each
navigable path of the plurality of navigable paths comprising nodes
and links between at least some of the nodes; analyzing feedback
including stored historical information of successes and failures
in generating business relationships of prior navigable paths from
previously-generated business relationship networks; determining
evaluation criteria from the feedback and the mapping, wherein the
determining of evaluation criteria includes: determining that a
value of "n" for n-degrees of separation between the source and the
target for each of the plurality of navigable paths is less than or
equal to a predetermined threshold; assigning, based on attributes
of each node, a tier value for each link in each of the plurality
of navigable paths, resulting in a plurality of tier values; and
assigning each of the plurality of navigable paths to one of the
plurality of tier values based on an order of the links from the
source to the target and their tier values, wherein links represent
relationships and the link closest to the source represents the
most significant relationship to lead to a business relationship
between the source and the target; and identifying, by a processor
of a computer system, based on the determined evaluation criteria,
a subset of the plurality of navigable paths as candidate paths
mapped from the collective knowledge set to generate a business
relationship between the source and the target based on the
evaluation criteria.
2. A computer system to determine and evaluate a business
relationship network for forming business relationships, the
computer system comprising: data storage to store a collective
knowledge set of business relationship information gathered from a
plurality of sources, including historical information on successes
and failures of using previously-generated business relationship
networks to develop a business relationship; a processor; and a
business relationship prospector comprising: a visualization module
to map the collective knowledge set as a plurality of navigable
paths forming the business relationship network between a source
and a target, wherein at least one of the navigable paths includes
a third party node and each of the plurality of navigable paths
comprising nodes and links between at least some of the nodes; and
a relationship finder module to: determine evaluation criteria from
the stored historical information and the plurality of navigable
paths, wherein the relationship finder module is to: determine that
a value of "n" for n-degrees of separation between the source and
the target for each of the plurality of navigable paths is less
than or equal to a predetermined threshold; assign, based on
attributes of each node, a tier value for each link in each of the
plurality of navigable paths, resulting in a plurality of tier
values; and assign each of the plurality of navigable paths to one
of the plurality of tier values based on an order of the links from
the source to the target and their tier values, wherein links
represent relationships and the link closest to the source
represents the most significant relationship to lead to a business
relationship between the source and the target; and identify, based
on the determined evaluation criteria, a subset of the plurality of
navigable paths as candidate paths mapped from the collective
knowledge set, to generate a business relationship between the
source and the target.
3. A computer system to determine and evaluate a business
relationship network for forming business relationships, the
computer system comprising: data storage to store a collective
knowledge set of business relationship information gathered from a
plurality of sources, including historical information on successes
and failures of using previously-generated business relationship
networks to develop a business relationship; a processor; and a
business relationship prospector comprising: a visualization module
to map the collective knowledge set as a plurality of navigable
paths forming the business relationship network between a source
and a target, wherein at least one of the navigable paths includes
a third party node and each of the plurality of navigable paths
comprising nodes and links between at least some of the nodes; and
a relationship finder module to: determine evaluation criteria from
the stored historical information and the plurality of navigable
paths, wherein the relationship finder module is to: determine that
a value of "n" for n-degrees of separation between the source and
the target for each of the plurality of navigable paths is less
than or equal to a predetermined threshold; assign, based on
attributes of each node, a tier value for each link in each of the
plurality of navigable paths, resulting in a plurality of tier
values; and assign each of the plurality of navigable paths to one
of the plurality of tier values representing a lowest tier valued
link in the respective navigable path, wherein the lowest tier
valued link is least likely of all links in the respective
navigable path to lead to a business relationship between the
source and the target; and identify, based on the determined
evaluation criteria, a subset of the plurality of navigable paths
as candidate paths mapped from the collective knowledge set, to
generate a business relationship between the source and the target.
Description
CLAIM OF PRIORITY
[0001] The present application claims the benefit of priority to
U.S. patent application Ser. No. 11/545,753, filed on Oct. 10,
2006, entitled Forming A Business Relationship Network, by David R.
Pendergraft et al., the disclosure of which is hereby incorporated
by reference in its entirety.
BACKGROUND
[0002] Currently, it is difficult to identify useful relationships
that employees may have with current or prospective clients and to
identify relationships which can be used to further business
development objectives. These business relationships may be
essential to the sales process and for developing the prospective
client into a client.
[0003] Current tools for business development typically include
storing contact information for current and prospective clients. It
is generally up to the user to review the contact list and
determine whether any of the contacts may be helpful in developing
new business relationships that can lead to new sales. However,
typically users focus on one-to-one relationships, such as whether
anyone in their contact list works for a company that is a
prospective client. However, developing a business relationship
with a client may require fostering relationships with two or three
intermediate people, and it is a difficult and time consuming task
to identify these intermediate people from a contact list.
[0004] Furthermore, typically contact list are limited by
organizational level, geographically limited, or may not be focused
lists. For example, a user may rely only on relationships with
high-level employees, such as board members, to generate a business
relationship with a prospective client, but many business
relationships may result from relationships with lower-level
employees. Also, a contact list may be generated from sources from
the same office and may not consider lucrative information from
affiliates or other sources located in other geographic areas.
Also, some approaches to business development include mass mailings
or cold calling based on purchased contact list, which is highly
inefficient and costly.
[0005] In addition, it may be difficult to harvest business
relationship information from multiple sources for the contact list
due to data confidentiality or other obstacles. Furthermore, people
may be unaware of the importance of their existing relationships
with friends or other people simply because they may not know that
these people work for a potential client or are somehow connected
to the potential client. Thus, it is difficult to collect
information that may be useful for identifying relationships which
can be used to further business development objectives. Also, even
with some useful business relationship information collected,
current tools and approaches that may use the collected information
for business development tend to be ineffective, time-consuming and
costly.
SUMMARY
[0006] According to an embodiment, a business relationship network
for developing business relationships is automatically generated. A
collective knowledge set of business relationship information from
a plurality of sources is generated. The collective knowledge set
is mapped as a plurality of navigable paths forming a business
relationship network between a source and a target. One or more of
the paths are identified as candidate paths most likely to lead to
a business relationship between the source and the target based on
an evaluation criteria formed from business objectives.
BRIEF DESCRIPTION OF THE DRAWINGS
[0007] The embodiments are illustrated by way of example and
without limitation in the accompanying figures in which like
numeral references refer to like elements, and wherein:
[0008] FIG. 1 illustrates a block diagram of a system, according to
an embodiment;
[0009] FIG. 2 illustrates a more detailed block diagram of the
system shown in FIG. 1, according to an embodiment;
[0010] FIGS. 3A-D illustrate examples of indirect business
relationships in a business relationship network and matching link
attributes to create navigable paths for the business relationship
network, according to an embodiment;
[0011] FIG. 4 illustrates an example of data in a refined data set
for matching link attributes, according to an embodiment;
[0012] FIGS. 5A-D illustrates examples of business network
visualizations, according to embodiments;
[0013] FIG. 6 illustrates an example of a business network
visualization including third party nodes having high target
participation, according to an embodiment;
[0014] FIG. 7 illustrates an example of a business network
visualization showing n-degrees of separation, according to an
embodiment;
[0015] FIG. 8 illustrates a flowchart of a method for determining a
business relationship network, according to an embodiment; and
[0016] FIG. 9 illustrates a block diagram of a computer system in
which one or more of the embodiments may be implemented.
DETAILED DESCRIPTION
[0017] For simplicity and illustrative purposes, in the following
description embodiments of systems and methods are described, and
numerous specific details are set forth in order to provide a
thorough understanding of the embodiments. It will be apparent
however, to one of ordinary skill in the art, that the embodiments
may be practiced without limitation to these specific details. In
other instances, well known methods and structures are not
described in detail so as not to unnecessarily obscure
understanding of the embodiments.
[0018] According to an embodiment a business relationship network
between a target and a source is automatically determined from a
collective knowledge set of business relationship information. The
business relationship network may include a plurality of navigable
paths that can be followed to develop business relationships to
further business objectives, such as understanding client's needs,
setting up meetings with key decision-makers, generating and
identifying new opportunities for sales, increasing the
probabilities of winning business proposals, increasing a return on
investment or for achieving other business objectives.
[0019] A business relationship is a relationship that may be used
to further the needs or objectives of a business entity. A business
relationship may include a relationship between a source and a
target. Examples of types of sources and targets include but are
not limited to business entities, such as companies, individuals,
groups, or other entities that may be leveraged to generate
business relationships. In one example, the source is a company
that is interested in doing business with a target company. The
target may also include existing customers or clients of the
source.
[0020] Business relationships may include direct or indirect
business relationships. A direct business relationship is a
business relationship between a source and a target without any
intervening third party nodes between the source and the target.
For example, Rich of a source company A knows the individual at a
target company B that decides whether to purchase goods or services
from the source company A.
[0021] An indirect business relationship is a business relationship
that includes at least one third party node between the source and
the target. Third party nodes are individuals or entities that are
intermediate to a target and a source in a business relationship.
In some instances, a third party node may include an event or a
place. Indirect business relationships have "n" degrees of
separation where "n" is the number of third party nodes between the
source and the target.
[0022] According to an embodiment, a target, a source and third
party nodes connecting the target and the source are identified and
used to create a business network. The business network includes
multiple navigable paths from one node to another node in the
network. Each node may represent a person, an entity or a group,
such as a corporation, affiliates, charity, organization, or an
event or place. Each navigable path is a logical path that can be
followed from one node in the path to another node in the path to
achieve a business objective, such as developing a business
relationship between the source and the target. For example, the
navigable paths include paths between a source node, such as a
source company, and a target node, such as a target company. The
navigable paths may include multiple links. Each link may be
provided between two nodes in a navigable path and represents a
relationship between the two nodes. At least some of the paths may
represent indirect business relationships between the source
company and the target company, and include one or more intervening
third party nodes between the source and the target node. A
navigable path may also represent a direct business relationship
without third party nodes.
[0023] The navigable paths in the business network may be evaluated
to identify one or more candidate navigable paths that are
determined to have a greatest likelihood of generating a business
relationship. Evaluation criteria may be used to select the
candidate navigable paths. Evaluation criteria may be static or
dynamic. For example, static evaluation criteria may characterize
paths as first tier, second tier, or third tier, based on
predetermined attributes of intervening nodes. Each tier is
representative of an estimated level of ability to develop a
business relationship network from navigable paths to be placed in
the tier. The tiers may be ranked or weighted based on the
estimated strength of the navigable paths to develop a business
relationship network. The tiers may be used to select or highlight
the best candidate paths for generating a business relationship
network. Dynamic criteria may be generated based on feedback, which
includes evaluating navigable paths from previously-generated
business networks. For example, navigable paths that resulted in
generating business relationships or resulted in achieving another
business objective are identified and any third party nodes in
those paths and attributes of those nodes are identified. This
information may be used to select future candidate navigable paths
and to modify a framework for collecting data to generate business
networks. Dynamic criteria may also be used to characterize nodes
or navigable paths in tiers.
[0024] FIG. 1 illustrates a system 100 for determining a business
relationship network 105. A source, such as the source company 101
is interested in targets, such as the target companies 102a-n. A
business relationship prospector 110 determines a business
relationship network 105, including navigable paths 104, between
the source company 101 and the target companies 102a-n from
information from a plurality of sources. For example, the source
company 101 provides information about itself, information about
the target companies 102a-n, and information about third party
nodes 103a-g to the business relationship prospector 110.
Information from other sources may also be gathered. One or more of
the third party nodes 103a-g may provide or exchange business
relationship information with one or more of the target companies
102a-n. Other sources may be used to gather information on the
source company 101, information about the target companies 102a-n,
and information about third party nodes 103a-g. Other sources may
include public or private databases or services gathering and
providing business relationship information.
[0025] The information about the source company 101 provided to the
business relationship prospector 110, for example, includes a list
of employees and link attributes for the employees. Link attributes
include information about an employee that can be used to link the
employee to a target. This may include associations with the third
party nodes 103a-g, familial information related to business, and
any other information that may be relevant to identifying a
business relationship. The source company 101 also provides a list
of the target companies 102a-n and the third party nodes 103a-g to
the business relationship prospector 110. The business relationship
prospector 110 uses the source company information and the
information about the target companies 102a-n and the third party
nodes 103a-g to generate the business relationship network 105 and
to identify the potential via navigable paths 104. Link attributes
may also be collected for the target companies 102a-n and the third
party nodes 103a-g. Also, third party nodes may be identified from
information collected from sources other than the source company
101.
[0026] FIG. 2 illustrates a more detailed diagram of the system
100, according to an embodiment. The system 100 comprises a user
interface 201, the business relationship prospector 110, and a data
store 202. The user interface 201 may include one or more devices
for entering information and receiving information. A user may
enter user information 202 via the user interface 201. The user
information 202 may include search guidance components, such as one
or more targets, constraints for searching for business
relationship information used to generate a business relationship
network for a target, and any other information that is useful for
identifying business relationship information used to generate a
business relationship network. For example, a user from the source
company 101 may input a list of target companies, such as the
target companies 102a-n shown in FIG. 1 and information for the
third party nodes 103a-g and employees at the source company 101.
This information may be used to generate a business relationship
network for each of the target companies 102a-n.
[0027] Constraints are used to focus the search for business
relationship information. For example, a constraint may include
identifying business relationships only with employees of a target
company that have the authority to purchase or influence the
purchase of goods or services provided by a source company. Another
example of a constraint is the maximum number of degrees of
separation that may be used to identify a business relationship.
For example, in many instances, the larger the value of "n" for
n-degrees of separation, the less likely a business relationship
will be able to be established that will achieve a business
objective, such as making a sale. The constraints may be entered
via the user interface 201 and stored in the data store 202 as the
constraints 240.
[0028] Other examples of the constraints 240 may include
constraints for searching the data sources 220 and constraints for
generating a business relationship network. For example, a
constraint may include generating business relationship networks
only identifying potential business relationships with C-suite
executives of the target company 102a and employees of the source
company 101 shown in FIG. 1. Examples of C-suite executives include
chief executive officers, chief financial officers, chief technical
officers, etc. In another example, a constraint may exclude certain
information from being used to generate a business relationship
network. For example, privacy laws or internal, company, privacy
policies may require that certain employee information be kept
confidential, and thus may not be used for determining business
relationships. Another example of a constraint may be a geographic
constraint. For example, a geographic constraint limits the search
to employees of the target company 102a in the greater Washington
D.C. area. The constraints 111 may be provided by the source
company 101 requesting the determination of the business
relationship network 105. The business relationship prospector 110
may generate business relationship networks taking into
consideration the constraints 240.
[0029] The user interface 201 may also be used to output a business
network visualization 203 which is further described with respect
to FIGS. 3-7. The business network visualization 203 is a
visualization of the business network that can quickly be used to
identify navigable paths in the business network. These navigable
paths may be used as a guide to generate business relationships.
The user interface 201 may also be used to output other
information, such as updates of business networks based on newly
collected information or other business relationship
information.
[0030] The search tool 212 performs a global search on the data
sources 220 to identify business relationship information, which
may include any information that may be pertinent to business
relationships between a source and a target. For example, the
search tool 212 searches the data sources 220 for information on
the source company 101, the third party nodes 103a-g and the target
companies 102a-n shown in FIG. 1. A collective knowledge set of
business relationship information is retrieved from the data
sources 220 and stored in the data store 202. The business
relationship prospector 110 uses the collective knowledge set of
business relationship information to generate business relationship
networks, as described in further detail below.
[0031] Conventionally, a user may use a single source, such as
their personal contact list, to contact people to form business
relationships. However, the information in the user's personal
contact list is typically a very limited amount of information, and
many opportunities for forming valuable business relationships may
be missed by relying solely or heavily on the user's personal
contact list. According to an embodiment, the collective knowledge
set may include business relationship information from many
different sources as opposed to a single source to generate a more
complete business relationship network between a source and a
target.
[0032] The global search performed by the search tool 130 may be a
comprehensive search for any information that may be used to
determine the navigable paths 104 between the source company 101
and the target companies 102a-n. However, the global searches may
be constrained, for example, based on the constraints 240. For
example, the global search may be limited to employees at the
target companies 102a-n that have authority to make or influence
purchasing decisions or may be limited to identify information for
indirect business relationships that only include certain third
party nodes that have been previously determined to be successful
for generating business relationships. Other types of constraints
may also be used.
[0033] The business relationship prospector 110 may guide the
search tool 212 to perform the global search. For example, the
source company 101 sends information associated with the source
company 101, such as lists of employees, lists of board members,
company or division names, subsidiaries, etc., a list of the target
companies 102a-n, a list of third party nodes 103a-g, link
attributes, and any other information that may be helpful for
identifying the navigable paths 104. The business relationship
prospector 110 generates a query from the information received from
the source company 101 and sends the query to the search tool 212.
The business relationship prospector 110 may organize and filter
the information received from the source company 101 before sending
the information to the search tool 212. For example, the
information determined to be most relevant for identifying business
relationships is identified and sent to the search tool 212 for
searching the data sources 220. Global searches may be periodically
performed to continually update the data store 202 with new
business relationship information that may be used to determine
business networks and business relationships. The search tool 212
may include a conventional search tool, such as a web crawler or
text search tool. In one embodiment, the search tool 212 is a
knowledge discovery tool described in U.S. patent application Ser.
No. 11/051,745, entitled "Knowledge Discovery Tool Relationship
Generator" and U.S. patent application Ser. No. 11/051,733,
entitled "Knowledge Discovery Tool Extraction and Integration",
both of which are by Bechtel et al. and both of which are
incorporated by reference in their entireties. For example, the
search tool 212 may extract data from multiple sources and/or
organize and store extracted data in a relational database, such as
performed by the knowledge discovery tool described in the
aforementioned patent applications incorporated by reference.
[0034] The data sources 220 may include one or more internal data
sources 222, such as company databases including employee
information or client lists for the source company 101, or external
data sources 223, such as information on the Internet 221 or
external commercial databases. The internal data and the external
data may be structured or unstructured. Internal databases or
external commercial databases that provide business-related
information are examples of structured data, such as lists of board
of directors, executives, etc. Unstructured data may include
information retrieved from the Internet, such as news articles
providing information on the target or the source, information
listed on web sites related to the target or source or third party
nodes, etc.
[0035] The data store 202 stores the business relationship
information retrieved from the data sources 220. The business
relationship information may be organized as profiles by a profile
builder 230. FIG. 2 shows examples of types of profiles stored in
the data store 202, such as employee profiles 231, company profiles
232 and third party profiles 233. Other types of profiles may also
be stored. Each profile may include link attributes and these link
attributes are used to create business relationship networks.
[0036] Also, the constraints 240 and evaluation criteria 241 may be
stored in the data store 202. The evaluation criteria 241 may
include criteria for evaluating business relationship networks and
selecting candidate navigable paths in a business relationship
network that are likely to result in business relationships. The
evaluation criteria may be used to weight candidate paths as an
estimate of the probability that a navigable path can generate a
business relationship or can be used to achieve another business
objective. The evaluation criteria 241 may be static or dynamic.
For example, static evaluation criteria may characterize paths as
first tier, second tier, or third tier, based on predetermined
attributes of third party nodes in the paths. Dynamic criteria may
be generated based on feedback, which includes evaluating navigable
paths from previously-generated business networks. For example,
navigable paths that resulted in generating business relationships
or resulted in achieving another business objective are identified
and any third party nodes in those paths and attributes of those
nodes are identified. This information may be used to select future
candidate navigable paths that are likely to generate a business
relationship or achieve a business objective.
[0037] In addition, a history 242 may be stored in the data store
202. The history 242 includes information regarding successes or
failures of using previously-generated business relationship
networks to generate business relationships.
[0038] The business relationship prospector 110 includes a
visualization module 210, a relationship finder module 211, a user
information module 213, and a feedback module 214. A module may
include only software, only hardware or a combination of hardware
and software. As described above, the business relationship
prospector 110 may guide the search tool 212 to perform the global
search. For example, the relationship finder module 211 of the
business relationship prospector 110 guides the search tool 212.
The relationship finder module 211 may organize and filter
information received from a user, such as targets, third party node
attributes, and other information relevant to the targets and the
source, and use this information to generate a query for the search
tool 212 to perform the global search. Queries for the global
search may be periodically updated and executed. The business
relationship information retrieved from the data sources 220 as the
search results may be stored in the data store 202.
[0039] The relationship finder module 211 may also generate a
business relationship network by mapping the business relationship
information stored in the data store 202 as a plurality of
navigable paths forming the business relationship network between a
source and a target. For example, the relationship finder module
211 searches the business relationship information stored in the
data store 202, including the profiles 231-233, for information
associated with business relationships between the source company
101, the target companies 102a-n and the third party nodes 103a-g
which link the source company 101 to the target companies 102a-n.
The information retrieved from the data store 202 is mapped to
navigable paths. For example, link attributes in the profiles
231-233 are matched to identify navigable paths between the source
company 101 and the target companies 102a-c. The navigable paths
form the business relationship network 105 shown in FIG. 1 between
the source company 101 and the target companies 102a-c. Examples of
mapping are further described with respect to FIG. 3. Also, any
constraints on generating the business relationship network 105 in
the constraints 240 are considered when performing the mapping.
[0040] The relationship finder module 211 may also evaluate the
navigable paths to identify one or more of the paths as candidate
paths most likely to lead to a business relationship between the
source and the target based on the evaluation criteria 241.
Examples of evaluation criteria may include whether a navigable
path includes a third party node that was successfully used to
generate a business relationships, whether the value of "n" for
n-degrees of separation is less than or equal to a predetermined
threshold, whether the navigable path includes a key-decision maker
or a C-suite executive, etc. The navigable paths may be classified
in tiers based on the evaluation criteria. For example, paths in
the highest tier may be candidate paths. In one embodiment, each
node or link in a path is classified to a tier based on attributes
of the node or nodes connecting a link, and the navigable path is
assigned to the tier of the node or link in the path having the
lowest tier. So if all the nodes or links in a navigable path are
tier 2 except for one node or link being in tier 3, the navigable
path is assigned to tier 3. In another example, the tier assignment
for a navigable path may be based on the order of the links and
their tier values. For example, if the first link closest to the
source node is tier 1 and the last link is tier 1, but a middle
link is tier 3, then the navigable path may be assigned tier 1,
because there is a strong likelihood that the first link is the
most significant relationship to be successfully used to form a
business relationship with the target. The feedback module 214 may
be used to determine some of the evaluation criteria 241 used to
identify candidate paths and classify navigable paths to tiers.
Other methods may be used to assign a navigable path to a tier.
[0041] Also, scoring may be used to assign navigable paths to
tiers. For example, a score may be assigned to each link in a
navigable path and/or an entire navigable path based on the
evaluation criteria. Predetermined ranges of scores are assigned to
different tiers. The tiers and scores are representative of a
weighting of the ability to use each navigable path to successfully
achieve a business objective.
[0042] The feedback module 214 in the business relationship
prospector 110 may evaluate navigable paths from
previously-generated business networks to identify information that
may be used to identify navigable paths which are the best
candidates to increase the likelihood that a navigable path may be
used to generate a business relationship between the source and the
target. For example, navigable paths that resulted in generating
business relationships or resulted in achieving another business
objective are identified through feedback. The information
concerning the best candidate paths including the links, third
party nodes, attributes, and any other pertinent information is
used to select the best candidate paths while developing future
business relationship networks. This information may be used to
develop or modify the evaluation criteria 241 for selecting future
candidate navigable paths. Information regarding whether navigable
paths in previously-generated business networks were successful or
unsuccessful may be provided by users or automatically determined
and stored as the history 242. The feedback module 214 may identify
link attributes, information regarding source nodes, links, also
referred to as segments, third party nodes, and target nodes for
successful or unsuccessful navigable paths. This information may be
used in the evaluation criteria 241 or known statistical analysis
may be performed on the information to determine the evaluation
criteria 241. For example, the number of times a specific third
party node was successful or unsuccessful for business development
or the number of degrees of separation for successful business
relationships are determined and used as evaluation criteria for
evaluating future candidate paths.
[0043] Based on an evaluation of previously generated business
relationship networks and the successes or failures of navigable
paths in those networks, the feedback module 214 may identify
attributes for placing third party nodes and other nodes in
different tiers. For example, third party nodes from successful
navigable paths are placed in a higher tier. Some third party nodes
may be labeled as unsuccessful if they were repeatedly unsuccessful
in generating a business relationship or achieving specified
business objectives. These third party nodes may be avoided or
placed in a lower tier. Also, third party nodes that have high
target participation are identified. This may include identifying
third party nodes that have many members which are employees or
high-level employees from the target. In another example, based on
an evaluation of previously generated business relationship
networks and the successes or failures of navigable paths in those
networks, the feedback module 214 determines that at least three
navigable paths should be tried to generate a business relationship
with the target. This information may be presented to the user via
the user information module 213 and the user interface 201. The
feedback module 214 may update or generate evaluation criteria for
the evaluation criteria 241 to reflect the feedback and identified
attributes of nodes.
[0044] The business relationship prospector 110 may use the
analysis of the history 242 performed by the feedback module 214 to
determine business guidance points. The user information module 213
may notify the user of the business guidance points via the user
interface 201, such that the user is operable to follow the
business guidance points to further a business objective. Business
guidance points are business heuristics or other information
determined from feedback, which may be used to determine, select or
create business relationships to achieve business objective.
Examples of business guidance points may include identification and
notification of high target participation third party nodes or
third party nodes that have been successful or unsuccessful for
generating business relationships. The user may use this
information to identify third party nodes to join or to contact, or
to identify third party nodes not to join or not to otherwise
pursue. Similar information may be gathered for source nodes and
target nodes to determine whether these nodes can be used to
successfully generate a business relationship. In another example,
the user information module 213 may notify the user that at least
three navigable paths should be tried to achieve at least a
predetermined percentage of success for generating a business
relationship or business outcome with the target. For example,
based on statistical analysis of the history 242, the feedback
module 213 determines that at least three navigable paths should be
followed to have at least a 50% chance of successfully generating a
business relationship with the target.
[0045] In addition to the information from the feedback module 214,
the user information module 213 may also provide guidance to a user
for information needed to collect business relationship
information. For example, the user information module 213 may
request information about predetermined attributes of employees of
the target company and potential third party nodes. The
predetermined attributes may be helpful in identifying third party
nodes that can be used in navigable paths. Also, the feedback
module 214 may determine the information for guiding the user based
on an evaluation of previously generated business relationship
networks and the successes or failures of navigable paths in those
networks.
[0046] The visualization module 210 generates the business network
visualization 201, which is a visual representation of the business
relationships network for the source and the target. The
visualization module 210 generates the business network
visualization 201 from the mappings determined by the relationship
finder module 211. The relationship finder module 211 maps the
business relationship information stored in the data store 202 as a
plurality of navigable paths forming the business relationship
network. In one embodiment, the mappings are determined by matching
link attributes for the sources, the target and third party nodes.
The mappings are used to form the navigable paths which are
represented in the business network visualization 201. The
navigable paths may include paths for direct and indirect business
relationships. The visual representation may be used to quickly
identify the navigable paths for forming the business
relationships.
[0047] FIGS. 3A-D illustrate examples of navigable paths in a
business relationship network between the source company 101 and
the target company 102a. FIG. 3 also represents an example of
visualizations generated by the visualization module 203 shown in
FIG. 2.
[0048] The source company 101 provides user information to the
business relationship prospector 110 shown in FIG. 2. For example,
the source company 101 provides the user information 202 to the
business relationship prospector 110 via the user interface 201.
The user information 202 may include one or more targets,
constraints for searching for business relationship information
used to generate a business relationship network for a target,
information for the third party nodes 103a-g and for the source
company 101, and any other information that is useful for
identifying business relationship information used to generate the
business relationship network 105. For example, the user
information 202 may include a list of employees for the source
company 101 and link attributes for the employees. The global
searches of internal databases and other data sources may have also
identified the link attributes for the employees. The link
attributes for the employees may be stored in employee profiles.
The global searches and/or information provided by the source
company 101 may also identify information about the target company
102a and the third party nodes 103a-b. Profiles for the third party
nodes 103a-b and the target company 102a may also be compiled from
the global searches and/or information provided by the source
company 101 and stored in the data store 202. The information from
the source company 101, the global searches and other sources form
the collective knowledge set for determining the business
relationship network between the source company 101 and the target
company 102.
[0049] The business relationship prospector 110 generates navigable
paths in a business relationship network from the collective
knowledge set of business relationship information gathered from a
plurality of sources, including the source company 101. FIG. 3A
illustrates an example of all the nodes and links generated from
the collective knowledge set by the business relationship
prospector 110 for a business relationship network. Some of the
links do not form complete navigable paths between the source
company 101 and the target company 102. For example, links 301-304
are not included in any complete navigable paths between the source
company 101 and the target company 102. The business relationship
prospector 110 removes links 301-304 from the business relationship
network, such as shown in FIG. 3B. FIG. 3B shows multiple,
complete, navigable paths between the source company 101 and the
target company 102. The business relationship prospector 110
identifies one or more of the navigable paths shown in FIG. 3B as
candidate paths most likely to lead to a business relationship
between the source company 101 and the target company 102 based on
evaluation criteria, and the candidate paths are shown in FIG.
3C.
[0050] FIG. 3D shows a more detailed example of a business
relationship network between the source company 101 and the target
company 102. In particular, FIG. 3D shows an example of using link
attributes to create navigable paths between the source company 101
and the target company 102.
[0051] The employees and their link attributes for the source
company 101, for example, include senior management employees, such
as John and Mary shown in FIG. 3. Also shown are link attributes
for John and Mary. For example, the link attributes for John
includes a college from which John graduated, a golf club of which
John is a member, and a regional technical counsel of which John is
a member. The link attributes for Mary include a charity of which
Mary is a board member.
[0052] Also, as shown in FIG. 3, the third party node 103a, for
example, is John's college, and the third party node 103b is Mary's
charity. The target company 102a is also shown and employees Bob
and Alice for the target company 102a are shown. For example, Bob
is senior management for the target company 102a and Alice is a
C-suite executive for the target company 102a. Employee profiles
for Bob and Alice include link attributes for Bob and Alice. The
global searches may have identified Bob as an IT manager at the
target company 102a. For example, Bob may have been quoted in an
article mentioning his name, title, and that he works for the
target company 102a. The search tool 212 retrieved the article and
stored the article in the relationship database 112. The article
may have been manually or electronically reviewed to identify Bob
and link attributes for Bob. A global search may also have
retrieved a list of alumni for John's college from the college's
website. Bob is also a graduate from that college. The relationship
finder module 211 generates and stores the profile for Bob. Thus,
Bob's profile indicates that Bob is an IT manager at the target
company 102a and graduated from John's college. A global search may
have identified Alice as a C-suite executive at the target company
102b. Also, a global search may have retrieved a list of board
members for Mary's charity, and Alice is also a board member of the
charity. This information is stored in Alice's profile.
[0053] The relationship finder module 211 of the business
relationship prospector 110 shown in FIG. 2 is operable to map the
business relationship information for the source company 101, the
third party nodes 103a-b and the target company 102a as a plurality
of navigable paths to form the business relationship network
between the source company 101 and the target company 102a. For
example, the relationship finder module 211 matches link attributes
for the source company 101, the third party nodes 103a-b and the
target company 102a to determine the links 310-311 and 320-321 that
form the navigable paths for the business relationship network. In
particular, the links 310-311 and the third party node 103a form
the navigable path between the source company 101 and the target
company 102a, and the links 320-321 and the third party node 103b
form another navigable path between the source company 101 and the
target company 102a.
[0054] In one embodiment, the relationship finder module 211 shown
in FIG. 2 searches the data store 202 for the matching link
attributes between the source company 101 and the target companies
102a-c. For example, the relationship finder module 202 identifies
John and Bob as being alumni of the same college, shown as the
third party node 103a and the links 310-311. The relationship
finder module 202 also identifies Mary and Alice as being board
members of the same charity, shown as third party node 103b and
links 320-321 linking Mary to Alice via the third party node
103b.
[0055] FIG. 4 shows a refined data set 400 which may be generated
by the business relationship finder module 211 to map the navigable
paths. For example, an entry 401 is created in the refined data set
400 for a navigable path between John and Bob. The entry 401
identifies John from the source company 101, Bob from the target
company 102a, link attributes for John and Bob, and any matching
link attributes for an indirect relationship. For Bob and John, the
matching link attribute is alumni of the same college, which is the
third party node 103a in this example. An entry 402 is created for
a navigable path between Mary and Alice. The entry 402 identifies
Mary from the source company 101, Alice from the target company
102b, link attributes for Mary and Alice, and any matching link
attributes for an indirect relationship. For Mary and Alice, the
matching link attribute is being a board member of the same
charity, which is the third party node 103b in this example.
[0056] It will be apparent to one of ordinary skill in the art that
the business relationship prospector 210 may identify navigable
paths for direct business relationships also. In addition,
depending on the amount and quality of business relationship
information collected for the source company 101 and the target
company 102a, many more navigable paths may be identified for the
business relationship network.
[0057] The business relationship prospector 210 is also operable to
identify one or more candidate paths most likely to lead to a
business relationship based on the evaluation criteria 241. For
example, navigable paths in the top two tiers may be considered
candidate paths or navigable paths with only senior management or
C-suite executives are selected in the evaluation criteria. In
another example, direct navigable paths and navigable paths having
third party nodes with high target participation are selected as
candidate paths or navigable paths with n-degrees of separation
where "n" is less than or equal to a threshold. It will be apparent
to one of ordinary skill in the art that other criteria from the
evaluation criteria 241 may be used to select candidate paths.
Also, the business network visualization may include only the
candidate paths or may include some or all of the navigable
paths.
[0058] FIGS. 5A-D illustrate examples of business network
visualizations for a business relationship network. FIGS. 5A-D also
show different layers of the business relationship network wherein
the top layer may represent an overall view of the business
relationship network and the lower layers show portions of the
business relationship network.
[0059] FIG. 5A is the top layer and illustrates navigable paths and
tiers assigned to the navigable paths. The links 501 and 502 and
the charitable organizations form a tier 3 navigable path. Assume
that tier 3 is the highest tier representing a navigable path most
likely to lead to a business relationship between the source
company and the target company. For example, this navigable path is
a tier 3 path because the evaluation criteria 241 shown in FIG. 2
indicate that the charitable organizations have been used multiple
times in previously-generated business relationship networks to
generate successful business relationships and that C-Suite
executives in the target company 101 are individuals that are
likely to make purchase decisions or influence purchase decisions.
These evaluation criteria may be generated by the feedback module
214 shown in FIG. 2 analyzing the success and failures of navigable
paths in past business relationship networks.
[0060] Links 503-504 and the schools shown in FIG. 5A form a tier 2
path. For example, the evaluation criteria 241 shown in FIG. 2
indicate that the schools are moderately successful in generating
business relationships, so this path is a tier 2.
[0061] Links 505-506 and the alliance partners shown in FIG. 5A
form a tier 3 path. For example, the evaluation criteria 241 shown
in FIG. 2 indicate that the alliance partners are less than
moderately successful in generating business relationships so this
path is a tier 1.
[0062] Links 507-508 and the social activities third party node
shown in FIG. 5A also form a navigable path. However, there may not
be sufficient data on the social activities third party node and/or
the employee in the employee base of the target company to assign a
tier to this path. Thus, this navigable path may be labeled
unknown.
[0063] FIG. 5B shows a lower layer to the top layer of the business
relationship network shown in FIG. 5A. For example, the senior
management of the source company includes Bob Franks and Fred
Johnson. The visual representation shown in FIG. 5B also shows the
navigable paths for Bob Franks and Fred Johnson of the senior
management of the source company. The visual representation shown
in FIG. 5B may have been generated in response to the user
selecting senior management and then the drop-down menu for the
senior management listing Bob Franks and Fred Johnson is shown to
provide more detail on those endpoints of the navigable paths.
Other navigable paths from the top layer may not be shown so the
user can focus on the navigable paths for the senior management of
the source company.
[0064] FIG. 5C shows a lower layer to the layer of the business
relationship network shown in FIG. 5B. For example, a user desires
to focus on the navigable path including the links 503-504 and the
schools third party node. The visual representation shown in FIG.
5C provides more detail on the schools third party node. For
example, University of Virginia is the third party node connecting
Bob Franks with a C-suite executive of the target company. The
visual representation shown in FIG. 5C may have been generated in
response to the user selecting the schools third party node and
then a drop-down menu for the schools lists University of Virginia
as the third party node connecting Bob Franks with a C-suite
executive of the target company.
[0065] FIG. 5D shows the employee profile of Bob Franks. For
example, the employee profile lists the tier rating for Bob Franks
or link including Bob Franks as Tier 2 based on evaluation criteria
developed from feedback. The employee profile also lists the target
nodes connected to Bob Franks via a navigable path and their
respective tiers. In this example, Chip Jones or link including
Chip Jones is tier 2 based on evaluation criteria developed from
feedback. The employee profile also lists the link attributes for
Bob Franks, such as employment history, charitable organizations,
civic associations, business associations, volunteer events,
volunteer activities, and schools. This list is not exhaustive, and
more link attributes may be provided in the employee profile. Also,
less link attributes may be provided in employee profiles. Also,
values for the link attributes, such as schools that Bob Franks
graduated from or associations that Bob Franks is a member of may
or may not be determined and shown in the profile depending on the
business relationship information collected for Bob Franks from the
data sources 220.
[0066] FIGS. 5A-D illustrate examples of different layers that may
be shown as visualizations of the business relationship network,
ranging from a comprehensive layer shown n FIG. 5A to a layer
providing detailed node information, such as the employee profile
shown in FIG. 5D.
[0067] FIG. 6 illustrates an example of a business network
relationship visualization including third party nodes determined
to have high target participation. For example, from the business
relationship information collected from the data sources 120, the
business relationship prospector 110 determines that the target
company has employees that are active members of the charitable
organizations, the civic associations and the social associations.
Also, the active members may be employees likely to make or
influence purchase decisions. Thus, these third party nodes are
determined to be high target participation third party nodes. A
user may use this visual representation to quickly identify third
party nodes to join or become an active member thereof to possibly
generate a business relationship. Although not shown, a visual
representation may also be provided to identify low-participation
third party nodes or third-party nodes that have been unsuccessful
for generating business relationships. The source company may avoid
those nodes when attempting to generate a business relationship or
when determining where to allocate resources for business
development.
[0068] In another embodiment, the links connecting the
high-participation third party nodes may not be shown, so a user
may quickly identify the high-participation third party nodes. A
list of the high-participation third party nodes may also be
provided.
[0069] A navigable path in a business relationship may be complex
and may include more than a single third party node between a
source and a target. FIG. 7 illustrates an example of a business
network visualization showing n-degrees of separation for a
navigable path. In this example, there are 2-degrees of separation
between Lisa Cutter, a C-suite executive of the source company, and
Jim Lange, a board member of the target company. For example, both
Lisa Cutter and Shannon Nolty are members of the Congressional Golf
Club. Shannon Nolty and Jim Lange are members of the Burning Tree
Golf Club. Lisa Cutter is connected to Jim Lange via Shannon Nolty
being a member of the Congressional Golf Club and Shannon Nolty
being a member of the Burning Tree Golf Club.
[0070] In addition to showing the n-degrees of separation, FIG. 7
shows that the business relationship prospector 110 is operable to
identify and connect different node layers. For example, a social
association is a type of third party node, and golf clubs are types
of social associations. In this example, specific golf clubs and
their memberships are identified to link the source company and the
target company.
[0071] It will be apparent to one of ordinary skill in the art that
multiple types of third party nodes, such as social associations
and civic associations, may be used to create a navigable path with
n-degrees of separation. In addition, it will be apparent to one of
ordinary skill in the art that the visual representations shown in
FIGS. 5A-D, 6 and 7 may include multiple targets and may show
direct business relationships. Furthermore, navigable paths may
include more than one or two degrees of separation.
[0072] FIG. 8 illustrates a flow chart of a method 800 for
determining a business relationship network, according to an
embodiment. The method 800 is described with respect to FIG. 2 by
way of example and not limitation. The method 800 may be used with
other systems.
[0073] At step 801, the business relationship prospector 110 shown
in FIG. 2 generates a collective knowledge set of business
relationship information from the data sources 120. In one
embodiment, generating a collective knowledge set may include the
business relationship prospector 110 guiding the search tool to
perform global searches of the data sources 220 to collect business
relationship information for one or more sources, one or more third
party nodes and one or more targets. In another embodiment,
generating a collective knowledge set may include receiving data
from a plurality of sources and/or organizing the received data.
Organizing may include storing the data in a format such that the
data can be searched and search results retrieved, such as storing
received data in a database. Received data may be converted to a
format that is searchable. This may include classifying data in
different categories and storing the classified data so it may be
searched for generating profiles. Classification may be performed
manually and/or automatically using machine-learning classifiers or
other known machine-learning technology.
[0074] At step 802, the business relationship prospector 110 maps
the collective knowledge set as navigable paths forming a business
relationship network between a source and a target. For example,
the business relationship prospector 110 matches link attributes of
the source, the target and third party nodes to form navigable
paths for a business relationship network between the source and
the target. The link attributes may be determined from the business
relationship information collected from the data sources 220.
[0075] At step 803, the business relationship prospector 110
identifies one or more navigable paths as candidate paths most
likely to lead to a business relationship between the source and
the target based on the evaluation criteria 241. Examples of
evaluation criteria may include whether a navigable path includes a
third party node that was successfully used to generate a business
relationship, whether the value of "n" for n-degrees of separation
is less than or equal to a predetermined threshold, whether the
navigable path includes a key-decision maker or a C-suite
executive, etc. The navigable paths may be classified in tiers
based on the evaluation criteria. For example, paths in the highest
tier may be candidate paths. The feedback module 214 may be used to
determine some of the evaluation criteria 241 used to identify
candidate paths and classify navigable paths to tiers. The
candidate paths may be provided to a user, for example, via a
display or other output, such that the user can select one or more
of the candidate paths for forming a business relationship with the
target. The weights or tiers of each candidate path may also be
presented or the list of candidate paths may be ordered to aid in
the selection.
[0076] After the business relationship network is generated and the
candidate paths are identified, a user may use one or more of the
candidate paths to form a business relationship with the target.
Using the candidate paths may include forming relationships with
each node or otherwise using each node in a candidate path to form
a business relationship with the target. For example, the user may
contact a node in a candidate path to request a meeting with a next
node in the path until the target is contacted.
[0077] The method 800 may be used to provide a service to a client.
The client may be a user or entity that desires to have the service
performed for forming a business relationship network for the
client. The service may include performing the steps of the method
800 to identify candidate paths that the client may follow to form
a business relationship with a target. Also, the client may be
presented with a plurality of candidate paths such that the client
can select one or more of the candidate paths to develop a business
relationship with the target.
[0078] FIG. 9 illustrates an exemplary block diagram of a computer
system 900 that includes one or more processors, such as processor
902, providing an execution platform for executing software, for
example, including at least some of the steps illustrated in the
method 800 and other steps described herein. The software may also
include the modules described in FIG. 2. The processor 902 may also
execute an operating system (not shown) for executing the software
in addition to performing operating system tasks. The computer
system 900 also includes a main memory 904, such as a Random Access
Memory (RAM), where software may be resident during runtime, and
mass storage 909. The mass storage 909 may include one or more hard
disk drives and/or a removable storage drive. Applications and
resources may be stored in the mass storage 909 and transferred to
the main memory 904 during run time. The mass storage 909 may also
include ROM (read only memory), EPROM (erasable, programmable ROM),
EEPROM (electrically erasable, programmable ROM). Components of the
computer system 900 may communicate via a bus 909.
[0079] A network interface 919 is provided for communicating with
other computer systems. For example, the business relationship
prospector 110 shown in FIGS. 1 and 2 may communicate with the
source company 101 and a user through a network using the network
interface 919. The user interface 202 shown in FIG. 2 may be
provided using I/O devices 916, such as a display, keyboard, mouse,
etc. The computer system 900 is a simplified example of a platform.
It will be apparent to one of ordinary skill in the art that the
other components may be added or components may be removed as
needed.
[0080] One or more of the steps of the method 800 and other steps
described herein and software described herein may be implemented
as software embedded or stored on a computer readable medium, such
as the main memory 904 or the mass storage 909, and executed by the
processor 902. The steps may be embodied by a computer program,
which may exist in a variety of forms both active and inactive. For
example, there may exist as software program(s) comprised of
program instructions in source code, object code, executable code
or other formats for performing some of the steps when executed.
Any of the above may be stored on a computer readable medium, which
include storage devices and signals, in compressed or uncompressed
form. Examples of suitable computer readable storage devices
include conventional computer system RAM (random access memory),
ROM (read only memory), EPROM (erasable, programmable ROM), EEPROM
(electrically erasable, programmable ROM), and magnetic or optical
disks or tapes. Examples of computer readable signals, whether
modulated using a carrier or not, are signals that a computer
system hosting or running the computer program may be configured to
access, including signals downloaded through the Internet or other
networks. Concrete examples of the foregoing include distribution
of the programs on a CD ROM or via Internet download. In a sense,
the Internet itself, as an abstract entity, is a computer readable
medium. The same is true of computer networks in general. It is
therefore to be understood that those functions enumerated herein
may be performed by any electronic device capable of executing the
above-described functions.
[0081] What has been described and illustrated herein are examples
of the systems and methods described herein along with some of
their variations. The terms, descriptions and figures used herein
are set forth by way of illustration only and are not meant as
limitations. Those skilled in the art will recognize that many
variations are possible within the spirit and scope of these
examples, which intended to be defined by the following claims and
their equivalents in which all terms are meant in their broadest
reasonable sense unless otherwise indicated.
* * * * *