CN113919648A - Digital catering loss early warning method, device, system and medium - Google Patents
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Abstract
The invention discloses a digital catering loss early warning method, a device, a system and a medium, wherein the method comprises the following steps: acquiring early warning target information at preset time intervals; acquiring historical purchase and operation information, and counting corresponding restaurant operation data according to the early warning target information and the historical purchase and operation information; and analyzing the loss of the statistical result of the operation data, and outputting corresponding early warning information when the operation loss exists. According to the embodiment of the invention, the early warning target information is acquired regularly, the digital loss analysis is carried out on the operation data of the restaurant according to the historical purchasing and operation information, and the early warning information is output in time when the loss exists, so that the accurate early warning is effectively carried out on the loss operation state of the restaurant, and the controllability of the loss in the digital catering is improved.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a digital catering loss early warning method, device, system and medium.
Background
Group meal, short for group meal service as the name implies, is a kind of group concentrated meal management. The group meal mainly covers various service crowds including armies, government offices, large, medium and small schools, hospitals, enterprises and public institutions and the like at present, has the characteristics of high viscosity and high frequency consumption, and has long-term and long-acting flow consumption service attributes.
Based on the characteristics of large cardinality, centralized personnel, short time and the like of group meal, compared with individual restaurant shops with small scale, if loss occurs during group meal operation, the amount of money involved is larger, the traditional catering management method is difficult to carry out accurate loss analysis on the operation condition of the restaurant, and further effective early warning cannot be carried out when the loss state initially occurs in the restaurant.
Accordingly, the prior art is yet to be improved and developed.
Disclosure of Invention
In view of the defects of the prior art, the invention aims to provide a digital restaurant loss early warning method, device, system and medium, and aims to solve the problem that accurate early warning on the loss condition of a restaurant is difficult in the prior art.
The technical scheme of the invention is as follows:
a digital catering loss early warning method comprises the following steps:
acquiring early warning target information at preset time intervals;
acquiring historical purchase and operation information, and counting corresponding restaurant operation data according to the early warning target information and the historical purchase and operation information;
and analyzing the loss of the statistical result of the operation data, and outputting corresponding early warning information when the operation loss exists.
In the digital restaurant loss early warning method, before the early warning target information is acquired at preset intervals, the method further comprises the following steps:
receiving a regular early warning instruction input by a user, wherein the regular early warning instruction comprises preset time and early warning target information.
In the digital catering loss early warning method, the early warning target information comprises an early warning type, a target restaurant and a statistical time interval.
In the digital restaurant loss early warning method, the obtaining of the historical purchasing and operation information and the statistics of the corresponding restaurant operation data according to the early warning target information and the historical purchasing and operation information specifically include:
and acquiring historical purchase and operation information, performing data screening on the historical purchase and operation information according to the early warning target information, and counting and outputting operation data of the target restaurant corresponding to the current early warning type in a counting time interval.
In the digital restaurant loss early warning method, the operation data of the target restaurant corresponding to the current early warning type in the statistical time interval is output in a statistical manner, and the operation data comprises the following steps:
when the early warning type is passenger unit price early warning, counting passenger unit price data of the target restaurant within a counting time interval;
and when the early warning type is business loss early warning, counting and outputting income and cost data of the target restaurant in the counting time interval.
In the digital restaurant loss early warning method, loss analysis is performed on statistical results of the operation data, and corresponding early warning information is output when operation loss exists, and the method specifically comprises the following steps:
when the early warning type is passenger order early warning, judging whether the passenger order of the target restaurant in the statistical time interval is lower than a preset passenger order, if so, outputting passenger order early warning information;
and when the early warning type is operation loss early warning, judging whether the cost of the target restaurant in the statistical time interval is greater than the income, and if so, outputting loss early warning information.
In the digital restaurant loss early warning method, the loss analysis is performed on the statistical result of the operation data, and after the corresponding early warning information is output when the operation loss exists, the method further includes:
and outputting reminding information of the data which does not meet the conditions when the operation loss does not exist.
The invention also provides a digital catering loss early warning device, which comprises:
the acquisition module is used for acquiring early warning target information every preset time;
the statistical module is used for acquiring historical purchase and operation information and counting corresponding restaurant operation data according to the early warning target information and the historical purchase and operation information;
and the analysis module is used for analyzing the loss of the statistical result of the operation data and outputting corresponding early warning information when the operation loss exists.
The invention further provides a digital catering loss early warning system, which comprises at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the above-described digital restaurant loss warning method.
Another embodiment of the present invention also provides a non-transitory computer-readable storage medium storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the above-mentioned digital restaurant loss warning method.
Has the advantages that: compared with the prior art, the embodiment of the invention has the advantages that early warning target information is obtained regularly, digital loss analysis is carried out on operation data of a restaurant according to historical purchasing and operation information, early warning information is output in time when loss exists, accurate early warning is effectively carried out on the loss operation state of the restaurant, and the controllability of the loss in digital catering is improved.
Drawings
The invention will be further described with reference to the accompanying drawings and examples, in which:
FIG. 1 is a flow chart of a digital restaurant loss early warning method according to a preferred embodiment of the present invention;
FIG. 2 is a functional block diagram of a digital restaurant loss warning device according to a preferred embodiment of the present invention;
fig. 3 is a schematic diagram of a hardware structure of a digital restaurant defect early warning system according to a preferred embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and effects of the present invention clearer and clearer, the present invention is described in further detail below. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention. Embodiments of the present invention will be described below with reference to the accompanying drawings.
Referring to fig. 1, the digital restaurant deficiency early warning method provided by the invention comprises the following steps:
and S100, acquiring early warning target information every preset time.
In the embodiment, loss early warning is performed through digital operation management software installed on a PC (personal computer) end or a mobile terminal, a user registers an account in advance and distributes corresponding authorities according to positions, job levels and the like of the account, operation management of grading, role-dividing and data-dividing is achieved, and information safety and operation convenience during digital operation are guaranteed. Specifically, when performing digital catering operation loss early warning, a user can enter a corresponding functional module to start loss early warning analysis operation after logging in the digital operation management software, and when performing loss early warning analysis, the system acquires early warning target information every preset time, for example, every 24 hours or every week, and the like, and specifically, the preset time can be flexibly set according to the periodic requirement of the loss early warning analysis, for example, if performing loss early warning analysis on restaurant operation every day, the early warning target information is acquired every 24 hours and then subjected to loss early warning analysis, specifically, the early warning target information includes an early warning type, a target restaurant and a statistical time interval, and the early warning target information can be manually input and set by a user with corresponding authority after starting the loss early warning analysis operation, or automatically acquired by the system before the preset time interval is reached, in order to carry out subsequent loss early warning analysis, this embodiment does not restrict this, comes to carry out comprehensive digital analysis to the loss early warning of dining room operation according to the data of these three dimensions, provides intelligent digital loss early warning suggestion for the food and beverage operation.
Further, before step S100, the digital restaurant deficiency early warning method provided by the invention further includes:
receiving a regular early warning instruction input by a user, wherein the regular early warning instruction comprises preset time and early warning target information.
In this embodiment, realize automatic and regular loss early warning through the regular early warning instruction that the user set up in advance, for example, the user can set up spaced preset time in advance and need carry out the early warning target information of loss early warning analysis, then obtain its early warning target information that sets up in advance and carry out subsequent loss analysis when every interval preset time, thereby realize full-automatic, regular loss state monitoring, for example can set up to carry out loss early warning analysis operation to the operation of target dining room in the past 24 hours every day fixed time during the regular early warning instruction, thereby obtain the state analysis of target dining room operation on the same day, so that the user can know the daily running state in target dining room constantly, effectively improve the degree of automation and the efficiency of food and beverage operation loss early warning.
S200, obtaining historical purchasing and operating information, and counting corresponding restaurant operating data according to the early warning target information and the historical purchasing and operating information.
In the embodiment, when digital catering loss early warning analysis is performed, the operation data of the corresponding restaurant needs to be counted and compared according to historical purchasing and operation information, specifically, the historical purchasing and the operation information are stored in a preset database for calling, when loss early warning analysis is started, the corresponding restaurant operation data is obtained from the historical purchasing and the operation information according to early warning target information, a real and reliable data base is provided for the loss early warning analysis, and the authenticity and the accuracy of a subsequent analysis result are ensured.
Specifically, the step S200 of the digital restaurant deficiency early warning method provided by the invention specifically includes:
and acquiring historical purchase and operation information, performing data screening on the historical purchase and operation information according to the early warning target information, and counting and outputting operation data of the target restaurant corresponding to the current early warning type in a counting time interval.
In this embodiment, historical purchase and operation information is screened according to an early warning type, a target restaurant and a statistical time interval included in early warning target information, and then operation data of the target restaurant in the statistical time interval is obtained through statistics, and the statistical output operation data under different early warning types are different, specifically, the early warning type includes customer unit price early warning and operation loss early warning, corresponding operation data is screened from the historical purchase and operation information according to the currently set early warning type and is counted, wherein the statistical time interval can be set to be 24 hours by default, for example, when loss early warning analysis is performed every day, the statistical time interval is automatically set to be 24 hours, and the statistical efficiency of the operation data is improved; of course, the operation data can be flexibly changed according to the specific time input by the user, for example, the operation data of the restaurant in a certain operation time period on a certain day is separately counted, so that the flexibility of the operation data statistics is improved, which is not limited in this embodiment.
Further, the counting and outputting the operation data of the target restaurant corresponding to the current early warning type in the counting time interval includes:
when the early warning type is passenger unit price early warning, counting passenger unit price data of the target restaurant within a counting time interval;
and when the early warning type is business loss early warning, counting and outputting income and cost data of the target restaurant in the counting time interval.
In this embodiment, different types of operation data are statistically output according to different warning types in the set warning target information, wherein when the warning is set as the guest unit price, guest unit price data of the target restaurant in a statistical time interval are statistically output, specifically, the guest unit price data can include the guest unit price of the target restaurant in each operation period and the daily guest unit price of the target restaurant, specifically, the guest unit price is average person consumption, that is, taking the guest unit price of each day as an example, and the calculation rule is that the daily income of the target restaurant is divided by the number of people having meals each day, in a specific implementation, the guest unit price data of the same target restaurant at different times can be compared according to the time dimension, for example, when the statistical time interval is set to 3 days, the guest unit price of the target restaurant in each three days is statistically output, and the guest unit price of each operation period each day can reflect the average person consumption condition of the restaurant at different times, specifically, the operation time interval and the target restaurant are set in a binding mode, and if the current target restaurant is not bound with the corresponding operation time interval, the customer orders in the operation time interval are not counted; meanwhile, when the early warning target information contains a plurality of target restaurants, the customer prices of all the restaurants can be compared transversely according to the restaurant dimensions, for example, the customer prices of different target restaurants in the same statistical time interval can be compared, the operation states of different target restaurants can be compared and counted visually, and the monitoring efficiency of the operation states of the restaurants can be improved.
When the business loss early warning is set, the income and cost data of the target restaurant in the statistical time interval are counted and output, and the income and cost data of the same target restaurant at different times can be compared according to the time dimension, for example, when the statistical time interval is set to be 3 days, the income and cost data of the target restaurant every three days are counted and output, so that the profit and loss state change of the target restaurant is monitored in time; and when the early warning target information contains a plurality of target restaurants and is compared according to restaurant dimensions, the income and cost data of different target restaurants in the same statistical time interval are counted, and the efficient transverse comparison of the profit and loss states of all the restaurants is realized.
S300, performing loss analysis on the statistical result of the operation data, and outputting corresponding early warning information when operation loss exists.
In this embodiment, further loss analysis is performed after the statistical result of the operation data of the corresponding restaurant is obtained, accurate operation loss analysis result is obtained by performing digital analysis on the accurate statistical data, and if the analysis result indicates that the operation loss exists, corresponding early warning information is output, a specific sending list can be set in advance, for example, the sending list is sent to a financial user and a restaurant management user, so that restaurant operation managers can timely know the current operation loss state, accurate early warning of the restaurant loss operation state is realized, and the restaurant operation scheme can be timely adjusted to reduce loss as much as possible.
Specifically, the step S300 of the digital restaurant deficiency early warning method provided by the invention specifically includes:
when the early warning type is passenger order early warning, judging whether the passenger order of the target restaurant in the statistical time interval is lower than a preset passenger order, if so, outputting passenger order early warning information;
and when the early warning type is operation loss early warning, judging whether the cost of the target restaurant in the statistical time interval is greater than the income, and if so, outputting loss early warning information.
In this embodiment, different judgment standards are provided for different early warning types during loss analysis to obtain corresponding early warning information, wherein when the early warning is set as the guest unit price, whether loss exists is judged by judging whether the guest unit price of the target restaurant in the statistical time interval is lower than the preset guest unit price, wherein the preset guest unit price can set a per-capita consumption value required to be reached by warranty in advance according to the cost of the restaurant and the stream of diners, that is, when the guest unit price in the statistical result is smaller than the preset guest unit price, a loss phenomenon may occur at this moment, and the guest unit price early warning information is timely output to the restaurant operation management user to remind the restaurant operation user of paying attention to the operation state of the restaurant, so that the loss risk of the restaurant operation is reduced.
When the early warning of the loss of business is set, whether the loss exists is judged by judging whether the cost of the target restaurant in the statistical time interval is larger than the income, namely, under the early warning type, the early warning information of the loss is sent again under the condition that the loss of the target restaurant is determined, so that a restaurant operation management user can quickly learn that the restaurant operation management user is in the loss state when receiving the early warning information of the loss, the loss state needs to be adjusted as soon as possible to recover the loss, and because the loss analysis is carried out once at every preset time in the embodiment, the controllability of the loss of the restaurant can be improved by properly shortening the value of the preset time, for example, the clear loss analysis is carried out under the type of the early warning of the loss of business every day, the profit and loss states of the restaurant are mastered constantly, and intelligent and timely loss analysis results are provided for the normal operation of the restaurant.
Preferably, when the user sets the early warning type in the preset target information, the early warning of the unit price of the customer or the early warning of the loss of business can be set independently, and the early warning of the unit price of the customer and the early warning of the loss of business can be set simultaneously.
Further, after step S300, the digital restaurant deficiency early warning method provided by the invention further includes:
and outputting reminding information of the data which does not meet the conditions when the operation loss does not exist.
In this embodiment, after the statistical result is analyzed and judged, if there is no operation loss, corresponding reminding information is output to remind the user that no condition data is currently met, so that loss early warning analysis of current early warning target information is finished.
According to the method, the early warning target information is obtained regularly, the digital loss analysis is carried out on the operation data of the restaurant according to historical purchasing and operation information, the early warning information is output in time when loss exists, accurate early warning is effectively carried out on the loss operation state of the restaurant, and the controllability of the loss in the digital restaurant is improved. It should be noted that, a certain order does not necessarily exist between the above steps, and those skilled in the art can understand, according to the description of the embodiments of the present invention, that in different embodiments, the above steps may have different execution orders, that is, may be executed in parallel, may also be executed interchangeably, and the like.
Another embodiment of the present invention provides a digital restaurant loss early warning device, as shown in fig. 2, the device 1 includes:
the acquisition module 11 is configured to acquire early warning target information every preset time;
the statistical module 12 is used for acquiring historical purchasing and operating information and carrying out statistics on corresponding restaurant operating data according to the early warning target information and the historical purchasing and operating information;
and the analysis module 13 is used for performing loss analysis on the statistical result of the operation data, and outputting corresponding early warning information when operation loss exists.
The acquisition module 11, the statistical module 12 and the analysis module 13 are connected in sequence, the module referred to in the present invention refers to a series of computer program instruction segments capable of completing a specific function, and is more suitable for describing the execution process of the digital catering loss early warning device than a program.
Another embodiment of the present invention provides a digital catering loss early warning system, which may be a mobile terminal, a desktop computer, a notebook, a palm computer, a server, and other computing devices, as shown in fig. 3, where the system 10 includes:
one or more processors 110 and a memory 120, where one processor 110 is illustrated in fig. 3, the processor 110 and the memory 120 may be connected by a bus or other means, and the connection by the bus is illustrated in fig. 3.
The memory 120 is a non-volatile computer-readable storage medium, and can be used to store non-volatile software programs, non-volatile computer-executable programs, and modules, such as program instructions corresponding to the digital restaurant damage warning method in the embodiment of the present invention. The processor 110 executes various functional applications and data processing of the system 10 by executing the nonvolatile software programs, instructions and units stored in the memory 120, that is, implements the digital restaurant loss warning method in the above method embodiment.
The memory 120 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to the use of the system 10, and the like. Further, the memory 120 may include high speed random access memory, and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some embodiments, memory 120 optionally includes memory located remotely from processor 110, which may be connected to system 10 via a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
One or more units are stored in the memory 120, and when executed by the one or more processors 110, perform the digital meal loss warning method in any of the above-described method embodiments, e.g., performing the above-described method steps S100-S300 in fig. 1.
Embodiments of the present invention provide a non-transitory computer-readable storage medium storing computer-executable instructions for execution by one or more processors, for example, to perform method steps S100-S300 of fig. 1 described above.
By way of example, non-volatile storage media can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), electrically erasable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM), which acts as external cache memory. By way of illustration and not limitation, RAM is available in many forms such as Synchronous RAM (SRAM), dynamic RAM, (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Sync Link DRAM (SLDRAM), and Direct Rambus RAM (DRRAM). The disclosed memory components or memory of the operating environment described herein are intended to comprise one or more of these and/or any other suitable types of memory.
In summary, in the digital catering loss early warning method, device, system and medium disclosed by the invention, the method obtains early warning target information at preset time intervals; acquiring historical purchase and operation information, and counting corresponding restaurant operation data according to the early warning target information and the historical purchase and operation information; and analyzing the loss of the statistical result of the operation data, and outputting corresponding early warning information when the operation loss exists. According to the embodiment of the invention, the early warning target information is acquired regularly, the digital loss analysis is carried out on the operation data of the restaurant according to the historical purchasing and operation information, and the early warning information is output in time when the loss exists, so that the accurate early warning is effectively carried out on the loss operation state of the restaurant, and the controllability of the loss in the digital catering is improved.
The above-described embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the scheme of the embodiment.
Through the above description of the embodiments, those skilled in the art will clearly understand that the embodiments may be implemented by software plus a general hardware platform, and may also be implemented by hardware. With this in mind, the above-described technical solutions may be embodied in the form of a software product, which can be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes instructions for causing a computer electronic device (which may be a personal computer, a server, or a network electronic device, etc.) to execute the methods of the various embodiments or some parts of the embodiments.
Conditional language such as "can," "might," or "may" is generally intended to convey that a particular embodiment can include (yet other embodiments do not include) particular features, elements, and/or operations, unless specifically stated otherwise or otherwise understood within the context as used. Thus, such conditional language is also generally intended to imply that features, elements, and/or operations are in any way required for one or more embodiments or that one or more embodiments must include logic for deciding, with or without input or prompting, whether such features, elements, and/or operations are included or are to be performed in any particular embodiment.
What has been described herein in the specification and drawings includes examples that can provide a digital restaurant loss warning method, apparatus, system, and medium. It will, of course, not be possible to describe every conceivable combination of components and/or methodologies for purposes of describing the various features of the disclosure, but it can be appreciated that many further combinations and permutations of the disclosed features are possible. It is therefore evident that various modifications can be made to the disclosure without departing from the scope or spirit thereof. In addition, or in the alternative, other embodiments of the disclosure may be apparent from consideration of the specification and drawings and from practice of the disclosure as presented herein. It is intended that the examples set forth in this specification and the drawings be considered in all respects as illustrative and not restrictive. Although specific terms are employed herein, they are used in a generic and descriptive sense only and not for purposes of limitation.
Claims (10)
1. A digital catering loss early warning method is characterized by comprising the following steps:
acquiring early warning target information at preset time intervals;
acquiring historical purchase and operation information, and counting corresponding restaurant operation data according to the early warning target information and the historical purchase and operation information;
and analyzing the loss of the statistical result of the operation data, and outputting corresponding early warning information when the operation loss exists.
2. The digital catering deficit warning method according to claim 1, wherein before obtaining warning target information every preset time, the method further comprises:
receiving a regular early warning instruction input by a user, wherein the regular early warning instruction comprises preset time and early warning target information.
3. The digital catering loss warning method of claim 1, wherein the warning target information comprises a warning type, a target restaurant and a statistical time interval.
4. The digitized catering loss early warning method according to claim 3, wherein the acquiring historical procurement and operation information and counting corresponding restaurant operation data according to the early warning target information and the historical procurement and operation information specifically comprises:
and acquiring historical purchase and operation information, performing data screening on the historical purchase and operation information according to the early warning target information, and counting and outputting operation data of the target restaurant corresponding to the current early warning type in a counting time interval.
5. The digital catering loss early warning method according to claim 4, wherein the counting outputs the business data of the target restaurant corresponding to the current early warning type in the counting time interval, and comprises the following steps:
when the early warning type is passenger unit price early warning, counting passenger unit price data of the target restaurant within a counting time interval;
and when the early warning type is business loss early warning, counting and outputting income and cost data of the target restaurant in the counting time interval.
6. The digitized catering loss early warning method according to claim 5, wherein the loss analysis is performed on the statistical result of the business data, and corresponding early warning information is output when an operation loss exists, and the method specifically comprises the following steps:
when the early warning type is passenger order early warning, judging whether the passenger order of the target restaurant in the statistical time interval is lower than a preset passenger order, if so, outputting passenger order early warning information;
and when the early warning type is operation loss early warning, judging whether the cost of the target restaurant in the statistical time interval is greater than the income, and if so, outputting loss early warning information.
7. The digital restaurant loss early warning method according to any one of claims 1-6, wherein the loss analysis is performed on the statistical result of the business data, and after outputting corresponding early warning information when there is an operation loss, the method further comprises:
and outputting reminding information of the data which does not meet the conditions when the operation loss does not exist.
8. The utility model provides a digital food and beverage loss early warning device which characterized in that, the device includes:
the acquisition module is used for acquiring early warning target information every preset time;
the statistical module is used for acquiring historical purchase and operation information and counting corresponding restaurant operation data according to the early warning target information and the historical purchase and operation information;
and the analysis module is used for analyzing the loss of the statistical result of the operation data and outputting corresponding early warning information when the operation loss exists.
9. A digital catering loss early warning system is characterized by comprising at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the digital restaurant loss warning method of any one of claims 1-7.
10. A non-transitory computer-readable storage medium having stored thereon computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform the digital restaurant loss warning method of any one of claims 1-7.
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