TECHNICAL FIELD

The present disclosure relates to the field of business management. In particular, it relates to use of a conversational user interface for obtaining information related to the business.

BACKGROUND

Business data related to supply chain management is often very detailed and complicated to understand or visualize. The total amount of data available is often far too large for one person to read all of it. Since there is so much data, choosing the relevant features from the data can be time-consuming and difficult.

Presenting the data poses a challenge since typical presentation methods (e.g. spreadsheets, charts) show raw numbers, whereas insights are left up to the reader to find. Furthermore, visualizations and graphs require trained skills to interpret meaningful results.

Therefore, reporting up-to-date, aggregated business data in an easily-digestible format would greatly improve efficiency in making business decisions to correct and/or improve the supply chain.

Currently, there are three main approaches to communicating aggregate business data: paper reports, phone or email communication, and interactive dashboards.

Paper reports have the problem that they are inflexible. Data cannot be filtered, modified or explored further. If more details are required or requested, a new report must be created. This uses up valuable time and financial resources. Often too much data is provided in these reports such that irrelevant details obscure important aspects and insights. However, if too little data is provided, the executive may miss out on critical information. Also, the data provided in a paper report is not live, i.e., it is not being updated in real-time. As such, the most up-to-date business metrics will not be available, thereby hindering decision-making processes. Furthermore, the data is often represented in the form of spreadsheets, graphs and other visualizations that require trained skills to gain insight. Learning to interpret these results to gain meaningful knowledge of the business state is a time-consuming and challenging process.

Phone or email communication can address the problem of up-to-date metrics. However, it comes at the cost of using human resources. For example, data scientists that report such information may not always be available for conversations and the results may be delayed.

Interactive dashboards are a popular approach since they are up-to-date and can be filtered or modified. However, these do not solve the issue of complicated visualizations and may require even more training to comprehend. Dashboards also introduce a new challenge of fitting all the relevant information on the screen of a device. This approach also does not allow the user to multitask while they consume their business metrics.

U.S. Pat. No. 9,977,808 B2 discloses intent based real-time analytical visualizations. Natural language processing is used to generate an analytical requirement statement from a received requirement statement (that is used to generate visualization analysis). The generated visualization analysis is displayed on a computer generated graphical user interface (GUI).

US2014351232 A1 discloses a method for accessing enterprise data using a natural language user interface. A mobile application converts voice data to text data, which is then used to generate a command for use by a business analytics engine or by an enterprise search engine. In either case, results are presented to the user on a user interface.

U.S. Pat. No. 9,996,531 B1 discloses methods, mediums, and systems for managing a conversation. The system includes a computer-implemented input interface for receipt of an input comprising information in natural language; a dialog manager configured to determine an intent of the input, determine information to fulfill the intent; a conversational understanding document that documents the intent and the identified information; and an output interface that forwards the conversational understanding document towards a task completion handler separate and distinct from the dialog manager.

US20180012163 discloses a method and system for providing sales information and insights through a conversational interface. The method and system processes data from data sources and analyzes the data to provide suggestions on how to improve the performance of the business.

U.S. Ser. No. 10/042,882 B2 discloses an analytics program interface for retrieving analytics data from a data sources. The method includes receiving a request to retrieve analytics data, issuing a first query for analytics data from a first data source; and issuing a second query for data from a second data source different from the first data source. The method can include providing the analytics data and the data.

It is thus advantageous to provide a conversational tool that is flexible, always available, up-to-date, easy to understand and provides only relevant information such as KPIs, business insights, anticipate future inquiries (i.e. requests for future data/metrics), and initiate collaboration to address problems in the supply chain.

SUMMARY

In accordance with one embodiment, a business analytics conversational tool comprising: a device comprising a communication channel, a natural language processor (NLP), a fulfillment application program interface (F-API), a database application program interface (D-API), and a business management database; wherein: the NLP receives a user-input from a user through the communication channel; the NLP deduces an intent of the user-input; the NLP communicates the intent to the F-API; the F-API communicates a request for data associated with the intent to the database via the D-API; the D-API communicates the data associated with the intent to the F-API; the F-API converts the data associated with the intent to conversational form and sends the conversational form for voice output through the communication channel.

In accordance with another embodiment, one or more computer-readable storage medium for executing a method for accessing business data and reporting an analysis thereof, the method comprising: receiving an oral query via a communication channel located in a device; converting the oral query to a command for communicating with a business database, performing a search and/or analysis of data in the database based on the command; retrieving the search and/or analysis results; and transmitting the search and/or analysis result in conversational form for voice output to the communication channel.

Disclosed herein is a conversational business tool that comprises a Natural Language Processing Model that is trained on business conversations; intelligent analytics to prioritize business insights; and data-driven speech that delivers insights in a conversational manner.

The conversational business tool may be integrated with a supply chain planning platform. A platform that provides rapid processing of business metrics and scenario simulations can be used to provide up-to-date analysis in a natural conversational flow when integrated with the conversational business tool. An example of a supply chain planning platform that provides rapid processing of business metrics and scenario simulations is disclosed in U.S. Pat. Nos. 7,610,212 B2; 8,015,044 B2; 9,292,573 B2; and U.S. Pub. No. 20130080200A1—all of which are incorporated herein by reference. Such a “rapid” platform is heretofore referred to as a “rapid response” supply chain planning platform. Such a conversation business tool can compare forecasts of customizable KPIs to planned targets using the scenario simulation functionality disclosed in U.S. Pat. Nos. 7,610,212 B2; 8,015,044 B2; 9,292,573 B2; and U.S. Pub. No. 20130080200A1 (all of which are incorporated herein by reference).

The foregoing and additional aspects and embodiments of the present disclosure will be apparent to those of ordinary skill in the art in view of the detailed description of various embodiments and/or aspects, which is made with reference to the drawings, a brief description of which is provided next.

