The present application generally relates to computer systems and more particularly to computer systems that are adapted to accurately and/or automatically provide network status insight information for an enterprise.
An enterprise, such as a business corporation, may utilize remote employees (e.g., employees who “work from home) that access centralized servers or cloud services via networks. There are various potential problems associated with such access that can pose substantial risks to the enterprise. For example, Internet Service Provider (“ISP”) network outages, electric power outages (e.g., associated with local weather events), problems with an employee's local router (e.g., resulting from other members of the household streaming data), etc. can all disrupt an employee's ability to work remotely. These risks can be substantial, especially when a large number of employees are working remotely (e.g., during a widespread health crisis).
It can be difficult to manually and accurately predict a level of risk for a particular enterprise. Similarly, it can be difficult to analyze and respond to problems in substantially real time—especially when there are a substantial number of remote employees. For example, the greatest new risk for remote worker enablement during a pandemic response may be the ability of the enterprise to successfully and consistently connect to systems to perform needed business functions. Primary among these concerns may be the ability of local ISPs to maintain a level of service to enable remote work.
It would be desirable to provide systems and methods to accurately and/or automatically provide network status insight information in a way that provides fast and accurate results. Moreover, the network insight information should be easy to access, understand, interpret, update, etc.
According to some embodiments, systems, methods, apparatus, computer program code and means are provided to accurately and/or automatically provide network status insight information in a way that provides fast and accurate results and that allow for flexibility and effectiveness when responding to those results.
Embodiments may be associated with a network status insight system implemented via a back-end application computer server. A network provider data store may contain electronic records, each electronic record representing a network provider of an enterprise. An enterprise data store may contain electronic records, each electronic record representing a remote analysis entity of the enterprise (e.g., an employee or worker). The computer server may receive, from the enterprise data store, information about analysis entities of the enterprise and, from the network provider data store, information about networks used by the enterprise. The computer may also receive, from a third-party outage detector platform information about outages associated with the enterprise (e.g., network outages and/or power outages). A network status algorithm may then be applied to correlate the received information to generate enterprise network status results (e.g., for display on an insight dashboard and/or a risk assessment prediction for the enterprise).
Some embodiments comprise: means for receiving, at a computer processor of a back-end application computer server from an enterprise data store, information about analysis entities of the enterprise, wherein the enterprise data store contains electronic records, each electronic record representing a remote analysis entity of the enterprise and including, for each analysis entity, an electronic record identifier and a set of analysis entity attribute values; means for receiving, from a network provider data store, information about networks used by the enterprise, wherein the network provider data store contains electronic records, each electronic record representing a network provider of an enterprise and including, for each network provider, an electronic record identifier and a set of network attribute values; means for receiving, from a third-party outage detector platform, information about outages associated with the enterprise; means for applying a network status algorithm to correlate the information about analysis entities of the enterprise, the information about networks used by the enterprise, and the information about outages associated with the enterprise to generate enterprise network status results; and means for arranging to output an indication of the enterprise network status results through a communication port and interactive user interface displays, including the enterprise network status results, via a distributed communication network.
In some embodiments, a communication device associated with a back-end application computer server exchanges information with remote devices in connection with an interactive graphical user interface. The information may be exchanged, for example, via public and/or proprietary communication networks.
A technical effect of some embodiments of the invention is an improved and computerized way to accurately and/or automatically provide network status insight information in a way that provides fast and accurate results. With these and other advantages and features that will become hereinafter apparent, a more complete understanding of the nature of the invention can be obtained by referring to the following detailed description and to the drawings appended hereto.
Before the various exemplary embodiments are described in further detail, it is to be understood that the present invention is not limited to the particular embodiments described. It is also to be understood that the terminology used herein is for the purpose of describing particular embodiments only, and is not intended to limit the scope of the claims of the present invention.
In the drawings, like reference numerals refer to like features of the systems and methods of the present invention. Accordingly, although certain descriptions may refer only to certain figures and reference numerals, it should be understood that such descriptions might be equally applicable to like reference numerals in other figures.
The present invention provides significant technical improvements to facilitate data analytics associated with network insight information. The present invention is directed to more than merely a computer implementation of a routine or conventional activity previously known in the industry as it provides a specific advancement in the area of electronic record analysis by providing improvements in data leveraging to identify network insight risk factors, identify the effect of these network insight risk factors on outcomes, and identify network insight risk mitigation strategies to improve outcomes. The present invention provides improvement beyond a mere generic computer implementation as it involves the novel ordered combination of system elements and processes to provide improvements in data leveraging to identify network insight risk factors. Some embodiments of the present invention are directed to a system adapted to automatically analyze network status records, aggregate data from multiple sources, automatically identify network insight risk drivers, automatically identify how these network insight risk drivers might affect insurance claim outcomes, and/or automatically provide network insight risk mitigation strategies that improve enterprise responses. Moreover, communication links and messages may be automatically established, aggregated, formatted, etc. to improve network performance (e.g., by reducing an amount of network messaging required to correct an existing problem).
The back-end application computer server 150 and/or the other elements of the system 100 might be, for example, associated with a Personal Computer (“PC”), laptop computer, smartphone, an enterprise server, a server farm, and/or a database or similar storage devices. According to some embodiments, an “automated” back-end application computer server 150 (and/or other elements of the system 100) may facilitate the automated access and/or update of electronic records in the historical network status data store 110. As used herein, the term “automated” may refer to, for example, actions that can be performed with little (or no) intervention by a human.
As used herein, devices, including those associated with the back-end application computer server 150 and any other device described herein, may exchange information via any communication network which may be one or more of a Local Area Network (“LAN”), a Metropolitan Area Network (“MAN”), a Wide Area Network (“WAN”), a proprietary network, a Public Switched Telephone Network (“PSTN”), a Wireless Application Protocol (“WAP”) network, a Bluetooth network, a wireless LAN network, and/or an Internet Protocol (“IP”) network such as the Internet, an intranet, or an extranet. Note that any devices described herein may communicate via one or more such communication networks.
The back-end application computer server 150 may store information into and/or retrieve information from the historical network status data store 110 and/or the network provider data store 120. The data stores 110, 120 may be locally stored or reside remote from the back-end application computer server 150. As will be described further below, the historical network status data store 110 may be used by the back-end application computer server 150 in connection with an interactive user interface to access and update electronic records. Although a single back-end application computer server 150 is shown in
The back-end application computer server 150 may analyze information from enterprise data 130 (e.g., a Human Resources (“HR”) department computer system), an outage detector 132 (e.g., adapted to detect network or power outages), and/or a network provider 134 (e.g., either directly or via the network provider data store 120 as illustrated in
Note that the system 100 of
At S210, a back-end application computer server may receive, from an enterprise data store, information about analysis entities of the enterprise. The enterprise data store may contain, for example, electronic records, each electronic record representing a remote employee of the enterprise and including, for each employee, an electronic record identifier and a set of employee attribute values. Examples of employee attribute values might include an employee identifier, an employee name, an employee status (e.g., online or offline), a network service provider, a communication address (e.g., an IP address, telephone number, etc.), location information (e.g., a latitude and longitude, a ZIP code, a home postal address), etc.
At S220, the system may receive, from a network provider data store, information about networks used by the enterprise. The network provider data store may contain, for example, electronic records, each electronic record representing a network provider of an enterprise and including, for each network provider, an electronic record identifier and a set of network attribute values. The network attribute values might include, for example, a network identifier, a network status, a network address (e.g., an IP address, a Media Access Control (“MAC”) address, etc.), location information (e.g., a latitude and longitude, a ZIP code, an ISP postal address), a status date and time, etc.
At S230, the system may receive, from a third-party outage detector platform, information about outages associated with the enterprise. As used herein, the phrase “third-party” may refer to, for example, a party independent of the system, the enterprise, and the network provider. According to some embodiments, the third-party outage detector platform comprises a network outage detector platform. According to other embodiments, the third-party outage detector platform comprises a power outage detector platform. In still other embodiments, the back-end application computer server receives information from both a network outage detector platform and a power outage detector platform.
At S240, the back-end application computer server may apply a network status algorithm to correlate (1) the information about analysis entities of the enterprise (e.g., employees or workers), (2) the information about networks used by the enterprise, and (3) the information about outages associated with the enterprise to generate enterprise network status results. Note that the back-end application computer server might also receive crowdsourced information from at least one crowdsourcing platform. For example, it might be detected that many employees in a particular area are calling or texting an enterprise IT department to complain that the “Internet is down.” The system may then use this crowdsourced information to generate the enterprise network status results. As used herein, the term “crowdsourced” might refer to, for example, information that was obtained using the services of a relatively large number of people, either paid or unpaid, via a communication network.
At S250, the system may arrange to output an indication of the enterprise network status results through a communication port and interactive user interface displays, including the enterprise network status results, via a distributed communication network. The interactive user interface displays might comprise insight dashboard displays that include, for example, map data, employee location data, network status data, power outage data, network drop counts, graphical indications of drop groupings, heat map data, filter conditions, offshore data, etc.
In some embodiments, the network status algorithm comprises a ML or Artificial Intelligence (“AI”) algorithm trained with historical network status information. For example, the enterprise network status results might be associated with a risk assessment prediction for the enterprise (e.g., how likely is it that the enterprise will see ten percent of all employees unable to access information during the next twelve months?). The risk assessment prediction might be performed, for example, by an insurance provider during an underwriting process. In some embodiments, the underwriting process is associated with a Business Interruption (“BI”) insurance policy for the enterprise. Moreover, results of a risk analysis (or future network insights) might be used as feedback to improve the ML or AI algorithm such that the system may automatically adapt to changing conditions.
The data analyzed by the system may then be presented on a Graphical User Interface (“GUI”). For example,
Thus, embodiments may provide remote worker connectivity and power outage real-time analytic solutions. Both analytic solutions might use in-house designed algorithms to combine enterprise data, enterprise machine-generated data, and third-party data to provide a real-time analysis of risks related to reliability and performance of major ISPs (in both the US and abroad) and power utility companies. Also, the solutions may generate historical datasets that can be used by the insurance industry for a ML analysis of reliability and risks related to ISPs and power utility companies
A remote worker connectivity analytic solution might combine Virtual Private Network (“VPN”) machine generated data, enterprise data, and third-party data (outage detectors, map services, etc.) to provide a real time analytics. For example, a first algorithm may find a correlation between a VPN (used by enterprise frontline teams and business essential personnel) connectivity drops and network outage detector (ISP and Internet backbone) failures. For example, an enterprise employee who was on a call with a customer may have experienced a connectivity drop that resulted in loss of potential business. The employee works from her home office in Avon, CT and uses ISP “Provider A.” The connectivity was dropped at 10:15 AM on Nov. 15, 2024. At the same time, several non-enterprise Provider A customers who also live in Avon, Conn. reported problems between 10 AM and 11 AM on the same date. The algorithm may call multiple Restful APIs from multiple third-party vendors and combine data with corporate databases to find this correlation in real-time and mark that incident as potentially ISP/backbone failure related.
As another example, a second algorithm may provide an ability to analyze time series (change connectivity status hour-by-hour for the last 24 hours) that can provide users with additional insights, for example connectivity was OK for all Provider A users located in Hartford, Conn., but starting at 9:30 AM a significant number of users experienced service interruption which may point to a cut fiber cable, or backbone problem, or power outage, or local ISP equipment problem.
As still another example, a third algorithm may provide an ability for users to identify a home Internet or router bandwidth and capacity problem. For example, a claim handler who works from his home office in Florida might share Internet bandwidth with his wife (who also works from home) and their teenage children (who play online games). The algorithm might identify such cases by displaying a larger bubble on a dashboard for users who have larger number of VPN connectivity drops per hour over an extended period of time.
Note that dashboard displays and network insight algorithms may be developed in a number of different ways. For example,
The computer server 560 may interface with an Application Programming Interface (“API”) manager, a JavaScript Object Notation (“JSON”) parser, a scheduling controller, and a notification manager 564, HR and other corporate data 566, and a Software Query Language (“SQL”) database 568. The architecture 500 may support various on-premises environment 550 components, such as those associated with compliance 570, insurance claims 572, sales 574, business recovery operation 576, operations 578, IT support 580, a service desk 582, etc.
Note that embodiments may utilize any number of various network insight dashboard displays. For example,
Other embodiments may provide power outage analytic solutions and/or data mining for real time analysis. For example, a power outage analytic solution may use enterprise HR data, Configuration Management DataBase (“CMDB”) information, IT data, and third-party data to provide a real time analytics. A power outage solution might, for example, provide a real time view of employees impacted by power outages classified by company hierarchy, job, and/or business essential function classifications. For example,
There are other ways to display the information described herein. For example,
Note that the displays and devices illustrated herein are only provided as examples, and embodiments may be associated with any other types of user interfaces. For example,
Many of the embodiments described herein are associated with remote employees of an enterprise. Note, however, that embodiments may be associated with other types of analysis entities associated with an enterprise. For example,
The embodiments described herein may be implemented using any number of different hardware configurations. For example,
The processor 1810 also communicates with a storage device 1830. The storage device 1830 may comprise any appropriate information storage device, including combinations of magnetic storage devices (e.g., a hard disk drive), optical storage devices, mobile telephones, and/or semiconductor memory devices. The storage device 1830 stores a program 1815 and/or a network insight risk evaluation tool or application for controlling the processor 1810. The processor 1810 performs instructions of the program 1815, and thereby operates in accordance with any of the embodiments described herein. For example, the processor 1810 may apply a network status algorithm to correlate received information to generate enterprise network status results (e.g., for display on an insight dashboard and/or a risk assessment prediction for the enterprise).
The program 1815 may be stored in a compressed, uncompiled and/or encrypted format. The program 1815 may furthermore include other program elements, such as an operating system, a database management system, and/or device drivers used by the processor 1810 to interface with peripheral devices.
As used herein, information may be “received” by or “transmitted” to, for example: (i) the back-end application computer server 1800 from another device; or (ii) a software application or module within the back-end application computer server 1800 from another software application, module, or any other source.
In some embodiments (such as shown in
Referring to
The network provider identifier 1902 may be, for example, a unique alphanumeric code identifying a service that is provide network connectivity for workers of an enterprise. The employee identifier 1904 might identify the worker, including, for example, a worker location. The date and time 1906 might indicate when the status 1908 was updated (e.g., if the status 1908 is network down or network up). The power outage indication 1910 might, according to some embodiments, overlay public utility data over the network status data.
Thus, embodiments may provide an automated and efficient way of mining network insight data (e.g., associated with various insurers, network providers, third-parties, etc.) to identify network insight risk factors and for developing network insight risk mitigation strategies in a way that provides fast and accurate results. Embodiments may also provide an ability to access and interpret data in a holistic, tactical fashion. According to some embodiments, the system may be agnostic regarding particular web browsers, sources of information, etc. For example, information from multiple sources (e.g., an internal insurance policy database and an external data store) might be blended and combined (with respect to reading and/or writing operations) so as to appear as a single “pool” of information to a user at a remote device. Moreover, embodiments may be implemented with a modular, flexible approach such that deployment of a new system for an enterprise might be possible relatively quickly.
The following illustrates various additional embodiments of the invention. These do not constitute a definition of all possible embodiments, and those skilled in the art will understand that the present invention is applicable to many other embodiments. Further, although the following embodiments are briefly described for clarity, those skilled in the art will understand how to make any changes, if necessary, to the above-described apparatus and methods to accommodate these and other embodiments and applications.
Although specific hardware and data configurations have been described herein, note that any number of other configurations may be provided in accordance with embodiments of the present invention (e.g., some of the information associated with the displays described herein might be implemented as a virtual or augmented reality display and/or the databases described herein may be combined or stored in external systems). Moreover, although embodiments have been described with respect to particular types of insurance policies, embodiments may instead be associated with other types of insurance policies in additional to and/or instead of the policies described herein. Similarly, although certain attributes were described in connection some embodiments herein, other types of attributes might be used instead.
The present invention has been described in terms of several embodiments solely for the purpose of illustration. Persons skilled in the art will recognize from this description that the invention is not limited to the embodiments described, but may be practiced with modifications and alterations limited only by the spirit and scope of the appended claims.