Patent Application
20220222591
The present invention relates to a system, method and computer program for providing a dynamic and intuitive user interface arranged to create a floor plan utilisable by allocation methodologies, or one or more configurable allocation algorithms to perform the task of allocation of space in a restaurant.
In one embodiment, the invention is directed to a computer-enabled method including a user interface accessible via a remote device such as a Point of Sale device, wherein the Point of Sale device is arranged to receive an interactive, real-time, dynamic floor plan including allocated and unallocated bookings, table numbers, chair position numbers and interact with a restaurant operator or operators.
To better understand the inventive concepts and embodiments of the invention described herein, an abridged history of the restaurant industry and known booking systems is may be found in an earlier filed PCT application PCT/AU2018/051168 (and co-pending PCT application PCT/AU2018/051169, PCT/AU2018/051170 and PCT/AU2018/051171), as well as Australian provisional application AU2019/900128.
To provide flexibility and efficient booking systems, restaurants require the ability to offer customised experiences for customers. Such customised experiences, have, in the past, been solely reliant on the staff of the restaurant performing various tasks manually, including interacting with customers, organising table allocations, providing specialised menus, providing specific ancillary services (such as the provision of flowers, etc.).
The earlier filed PCT applications listed above provide a system and method, which, amongst other tasks, is capable of offering a full and rich set of options to potential customers, including various dining times, menus, ancillary services, etc.
However, providing such a large range of options/potential outcomes requires a large amount of flexibility in a restaurant layout. The system and method outlined in the above-mentioned PCT applications is required to offer what is potentially a staggering number of interrelated options. To provide such an array of options relies on the ability of a restaurant operator to provide the “building blocks” which can be arranged in any number of manners to provide a multitude of solutions. It is also necessary to be able to communicate those solutions in a manner that is understandable and actionable by staff who have no specific expertise. It is known that restaurant staff develop certain habits and generally interact with restaurant booking systems in specific ways, and that restaurant staff, in general, have no specific training or knowledge of expert systems, programming, yield management or devising floor plans to optimise desired outcomes. To the extent that staff have any expertise in the aforementioned areas, it is generally ad hoc or based on information passed on by other individuals and is not based on a coherent set of principles and underlying interconnected framework for decision making.
Moreover, it is common nowadays for service providers to provide specific options to some customers and not to others, based on customer requirements. Such options require the relevant choice of options to be relayed to restaurant staff in a manner that is reliable, easy to understand and intuitive, so that the restaurant staff can provide correct and prompt service. Such options may involve additional cost and sometimes additional logistical considerations, such as the need to organise third party services. Such tasks require not only the relaying of information, but the application of cognitive ability and knowledge in order to provide a relevant service or product.
In the present specification, there is reference made to the use of “artificial intelligence”, which is generally acknowledged, in the context of the present specification, as referring to analytical artificial intelligence—namely, the ability of a software application to perform tasks that require some form of “cognitive intelligence”, including the ability to generate a cognitive representation of a real-world situation, and utilising past learning from the performance of similar tasks to inform present and future decisions regarding present and future tasks.
In a first aspect, there is provided a computer-enabled method for creating a volumetric space/time framework of constraints for the dynamic allocation of bookings to one or more spaces in a venue, comprising the steps of,
providing a user interface arranged to receive input regarding spatial and qualitative attributes of the one or more spaces as represented within a volumetric space/time framework, and also to receive input regarding physical and spatial and qualitative attributes of one or more furniture items including modifications to the furniture items and the associability of the one or more furniture items to the one or more spaces in the venue as represented within the volumetric space/time framework, whereby the attributes define a plurality of relativities and contextual relationships between the one or more spaces and each one of the one or more furniture items,
whereby the relativities and contextual relationships within the volumetric space/time framework provide dynamic variation in the allocation of furniture items within the one or more spaces in response to a booking request for one or more of the one or more furniture items in the one or more spaces in the venue, to satisfy quantitative and qualitative optimisation criteria associated with the booking request.
In one embodiment, the physical constraints include at least one of a dimension, a size and a shape of a space or furniture item.
In one embodiment, the further constraint includes a characteristic of the space or furniture item.
In one embodiment, a further constraint includes at least one of a set of products and services associated with at least one of a furniture item and the space to define the plurality of relativities, utilities, contextual relationships and contexts between the space and each one of the one or more furniture items.
In one embodiment, the method includes the further step of, upon receiving the booking request, collecting customer identity information, the customer identity information being utilisable to create or identify one or more further constraints associated with at least one of the space and the furniture items to define the plurality of relativities, utilities, contextual relationships and contexts between the space, each one of the one or more furniture items and at least one of a booking requestor and other persons associated with the booking request.
In one embodiment, the method includes the further step of identifying a channel associated with a booking request, the channel identity being utilisable to create or identify one or more further constraints associated with at least one of the space and the furniture items with at least one of the space and the furniture items defining the plurality of relativities, utilities, contextual relationships and contexts between the space, each one of the one or more furniture items and at least one of a booking requestor and other persons associated with the booking request.
In one embodiment, the set of products and services associated with the at least one of a furniture item and the space is further selected dependent upon at least one of the customer identity information and the channel identity.
In one embodiment, the relativity of one of the space or furniture items is a constraint that is only operational in specific placements of the space or furniture item relative to another space or furniture item.
In one embodiment, the utility of the one of the space or furniture items is a constraint that produces, when applied, a qualitative outcome, and is derived from one or more quantitative physical or operational constraints associated with the space or furniture item.
In one embodiment, the method includes the further step of utilising the volumetric space/time framework as an input to an allocation algorithm, wherein the allocation algorithm utilises the space/time framework to dynamically allocate furniture to allow for the allocation of a booking request.
In one embodiment, for each booking request in a plurality of received booking requests, the allocation algorithm iteratively allocating each booking request to produce an optimised allocation instruction set.
In one embodiment, the method includes the further step of displaying the optimised allocation instruction set on a graphical user interface.
In one embodiment, the optimised allocation instruction set is displayed as a two-dimensional floor plan.
In one embodiment, the allocation algorithm, on not being able to dynamically allocate a booking, varies at least one of the operational constraints to vary the plurality of relativities, utilities, contextual relationships and contexts between the space and each one of the one or more furniture items, to allow the allocation of the booking request.
In one embodiment, there is provided a further strategic framework arranged to interface with the allocation algorithm, the strategic framework including user selectable strategic constraints that define an integrated set of quantitative and qualitative criteria utilisable to vary the operational constraint information, whereby the strategic constraints are variable based on one of a threshold and an event value.
In one embodiment, the threshold value is associated with a seat which is in turn associated with a table, table combination or other furniture or fitting.
In one embodiment, the determination of the threshold value includes the selection of at least one of a table, table combination, other furniture or fittings to which a booking has been allocated to for a specific time period, a specific group size or other constraint information associated with the booking and the type of seats that can be utilised for that table or table combination.
In one embodiment, the determination of the threshold value includes the variables of at least one of a minimum or maximum preferred number of seats around a table, table combination, other furniture or fittings and the preferred physical locations of those seats, stool and seats around each table or table combination.
In one embodiment, the method includes the further step of varying the threshold value over time, whereby the varied thresholds is applied to re-allocate seats.
In one embodiment, the method includes the further step of arranging seats into sub-groupings and associating the seating sub-groupings with sub-groupings of tables, table combinations, other furniture and fittings utilising operational constraint information, whereby the allocation module iteratively allocates requests for each sub-group independently of other sub-groups.
In one embodiment, the method includes the step of the allocation module utilising physical and operational constraint information to allocate at least a sub-set of seats to tables, table combinations, other furniture or fittings in the space to one or more classes, whereby a ranking is associated with the at least a sub-set of the allocated seats with the tables, table combinations, furniture or fittings.
In one embodiment, the method includes the further step of utilising constraint information including the ranking of each seat, table, table combination, other furniture and fittings to create combined chair and table rankings within a venue and spaces within a venue.
In one embodiment, the physical constraint information includes the space required for a person to be seated at a table, table combination, furniture or fitting.
In one embodiment, the method includes the further step of allocating position numbers for seats associated with a table, table combination, other furniture or fitting.
In one embodiment, the method includes the further step of utilising the physical constraint information to determine the physical maximum number of seats that can be accommodated around a table, table combination, furniture or fitting.
In one embodiment, the method includes the further step of allocating an arbitrary limit lower than the maximum physical number of seats that can be physically allocated to a table or table combination, other furniture or fittings.
In one embodiment, the method includes the further step of utilising customer identity information including booking requestor identity information received from at least one of an internal and a third-party database of information, whereby the identity of the booking requestor and or one or more diners is utilised to determine the types of seats to be allocated to the table, table combination, other furniture or fittings that are allocated to the booking requestor.
In one embodiment, the customer identity information includes booking requestor identity information received from at least one of an internal and a third-party database of information, whereby the identity is utilised to determine the seat position number allocated to the booking requestor.
In one embodiment, the method includes the further step of dynamically allocating each one of the tables, table combinations, other furniture and fittings a variable identifier such that each one of the tables, table combinations, furniture and fittings retain a unique identifier to allocate the correct number of seats.
In one embodiment, the method includes the further step of utilising a seating allocation algorithm to allocate each of the seats associated with each table, table combination, other furniture or fitting in a pre-defined location relative to the table, table combination, other furniture or fitting.
In one embodiment, the method includes the further step of the seat allocation module interfacing with a menu module arranged to vary the constraint determining the seats available and that can be allocated to a table, table combination, other furniture or fixtures.
In one embodiment, the method includes the further step of varying the number of seats available that can be allocated to a table, table combination, other furniture or fixtures as a function of the occasion, class, promotion, date, service, menu or any other operational constraint associated with the table, table combination, other furniture or fixture.
In one embodiment, the physical constraints include at least one of the quantity and types of seats located within the venue, stored within the venue or receivable by the venue within a specified period of time.
In one embodiment, the further step of generating one of a floor plan, Gantt chart and figures table which is provided to a space allocation user interface.
In one embodiment, the space allocation user interface is interactive, whereby each of the representations of a table, table combination, other furniture, fixture and seat are selectable by the user of the interface.
In one embodiment, the method includes the further step of, on selection of a seat at a table by the user, the interface providing the user with access to an ordering interface arranged to allow the input of orders or associated information against the seat and associated table, table combination, other furniture or fixture selected by the user.
In one embodiment, the table plan, Gantt chart or figures table is integrated within a point of sale system whereby the displayed representations of tables, seats, other furniture and fittings vary in real time in accordance with events and changes within a venue.
In one embodiment, the method includes the further step of interfacing with an artificial intelligence module arranged to receive the booking request information and review the one or more of the plurality of constraints to determine whether variation of the one or more constraints to allow acceptance of the booking request results in a greater maximisation in the probability of achieving the selected outcome, whereby if the variation of the one or more constraints to allow acceptance of the booking request results in a maximisation in the probability of achieving the selected outcome, the one or more of the plurality of constraints are varied and the varied constraints are utilised for all subsequent booking requests for the service period, and the initial booking request information is provided to an allocation module arranged to accept the booking request and allocate the booking request together with all previously received booking requests to one or more spaces in the venue, whereby if all booking requests can be allocated, the received booking request is accepted and utilised to produce an optimised allocation instruction set which is utilisable by one or more users associated with the venue.
In another aspect, the invention provides a computer-enabled method for creating a list of tables for the dynamic allocation of booking requests to a table in an area or a sub-area in a venue, comprising the steps of,
providing a user interface arranged to receive input regarding constraint information including multiple physical characteristics of each table within an area or sub-area and further constraints associated with each table, whereby the input of multiple physical constraints and further constraints define a plurality of relativities, utilities, contextual relationships and contexts between the area or sub-area and each table,
whereby the relativities, utilities, contextual relationships and contexts define a table/time framework
whereby a further framework includes selectable strategic constraints for the development of an integrated set of quantitative and qualitative criteria utilisable to vary the constraint information
whereby the strategic constraints are variable based on threshold or event values to thereby enable a dynamic allocation of each table in the area or sub-area to meet desired quantitative and qualitative optimisation criteria in response to the receipt of the booking requests.
In another aspect, the invention provides a computer-enabled method for creating a table/time framework for the dynamic allocation of bookings to a space comprising one or more subs-spaces in a venue, comprising the steps of,
providing a user interface arranged to receive input regarding physical and operational constraints associated with a set of tables and table combinations associated with the one or more sub-spaces within the space,
whereby a further set of tables and table combinations are input, whereby at least one or more of the tables and table combinations in the further set are interchangeable with one or more of the tables and table combinations in the set of tables and table combinations, such that a different number of individual tables are used or a different type or size of table is used in the booking allocation process to achieve an optimised outcome.
In another aspect, the invention provides a computer-enabled method for creating a table/time framework for the dynamic allocation of bookings to a space in a venue, comprising the steps of, providing a user interface arranged to receive input regarding physical and operational constraints associated with a first set of tables and table combinations associated with the space,
receiving input regarding physical and operational constraints associated with at least one further set of tables and table combinations, the further set of tables including at least one of a different number of tables or at least one table of a different size or shape,
whereby at least one or more of the tables and table combinations in the further set are interchangeable with one or more of the tables and table combinations in the first set of tables and table combinations,
whereby the physical and operational constraints regarding the first set of tables and table combinations and the further set of tables and table combinations are utilised by an allocations module to define a plurality of relativities, utilities, contextual relationships and contexts between the sets of tables and table combinations,
whereby the allocations module utilises a further framework including selectable strategic constraints for the development of an integrated set of quantitative and qualitative criteria utilisable to vary the physical and operational constraint information of the first and further sets of tables and table combinations,
whereby the strategic constraints are variable based on threshold or event values to thereby enable a dynamic allocation of each table to meet desired quantitative and qualitative optimisation criteria in response to the receipt of the booking requests.
In one embodiment, the framework is utilised, when populated with booking requests, to provide at least one of accounting functionality, financial transaction functionality, point of sale functionality, rostering functionality and operational functionality.
In one embodiment, the method includes the further step of the framework utilising at least one of a forecasting module and an artificial intelligence module to operate at least one of an accounting system, a financial transaction system, a point of sale system, a rostering system and an operational system.
In another aspect, the invention provides a computer-enabled method to allocate a user to a predetermined table within a volumetric space/time framework or a table and table combination framework comprising the steps of, for a booking allocation system including allocated bookings, reviewing all allocated bookings to create a priority booking allocation list including one or more of the following criteria:
In another aspect, the invention provides a computer-enabled method to allocate a user to a predetermined table available within a volumetric space/time framework or a table and table combination framework comprising the steps of, for a booking allocation system including allocated bookings, reviewing all allocated bookings to create one of a table, remove a table or maintain a predetermined list of tables, whereby on addition or removal of a table or table combination, the framework maintains unique table identifiers and unique seat identifiers.
In another aspect, the invention provides a computer-enabled method for creating a volumetric space/time framework or a table/table combination framework of constraints for the dynamic allocation of bookings to a space in a venue, comprising the steps of,
providing a user interface arranged to receive input regarding physical and further constraints of the space and time to the volumetric space/time framework or table/table combination framework, and also to receive input regarding physical and further constraints of one or more furniture items in the venue, whereby the input of physical constraints and further constraints define a plurality of relativities, utilities, contextual relationships and contexts between the space and each one of the one or more furniture items,
whereby the relativities, utilities, contextual relationships and contexts define a volumetric space/time framework or table/table combination framework over time that allows for the dynamic variation of the allocation of furniture items in the space in response to the receipt of a booking request for the space in the venue to meet desired quantitative and qualitative optimisation criteria,
whereby the volumetric space/time framework or table/table combination framework includes an allocation instruction set, the allocation instruction set being capable of being provided with a representation of a floor plan to a third party application.
In one embodiment, the third party application is a point of sale application.
In another aspect, the present invention provides a computing system for allocating furniture to devise a floor plan capable of receiving bookings allocated to one or more spaces in a venue, comprising:
an allocation module including one or more optimisation algorithms in communication with a processor and arranged to receive at least one request to assign chairs to a table, table combination or other furniture or fittings and communicate with a database of other saved booking requests,
wherein the allocation module determines whether one or more predetermined chair, stool or other seat thresholds designated to a table, table combination or other furniture or fittings have been exceeded, and if so, the allocation module receives the saved booking requests and combines the at least one booking request with the saved booking requests to form a pool of requests, retrieve constraint information regarding the chairs, stools, seats, tables, table combinations, other furniture and or fittings and iteratively allocates chairs, stools and other seats to each of the requests from the pool of requests to a table or table combination utilising the constraint information to select the chairs, stools, seats to a table, table combination, furniture or fittings,
wherein an optimised allocation instruction set of allocated chairs, stools and seats for each booking is produced,
wherein the optimised allocation instruction set is saved in the database,
wherein the optimised allocation instruction set is further provided by a space allocation user interface in the form of a floor plan, Gantt chart, diagram or figures table that shows the exact chairs optimised, assigned, or allocated for the booking request for the booking accepted for the table, table combination, other furniture or fittings to one or more users associated with the venue.
In one embodiment, the determination of the threshold value includes at least one of the table, table combination, other furniture or fittings selected upon which a booking has been allocated to for a specific time period, a specific group size or other constraint information associated with the booking and the type of chairs, stools or seats that can be utilised for that table, table combination or other furniture and fittings.
In one embodiment, the determination of the threshold value includes at least one of a minimum or maximum preferred number of chairs, stools, seats around a table, table combination, other furniture or fittings and the preferred physical locations of those seats, stool and seats around each table, table combination, other furniture or fittings.
In one embodiment, the determination of the threshold value is varied over time, wherein the multiple thresholds are applied to re-allocate chairs, stools or seats.
In one embodiment, the chairs, stools and seats are arranged into sub-groupings and matched to different subgroupings of tables, table combinations, other furniture and fittings based on constraint information, wherein the allocation module iteratively allocates requests for each sub-group independent of other sub-groups.
In one embodiment, the allocation module is arranged to utilise constraint information to group at least a sub-set of chairs, stools and seats to tables, table combinations, other furniture or fittings in the space into different classes to create a ranking for the at least the sub-set of the allocated chairs, stools and seats with the tables, table combinations, furniture or fittings.
In one embodiment, the allocation module utilises constraint information including the ranking of each chair, stool, seat, table, table combination, other furniture and fittings to create combined chair and table rankings within a venue and spaces within a venue.
In one embodiment, the constraint information includes the dimensions of all the different chairs, stools, seats, tables, table combinations, furniture and fittings, the relativities of the different items and the relativities of the different items within a venue or a space within the venue.
In one embodiment, the constraint information includes the space required for a diner around a table, table combination, furniture or fittings.
In one embodiment, the constraint information includes a methodology to determine and allocate position numbers for chairs, stools and seats around specific tables, table combinations, other furniture or fittings.
In one embodiment, an algorithm utilises the constraint information to determine the physical maximum chairs, stools and seats that can be accommodated around a table, table combination, furniture or fitting.
In one embodiment, the constraint information includes an arbitrary limit which is less than the maximum physical number of chairs, stools and seats that can be physically accommodated around a table, table combination, other furniture or fittings which can be used to limit the number of chairs, stools, seats placed around a table, table combination, other furniture or fittings.
In one embodiment, the constraint information includes booking requestor identity information received from at least one of an internal and a third-party database of information, wherein the identity is utilised to determine the number types of chairs, stools or seats to be allocated to the table, table combination, other furniture or fittings allocated to the booking requestor.
In one embodiment, the constraint information includes booking requestor identity information received from at least one of an internal and a third-party database of information, wherein the identity is utilised to determine the chair, stool, seat position number for the booking requestor to be allocated to.
In one embodiment, each of the tables, table combinations, other furniture and fittings are allocated a dynamically variable identifier such that each one of the tables, table combinations, furniture and fittings retain a unique consistent identity to which the chair, stool and seat algorithm and allocator can determine the correct number of chairs, stools and seats required for that booking based on the table, table combination, other furniture or fittings to which that booking was allocated.
In one embodiment, the chairs, stools and seats are placed in specific position around the table, table combination, other furniture or fittings to which they have been allocated are given unique and easily identifiable position numbers in accordance with the chair, stool, seat position numbering constraints such that each chair, stool, seat within a venue has a consistent and unique identifier in the form of a table and position number and saved in the database
In one embodiment, the chair, stool and seat allocation module interfaces with a menu module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures.
In one embodiment, the chair, stool and seat allocation module interfaces with a group size module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures
In one embodiment, the chair, stool and seat allocation module interfaces with an occasion module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures
In one embodiment, the chair, stool and seat allocation module interfaces with a class module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures
In one embodiment, the chair, stool and seat allocation module interfaces with a promotion module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures
In one embodiment, the chair, stool and seat allocation module interfaces with a calendar module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures by time and by service.
In one embodiment, the constraints include the number in quantity and types of chairs, stools and seats located within the venue, stored within the venue or can be brought in and used by the venue
In one embodiment, the module determines chair, stool and seat availability.
In one embodiment, the floor plan, Gantt Chart or figures table generated are provided by a space allocation user interface where tables and chairs are touch sensitive and all chairs, stools and seats allocated to all tables, table combinations, other furniture and fittings are uniquely identified and when touch activated contain unique references.
In one embodiment, the selection of a chair at a table on a device such as a touch screen device opens up a module to permit the placement of orders and information against that specific chair, stool or seat within that table, table combination, and other furniture or fixture identifier.
In one embodiment, the order or information placed against a chair, stool or seat within a booking for a table, table combination, other furniture or fixture can be used at least in one of the following manners:
In one embodiment, the table plan, Gantt chart or figures table is integrated within a separate point of sale system to provide dynamic floor plans, Gantt charts and figures tables whereby the tables, chairs, seats, other furniture change locations within the screen in real time in accordance with actual events and changes within a venue.
In one embodiment, the chair optimising, assigning and allocation algorithms work in conjunction with and simultaneously with the table allocation algorithms in the allocation of bookings within a venue with one or more spaces. to create a further amended and optimised allocation instruction set of allocated chairs, stools and seats for each table, table combination, other furniture and fittings set which is saved in the database, wherein the optimised allocation instruction set is further provided by a space allocation user interface.
In one embodiment, the chair optimising assigning and allocation algorithms are applied subsequent to the table, table combination, other furniture or fixtures allocation algorithms utilising arbitrary minimum and maximum chairs, stools and seats per table, table combination, other furniture or fittings in the allocation of bookings within a venue with one or more spaces and where additional chairs, stools and seats constraints are different to those minimum and maximum chair, stool and seat values including the physically logical maximum chairs, stools and seats that can be optimised, assigned or allocated to the tables, table combinations, other furniture or fittings then the allocation of chairs, stools and seats will be changed in accordance with the additional chair, stool and seat constraints to create a further amended and optimised allocation instruction set of allocated chairs, stools and seats for each table, table combination, other furniture and fittings set which is saved in the database, wherein the optimised allocation instruction set is further provided by a space allocation user interface.
In one embodiment, the chair, stool, and seat optimising, assigning and allocation algorithms are utilised to determine and select which one or more tables, table combinations, or other furniture or fixtures to which one or more bookings could be allocated to as part of the booking allocation process to create a further amended and optimised allocation instruction set of allocated chairs, stools and seats for each table, table combination, other furniture and fittings set which is saved in the database, wherein the optimised allocation instruction set is further provided by a space allocation user interface.
In one embodiment, the allocation of a booking request to a chair, stool, seat, a table, table combination, other furniture or fixture is undertaken on a first booking received first booking allocated basis or when one or more specific threshold values are met or completely dynamically and iteratively with all previous booking requests forming a pool of requests and the bookings being allocated from that pool of requests using one or more ordering processes for the optimisation of the quantitative and qualitative outcomes set by the venue.
In one embodiment, there is provided an artificial intelligence model arranged to receive the request information and review the one or more of the plurality of constraints to determine whether variation of the one or more constraints to allow acceptance of the booking request result in a greater maximisation in the probability of achieving the selected outcome, whereby if the variation of the one or more constraints to allow acceptance of the booking request results in a maximisation in the probability of achieving the selected outcome, the one or more of the plurality of constraints are varied and the varied constraints are utilised for all subsequent booking requests for the service period, and the initial booking request information is passed on to an allocation module arranged to accept the booking request and allocate the booking request together with all previously received booking requests to one or more spaces in the venue, whereby if all booking requests can be allocated the received booking request is accepted, whereby the booking information is utilised to produce an optimised allocation instruction set which is utilisable by one or more users associated with the venue.
In a further aspect, the invention provides a computer-enabled method for creating a framework for the dynamic allocation of a booking request to one or more tables and table combinations furniture items in a space, comprising the steps of,
providing a user interface arranged to receive input regarding spatial and qualitative attributes of one or more furniture items including modifications to the furniture items and the associability of the one or more tables and table combinations furniture items to each other and to the space, whereby the attributes define a plurality of relativities and contextual relationships between the space and each one of the one or more furniture items, the user interface further being arranged to receive input regarding one or more quantitative and qualitative constraints utilisable by the framework to optimally allocate the booking request,
whereby the relativities and contextual information and the constraints are utilised by an algorithm to create the framework that provides for the dynamic variation in the allocation of the one or more tables and table combinations furniture items within the space in response to the booking request for the one or more of the one or more tables and table combinations furniture items in the space, to satisfy the quantitative and qualitative optimisation criteria, whereby upon execution of the algorithm, the framework is arranged to produce an optimised allocation instruction set for the space and the allocated bookings, whereby the optimised allocation instruction set is saved in the database and displayed, upon request, by a space allocation user interface to one or more users.
In a further aspect, the invention provides a computer-enabled method for creating a framework for the dynamic allocation of a booking request for a defined time period to one or more items and to a space, comprising the steps of,
providing a user interface arranged to receive input regarding spatial and qualitative attributes of one or more items associable with the booking request and the associability of the one or more items to each other, to the space and to a defined time range, whereby the attributes define a plurality of relativities and contextual relationships between the space, the defined time range and each one of the one or more items, the user interface further being arranged to receive input regarding one or more quantitative and qualitative constraints utilisable by the framework to optimally allocate the booking request,
whereby the relativities and contextual relationships include information utilised by an algorithm to create the framework that provides for the dynamic variation in the allocation of one or more items in the space for the defined time period within the defined time range in response to the booking request, to satisfy quantitative and qualitative optimisation criteria,
whereby upon execution of the algorithm, the framework is arranged to produce an optimised allocation instruction set for the defined time periods and the allocated bookings, whereby the optimised allocation instruction set is saved in the database and displayed, upon request, by a space allocation user interface to one or more users.
In a further aspect, the invention provides a computer-enabled method for creating a framework for the dynamic allocation of a booking requests to one or more tables and table combinations in a space, comprising the steps of,
providing a user interface arranged to receive input regarding spatial and qualitative attributes of one or more tables and table combinations including the attributes of the tables and table combinations to each other and to the space, whereby the attributes define a plurality of relativities and contextual relationships between the space and each one of the one or more tables and table combinations, the user interface further being arranged to receive input regarding one or more quantitative and qualitative constraints utilisable by the framework to optimally allocate the booking request,
whereby the relativities and contextual provide information utilised by an algorithm to create the framework that provides for the dynamic variation in the allocation of tables and table combinations within the space in response to a booking request in a manner to satisfy the quantitative and qualitative optimisation criteria, whereby upon execution of the algorithm, the framework is arranged to produce an optimised allocation instruction set for the tables and table combinations and the allocated bookings, whereby the optimised allocation instruction set is saved in the database and displayed, upon request, by a space allocation user interface to one or more users.
Further features of the present invention are more fully described in the following description of several non-limiting embodiments thereof. This description is included solely for the purposes of exemplifying the present invention. It should not be understood as a restriction on the broad summary, disclosure or description of the invention as set out above. The description will be made with reference to the accompanying drawings in which:
The present invention relates generally to a computing system, method, computer program and data signal for allocating furniture to devise a floor plan capable of receiving bookings allocated to one or more spaces in a venue.
The system generally comprises an allocation module including one or more optimisation algorithms in communication with a processor and arranged to receive at least one request to assign chairs to a table, table combination or other furniture or fittings and communicate with a database of other saved booking requests.
The allocation module determines whether one or more predetermined chair, stool or other seat thresholds designated to a table, table combination or other furniture or fittings have been exceeded, and if so, the allocation module receives the saved booking requests and combines the at least one booking request with the saved booking requests to form a pool of requests, retrieve constraint information regarding the chairs, stools, seats, tables, table combinations, other furniture and or fittings and iteratively allocates chairs, stools and other seats to each of the requests from the pool of requests to a table or table combination utilising the constraint information to select the chairs, stools, seats to a table, table combination, furniture or fittings.
This in turn creates an optimised allocation instruction set of allocated chairs, stools and seats for each booking produced, wherein the optimised allocation instruction set is saved in the database and the optimised allocation instruction set is further provided by a space allocation user interface in the form of a floor plan, Gantt chart, diagram or figures table that shows the exact chairs optimised, assigned, or allocated for the booking request for the booking accepted for the table, table combination, other furniture or fittings to one or more users associated with the venue.
The determination of the threshold value includes at least one of the table, table combination, other furniture or fittings selected upon which a booking has been allocated to for a specific time period, a specific group size or other constraint information associated with the booking and the type of chairs, stools or seats that can be utilised for that table, table combination or other furniture and fittings.
The determination of the threshold value includes at least one of a minimum or maximum preferred number of chairs, stools, seats around a table, table combination, other furniture or fittings and the preferred physical locations of those seats, stool and seats around each table, table combination, other furniture or fittings.
The determination of the threshold value is varied over time, wherein the multiple thresholds are applied to re-allocate chairs, stools or seats.
The chairs, stools and seats are arranged into sub-groupings and matched to different subgroupings of tables, table combinations, other furniture and fittings based on constraint information, wherein the allocation module iteratively allocates requests for each sub-group independent of other sub-groups.
The allocation module is arranged to utilise constraint information to group at least a sub-set of chairs, stools and seats to tables, table combinations, other furniture or fittings in the space into different classes to create a ranking for the at least the sub-set of the allocated chairs, stools and seats with the tables, table combinations, furniture or fittings.
The allocation module utilises constraint information including the ranking of each chair, stool, seat, table, table combination, other furniture and fittings to create combined chair and table rankings within a venue and spaces within a venue.
The constraint information includes the dimensions of all the different chairs, stools, seats, tables, table combinations, furniture and fittings, the relativities of the different items and the relativities of the different items within a venue or a space within the venue.
The constraint information includes the space required for a diner around a table, table combination, furniture or fittings.
The constraint information includes a methodology to determine and allocate position numbers for chairs, stools and seats around specific tables, table combinations, other furniture or fittings.
The algorithm can utilise the constraint information to determine the physical maximum chairs, stools and seats that can be accommodated around a table, table combination, furniture or fitting.
The constraint information includes an arbitrary limit which is less than the maximum physical number of chairs, stools and seats that can be physically accommodated around a table, table combination, other furniture or fittings which can be used to limit the number of chairs, stools, seats placed around a table, table combination, other furniture or fittings.
The constraint information includes booking requestor identity information received from at least one of an internal and a third-party database of information, wherein the identity is utilised to determine the number types of chairs, stools or seats to be allocated to the table, table combination, other furniture or fittings allocated to the booking requestor.
The constraint information includes booking requestor identity information received from at least one of an internal and a third-party database of information, wherein the identity is utilised to determine the chair, stool, seat position number for the booking requestor to be allocated to.
Each of the tables, table combinations, other furniture and fittings are allocated a dynamically variable identifier such that each one of the tables, table combinations, furniture and fittings retain a unique consistent identity to which the chair, stool and seat algorithm and allocator can determine the correct number of chairs, stools and seats required for that booking based on the table, table combination, other furniture or fittings to which that booking was allocated.
The chairs, stools and seats are placed in specific position around the table, table combination, other furniture or fittings to which they have been allocated are given unique and easily identifiable position numbers in accordance with the chair, stool, seat position numbering constraints such that each chair, stool, seat within a venue has a consistent and unique identifier in the form of a table and position number and saved in the database.
The chair, stool and seat allocation module interfaces with a menu module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures.
The chair, stool and seat allocation module interfaces with a group size module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures.
The chair, stool and seat allocation module interfaces with an occasion module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures.
The chair, stool and seat allocation module interfaces with a class module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures.
The chair, stool and seat allocation module interfaces with a promotion module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures.
The chair, stool and seat allocation module interfaces with a calendar module arranged to vary the constraint determining the chairs, stools and seats available and that can be allocated to a table, table combination, other furniture or fixtures by time and by service.
The constraints include the number in quantity and types of chairs, stools and seats located within the venue, stored within the venue or can be brought in and used by the venue
The module determines chair, stool and seat availability.
The floor plan, Gantt Chart or figures table generated are provided by a space allocation user interface where tables and chairs are touch sensitive and all chairs, stools and seats allocated to all tables, table combinations, other furniture and fittings are uniquely identified and when touch activated contain unique references.
The selection of a chair at a table on a device such as a touch screen device opens up a module to permit the placement of orders and information against that specific chair, stool or seat within that table, table combination, other furniture or fixture identifier.
The order or information placed against a chair, stool or seat within a booking for a table, table combination, other furniture or fixture can be used at least in one of the following manners:
a) To permit the booking requestor to determine within their allocated table, table combination, other furniture or fixture which chair, stool or seat that each of their individual guests within the booking are allocated to;
b) To permit the booking requestor to enter the names, emails and other details of the individual guests against the actual chairs, stools and seats that they have been allocated to;
c) To permit the booking requestor to request name cards be printed for their guests and placed on their allocated table in front of their allocated chair, stool or seat;
d) To permit the booking requestor to invite his guests to log into the system and pre-order and or prepay for their requested food and beverage items;
e) To permit the individuals to place orders for food and beverages while sitting at the venue against their seat and identifier;
f) To permit orders from different seats within a table to consolidated together and summarised prior to those orders being sent to the kitchen or bar for preparation, such that multiple orders for the same table can be consolidated and added together to ease of use and reference by kitchen staff or by any robotics process; and/or
g) To permit the creation of individual bills by seat number within a table or alternatively any combination of seats within an allocated table, table combination, other furniture or fittings.
The table plan, Gantt chart or figures table can by integrated within a separate point of sale system so that dynamic floor plans, Gantt charts and figures tables whereby the tables, chairs, seats, other furniture change locations within the screen in real time in accordance with actual events and changes within a venue.
The chair optimising, assigning and allocation algorithms work in conjunction with and simultaneously with the table allocation algorithms in the allocation of bookings within a venue with one or more spaces. to create a further amended and optimised allocation instruction set of allocated chairs, stools and seats for each table, table combination, other furniture and fittings set which is saved in the database, wherein the optimised allocation instruction set is further provided by a space allocation user interface.
The chair optimising assigning and allocation algorithms are applied subsequent to the table, table combination, other furniture or fixtures allocation algorithms utilising arbitrary minimum and maximum chairs, stools and seats per table, table combination, other furniture or fittings in the allocation of bookings within a venue with one or more spaces and where additional chairs, stools and seats constraints are different to those minimum and maximum chair, stool and seat values including the physically logical maximum chairs, stools and seats that can be optimised, assigned or allocated to the tables, table combinations, other furniture or fittings then the allocation of chairs, stools and seats will be changed in accordance with the additional chair, stool and seat constraints to create a further amended and optimised allocation instruction set of allocated chairs, stools and seats for each table, table combination, other furniture and fittings set which is saved in the database, wherein the optimised allocation instruction set is further provided by a space allocation user interface.
The chair, stool, and seat optimising, assigning and allocation algorithms are utilised to determine and select which one or more tables, table combinations, or other furniture or fixtures to which one or more bookings could be allocated to as part of the booking allocation process to create a further amended and optimised allocation instruction set of allocated chairs, stools and seats for each table, table combination, other furniture and fittings set which is saved in the database, wherein the optimised allocation instruction set is further provided by a space allocation user interface.
The allocation of a booking request to a chair, stool, seat, a table, table combination, other furniture or fixture is undertaken on a first booking received first booking allocated basis or when one or more specific threshold values are met or completely dynamically and iteratively with all previous booking requests forming a pool of requests and the bookings being allocated from that pool of requests using one or more ordering processes for the optimisation of the quantitative and qualitative outcomes set by the venue.
In another aspect, there is also included an artificial intelligence module arranged to receive the request information and review the one or more of the plurality of constraints to determine whether variation of the one or more constraints to allow acceptance of the booking request result in a greater maximisation in the probability of achieving the selected outcome, whereby if the variation of the one or more constraints to allow acceptance of the booking request results in a maximisation in the probability of achieving the selected outcome, the one or more of the plurality of constraints are varied and the varied constraints are utilised for all subsequent booking requests for the service period, and the initial booking request information is passed on to an allocation module arranged to accept the booking request and allocate the booking request together with all previously received booking requests to one or more spaces in the venue, whereby if all booking requests can be allocated the received booking request is accepted, whereby the booking information is utilised to produce an optimised allocation instruction set which is utilisable by one or more users associated with the venue.
In the following description of an embodiment, specific terms will be used to broadly define particular features or aspects of the inventive concept or the information utilised to allocate a booking request, within the context of a specific example embodiment, namely the allocation of bookings in a restaurant. However, it will be understood that the invention has broader application than the allocation of bookings in a restaurant. Examples of the use of the interface are provided outside of the booking of restaurants.
One embodiment of the computing system is shown at
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The computing system 100 includes instructions that may be installed in ROM 104, RAM 106 or disc drives 112 and may be executed by the processor 102. There may be provided a plurality of communication links 114 which may variously connect to one or more user devices 110, such as computers, smartphones or tablets, wherein the one or more user devices have a user interface for interacting with user by collecting and displaying data or information using the conventional means provided by such devices. At least one of a plurality of communications link 114 may be connected to an external computing network through a telecommunications network, including Internet cloud services 120.
In one particular embodiment the device may include a database 116 which may reside on the storage device 112. It will be understood that the database may reside on any suitable storage device, which may encompass solid state drives, hard disc drives, optical drives or magnetic tape drives. The database 116 may reside on a single physical storage device or may be spread across multiple storage devices, either locally or remotely.
The computing system 100 includes a suitable operating system 118 which may also reside on a storage device or in the ROM of the server 100. The operating system is arranged to interact with the database 116 and with one or more computer programs to cause the server to carry out the steps, functions and/or procedures in accordance with the embodiments of the invention described herein.
The user interface 110 of one or more mobile devices facilitates the collection and display of user data for the computing system 100. The user interface 110 may be a program or website accessed on a computer or mobile device via a communication network, such as the Internet. Alternatively, the user interface 110 may be a widget arranged on a website that may be accessed by a user using a computer or mobile device via a communication network such as the Internet. The user interface 110 may also be provided as a mobile application or “app” present on the user device, such as a tablet or smart phone.
The at least one user interacts with the user interface 110 and may be a first user (also referred to as the “booking requestor”) requesting to use a space in a venue. The at least one user may also include a second user (referred to as the “operator” or “venue operator”), who is associated with the venue and utilizes the optimised space allocation instruction set provided by the allocation module to enable the use of the space by the booking requestor.
The booking requestor interacts with the computing system to make a request. The requestor may make a request for one or more patrons of the venue to use the space in a venue, where the requestor may also be one of the patrons of the venue. That is, a user that interacts with the system is referred (on their own behalf or on behalf of a group of people) is referred to as a booking requestor and the person (or group of people) that will be allocated a table (i.e. attend the venue or restaurant) may be variously referred to as the “patron” or “patrons”, the “customer” or “customers”, the “guest” or “guests” and/or the “diner” or “diners”, or any other term as appropriate for the venue.
An embodiment includes the computer system 100 processing the request and undertaking all subsequent steps in an autonomous manner. Alternatively, in another embodiment, the operator may use one of the user interfaces 110 provided to one or more devices to receive, input, or modify information in order to provide further input to the computer system 100, so that the computing system may process the request and provide instructions to the entity.
In processing the request, the computer system 100 may arrange objects in the space in accordance with the optimised space allocation instruction set. That is, the booking requestor acts as a customer making a request which is to be “serviced” by the operator in accordance with the optimised space allocation instruction set. As may be appreciated by a skilled addressee, there may be any number of remote users and operators who are able to interact with the computing system via the user interface 110 via any number of different devices.
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In other words, the volumetric framework, in addition to the calendar and the floor creation module and time constraint module create a real time simulation of the restaurant, allowing the operator to track all aspects of the restaurant/space over time. This framework is derived from the realisation that the pivotal structure (both physical and conceptual) in the operation of a space such as a restaurant, is the booking and how the booking is allocated and managed. The placement of tables and chairs, the opening hours, the food served, the staff employed, etc., are ultimately all connected to the booking. As such, the volumetric model is a completely different manner in which to conceptualise the operation of a space (and in particular a restaurant space or any other space where a service is provided and there are multiple constraints).
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The following references serve as a summary of the information referred to within the embodiment detailed by
Restaurant Set-up Rules (278): There are three basic embodiments disclosed herein, each of which utilise a different set of rules to set up a restaurant or any other space that can be reserved for any purpose. In all embodiments, the rules and constraints are arranged to permit the proper contextual relationships, relativities, utility of and flexible table and chair or equipment capacity to allow for effective differentiation, discrimination, yield management, dynamic pricing, revenue management, cost and operations management and the achievement of bespoke (configurable) individual quantitative and qualitative goals of a restaurant.
In the context of the specification and the embodiments and broader invention described herein, the terms “relationship”, “relativity”, “utility” and “contextual relationships” have specific meanings as related to equipment, furniture and other items which can be arranged within a space/venue and which can be ascribed specific attributes, constraints and by extension rules which utilise the attributes and constraints.
Firstly, the term “relativity” in the context of the specification refers to quantifiable attributes and constraints that describe quantifiable variables of a table, chair, furniture or equipment that in turn form the basis for a qualitative assessment of the table, chair and/or equipment. For example, the size and shape of the table, which are quantitative variables, may have an impact on a qualitative attribute of the table, such as the “class” of table. A first class table may be of a larger size and a first class chair may be more luxurious (larger chair). The attribute, however, is relative to other attributes and therefore in and of itself may not be determinative of the overall qualitative assessment of the table. For example, in addition to a physical attribute of the table, the location of the table relative to the space may also be determinative of the class of the table. For example, a table that is near a window and has a view may be considered a first class table, even if the physical attributes of the physical table do not necessarily match those of a “first class” table.
In other words, the term “relativity” refers to quantifiable attributes of furniture/equipment.
Correspondingly, the term “utility” refers to the overall utility that is derivable from the relative attributes and constraints that are associated with each item of furniture, including tables, chairs and other items of equipment.
Secondly, the term “relationship” refers to an association between two or more items, objects etc. For example, a relationship may be that a table is capable of being placed in a particular section. This is a constraint that defines a relationship between the table and the section.
Relationships may be one-to-one, or may be multiple, in that an object or item may have a relationship with a number of other objects or items. In other words, the relationships behave as a constraint with respect to how the two objects or items can interact.
In the past specification, the reference to a “contextual relationship” or to “context”, refers to a relationship that acts as a constraint when specific conditions are met. For example, two tables may have a contextual relationship when placed adjacent to each other, or together, but have no such relationship when they are not placed adjacent to each other.
The rules and constraints stand in contrast to the prior art solutions, which are limited to a predetermined and unchanging limited solution set of non-descript tables and table combinations with simple minimum and maximum chair constraints. The three embodiments shown at (278) are “space”, “tables” and “tables, table combinations and shadow tables” described further below:
The space embodiment uses a volumetric framework, and a restaurant floor plan or other file or data base to provide a series of restaurant allocation and organisation rules, including the relationships, relativities, utility and capacity of tables, chairs, other furniture and all other constraints within the restaurant.
Each table is ascribed an extensive set of characteristics and constraints, such that each table has a specific relativity, relationship, utility and capacity relative to each other table. Moreover, each chair is also ascribed a space relativity which is treated as a second aspect of the invention. This embodiment is similar to the space embodiment noted above. However, there is no utilisation of exact dimensions. In other words, less emphasis is placed on the spatial/dimensional aspect of the “space”, but the rules and algorithm still mimic the “space” embodiment above to achieve a similar outcome. This additional embodiment permits the addition and/or removal of tables from the total capacity of the restaurant.
The use of a list of tables and associated attributes as the underlying set of variables used to define the relativity, relationship, utility and capacity of each table and chair acts as a “common denominator” or as a benchmark for those relativities, relationships, utilities and capacities that provides that relativity. Hence, the use of a list of tables detailing the relationships, relativities, utilities and capacity between each other is an embodiment of the claimed invention. A further embodiment is any combination or permutation of relativities, relationships utilities and capacities of tables, chairs, and the restaurant rules that permits the differentiation, discrimination, yield management, dynamic pricing, revenue management, cost and operations management to achieve bespoke outcomes as disclosed within this and the other related applications.
Through an extensive definition of the relationship, relativity, utility and capacity of each table and table combination with each other table and table combination to define a set of constraints rules can be applied to achieve desired outcomes. The development of rules provide granular differentiation and improve outcomes.
Within this embodiment is the concept of “shadow tables”, defined as tables that do not physically exist in the total solution set of tables and table combinations as in the prior art. Alternatively stated, these “shadow tables” are not shown and do not exist on the floor plan within the prior art. These “shadow tables” are a list of permutations of tables that can be placed in an area, sub area, or space such that they can replace previously existing table or table combination within that area, sub area or space such that the allocation process permits the addition of or removal of tables and or chairs from the floor plan to provide a different and more optimised outcome than the prior art.
It will be understood that the permutations are not limited to a fixed number of tables, but can include the addition or removal of tables. For example, a permutation may include two separate tables T1 and T2 and a combined table T1+T2 as per the prior art. However, in the present embodiment, there can also be provided a further table not existing in the prior art (T3) which permits the addition of a different combined table T1+T2+T3. In other words, the permutation allows for the incorporation of additional tables or removal of tables providing completely different configurations and numbers of table to vary the seating capacity, orientation, or any other aspect of the table combination in the sub area or area.
Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications, but more specifically with the following related patent applications:
The restaurant set-up rules shown at (278) in one embodiment also include set-up rules for all other spaces or purposes such as for the set-up and booking of functions and/or events with an area, subarea, private room or the entire restaurant. In a further embodiment the set-up rules referred to at (278) also refer to function spaces, event spaces, theatre, show and other spaces, such that a complete event can be enquired, modified, confirmed with or without part or full payment on-line and without the requirement of manual intervention by venue staff.
Embodiments are further described in related co-pending patent applications, with particular reference to the following related patent applications:
1. Functions—as Described in Table 1
In a further embodiment, the restaurant set-up measurements provide information that permits a venue to detail the normal or standard set-up for a restaurant including the type, size and normal number of chairs that would be used for a table at a particular location. The restaurant set-up information can be used to determine if more than the standard number of chairs normally set for that table at that location is the physical maximum number of chairs that can be allocated to the table. In a further embodiment the restaurant set-up information can include information which indicates where one or more extra chairs can be placed on a table to increase the capacity of a table (which may also be determined by the relative location of the table in the venue).
For example where a table of two is placed up against a wall (and, hence the wall side is unusable) but, the other side can take an extra chair (as that chair will not be in a walk-way or interfere with any other table, the system is aware of the constraint and can add an extra chair to the table to increase its capacity if required during the booking allocation process.
In a further embodiment the information where the “change” of a table top from say one that is say 750 mm by 700 mm to one that is 800 mm round to permit the seating of 4 people and not 2 (as per the original 750 mm by 700 mm) in the same location, the restaurant set-up rules can include information as to when a restaurant reaches a certain threshold or capacity, such that the rules and algorithms can be used to apply one or more of increasing the capacity to some or all the tables to the maximum number of chairs; or to the maximum table top size, or some other permutation within the information provided and available within the restaurant set-up rules.
In another embodiment the restaurant set-up rules can be combined with any other information or any other permutation of the available information as described herein such that the restaurant allocation rules and algorithms can achieve any of the required quantitative and qualitative outcomes desired by the restaurant. For example, knowledge of the restaurant space, tables, table classes, table locations can be used in conjunction with the information available within a customer's history or CRM to allocate the customer's booking request instantaneously to their favourite or preferred table and preferred chair, or if the customer's favourite is not available to the customer's second preferred table and a preferred seating position, or failing that allocate the booking request to the next highest ranking class of table or table location as so on until that booking is allocated.
In one embodiment, the allocation of a booking can be associated with one physical space, physical item and the same booking can be transferred to another physical space or physical item such that a booking can comprise more that one “experience”. For example, a booking can be allocated to a bar table or bar stool for say 7 pm to 7:30 pm and then moved to the main dining room from 7:30 pm to 9:30 pm and then back to the bar at 9:30 pm for a night cap. In a further embodiment, as this sequence of events can treated as a single booking during the booking allocation process then the system can maintain all financial details and information within that one booking and one account so that information does not have to be manually transferred, or manually reconciled, including any pre-payments within the system or the process by which it is integrated within any POS system.
In a further embodiment the restaurant set-up rules referred to above could be applied to other industries and businesses including, for example, hairdressers, gyms, libraries, accommodation, car rentals and aviation, or any business that requires the allocation of a physical space, physical item during a booking allocation process.
In a further embodiment, the framework, rules, methods, procedures and algorithms, of the current invention can also be applied to the booking of appointments where the primary purpose of the appointment is not the physical space or a physical item but the provision of services such as legal advice, accounting advice, doctors' appointments, hospital appointments etc.
Menus (280): Menus and the use of menus, rather than simply being a presentation of products available for purchase, are integrated into various aspects of the broader system These include channel and widget configuration to offer different menus, not only by time, but by other constraints such as class and specific table; availability and search by different courses and menus; the ability to require customers to commit to different menus and different courses at different times; the ability to recognise and identify different channels and customers to offer specific menus and tailored menus with different conditions such as duration times, prices, payment conditions etc.; eliminate the need for indicating allergy details on menus as alternate menu items would be displayed that did not include the “offending” allergic ingredients, similarly with dietary requirements; the use of alternate menu items not only makes the display to the customer more friendly and personal but permits proper stock decrementing and revenue/sales analysis; the requirement for a customer to select a menu and the number of courses so that more accurate duration times can be calculated or requiring customers to accept variable duration times based on the number of courses they have selected in conjunction with one or more other constraints (such as occasion, time of booking, group size, etc.) in determining the duration a booking would be permitted to occupy a table; the integration of menus into a “product tree” to permit the seamless integration of pre-orders into point of sales systems and the seamless integration of the reconciliation process of prepayments and deposits without the need to create separate pre-paid accounts within POS systems. These embodiments shown at (280).
In one embodiment, the claimed invention includes the ability of the operator to offer different menus with different dishes, different prices, different numbers of courses, different time durations and can be incorporated with different time durations and that specific information can be used and applied as part of the optimisation and booking allocation process.
In one embodiment, the booking allocation system can identify the customer seeking to make a booking and present them with an individual menu or another specific menu and with the knowledge of the individual access that individuals CRM details and apply other additional constraints with respect to their menu selection such as a different duration time or a different duration time at their preferred table as part of the optimisation and booking process.
In one embodiment, a customer can be required to select a specific menu and or courses and with that required selection would be a set time such that the selection of the menu item and/o courses, a specific time duration could be applied to that selected menu and courses, incorporating other additional constraint information such as group size, occasion, day of the week, time of booking etc, to apply and or determine a duration time to be applied to that booking request and for that duration time to be used and applied as part of the booking allocation process.
In one embodiment, a customer who has an allergy or dietary preference is only shown dishes that are compatible with their requirements, such that the menu item displayed does not include the inappropriate ingredients and simply shows the menu item as the dish will be presented when cooked.
In one embodiment the booking allocation system contains a menu building module and/or a separate menu building module includes a product tree structure for the development of menu items (products) that contain ingredients for stock decrementing as well as alternate menu items and ingredients where those menu items are modified for allergies or dietary requirements so that proper stock decrementation can occur. In one embodiment, each menu item by being linked to a product tree permits seamless integration with POS systems, kitchen and bar printing.
In a further embodiment pre-orders are linked to the booking and there is no need to manually re-enter any pre-payments or pre-orders to a POS system as prepayment accounts as prepaid amounts can remain and be controlled within the ordering system and the booking allocation process such that an automatic reconciliation process can be applied when the booking arrives such that the manual transfer between accounts is not required.
Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent application, but more specifically with the following related patent applications which are incorporated herein by reference:
1. Menus—as described in Table 1
2. Widget—as described in Table 1
3. Yield management—as described in Table 1
4. POS Transactions—as described in Table 1
5. Rosters—as described in Table 1
6. Functions—as described in Table 1
7. Artificial Intelligence—as described in Table 1
8. PCT Applications—as described in Table 1
Dynamic Pricing and Dynamic Product and Service Promotional Offers (282): The embodiments described herein include the complete differentiation of the products, services and benefits that can be utilised in the differentiation of a product and service during a booking or appointment process; the use of the complete list of options available for the differentiation of the product or service to create a unique set of differentiated products and services as compared to competitors that can then be offered to their customers; the use of the differentiated products and services as part of a booking or appointment process.
Through these processes, a restaurant online booking process, or other booking or appointment process can be used and permits a restaurant or other business to apply proper and complete yield management including dynamic pricing, peak period pricing, higher pricing of tables with better or higher utility, etc., as compared to the current practice of only offering simple discounts during off-peak periods and incorrectly referring to this as yield management. In a further embodiment the use of and the ability of adding the tailoring of a dining or other bookable experience or appointment such that additional, related or the simple re-arrangement of the sequence of activities can offer greater satisfaction and personalisation to create a total revenue management process. These embodiments are shown at (282) and include the differentiation of products.
In one embodiment additional constraints have been developed and incorporated within the booking allocation system including through the use of the volumetric framework within one embodiment of the invention to permit a full and complete differentiation of the products and services offered by a restaurant including differentiation not considered or accounted for by the prior art including by location, by ambiance, by class, by privacy, by individual table, by ranking of each individual table, by menu, by number of courses, by occasion, by category of customer, by ranking of customer, by event, by conditions or constraints by time of booking, by payment terms, by additional supplementary items committed to, by channel and then these additional differentiation aspects being incorporated and used within the booking allocation process so that the a restaurant can configure these items to optimise their preferred quantitative and qualitative outcomes.
In one embodiment the additional product differentiation referred to above is utilised by the claimed invention to permit the control of capacity offered by differentiated products and services and then to apply yield management techniques which permit the incorporation of dynamic pricing, differential pricing by the differentiated items. In a further embodiment the incorporation of additional and supplementary items including the ability to tailor the sequence of events within a booking or appointment (as one simple example of this embodiment is the ability to permit customers to design their own sharing platters and eliminating the need have an entrée and/or a main course in a traditionally three course a la carte restaurant.
In one embodiment the incorporation of configurable promotions, configurable back fill promotions, and interactive tactical upsell promotions to people hesitating during the booking process or to people who have already booked or to encouraging people to pre-order or while at the restaurant in-service ordering process.
In one embodiment the incorporation the sale of specific tables or packages by individual sale by the restaurant or through an “exchange”, “website” or other process that permits the resale of the tables and packages.
In one embodiment there is provided a module that allows the incorporation of additional third-party or ancillary items to personalise the restaurant experience, change the order of service, provide bespoke offerings and experiences not normally or traditionally provided by restaurants, upsell during the booking and ordering process unusual items so that a restaurant can create greater differentiation to competitors. These experiences are not limited to the experiences normally provided by restaurants but targeted at experiences and offering that are outside existing norms to include anything desired by a customer and within the level of acceptability of the restaurant. In a further embodiment the additional information, spending and revenue for a booking can be used within the booking allocation process to provide higher spending, higher revenue, higher contribution or other classification of customers, or more specific experience requirements in the booking allocation process of the claimed invention. In one embodiment this can result in a higher spending customer being given a better table or being provided with an upgrade to a better class of table, extended duration or other benefits or preferential treatment.
Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications, but more specifically with the following related patent applications which are incorporated herein by reference:
1. Widget—as described in Table 1
2. Yield management—as described in Table 1
3. Space—as described in Table 1
4. Exchange—as described in Table 1
5. Gaming—as described in Table 1
6. Rosters—as described in Table 1
7. POS Transactions—as described in Table 1
8. Artificial Intelligence—as described in Table 1
Special Events Scheduled by Venue (284): In some embodiments, there is provided a process by which special events may be included by utilising the forecasting and planning modules to create and classify specific events as “one off” events so that they can be properly understood and interpreted by the forecasting modules and therefore also correctly classified and utilised as input data by the artificial intelligence module. More specifically these embodiments are shown at (284).
Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications, but more specifically with the following related patent applications which are incorporated herein by reference:
1. Yield Management—as described in Table 1
2. Rosters—as described in Table 1
3. Artificial Intelligence—as described in Table 1
CRM (286): In the embodiments described herein, the CRM is not merely a repository of information and historical data base, as is the case with all prior art, but is a system that contains constraints and information that can be accessed and utilised as part of the booking allocation process. These embodiments include the allocation of a Super VIP and or VIP to their favourite or preferred table automatically during the booking allocation process and not through a manual allocation process undertaken after the booking is accepted, as is the case with the prior art.
Further, in additional embodiments the restaurant or the venue can provide additional information and constraints as to how this CRM information should be utilised, how it should be enhanced, modified or applied during the booking allocation process, including, the addition of complementary items being added to their “running sheet” or “order of service” for their booking, for example, a free glass of wine, or an extended booking duration time, that no deposit or prepayment is required unlike other bookings or other benefit or information.
In a further embodiment, the booking allocation process can automatically embellish the booking allocation process by permitting differentiation between customers and better tailoring and personalise a person's restaurant experience. More specifically these embodiments are shown at (286). Embodiments and aspects of this application are supported by, and with further details provided within all the additional related patent applications:
External Websites (288): In some embodiments, external websites are utilised as not merely a source of information or reference data but as data and information that can be accessed and utilised in the booking allocation process. Embodiments of the allocation methodology, processes and rules can include, a person's social media influence rating, a person's occupation, or other distinguishing feature as inputs to determine the constraints to be utilised by the booking allocation process. More specifically these embodiments are shown at (288).
Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications.
Forecasting and Predictive Model (290): The level of detail used by the embodiments in the differentiation of the product or service, yield management, dynamic pricing, revenue management, the detail within a restaurant the personalisation of services etc., allow the forecasting and predictive model of the embodiment to be extremely sensitive and therefore results in far more accurate forecasts and predictions as there is greater monitoring ability as well as “levers” to make changes to achieve desired outcomes.
Specifically in one embodiment the forecasting and predictive model directly accesses the extensive constraints, variables, inputs, historical outcomes and trends, allocation rules, as well as planned events, third party websites, and use that information to develop its forecasts and then to monitor activity against those forecasts by the allocation methods, procedures, algorithms and allocation rules in the allocation of bookings to a space, a table, a table combination, chair or other item to achieve better forecasts and to make changes to the constraints so as to achieve even better outcomes. Embodiments also include the forecasts of functions and events as well as the monitoring of those events and the recommendation of changes or the making of changes to the applied constraints; booking capacities; booking classes; staffing; rosters; resource requirements; operational requirements; maintenance requirements, etc. More specifically these embodiments are shown at (290). Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications, but more specifically with the following patent applications:
1. Yield management—as described in Table 1
2. Rosters—as described in Table 1
3. Artificial Intelligence—as described in Table 1
4. Functions—as described in Table 1
5. Operations—as described in Table 1
6. PCT applications—as described in Table 1
Suppliers (292): Orders; Deliveries; Constraints, details etc. (292) The embodiment includes the ability to link a supplier to the booking allocation process such that the suppliers items can be offered within the booking process, the selection of what a person has chosen can then be added to the booking allocation process and algorithm and then an order be placed with the supplier when a person confirms their booking to create a completely integrated process. Embodiments of this process are supported by, and with further details provided within the additional related patent applications.
Database of Booking Requests (294): In one embodiment, the historical booking requests are directly accessed by the booking allocation methods, procedures, algorithms and allocation rules for the allocation of bookings to a space, a table, a table combination, chair, other item or for the allocation or creation of an appointment.
In a further embodiment additional information can be added to the data base of historical booking requests, their behaviour at the restaurant, the allocation provided to them in previous booking requests, overall demand for a time or a service that could not be satisfied and the timing and booking profile of those bookings, etc., (294) Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications.
Optimisation Quantitative and Qualitative Strategic Rules and Outcomes (296): Embodiments of the allocations, methods, procedures, algorithms and allocation rules include the creation of specific rules to undertake specific outcomes which can be selected by a venue to create specific outcomes dynamically (the prior art cannot dynamically allocate bookings and relies on a predetermined single priority table and table combination list to allocate bookings).
The specific dynamic allocation can also be combined in different sequences combinations by different time periods, different services, etc., so as to create bespoke outcomes for the benefit of individual venues to better meet their targeted goals and the requirements of their customers. Embodiments with respect to this aspect are not limited to the following examples, detailed; Floor Space Optimisation Algorithm; Time Related Optimisation Algorithm; Event Related Optimisation Algorithm; Strategy Related Optimisation Algorithm; Third-Party Optimisation Algorithm; Pre-service Optimisation Algorithm; In-service Optimisation Algorithm; Self-Seating Optimisation Algorithm (296). Embodiments and aspects of this application are supported by, and with further details provided within all the additional patent applications:
1. PCT applications—as described in Table 1
Resource Parameters (298): The resource parameters include; Venue set-up times, bar set-up times, hosting requirements, kitchen set-up times, roster structures and frameworks including staff metrics such as customers that each staff member can cater for, minimum staffing levels, amount of food that each chef or food station can produce, minimum hours, pay rates, broken chairs, broken tables, equipment out of service etc. (298). Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications, but more specifically with the following patent applications:
1. Rosters—as described in Table 1
2. Operations—as described in Table 1
3. Artificial Intelligence—as described in Table 1
Reporting (231): Performance analysis; Customer satisfaction; Deliverables; Labour Analysis; Actual v. Predicted etc. (231) Reporting relates to the additional constraints possible within the claimed invention and the analysis of those constraints and their outcomes. In one embodiment, reporting relates to the use of that analysis to better forecast and utilise that information to create a feedback loop and information to the artificial intelligence module so that it can continually learn and improve this processes and outcomes. This application is supported by, and with further details provided within the additional related patent applications, but more specifically with the following patent applications:
1. Yield Management—as described in Table 1
2. Artificial Intelligence—as described in Table 1
Database Historical Information (233): Database historical information relate to information not currently available or used by the prior art. This information includes: booking duration times by courses, by individual table, by class of table, by occasion etc.; the time bookings made—booking time; classes of bookings; spend by booking types; yield management outcomes; revenue efficiency; walk-in promotions; etc. and wherein this information can be accessed and utilised within the booking allocation process and all other modules including forecasting and artificial intelligence (233) this application is supported by, and with further details provided within the additional related patent applications, but more specifically with the following patent applications, but more specifically with the following patent applications:
1. Yield—as described in Table 1
2. Artificial Intelligence—as described in Table 1
External Websites (235): External websites including weather information relate to information that is accessed and used by the current invention within it booking allocation process, forecasting and artificial intelligence. Embodiments relating to the use of information from external websites within the claimed are supported by, and with further details provided within the additional related patent applications.
Printed Operational In-Service Run Sheets (237): Printed operational and in-service run sheets relate to information that includes the results of the autonomous booking allocation process, the autonomous chair allocation or selection process etc., and is supported by, and with further details provided within the additional related patent applications.
Operational Requirements and Planning (239): Operational requirements and planning within this application refer to staffing levels; rosters, including roster frameworks and standard rosters, roster creation, staff allocation to rosters, adjustments to rosters based on bookings received as compared to bookings forecasted; start/finish times, including pre-times, set-up times, closing procedures and times; orders; delivery schedules; maintenance planning; equipment replacement; occupational health and safety; procedure and policy monitoring; etc. (239). Embodiments within this aspect of the application are supported by, and with further details provided within the additional related patent applications, but more specifically:
1. Rostering—as described in Table 1
2. Operations—as described in Table 1
3. POS Transactions—as described in Table 1
Point of Sale Integration (241): In one aspect, embodiments of the point of sale (POS) integration relate to transactional aspects. These embodiments include the “real time” dynamic floor plan created by the claimed invention being integrated into POS systems with or without the application of the Cartesian “volumetric framework” (which in one embodiment includes more than a three dimensional volumetric framework, as it can include more than three axis) within the integrated POS systems such that the “real time dynamic floor plan” including details of the table, the chairs and booking details by chair, replaces the existing static floor plan within the prior art POS systems. The benefits of this dynamic real time floor plan ensure that restaurant tables are always shown as how they appear in real life, that the tables have the correct table numbers, that the tables show the correct chair set up and all pre-orders are shown on the correct table and the correct chair numbers that change in accordance with the customers request and the booking allocation process.
In a further embodiment any pre-payments, part payments or deposits including food, beverage and other items are transferred and referenced in detail by the booking system or ordering system, to the POS system on arrival and eliminate the need for the opening of pre-paid accounts within POS systems or other accounting systems which then require manual transfer of amounts between accounts etc. and a subsequent manual reconciliation process. Embodiments, therefore include integrations for dynamic floor plans; table and chair seating plans, allocations and details; orders; payments; deposits; sale items; Etc.; CRM detail integration as it related to the booking allocation and ordering processes of the current invention (241) Embodiments of this application are supported by, and with further details provided within the additional related patent applications:
1. POS Transactions—as described in Table 1
2. Space—as described in Table 1
3. Menus—as described in Table 1
In a further embodiment, the booking allocation system incorporates a transaction system that replaces and enhances the functionality of a traditional P.O.S. system. A transaction system is far more efficient and renders a traditional P.O.S. system obsolete, as most transactions do not occur at one point (hence the current name and terminology of Point-of-Sale systems) but the transactions occur at multiple points and the traditional P.O.S. systems no longer represent an efficient core revenue or accounting system.
In a further aspect the current invention with respect to POS systems relates to the integration and use of POS systems with a booking allocation system such that a person making an order at a counter can be allocated a table and or seat within the venue at the same time with or without a stipulated duration time. In another embodiment a person making an order at an ordering kiosk within a venue can be allocated a table or a seat at the venue with or without a stipulated duration time. In another embodiment where a person is allowed to enter a venue and choose a table or seat of their choice and then order, the embodiment through the integration of a booking system can advise the person how long they can occupy or use the table or chair. In another embodiment through the integration of a seating kiosk (self-seating kiosk), an appointment app a person can be allocated a table including duration permitted. In other embodiments the application of the invention to gyms, hairdressers and even to the appointment setting processes of lawyers etc. Embodiments of this application are supported by, and with further details provided within the additional related patent applications and more specifically:
1. Ordering and Allocation Integration—as described in Table 1
Stock Control, Ordering and Purchasing (243): In one aspect, embodiments of stock control relate the creation of alternate menu item for allergies and dietary requirements of the claimed invention. In one aspect the ordering and purchasing of the claimed invention relate to the creation offering for sale items not traditionally associated with restaurants and the automation of the transactional aspects so that no manual intervention or work is required. This includes the ordering of additional tables and chairs if the allocation model determines the requirement for additional furniture. Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications:
1. Space—as described in Table 1
2. Rosters—as described in Table 1
3. POS Transactions—as described in Table 1
Home Delivery and Takeaway Integrations for Production and Time Scheduling (245): In one aspect, embodiments of the home delivery, takeaway integrations for production and time scheduling include the monitoring of time durations, and the autonomous turning on, turning off, or provision of time information concerning food production times, yield management, dynamic pricing and point of sale (POS) integration of the transactional aspects. Embodiments and aspects of this application are supported by, and with further details provided within all the relevant patent applications.
Payment Rules (247): In one aspect, embodiments of payments include the ability to have different payment rules for different menus, different courses, different booking times, different prices by booking channel, etc, so that a completely dynamic pricing system and payment constraints are created. Embodiments include; payment decision trees; prepayment and payment constraints, different channel constraints, product differentiation, dynamic pricing etc. (247) Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications.
Artificial Intelligence (251): In one aspect, embodiments of artificial intelligence include the complete automation of the entire restaurant process from a systems perspective which is beyond the ability and scope of prior art systems. Including data mining, advanced analytics, modelling and predictive analysis to automatically amend constraints. (251) Embodiments and aspects of this application are supported by, and with further details provided within additional patent applications and more specifically by the following applications:
1. Artificial Intelligence—as described in Table 1
2. Yield Management—as described in Table 1
Alternate Payment Systems (253): In one aspect, embodiments of the alternate payment systems is the ability of a venue to offer alternate payment such as a progress payment option, not available within the prior art. This becomes a viable option within the claimed invention as the autonomous reconciliation of part payments means that the manual reconciliation processes and labour burdens of the prior art are no longer cost prohibitive. Embodiments and aspects of this application are supported by, and with further details provided within the additional related patent applications.
Referring to
Processes, Methods and Algorithms within the Current Invention
User, in one embodiment (255)
Various Configurable Access Channels, such that the offers, products services etc., can be completely different by channel (257)
Configurable User/User Interfaces: Restaurant booking widget, function booking widget, self-seating kiosk, self-seating app, restaurant booking app, menu pre-ordering app/widget, promotional apps/widgets, booking form, and integrated systems such as POS systems. (259)
User requirements used in the Booking Allocation: Buy a specific table, request a specific table, request an extended dining duration, flowers, chocolates, card, entertainment, gift, different order of service, personal waiter, specific personal waiter, budget, occasion etc. (261)
Strategic Control of Capacity, Product and Services for Booking Allocations: Strategic capacity availability by Area, Sub-area, Section and Class. Strategic Product and Service Availability by Menu, by Courses, by Variable Time Durations to meet revenue and yield management targets. (263)
Booking Allocation for the Optimisation of Space: (Sale of specific tables with guaranteed allocation, Super VIP guaranteed seating, VIP prioritised seating, Optimisation of remaining table allocations to Area, Sub-areas, Sections and Classes based on venue strategy, the introduction of additional tables and/or chairs, the removal of tables and/or chairs, the interchange of tables, the interchange of table tops, etc. (265)
Payment/Deposit Confirmation (267)
Butler Service: Ordering of 3rd Party Services/Products, the changing of the order of service, the introduction of items not traditionally offered by restaurants. (271)
Time-Related Booking Optimisation: At a predetermined time (e.g. 1 hr before service), reallocation of all bookings to offer the best tables to the highest ranking, non-guaranteed table-allocated customers (Musical Chairs) (269)
Event-Related Booking Optimisation: At the occurrence of an event, e.g.: Rain, reallocation of outdoor bookings to tables in undercover Areas, Sub-areas, Sections and Classes. Such a reallocation can be automatic through a linking of the booking process to a third party weather site or through a re-allocation allocation process that has been programmed and can identify the weather affected tables. (273)
Capacity-Related Booking Optimisation: An event that a particular class of table is at full capacity, a determination if demand for other classes of tables is such that they can be reduced and additional tables offered for the class in demand. (275)
Strategy-Related Booking Optimisation: An ambience re-allocation: if restaurant is not expected to fill up or other parameters apply. (277)
Third Party Information Booking Optimisation: Theatre information, website information which may have an impact on capacity decision. E.g. allocating bookings to a minimum space in anticipation of a full theatre next door. (279)
Pre-service Booking Allocation Optimisation: A final optimisation before service taking all the above factors into account, as well as opening up capacity for walk-ins, if such capacity had been previously excluded from the allocated capacity. Creation of run sheets and service notes for staff. If a venue selects self-seating option, floor plans and seating locations as they would appear at time of arrival of each booking are sent to each customer. (281)
Cockpit Dashboard: Dynamic Floor Plan; Time-based floor plan, the booking system having an inbuilt POS system, and the ability to take orders, receive orders, reconcile accounts, etc. including integration to other systems including other POS systems to create a completely integrated dynamic real-time systems environment (283)
In-service Booking Allocation Optimisation: Optimisation can be based on any combination or permutation of the above optimisation algorithms or different algorithms which can only use tables located within the restaurant and/or without moving pre-allocated bookings and/or allocating bookings based on space optimisation or other dimension such as allocation to the best table. (285)
Self-Seating Kiosk (Booking Allocation): Applicable for venues that have selected the self-seating option. The kiosk can provide information on the seating location of confirmed bookings as well as the ability of accepting new walk in bookings as well as providing direction such that a host or someone to seat guests is not required. (287)
Autonomous Restaurant and Complete Integration: Fully integrated information system including table and position sensors. (289)
Point of Sale System: A fully integrated with dynamic real-time table plan layout with orders sent to kitchen and bar as appropriate and automatic reconciliations. (291)
Payments: Fully integrated with links to original booking including part payments by table, customer and position number. (293)
Accounting System: The complete integration of the booking systems with all accounting and transaction systems to produce all reports including revenue; P&L statements such that manual input is minimal (295). Including the implementation of a volumetric framework within the various accounting systems, for example the use of the volumetric framework for per-ordering, the POS system and other accounting systems.
Referring to
Prior Art (223)
User (2000)
Access Channels (2002)
User/User Interfaces: Restaurant Booking Widget, Booking Form. (2004)
User requirements used in the Booking Allocation: (Prior Art) Date, time, meal period, pax (2006)
Strategic Control of Capacity, Product and Services for Booking Allocations: (Prior Art) Capacity and Max Group Size by booking time interval for a standard time duration for the whole service or by group size (2008).
Payment/Deposit Confirmation (2010)
Allocation of Booking Request: (Prior Art) Use of a prioritised list of tables and table combinations to allocate bookings. Prior Art process finishes with this step. (2012)
Dashboard: Static Floor Plan (2014)
Payments (2016)
Referring to
Restaurant Set-up Rules: Open/closed; Meal periods; Floor Plan (not to scale); Seat block-outs; Rooms, Areas, Bars; Tables and table combinations prioritised list; Standard booking time duration or by group size (2020)
Promotional Offers: Discount by time interval (2022)
Database: List of unused tables and table combinations (2024)
It will be understood that the description with regard to
It will be understood that the description with regard to
Moreover, there is described below a series of algorithms, which for convenience, are numbered. However, it will be understood that each algorithm is independent, and the numbering is not reflective of any specific order in which the algorithms are to be applied. The embodiment may apply one or more algorithms dependent on constraint information and the application can be separate to other algorithms, in conjunction with one or more other algorithms, in different sequences with the one or more other algorithms to achieve the desired outcomes for the booking time period in question. The application, sequence, mixture of the algorithms can be configured by each individual restaurant in accordance with their individual strategies and required outcomes.
The first embodiment referred to as the First Algorithm is termed the “Strategic Capacity Control” algorithm, module 263, which makes an assessment of requests based on availability with reference to allocations by space, subspace, class, by time, allowing capacity for walk-ins, by menu, by course, etc.
The second embodiment referred to as the Second Algorithm is termed the “Optimisation of Space Outcomes” module 265, and is relevant to guaranteed table allocations. The algorithm which is an iterative seating optimisation algorithm which is arranged to allocate seating first to Super VIP's and guaranteed seating allocations then based on availability by VIP, group size, etc., to optimise the allocation and position of tables. This algorithm is arranged to optimise floor space efficiency around guaranteed table allocations.
The third embodiment referred to as the Third Algorithm is termed the “Time Related Optimisation” algorithm, module 269, which is best described by an example. For example, one hour before service, if it is decided that no new tables should be added, all bookings are reviewed, and, if there are two different bookings at 6 pm and one booking is from a regular customer and one is from a first time visitor, the regular customer is allocated to the better table and the first time customer is allocated to the other table.
The fourth embodiment referred to as the Fourth Algorithm is termed the “Event Related Optimisation” algorithm, module, 273, which is triggered or undertaken by the occurrence of an event. For example, if it rains, the algorithm would re-allocate part or all of the bookings to outside tables to inside tables as all or part of the outside tables may be rendered unusable.
The fifth embodiment referred to as the Fifth Algorithm is termed the “Full Capacity Optimisation”, module, 275, which is triggered or undertaken when one space, subspace, or class is full. For example, if a specific class within the restaurant was full the algorithm would evaluate if demand for the other classes for that service had availability. If other classes had availability then it would determine if those tables would be filled and what the revenue and contribution would be and if it then determined that it would be best to increase the size of the class that was full and reduce the seating availability in another class it could do so and increase the capacity within the class for which the booking request was received and allocate the booking request against one of the additional tables created in the expanded class.
The sixth embodiment referred to as the Sixth Algorithm is termed the “Strategy and Ambiance Optimisation”, module 277, algorithm. All bookings are reviewed, and if it is found that the restaurant will not be at capacity, the bookings are spread around the restaurant so that a better ambience is achieved within the restaurant. For example, if a restaurant only has two bookings for a Monday evening, the Second Algorithm may have sat both bookings next to each other in a back corner of the restaurant as this was the most efficient use of the restaurant space. This algorithm recognises that this arrangement is not an ideal seating arrangement for an empty restaurant and allocates the two bookings in this example to give both bookings the two best available tables.
The seventh embodiment referred to as the Seventh Algorithm is termed the “Third Party Information Optimisation”, module 279 algorithm. For example, the optimisation algorithm could access third party information such as the bookings for the local theatre and the start and finish times of a show to determine capacity allotments and constraints. Further, it can determine not to offer discounts or promotions at 9 pm as the theatre will finish and it expects numerous walk-in customers.
The eighth embodiment referred to as the Eighth Algorithm is termed the “Pre-Service Quantitative and Qualitative” algorithm, module 281. This is the final optimisation algorithm before a service and can be a combination of one or more of the previous algorithms at the discretion of the restaurant manager. It is run at a predetermined time before service and is also used to create run sheets and provide information to restaurant staff as well as provide final seating plans and arrangements for self-seating customers. As another example, as a restaurant can be split into different classes part of a restaurant can offer self-seating and part of a restaurant can offer full table service.
The ninth embodiment referred to as the Ninth Algorithm is termed the “In-service Allocations without additional tables or changing existing table allocations” algorithm, module 285. This algorithm is executed after service begins and new bookings are limited to the use of only tables physically available within the restaurant. The in-service optimisation process uses the In-service Allocations algorithm to provide a limited optimisation process which limits the allocation process by means of additional constraints to optimise request allocation process with minimise the disturbance to current patrons.
The Ninth Algorithm is not mandatory as the eighth algorithm or any other algorithm or a combination thereof could continue to be used without the need to unseat existing bookings whilst maintaining the ability to add or remove one or more tables. Further, additional algorithms or variations of the booking algorithms could be added to provide additional and different allocation outcomes and as a consequence provide additional tools for both the customer and the restaurant to achieve their preferred objectives and customer service standards.
Referring to Annexures 1 to 11 details are provided of the measures and metrics used by the prior art and by the embodiments and broader invention described herein which are significantly greater and beyond the scope, functionality, integration and ability of the prior art. Specifically the prior art measures and metrics are contained within Annexure 1 while embodiments of the measures and metrics utilised within our claimed invention are detailed in annexures 2 to 11. The prior art is extremely limited in the ability to analyse and report as the prior art firstly does not appreciate and recognise the importance of additional measures and metrics for reporting, forecasting and artificial intelligence. Secondly the prior art does not have the structures, methods and procedures to be capable of calculating the measures and metric calculations to achieve better outcomes. Two such measures are “revenue yield” and “efficiency”.
Referring to Annexures 1 to 11 the following references are provided as a summary of the measures and metrics detailed within the Annexures:
Annexure 1 Prior art measures and metrics: This annexure highlights the prior art metrics and measures are limited to a limited number of practical and theoretical measures that are used and taught within universities to measure restaurant performance and measurements.
Annexure 2 Floor plan guidelines, rankings, and space efficiency measures for the claimed invention: This annexure provides variables related to spatial guidelines and measures, such as; floor space allocation, dining, bar and customer spaces, table top guide, fixed and flexible seating areas including walkways, chair size guide, spacing between tables, waiter stations guide, bar space and bar stools guide, area per person size guide, area per person size guide, area, sub-area, class, section, and table and stool rankings, table analysis, tables for sale, tables for auction, tables dedicated to specific channels, location analysis and floor space efficiency.
Annexure 3 Capacity utilisation and revenue efficiency measures for the claimed invention: This annexure provides variables related to capacity, utilisation and revenue efficiency measures, which include the concept of dynamic floor plans which is a concept of the claimed invention where by additional tables and chairs can be added to a floor plan during the booking allocation process and these additional tables and chairs need to be included within these performance measures and metrics. These measures and metrics include; revenue yield, seat capacity (production) and utilisation, table capacity (production) and utilisation, units of measure of capacity, physical constraints, hours open, service periods open, service hours open, back of house (kitchen) hours, front of house (dining room) hours, revenue measures.
Annexure 4 Booking Analysis for the claimed invention: This annexure provides variables related to booking analysis, such as; Booking requests allocated analysis, booking profile analysis, booking requests rejected analysis, source of booking analysis.
Annexure 5 Duration Time Analysis for the claimed invention: This annexure provides variables related to duration time analysis, such as; duration times by booking size, by occasion, by menu selected, by courses selected, by booking time, by booking day, by customer type, by requests for extended durations, by duration times extended, by table, by class.
Annexure 6 Product Mix Analysis for the claimed invention: This annexure provides variables related to a product mix analysis, for areas, subareas, classes, sections, tables, distribution and channel for items such as; food: by time, by service, by day, by server, by channel; Beverage: by time, by service, by day, by server, by channel; Supplementary items: by time, by service, by day, by server, by channel.
Annexure 7 Revenue and Customer Performance Analysis for the claimed invention: This annexure provides variables related to revenue and customer performance analysis, such as; detailed revenue analysis, detailed customer analysis detailed customer ranking and detailed channel analysis.
Annexure 8 Staff and Roster Parameters for the claimed invention: This annexure provides variables related to staff ratios, requirements, hours, set-up times for the creation of forecasted rosters, performance measurements against those rosters and the use of artificial intelligence to update and maintain those performance measures and use the information to create further improvements to those rosters.
Annexure 9 Profit and Loss Layout (a la carte) structure and definitions for variable costs and fixed costs and contribution analysis for the claimed invention: This annexure variables related to the structure and the relationship between revenue and costs and how those revenues and costs can be determined and understood from a contribution perspective and marginal cost perspective such that decisions and actions taken can be measured in terms of cash generation, contribution and performance for reporting, forecasting as well as for feedback in the artificial intelligence loop.
Annexure 10 Break Even Analysis, Contribution Margins and Variable Pricing Analysis for the claimed invention: This annexure provides variables related to the specific analysis of the financial performance of the claimed invention, the monitoring of the financial performance, for forecasting and for the use of these measures and metrics for learning and artificial intelligence within the framework of the other annexures detailed within this embodiment. This analysis includes; break even analysis utilising the defined profit and loss statement within annexure 9 and other cost performance and analysis measures.
Annexure 11 Supplier Pricing Comparisons and Monitoring for the claimed invention: This annexure provides variables related to requesting comparative pricing, supplier performance and reliability and the monitoring of their performance for recommendations and the automatic placement of orders.
Those skilled in the art can appreciate that the structure of the claimed invention, and more specifically with the measures and metrics referred to within the annexures, that these measures and metrics can easily be converted or adopted within the other industries referred to and to which this claimed invention can be applied to.
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Importantly, at a practical level, the starting floor plan also serves as a visual indicator to a restaurant operator and other staff, as it serves as a visual “starting point” so that, before bookings are received, the operator is given a sense of the likely layout of a restaurant.
Turning to
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Referring to
At step 601, restaurant setup is selected. Thereafter, the operator selects a sub area setup option 629. A new sub area option is selected at 631, after which a name is input 607, a description is input 609, a length value 633 is input, a depth value 635 is input, a restaurant is selected 615 and an area is selected 637. Thereafter, the operator has the option to define whether the area may be affected by weather conditions 638, the option to “turn off bookings” 639 (so that the algorithm will not allocate bookings to the sub area), select an enable checkbox 621, which allows for the utilisation of the sub area on the floor plan, and finally the operator saves the sub area setup at step 623 and the process ends at 625.
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At step 805, if the operator selects rectangle table type, the operator can then ascribe a name to the table type at step 607 (a free form name that may have significance to the operator), after which the operator inputs a table length at step 807, a table depth at step 809, a chair configuration option at step 811, a chair depth at step 813 and a chair width at step 815, before the process continues along arrow 1 which is described in
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Importantly, the floor plan setup interface also serves a second purpose, namely the provision of an interface that allows a user with little or no planning or programming experience to provide all relevant venue constraints in a manner that is visual in nature and guides the user through the necessary steps to build a comprehensive set of constraints. In other words, all prior art systems (whether related to the creation of a floor plan for a restaurant or a floor plan for any other purpose) require some knowledge of how to enter constraints, how such constraints affect the system as a whole, etc. However, in the embodiment described herein, the operator does not require any knowledge of planning, how to create specialised constraint files in specialised formats, etc. The operator simply “builds” a restaurant floor plan through the use of simple drag and drop icons and through the input of simple information, and the system generates all necessary constraints. In other words, the embodiment of the invention described herein allows for intuitive creation of a set of constraints that are then used by the allocation algorithm and other algorithms within the restaurant management and booking system to operate all aspects of the restaurant. There is no need for specialised programmer or planner input. As a corollary, where a fundamental change is required to the floor plan (e.g. all 600 mm wide tables are replaced with 700 mm wide tables), the operator simply needs to make the single change in the system, and all associated constraints which are affected by the single change are also immediately updated, with the floor plan and constraints being updated automatically. As such, decisions made regarding a change in the physical setup of the restaurant can be immediately reflected in the system, with no need for specialised reprogramming or “tweaking” of any kind.
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If the process continues to step 1107, the add furniture option is selected. This causes an interactive floor plan editing module to be displayed at step 1109. At step 1111, the operator can add walls, sections, windows, doors, walkways tables, etc., as required to correctly describe the venue and all furniture, as will be described with reference to the screenshots of
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The association of tables with channels is selectable via the interface shown at the right hand side of
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Next, at step 1607, the desired days of the week are enabled, and at step 1609, the desired opening times are set. At step 1611, the desired menu is set and then the desired days of the week are enabled for a floor plan at step 1613. The desired floor plan is selected for each enabled day of the week at step 1615, followed by the desired days of the week being enabled for the allocation rules at step 1619. Lastly, the selected constraints are posted to the calendar by meal period, day of the week and selected date range, before the process ends at step 625.
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Unlike prior art solutions, the embodiment described herein, while being comprised of different modules, works in cooperation with all computerised aspects of the operation of a restaurant. Rather than manually entering data into different systems or attempting to link (generally in a crude manner) various disparate systems, the embodiment described herein utilises a central hub (the transaction management system 1912) to ensure the entire transaction is managed correctly.
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Returning to the booking system 2382, the booking system interfaces with the volumetric framework 2348, which includes multiple files 2350, each file representing a particular service period 2350, including booking constraints 2352, available promotions 2354, allocated bookings 2358 and multiple menus 2356. In turn, the volumetric framework 2348 also interfaces with an in-service system 2311, including an in-service app 2315, a payment getaway 2317 and a docket printer 2313. The volumetric framework 2348 interfaces with a system admin dashboard 2346 and an individual or group restaurant dashboard containing menu availability setup interfaces 2362, menu setup interface 2364, and loyalty benefit set up 2366, each of which utilise logic engines 2368, 2370, 2372 ad 2374 to interface variously with the volumetric framework 2348, databases 2376 including menu database 2378 and loyalty benefits database 2380, which in turn interfaces with CRM 2305 including global CRM 2309 and individual restaurant CRMs 2307.
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Returning to the customer file 2329, the information from customer file 2329 is provided, via various APIs such as 2395, 2397 and 2399, or via the AI module 2371 and corresponding AI API 2375 to the passport 2377, through which a customer (user) can provide payment details 2379, or receive booking suggestions 2381, loyalty benefits 2383, a customer profile 2385 including customer details 2387, customer preferences 2389, field input suggestions 2391 and promotion suggestions 2393. As previously described with reference to
In short, the CRM 2325 acts with the passport 2377 via various APIs to provide a comprehensive and detailed “assistant” to simplify and enrich the experience the customer (user) has with the ResButler system. The passport acts as a portal into a comprehensive set of information that allows the CRM to integrally operate with the ResButler booking system to provide a number of functions which include but are not limited to:
In addition to the advantages summarised above, the passport is not tied to a single restaurant or group of restaurants, but provides a “global” set of preferences which allows the customer to be provided with a personalised service across all restaurants that provide a booking service through the ResButler platform. In this manner, the information in the Global database is universalised in a manner that allows the information to be used across different restaurants with different layouts, different cuisines, different menus, etc. For example, while the customer may not have specific knowledge of a restaurant, if the preference data includes information that suggests that the customer prefers a table with a view, such information can be applied to any restaurant with a view, without the need for specific knowledge by the customer. To take a more (arguably) important example, utilising allergy information, the passport, in conjunction with the volumetric framework, the CRM and the menu database, is capable of building a customised menu which automatically excludes menu items that contain allergens, and/or autonomously provide alternative menu items to the customer that do not include ingredients that are allergens. As such, the passport allows the customer to have a completely unique experience in keeping with their preferences, irrespective of the restaurant chosen, the customer's fellow diners, the service period, or any other factor that would normally result in the need for manual intervention to accommodate the customer. This information is provided to the restaurant CRM from the Global CRM autonomously.
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Returning to the customer file 23112, the information from customer file 23112 is provided, via various APIs such as 23176, 23178 and 23180, or via the AI module 23152 and corresponding AI API 23156 to the passport 23158, through which a customer (user) can provide payment details 23160, or receive booking suggestions 23162, loyalty benefits 23164, a customer profile 23166 including customer details 23168, customer preferences 23170, field input suggestions 23172 and promotion suggestions 23174. As previously described with reference to
In short, the CRM 23106 acts with the passport 23158 via various APIs to provide a comprehensive and detailed “assistant” to simplify and enrich the experience the customer (user) has with the ResButler system, with the advantages previously described.
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In one embodiment, the CRMs may exist in a strict hierarchical format. That is, information may only “flow” in one direction, with one CRM being a master CRM and the other being a slave CRM. In more detail, the Global CRM may be set up as the “single source of truth”, with information captured from the customer/client/booking requestor by the global CRM and then only provided to the Restaurant CRM as required. This hierarchical structure may be instituted to ensure that customer data is only collected by the Global CRM when the customer is making a booking via a Global Channel. In this way, any customers making bookings via any Restaurant-owned channels do not have their data copied or replicated to the global CRM, which may be important for commercial reasons (e.g. ownership of data) or for legal reasons (e.g. maintaining privacy of data). Such variations are within the urview of a person skilled in the art.
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The embodiment and broader invention described herein provides a number of advantages.
Firstly, the system allows an unskilled restaurant operator to enter information to define the space/venue, define rooms, define furniture, define classes, define menus, etc., in a manner that is instantly understandable to the restaurant operator. The floor plan configurator then utilises this information to create a series of constraints and options in a manner that is usable by the underlying allocation methodology and or the one or more allocation algorithms.
Secondly, the system allows the addition of constraints with respect to individual tables, classes of tables etc., that permit a level of product differentiation and the incorporation of dynamic pricing levels not possible under the prior art.
Thirdly, the system, once set up, works with the allocation methodology and/or the one or more algorithms to provide seamless management of all aspects of the customer's dining experience, from the initial booking, through to meal preparation, service, and payment for the dining service. As such, very little to no manual intervention is required (mainly limited to bringing the meal to the table and assisting diners with enquiries).
Fourthly, in combination with the widget and with the CRM, the system is capable of providing truly individual service not only to each dining party, but to each individual guest in each dining party. Depending on the number of options and the constraints of the venue, the system can provide billions of customised experiences, such that no two dining experiences are exactly alike. To put it another way, the system allows the diner to choose any option and any combination that is possible, without the need for intervention by the restaurant operator.
Fifthly, the system allows for the seamless integration into other financial and operational systems so as to minimise and/or eliminate all manual intervention within those systems such as the manual set-up and transfer of operational and financial information.
The use of the computer-enabled method, system and computer program disclosed herein has provided examples within the restaurant industry, however, they are equally applicable within other industries and businesses such as airlines, accommodation, hotels, travel, cruise ships, car rentals, clubs, pubs, gyms, hairdressers, workspaces, and the provision of advice and consulting services.
Throughout this specification, unless the context requires otherwise, the word “comprise” or variations such as “comprises” or “comprising”, will be understood to imply the inclusion of a stated feature or group of features but not the explicit exclusion of any other feature or group of features.
Those skilled in the art will appreciate that the embodiments described herein are susceptible to obvious variations and modifications other than those specifically described and it is intended that the broadest claims cover all such variations and modifications. Those skilled in the art will also understand that the inventive concept that underpins the broadest claims may include any number of the steps, features, and concepts referred to or indicated in the specification, either individually or collectively, and any and all combinations of any two or more of the steps or features may constitute an invention.
Where definitions for selected terms used herein are found within the detailed description of the invention, it is intended that such definitions apply to the claimed invention. However, if not explicitly defined, all scientific and technical terms used herein have the same meaning as commonly understood to one of ordinary skill in the art to which the invention belongs.
Although not required, the embodiments described with reference to the method, computer program, computer interface and aspects of the system can be implemented via an Application Programming Interface (API), an Application Development Kit (AD K) or as a series of program libraries, for use by a developer, for the creation of software applications which are to be used on any one or more computing platforms or devices, such as a terminal or personal computer operating system or a portable computing device, a smartphone or a tablet computing system operating system, or within a larger server structure, such as a ‘data farm’ or within a larger computing transaction processing system.
Generally, as program modules include routines, programs, objects, components and data files that perform or assist in the performance of particular functions, it will be understood that the functionality of the method, computer program and computer interface defined herein may be distributed across a number of routines, programs, objects or components to achieve the same functionality as the embodiment and the broader invention claimed herein. Such variations and modifications are contemplated by the inventor and are within the purview of those skilled in the art.
It will also be appreciated that where methods and systems of the present invention and/or embodiments are implemented by computing systems or implemented across multiple computing systems then any appropriate computing system architecture may be utilised without departing from the inventive concept. This includes standalone computers, networked computers and dedicated computing devices that do not utilise software as it is colloquially understood (such as field-programmable gate arrays).
Where the terms “computer”, “computing system”, “computing device” and “mobile device” are used in the specification, these terms are intended to cover any appropriate arrangement of computer hardware for implementing the inventive concept and/or embodiments described herein.
Where the terms “software application”, “application”, “app”, “computer program”, “program” and “widget” are used in the specification when referring to an embodiment of the invention, these terms are intended to cover any appropriate software which is capable of performing the functions and/or achieving the outcomes as broadly described herein.
Where reference is made to communication standards, methods and/or systems, it will be understood that the devices, computing systems, servers, etc., that constitute the embodiments and/or invention or interact with the embodiments and/or invention may transmit and receive data via any suitable hardware mechanism and software protocol, including wired and wireless communications protocols, such as but not limited to second, third, fourth and fifth generation (2G, 3G, 4G and 5G) telecommunications protocols (in accordance with the International Mobile Telecommunications-2000 (IMT-2000) specification), Wi-Fi (in accordance with the IEEE 802.11 standards), Bluetooth (in accordance with the IEEE 802.15.1 standard and/or standards set by the Bluetooth Special Interest Group), or any other radio frequency, optical, acoustic, magnetic, or any other form or method of communication that may become available from time to time.
The following is an extensive list of the current theoretical revenue measures applied to restaurants. There are no prior art systems that can provide measures related to space, classes of tables, extended durations, by differentiated products etc., as such information is beyond the capture of existing systems and hence calculations and performance monitoring and adjustment is also beyond current systems.
Floor Space Allocation
Dining, Bar and Customer Spaces (Required to Scale)
Table Top Size Guide
Fixed and Flexible Seating Areas to scale including walkways
Chair Size Guide
Spacing Between Tables (Allowing for Chairs and Movement)
Waiter Stations Size Guide
Bars Space and Bar Stools Size Guide
Area per Person Size Guide
The below measures and metrics must include additional tables and chairs added for a service and deduct the tables and chairs removed for a service. That is the use of one embodiment of the claimed invention and dynamic allocation process which permits which the addition and removal of tables from the capacity and inventory made available for the allocation of a booking. The concept of adding or removing tables and chairs from the available capacity during the booking allocation process is outside the scope (and beyond the prior art). Also refer to Annexure 7 for further details of this embodiment.
Capacity
Revenue
Utilisation
Efficiency
Costs
Capacity
Revenue
Utilisation
Efficiency
Costs
Physical Constraints
Hours Open
Service Periods Open
Service Hours Open
Back of House (Kitchen) Hours
Front of House (Dining Room) Hours
1. Food (by, time, by service, by day, by server or channel)
1. Revenue Analysis
2. Customer Analysis
3. Customer Ranking
4. Channel Analysis
1. Staff Analysis and Ratios (based on customer numbers, menu complexity and menu diversity)
Food Revenue
Beverage Revenue
Supplementary Revenue
Less: Credit Card Fees
Less: Commissions
Less: Variable Booking Fees
Less: Loyalty program allowance (“hard currency”)
Net Revenue
Food Costs
Beverage Costs
Alcoholic Beverage Costs
Non-Alcoholic Beverage Costs
Tea and Coffee Costs
Total Cost of Goods Sold
Contribution 1
Gross Back of House Wages (including overtime and temp workers)
On-Cost Back of House Wages (super, workers comp, payroll tax)
Back of House additional Costs (staff meals, uniforms, etc,)
Total Back of House Wage Costs
Contribution 2
Gross Front of House Wages (including overtime and temp workers)
On-Cost Front of House Wages (super, workers comp, payroll tax, staff meals)
Front of House additional Costs (staff meals, uniforms, etc,)
Total Front of House Wage Costs
Contribution 3
Packaging
Repairs and maintenance
Breakages
Delivery Costs
Laundry
Chemicals
Linen
Tea towels
Kitchen Duct Cleaning
Restaurant Cleaning
Garbage and Sanitation
Printing and Menus
Decoration Expenses (flowers)
Equipment Hire
Transport
Security
Variable Booking Fees
Total Operational Variable Costs 4
Contribution 4
Entertainment (Bands, Djs)
Events
Total Entertainment Variable Costs 5
Contribution 5
Social Media
Advertising
Total Marketing variable Costs 6
Contribution 6
Water
Electricity
Rates and Taxes
Utility Variable Costs 7
Contribution 7
Rental Costs
Lease marketing levy
Lease Outgoing expenses
Council Rates and Fees
Contribution 8
Depreciation
Interest
Insurance
Health Inspections and Compliance
Ownership Overhead Costs 2
Contribution 9
Administration Wages
Accounts
Marketing (Memberships and registration)
Telephone & Communications
Consultants
Computer
Head Office Overhead Costs 3
Other Items (Extra Ordinary items)
1. Break-Even Analysis
2. Profit and Loss Statement, Cost Analysis Ratios and Percentages
a) Level 1 Analysis—Cost of Goods Sold
b) Level 2 Analysis—Back of House Wages
c) Level 3 Analysis—Front of House Wages
d) Level 4 Analysis—Operational Variable Costs
e) Level 5 Analysis—Entertainment Costs
f) Level 6 Analysis—Marketing Variable Costs
g) Level 7 Analysis—Utility Variable Costs
h) Level 8 Analysis—Premises Fixed Overhead Costs
i) Level 9 Analysis—Ownership Fixed Overhead Costs
j) Level 10 Analysis—Head Office Administration Overhead Costs
| Number | Date | Country | Kind |
|---|---|---|---|
| 2019901444 | Apr 2019 | AU | national |
| 2019903010 | Aug 2019 | AU | national |
| 2019903511 | Sep 2019 | AU | national |
| Filing Document | Filing Date | Country | Kind |
|---|---|---|---|
| PCT/AU2020/050408 | 4/28/2020 | WO | 00 |
