A restaurant service system for assessing the accuracy of estimated delivery time provided by a restaurant includes an order server, a restaurant server, a service server, and an assessment server. Each of the servers includes a server software application. The order server software application collects a set of orders from a set of diner devices. The restaurant server software application retrieves an estimated delivery time for each order in the set. The service server software application determines an order actual delivery time for at least one order in the set. The assessment server software application determines an accuracy measure of estimated delivery time for the restaurant.

Methods, apparatuses, and computer program products are described herein that are configured to be embodied as a benchmarking service. In an example, an apparatus is configured to access input data, wherein the input data is representative of a current project; parse the input data to generate one or more input project units; extract one or more features from the one or more input project units, wherein the features are representative of at least one of project statistics, project bugs, project releases, project documentations, and organization data; receive a benchmarking model, wherein the benchmarking model was derived using a historical data set; and generate an output based on the benchmarking model and the one or more features, wherein the output is configured to provide an evaluation of the current project in the form at least one of a score and one or more recommendations.

A system and method for efficiently responding to a query. The method comprises generating a lowest level data layer, wherein the lowest level data layer is a common dataset that can be served by a plurality of higher level data layers; generating, based on the lowest level data layer, at least one dataset, wherein each generated dataset is one of the plurality of higher level data layers, wherein each higher level data layer is accessed more rapidly than all lower level data layers; searching, in at least one of the generated data layers, for data needed to generate a response to the query; determining, based on the search, at least one data layer from which the response can be generated, wherein the determined at least one data layer includes the highest level data layer from which the response can be generated; and generating, based on data of the determined at least one data layer, a response to the query.

In operational methodology and a software package or other computer enabled business method, which enables users to apply the method and practice. A wide variety of means for identifying, evaluating and mitigating risk and performance factors within an organization are also provided.

A computer-implemented method includes a method comprising using at least one hardware processor to: receive a plurality of data from a plurality of data sources; standardize the plurality of data; tag the standardized plurality of data with one or more companies; train a prediction model to predict a metric for each of the one or more companies based on the standardized plurality of data tagged with that company and historical measurements for that company; and apply the prediction model to new data to predict the metric for at least one of the one or more companies.

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.

A contextual lead generation in an automated communication link establishment and management system may store information related to sales calls. The system may identify strengths and weaknesses of a sales representative. The system may provide training content to the sales representative in real time base on the identified strengths and weaknesses.

An apparatus (10) for generating benchmarking metrics of current operational workflow performance of a hospital department includes at least one electronic processor (20) programmed to: generate a department profile (34) identifying resources of the hospital department including at least an active medical equipment inventory and a personnel profile; retrieve current statistics for the hospital department including at least one of patient arrival timeliness, patient no-show, and emergency department (ED) arrival statistics; compute values of one or more key performance indicator (KPI) metrics (40) for the current statistics; generate an executable workflow model (44) for workflow processes of the hospital department including temporal aspects of the workflow processes, the workflow model having variables representing at least patient arrival timeliness, patient no-show, and ED arrival; simulate a best case scenario (50) by executing the workflow model on inputs including the department profile and best case values for the variables of the workflow model and compute values of the one or more KPI metrics for the simulated best case scenario; simulate a worst case scenario (52) by executing the workflow model on inputs including the department profile and worst case values for the variables of the workflow model and compute values of the one or more KPI metrics for the simulated worst case scenario; and output, on at least one display device (24), the values of the one or more KPI metrics computed for the simulated best case scenario, the values of the one or more KPI metrics computed for the simulated worst case scenario, and the values of the one or more KPI metrics computed for the current statistics.

A dashboard having a plurality of selectable hierarchical dashboard levels is displayed, where a higher dashboard level of the dashboard displays a Key Performance Indicator (KPI) that represents an aggregation of a plurality of related KPI's at a next lower dashboard level. The dashboard displays service cases that are related to one or more of the building system components of the building. The service cases displayed at the next lower dashboard level are identified as having a negative impact on at least one of the plurality of related KPI's displayed at the next lower dashboard level and the service cases displayed on the higher dashboard level represent an aggregation of the service cases displayed at the next lower dashboard level.

Various embodiments described herein relate to performance assurance modeling for a portfolio of assets. In this regard, a request to generate one or more performance assurance insights related to one or more assets is received. The request includes a fault descriptor describing one or more faults associated with the one or more assets. In response to the request, a first risk level associated with the one or more faults is determined based on the fault descriptor and asset data associated with the one or more assets. Additionally, in response to the request, a second risk level associated with the one or more faults is generated based on one or more predetermined relationships between faults and asset performance indicator thresholds. The one or more performance assurance insights are then generated based on a comparison between the first risk level and the second risk level.