Shared service demand prediction method

Abstract

The invention relates to the technical field of shared service demand prediction, and discloses a shared service demand prediction method, which comprises the following steps: S1, demand prediction value: helping a shared service to accurately predict market demands and reasonably arrange production and supply chain management so as to improve the operation efficiency of the shared service; the method has the beneficial effects that by setting cloud service enhancement, a cloud service provider can continuously enhance security measures to protect data and application programs of a user, the latest security function and enhanced security performance can be obtained by upgrading the cloud service, data leakage and other security risks are reduced, and the user experience is improved. A cloud service provider can regularly add new functions and characteristics to meet the constantly changing requirements of users, the latest functions and characteristics can be obtained through upgrading, the productivity and efficiency of enterprises are improved, the stability can be kept even if many sharing service users are used, unstable collapse of a server is avoided, the sharing service platform is high in practicability, and the user experience is improved. And the use effect of the shared service demand prediction method is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of shared service demand prediction, and in particular to a shared service demand prediction method. Background Art

[0002] Shared services enable data centralization, which in turn supports improved reporting and analysis. It also helps improve compliance and enables organizations to make better decisions. Shared services can give organizations the flexibility to expand or shrink as needed without making major changes to their organizational structure. During mergers and acquisitions, shared services can simplify the process of integrating two organizations to combine operations and achieve synergies. However, the above scenarios may cause disruptions to these applications and systems, affecting the normal operation of the business and possibly resulting in data loss, which in many cases is difficult to recover. Summary of the invention

[0003] The purpose of the present invention is to provide a shared service demand prediction method in order to solve the above problems, thereby solving the problems mentioned in the background technology.

[0004] In order to solve the above problems, the present invention provides a technical solution:

[0005] A shared service demand forecasting method comprises the following steps:

[0006] S1: The value of demand forecasting: helping shared services accurately predict market demand and rationally arrange production and supply chain management, thereby improving the operational efficiency of shared services;

[0007] S2: Demand forecasting system: By predicting the customer demand for shared services in a certain period of time in the future, shared services can purchase raw materials and arrange production activities in advance to cope with changes in customer demand;

[0008] S3: Sharing service: a tool that enables information sharing and collaboration. It can help people share and collaborate on files at different locations and times, improving work efficiency and collaboration capabilities.

[0009] S4: Forecast implementation: Forecasting refers to the speculation and estimation of possible shared services in the future based on existing information and experience. As a thinking and coping tool, forecasting plays an important role in shared services;

[0010] S5: User promotion and operation: Through effective brand promotion and communication, sharing services can shape their own image and make consumers have a positive sense of identity with their products or services;

[0011] S6: Cloud service enhancements: Providers typically regularly update and upgrade their infrastructure and services to improve performance and reliability.

[0012] As a preferred solution of the present invention, the value predicted according to the demand in S1 mainly includes the following steps:

[0013] S11: Smoothing demand: By estimating the possible needs of customers in advance, the production rhythm can be reasonably arranged to avoid suddenly issuing large-scale production tasks when receiving customer needs;

[0014] S12: Long-term resource preparation: Anticipate possible customer demands in advance to gain ample lead time for resources that require a longer time to prepare.

[0015] As a preferred solution of the present invention, the demand forecasting system in S2 mainly includes the following steps:

[0016] S21: Demand forecasting: Make demand forecasts, that is, determine the demand for a certain product by a certain organization within a certain period of time;

[0017] S22: Actual order comparison: Continuously replace or compare demand forecasts with actual orders;

[0018] S23: Cancellation of surplus: Automatically cancel the unreplaced forecast quantity within the product standard fulfillment cycle;

[0019] S24: Process improvement: Adjust forecasting methods or strengthen demand formation management.

[0020] The shared service according to S3 mainly includes the following steps:

[0021] S31: Establish a sharing platform: A sharing platform can be an online website or application, or an offline community or organization. Through the sharing platform, people can publish their resources or needs and connect and communicate with others;

[0022] S34: Information sharing: On the sharing platform, people can post the information they want to share, such as idle items, personal skills, travel experiences, etc. Through information sharing, others can learn about these resources and communicate with the sharers;

[0023] S33: Determine the sharing method: The sharing method can be free, paid, reciprocal, etc. Sharers can determine the sharing method based on their own needs and the value of resources;

[0024] S34: Conduct sharing transactions: Through the sharing platform, people can find suitable sharing objects and conduct transactions. The transactions can be online payments, offline barter, etc.

[0025] As a preferred solution of the present invention, the implementation according to the prediction in S4 mainly includes the following steps:

[0026] S41: Select a suitable forecasting model: According to the characteristics of the data and the forecasting objectives, select a suitable forecasting model. Commonly used forecasting models include time series models, regression models, neural network models, etc.

[0027] S42: Model training and evaluation: After selecting the prediction model, it is necessary to use historical data to train the model and use part of the data to evaluate the model;

[0028] S43: Demand forecasting: After model training and evaluation are completed, the trained model can be used to forecast demand. According to the forecast time range and the choice of forecast model, the demand forecast results for a period of time in the future can be obtained;

[0029] S44: Forecast result analysis and adjustment: Analyze and verify the forecast results. If the forecast results do not match the actual situation, adjust and optimize the model and re-forecast, which can continuously improve the accuracy and stability of the forecast;

[0030] S45: Carry out corresponding demand management based on the demand forecast results, including inventory management, logistics planning, production scheduling, etc., to better meet market demand.

[0031] As a preferred solution of the present invention, the user promotion and operation in S5 mainly includes the following steps:

[0032] S51: Marketing: Promote the advantages and features of the platform through various channels to attract more users to register and use platform services;

[0033] S52: User management: Establish a user database, handle user feedback and complaints in a timely manner, provide high-quality customer service, and enhance user stickiness and satisfaction;

[0034] S53: Data analysis and decision-making: Through the analysis of user data, extract information about user needs and behaviors, and provide reference for platform optimization and decision-making.

[0035] As a preferred solution of the present invention, the cloud service enhancement in S6 mainly includes the following steps:

[0036] S61: Security: This includes physical security, network security, data encryption, and access control, which are the basis for ensuring the stable operation of cloud services;

[0037] S62: Technical support and service quality: Good customer service and technical support are important components of cloud service quality, ensuring timely assistance when problems arise;

[0038] S63: Service Level Agreement: The service indicator commitments reached between the service provider and the user, including quality, availability, responsibility, etc., are an important basis for measuring service stability;

[0039] S64: Service stability indicators: Different types of services will have different key performance indicators, such as latency, throughput, etc. These indicators are crucial to ensuring business stability.

[0040] The beneficial effects of the present invention are: by setting up cloud service enhancements, the cloud service provider will continuously strengthen its security measures to protect user data and applications. Upgrading cloud services can obtain the latest security features and enhanced security performance, reduce data leakage and other security risks, and the cloud service provider will regularly add new functions and features to meet the ever-changing needs of users. Upgrading can obtain the latest functions and features, improve the productivity and efficiency of the enterprise, and enable the shared service to maintain stability even when there are many users, avoid server instability and crashes, and make the shared service platform highly practical. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] For ease of explanation, the present invention is described in detail with reference to the following specific implementations and the accompanying drawings.

[0042] Figure 1 It is a flow chart of the shared service demand prediction method of the present invention. DETAILED DESCRIPTION

[0043] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0044] Embodiment 1:

[0045] See also Figure 1 The present invention provides a technical solution: a method for predicting demand for shared services, comprising the following steps:

[0046] S1: The value of demand forecasting: helping shared services accurately predict market demand and rationally arrange production and supply chain management, thereby improving the operational efficiency of shared services;

[0047] S2: Demand forecasting system: By predicting the customer demand for shared services in a certain period of time in the future, shared services can purchase raw materials and arrange production activities in advance to cope with changes in customer demand;

[0048] S3: Sharing service: a tool that enables information sharing and collaboration. It can help people share and collaborate on files at different locations and times, improving work efficiency and collaboration capabilities.

[0049] S4: Forecast implementation: Forecasting refers to the speculation and estimation of possible shared services in the future based on existing information and experience. As a thinking and coping tool, forecasting plays an important role in shared services;

[0050] S5: User promotion and operation: Through effective brand promotion and communication, sharing services can shape their own image and make consumers have a positive sense of identity with their products or services;

[0051] S6: Cloud service enhancements: Providers typically regularly update and upgrade their infrastructure and services to improve performance and reliability.

[0052] Embodiment 2:

[0053] According to the value of demand forecast in S1, the following steps are mainly included:

[0054] S11: Smoothing demand: By estimating the possible needs of customers in advance, the production rhythm can be reasonably arranged to avoid suddenly issuing large-scale production tasks when receiving customer needs;

[0055] S12: Long-term resource preparation: Anticipate possible customer demands in advance to gain ample lead time for resources that require a longer time to prepare.

[0056] First, it is necessary to clarify the specific object of the forecast, such as the demand for a certain product or the frequency of use of a certain service, and collect all historical data and information related to the forecast target. These data should include as many variables as possible, such as seasonal changes, historical sales data, etc. Based on the selected method, establish a forecast model and perform calculations. This step may involve complex statistical analysis and data processing. Evaluate the forecast results to ensure their accuracy and reliability, and organize the results into a report form for decision makers to understand and use.

[0057] Embodiment 3:

[0058] According to S2, the demand forecasting system mainly includes the following steps:

[0059] S21: Forecasting system: Make demand forecasts, that is, determine the demand for a certain product by a certain organization within a certain period of time;

[0060] S22: Actual order comparison: Continuously replace or compare demand forecasts with actual orders;

[0061] S23: Cancellation of surplus: Automatically cancel the unreplaced forecast quantity within the product standard fulfillment cycle;

[0062] S24: Process improvement: Adjust forecasting methods or strengthen demand formation management.

[0063] After collecting the raw data, data cleaning is required to eliminate errors and outliers. This includes processing missing values, outliers, and duplicate values ​​to ensure the accuracy and reliability of the data, extracting meaningful features from the raw data for use in the prediction model, and selecting a suitable demand prediction model based on goals and needs.

[0064] Embodiment 4:

[0065] According to S3, the sharing service mainly includes the following steps:

[0066] S31: Establish a sharing platform: A sharing platform can be an online website or application, or an offline community or organization. Through the sharing platform, people can publish their resources or needs and connect and communicate with others;

[0067] S34: Information sharing: On the sharing platform, people can post the information they want to share, such as idle items, personal skills, travel experiences, etc. Through information sharing, others can learn about these resources and communicate with the sharers;

[0068] S33: Determine the sharing method: The sharing method can be free, paid, reciprocal, etc. Sharers can determine the sharing method based on their own needs and the value of resources;

[0069] S34: Conduct sharing transactions: Through the sharing platform, people can find suitable sharing objects and conduct transactions. The transactions can be online payments, offline barter, etc.

[0070] Service standardization is a key step in achieving service sharing. Enterprises need to formulate unified service standards, processes and policies to ensure the coordination and consistency of services among different departments, which will help eliminate duplication and unnecessary processes and improve service efficiency. The implementation of shared services may require training and support for employees to adapt to new working methods and processes. Enterprises need to provide employees with necessary training and ensure that they have the skills and knowledge to provide high-quality services. In addition, enterprises should provide support and guidance to employees to help them smoothly transition to the new service model.

[0071] Embodiment 5:

[0072] The implementation according to the prediction in S4 mainly includes the following steps:

[0073] S41: Select a suitable forecasting model: According to the characteristics of the data and the forecasting objectives, select a suitable forecasting model. Commonly used forecasting models include time series models, regression models, neural network models, etc.

[0074] S42: Model training and evaluation: After selecting the prediction model, it is necessary to use historical data to train the model and use part of the data to evaluate the model;

[0075] S43: Demand forecasting: After model training and evaluation are completed, the trained model can be used to forecast demand. According to the forecast time range and the choice of forecast model, the demand forecast results for a period of time in the future can be obtained;

[0076] S44: Forecast result analysis and adjustment: Analyze and verify the forecast results. If the forecast results do not match the actual situation, adjust and optimize the model and re-forecast, which can continuously improve the accuracy and stability of the forecast;

[0077] S45: Carry out corresponding demand management based on the demand forecast results, including inventory management, logistics planning, production scheduling, etc., to better meet market demand.

[0078] The model can choose a quantitative model or a qualitative model, depending on the prediction target and data characteristics. According to the constructed prediction model, the prediction results are output. The prediction results can be quantitative data or qualitative descriptions, which are selected according to the prediction targets and needs. After the data is cleaned and sorted, the next step is data analysis and modeling. Data analysis can be carried out through statistical methods, machine learning algorithms, etc., in order to reveal the hidden patterns and laws in the data. Modeling can use regression analysis, time series analysis, spatial analysis and other techniques to establish prediction models. These models can predict the possible location, time and type of crime.

[0079] Embodiment 6:

[0080] According to S5, user promotion and operation mainly include the following steps:

[0081] S51: Marketing: Promote the advantages and features of the platform through various channels to attract more users to register and use platform services;

[0082] S52: User management: Establish a user database, handle user feedback and complaints in a timely manner, provide high-quality customer service, and enhance user stickiness and satisfaction;

[0083] S53: Data analysis and decision-making: Through the analysis of user data, extract information about user needs and behaviors, and provide reference for platform optimization and decision-making.

[0084] Market research is the first step in operational promotion planning. By deeply understanding the needs of the target market and the situation of competitors, it can help companies develop corresponding promotion strategies. On the basis of market research and analysis, companies need to develop operational promotion goals and strategies based on their own conditions. The implementation and monitoring of promotion plans are key steps to ensure promotion effectiveness. Only by timely and accurate grasp of the situation of promotion activities can strategies be adjusted in time to improve results.

[0085] Embodiment 7:

[0086] According to S6, cloud service enhancement mainly includes the following steps:

[0087] S61: Security: This includes physical security, network security, data encryption, and access control, which are the basis for ensuring the stable operation of cloud services;

[0088] S62: Technical support and service quality: Good customer service and technical support are important components of cloud service quality, ensuring timely assistance when problems arise;

[0089] S63: Service Level Agreement: The service indicator commitments reached between the service provider and the user, including quality, availability, responsibility, etc., are an important basis for measuring service stability;

[0090] S64: Service stability indicators: Different types of services will have different key performance indicators, such as latency, throughput, etc. These indicators are crucial to ensuring business stability.

[0091] The service quality of cloud computing is also closely related to its performance. To achieve efficient operation, enterprises must ensure that the system can operate normally under high load and provide sufficient storage space and bandwidth to support the smooth execution of business. Therefore, performance optimization from multiple aspects such as hardware, software, and network plays a vital role in improving the quality and efficiency of services. In this process, it is necessary to innovate and reform the existing business model from aspects such as service model, implementation method, and service management, and try to find a development path that suits them in order to better meet the needs of customers and the market.

[0092] To sum up, the main specific plans are as follows: first, it is necessary to clarify the specific object of the forecast, such as the demand for a certain product or the frequency of use of a certain service, collect all historical data and information related to the forecast target, these data should include as many variables as possible, such as seasonal changes, historical sales data, etc., based on the selected method, establish a forecast model and perform calculations. This step may involve complex statistical analysis and data processing, evaluate the forecast results, ensure their accuracy and reliability, and organize the results into a report form for decision makers to understand and use. After collecting the raw data, data cleaning is required to eliminate errors and outliers, which includes processing missing values, outliers and duplicate values ​​to ensure the accuracy and reliability of the data. Extract meaningful features for use in prediction models. Select a suitable demand prediction model based on goals and needs. Service standardization is a key step in achieving service sharing. Enterprises need to develop unified service standards, processes, and policies to ensure coordination and consistency of services between different departments, which helps eliminate duplication and unnecessary processes and improve service efficiency. The implementation of shared services may require training and support for employees to adapt to new ways of working and processes. Enterprises need to provide employees with necessary training and ensure that they have the skills and knowledge to provide high-quality services. In addition, enterprises should provide employees with support and guidance to help them smoothly transition to the new service model. The model can choose a quantitative model or a qualitative model, depending on According to the prediction target and data characteristics, the prediction results are output according to the constructed prediction model. The prediction results can be quantitative data or qualitative descriptions, which are selected according to the prediction target and needs. After the data is cleaned and sorted, the next step is data analysis and modeling. Data analysis can be carried out through statistical methods, machine learning algorithms, etc., in order to reveal the hidden patterns and laws in the data. Modeling can use regression analysis, time series analysis, spatial analysis and other technologies to establish prediction models. These models can predict the possible location, time and type of crime. Market research is the first step in operation and promotion planning. By deeply understanding the needs of the target market and the situation of competitors, it can help companies formulate corresponding promotion strategies. In the process of market research and analysis Based on the analysis, enterprises need to formulate operation and promotion goals and strategies according to their own situation. The implementation and monitoring of the promotion plan are key steps to ensure the effectiveness of the promotion. Only by timely and accurately grasping the situation of the promotion activities can the strategy be adjusted in time to improve the effect. The service quality of cloud computing is also closely related to its performance. To achieve efficient operation, enterprises must ensure that the system can operate normally under high load and provide sufficient storage space and bandwidth to support the smooth execution of the business. Therefore, performance optimization from hardware, software, network and other aspects is crucial to improving the quality and efficiency of services. In this process, it is necessary to innovate and reform the existing business model from aspects such as service model, implementation method and service management, and try to find a development path that suits you.In order to better meet the needs of customers and the market.

[0093] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for predicting demand for shared services, characterized in that: The following steps are involved: S1: The value of demand forecasting: helping shared services accurately predict market demand and rationally arrange production and supply chain management, thereby improving the operational efficiency of shared services; S2: Demand forecasting system: By predicting the customer demand for shared services in a certain period of time in the future, shared services can purchase raw materials and arrange production activities in advance to cope with changes in customer demand; S3: Sharing service: a tool that enables information sharing and collaboration. It can help people share and collaborate on files at different locations and times, improving work efficiency and collaboration capabilities. S4: Forecast implementation: Forecasting refers to the speculation and estimation of possible shared services in the future based on existing information and experience. As a thinking and coping tool, forecasting plays an important role in shared services; S5: User promotion and operation: Through effective brand promotion and communication, sharing services can shape their own image and make consumers have a positive sense of identity with their products or services; S6: Cloud service enhancements: Providers typically regularly update and upgrade their infrastructure and services to improve performance and reliability.

2. A method for predicting shared service demand according to claim 1, characterized in that: The value of demand prediction in S1 mainly includes the following steps: S11: Smoothing demand: By estimating the possible needs of customers in advance, the production rhythm can be arranged reasonably to avoid suddenly issuing large-scale production tasks when receiving customer needs; S11: Long-term resource preparation: Anticipate possible customer demands in advance to gain ample lead time for resources that require a longer time to prepare.

3. A method for predicting shared service demand according to claim 1, characterized in that: The demand forecasting system according to S2 mainly includes the following steps: S21: Demand forecasting: Make demand forecasts, that is, determine the demand for a certain product by a certain organization within a certain period of time; S22: Actual order comparison: Continuously replace or compare demand forecasts with actual orders; S23: Cancellation of surplus: Automatically cancel the unreplaced forecast quantity within the product standard fulfillment cycle; S24: Process improvement: Adjust forecasting methods or strengthen demand formation management.

4. A method for predicting shared service demand according to claim 1, characterized in that: The shared service according to S3 mainly includes the following steps: S31: Establish a sharing platform: A sharing platform can be an online website or application, or an offline community or organization. Through the sharing platform, people can publish their resources or needs and connect and communicate with others; S34: Information sharing: On the sharing platform, people can post the information they want to share, such as idle items, personal skills, travel experiences, etc. Through information sharing, others can learn about these resources and communicate with the sharers; S33: Determine the sharing method: The sharing method can be free, paid, reciprocal, etc. Sharers can determine the sharing method based on their own needs and the value of resources; S34: Conduct sharing transactions: Through the sharing platform, people can find suitable sharing objects and conduct transactions. The transactions can be online payments, offline barter, etc.

5. A method for predicting shared service demand according to claim 1, characterized in that: The implementation according to the prediction in S4 mainly includes the following steps: S41: Select a suitable forecasting model: According to the characteristics of the data and the forecasting objectives, select a suitable forecasting model. Commonly used forecasting models include time series models, regression models, neural network models, etc. S42: Model training and evaluation: After selecting the prediction model, it is necessary to use historical data to train the model and use part of the data to evaluate the model; S43: Demand forecasting: After model training and evaluation are completed, the trained model can be used to forecast demand. According to the forecast time range and the choice of forecast model, the demand forecast results for a period of time in the future can be obtained; S44: Forecast result analysis and adjustment: Analyze and verify the forecast results. If the forecast results do not match the actual situation, adjust and optimize the model and re-forecast, which can continuously improve the accuracy and stability of the forecast; S45: Carry out corresponding demand management based on the demand forecast results, including inventory management, logistics planning, production scheduling, etc., to better meet market demand.

6. A method for predicting shared service demand according to claim 1, characterized in that: The user promotion and operation according to S5 mainly includes the following steps: S51: Marketing: Promote the advantages and features of the platform through various channels to attract more users to register and use platform services; S52: User management: Establish a user database, handle user feedback and complaints in a timely manner, provide high-quality customer service, and enhance user stickiness and satisfaction; S53: Data analysis and decision-making: Through the analysis of user data, extract information about user needs and behaviors, and provide reference for platform optimization and decision-making.

7. A method for predicting shared service demand according to claim 1, characterized in that: The cloud service enhancement according to S6 mainly includes the following steps: S61: Security: This includes physical security, network security, data encryption, and access control, which are the basis for ensuring the stable operation of cloud services; S62: Technical support and service quality: Good customer service and technical support are important components of cloud service quality, ensuring timely assistance when problems arise; S63: Service Level Agreement: The service indicator commitments reached between the service provider and the user, including quality, availability, responsibility, etc., are an important basis for measuring service stability; S64: Service stability indicators: Different types of services will have different key performance indicators, such as latency, throughput, etc. These indicators are crucial to ensuring business stability.

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