Modeling, simulation, and predictive analysis

1. A method, comprising:

providing executable instructions to a processor of a server from a non-transitory computer-readable storage medium causing the processor to perform operations comprising:

modeling activity of a physical environment representing a customer traffic flow and resource utilization as a modeled physical environment that represents physical resources and a physical layout of the physical resources for the physical environment, wherein the modeled physical environment comprises available physical resources, types of physical resources, capacity of the types of physical resources, and known layout patterns of the physical resources within the physical environment;

receiving utilization metrics for customer traffic flow within the physical environment and linking the utilization metrics to given known layout patterns associated with the modeled physical environment;

wherein the utilization metrics comprise seating utilization, employee utilization, customer traffic flow rates, and the corresponding known layout patterns deployed for the physical environment when the utilization metrics were captured;

wherein the customer traffic flow rates comprise specific patterns for a given day of a week and a given calendar day within a given period of time;

wherein the physical resources comprise a total number of available tables, table capacity for each table, a total number of available chairs, and types of the tables;

wherein each given model is associated with a specific physical layout for the physical resources and that given model's corresponding linked utilization metrics;

simulating, by a simulator, anticipated activity within the modeled physical environment using the simulated operational data that changes a given rate associated with the customer traffic flow and using the given known layout patterns for the physical resources of the modeled physical environment, wherein the simulator processes a Stochastic algorithm trained on different random sets of operational data with resulting averages for the random sets of operational data measured against observed operational data associated with observed customer wait times, observed staffing, and observed profitability; and

providing a predictive result based on simulating the anticipated activity with the simulated operational data using the Stochastic algorithm;

providing with the predictive result a specific one of the known layout patterns of the modeled physical environment based on the anticipated activity and suggested changes to staffing, wherein the specific one of the known layout patterns includes a change for the physical environment and different allocations of the physical resources from what was currently present in the physical environment that optimizes anticipated utilization metrics for the anticipated activity within the physical environment;

providing an interface that renders a visualization of a playback of a given set of operational data for a given activity of a given customer traffic flow with a given physical layout having given allocations of physical resources and illustrating expected or known utilization metrics within the visualization, wherein the visualization during the playback visually depicts corresponding customer wait times, corresponding customer throughout, corresponding utilization rates, and corresponding profitability for the given physical layout having the given allocations of the physical resources;

visually presenting the visualization within the interface;

receiving a stop instruction from the interface;

stopping the visualization responsive to the receiving of the stop instruction;

receiving a change associated with the given set of operational data for the given customer traffic flow with the given physical layout having the given allocations;

visually presenting a second visualization within the interface that illustrates predictive changes to the expected or known utilization metrics with the change along with additional suggested changes to staffing; and

continuously iterating back to the modeling and the receiving of the utilization metrics at preconfigured intervals of time by gathering and monitoring current operational data, creating a dynamic feedback loop that processes changes to the modeled physical environment based on current traffic flow in a given interval and current utilization metrics in the given interval along with updated linkages to a current corresponding known layout pattern.

2. The method of claim 1 , wherein modeling further includes modeling types for each of the physical resources present within the physical layout.

3. The method of claim 1 , wherein modeling further includes modeling the activity for a configured period of time.

4. The method of claim 1 , wherein modeling further includes dynamically adjusting in real time models for the physical environment based on changes detected in the activity.

5. The method of claim 1 , wherein modeling further includes generating models for the activity, each model representing a unique pattern of activity and set of metrics for the physical environment.

6. The method of claim 1 , wherein simulating further includes automatically generating the anticipated activity based on real-time activity detected in the physical environment.

7. The method of claim 6 , wherein automatically generating further includes generating the anticipated activity by matching a pattern detected in a portion of the real-time activity.

8. The method of claim 1 , wherein generating further includes receiving the anticipated activity as input from an operator through the interface.

9. The method of claim 1 , wherein providing the predictive result further includes providing the predictive result to an interface being operated by an operator over a network connection.

10. The method of claim 1 , wherein providing the predictive further includes providing with the predictive result proposed changes to some of the activity for a different predictive result.

11. A server, comprising:

a hardware processor;

non-transitory computer-readable storage medium having executable instructions representing as a site optimizer;

a site optimizer when executed by the hardware processor from the non-transitory computer-readable storage medium cause the hardware processor to:

obtain the executable instructions for the site optimizer;

process the executable instructions to perform processing comprising:

generating models for activity and metrics of a physical environment, wherein the activity associated with customer traffic flow and resource utilization during the customer traffic flow, each model including a specific physical layout pattern of physical resources for the physical environment, and specific allocations of the physical resources based on types of physical resources within the specific physical layout pattern along with utilization metrics for the physical resources with the corresponding model, wherein the utilization metrics comprise seating utilization, employee utilization, customer traffic flow rates, and the modeled physical environment with specific physical layout pattern of particular physical resources deployed for the physical environment when the utilization metrics were captured, wherein the customer traffic flow rates comprise specific patterns for a given day of a week and a given calendar day within a given period of time;

wherein the physical resources comprise a total number of available tables, table capacity for each table, a total number of available chairs, and types of the tables;

simulating, by a simulator, changes for a proposed activity in the models using simulated operational data, wherein the simulator processes a Stochastic algorithm trained on different random sets of operational data with resulting averages for the random sets of operational data measured against observed operational data associated with observed customer wait times, observed staffing, and observed profitability;

providing impacts to the metrics based on simulation of the changes within the models, wherein the impacts at least include utilization rates of the physical resources;

providing a different physical layout pattern from a current physical layout pattern selected from known physical layout patterns, wherein the different physical layout pattern is selected from the known physical layout patterns and includes different physical resource allocations from current physical resource allocations based on the impacts to achieve optimal utilization metrics;

providing an interface that renders a visualization of a playback of a given set of operational data for a given activity of a given customer traffic flow with a given physical layout pattern having given allocations of physical resources and illustrating expected or known utilization metrics within the visualization along with suggested changes to staffing, wherein the visualization during the playback visually depicts corresponding customer wait times, corresponding customer throughout, corresponding utilization rates, and corresponding profitability for the given physical layout having the given allocations of the physical resources;

visually presenting, the visualization within the interface;

receiving a stop instruction from the interface;

stopping the visualization responsive to the receiving of the stop instruction;

receiving, by the executable instructions, a change associated with the given set of operational data for the given customer traffic flow with the given physical layout pattern having the given allocations;

visually presenting a second visualization within the interface that illustrates predictive changes to the expected or known utilization metrics with the change along with additional changes to staffing; and

continuously iterating back to the generating at preconfigured intervals of time by gathering and monitoring current operational data, creating a dynamic feedback loop that processes changes to the physical environment based on a current customer traffic flow rate in a given interval and current utilization metrics in the given interval along with updated linkages to a current specific physical layout pattern in the given interval.

12. The server of claim 11 , wherein the physical environment is a restaurant environment.

13. The server of claim 12 , wherein the metrics include:

profitability, customer traffic flow rates, table utilization, server utilization, kitchen efficiency, customer wait times, and customer throughput.