Enterprise cost optimization method and system based on big data

Abstract

The invention provides an enterprise cost optimization method and system based on big data, and relates to the technical field of big data processing. The method comprises the following steps: acquiring cost income data of an enterprise, carrying out cost influence analysis for profits, and determining an important control cost item; according to the cost item change information corresponding to different important control cost items, combining the profit change information to carry out cost influence size analysis, and forming cost item influence degree data; and according to the cost item influence degree data, performing cost control optimization analysis on different important control cost items to form cost control optimization data. According to the method, the historical cost data of the enterprise is reasonably controlled and analyzed in combination with the big data technology, so that the enterprise cost is more reasonably and effectively controlled and optimized, and the enterprise development can be effectively promoted while the enterprise cost is reasonably controlled and optimized.

Description

Technical Field

[0001] The present invention relates to the field of big data processing technology, and in particular to a method and system for enterprise cost optimization based on big data. Background Art

[0002] In order to obtain better profits, enterprises not only need to promote the growth of income sources, but also need to reasonably control the costs of the enterprise, and ensure that the enterprise forms a good operating system by reducing costs and increasing efficiency. Of course, with the intensification of market competition, it is more difficult for enterprises to expand and develop their business in the market and to increase their profit growth points to a greater extent. Therefore, more reasonable cost control for enterprises is particularly prominent in increasing corporate benefits.

[0003] At present, the cost control of enterprises is usually achieved by re-evaluating and tracking specific cost items, and it is impossible to comprehensively consider cost expenditures, resulting in some cost reduction control methods having a significant side effect on the operation and even development of the enterprise. With the progress of science and society, big data technology is becoming more and more mature, and it is possible to use big data to conduct a comprehensive and comprehensive analysis of relatively large enterprise cost data to achieve reasonable optimization and cost control of cost items.

[0004] Therefore, designing an enterprise cost optimization method and system based on big data, combining big data technology to conduct reasonable control analysis on the enterprise's historical cost data, and then achieving more reasonable and effective control and optimization of enterprise costs, ensuring that the enterprise's costs can be effectively promoted while being reasonably controlled and optimized, is an urgent problem to be solved. Summary of the invention

[0005] The purpose of the present invention is to provide an enterprise cost optimization method based on big data. By analyzing the impact of different cost items on profits from the historical cost-revenue data of the enterprise, the cost items with greater impact on profits are identified, and then the optimization control direction and specific quantitative data of the optimization control of different cost items are determined according to the quantitative relationship between the degree of impact of the cost items on profits. This realizes reasonable enterprise cost optimization control based on the different degrees of impact on enterprise profits. Compared with the traditional manual control and analysis of a single cost item, it is more efficient. In addition, due to the combination of big data information, it can more comprehensively and intuitively determine the specific impact of different cost items on profits, and then make adaptive adjustments, avoiding the impact of unreasonable cost control on the basic necessary expenditures of the cost items, thereby avoiding the negative impact of unreasonable cost control on the operation and development of the enterprise, and can provide accurate and reliable data reference for the cost optimization control of the enterprise.

[0006] The purpose of the present invention is also to provide an enterprise cost optimization system based on big data. The system can configure an overall system that can adaptively realize the reasonable optimization control of cost items by obtaining the impact of different cost items on profits from the enterprise cost-revenue data, thereby ensuring the efficient realization of reasonable and comprehensive optimization control of enterprise costs. It is an important material basis for completing and realizing enterprise cost optimization control.

[0007] In a first aspect, the present invention provides an enterprise cost optimization method based on big data, comprising: obtaining the enterprise's cost-benefit data, and conducting a cost impact analysis on profits to determine important control cost items; conducting a cost impact analysis based on cost item change information corresponding to different important control cost items and combining the profit change information to form cost item impact data; based on the cost item impact data, conducting a cost control optimization analysis on different important control cost items to form cost control optimization data.

[0008] In the present invention, the method analyzes the impact of different cost items on profits from the company's historical cost-revenue data to identify cost items with greater impact on profits, and then determines the optimization control direction and specific quantitative data of different cost items based on the quantitative relationship between the impact of cost items on profits, thereby achieving reasonable enterprise cost optimization control based on the different degrees of impact on enterprise profits. Compared with the traditional manual control and analysis of a single cost item, it is more efficient, and because it combines big data information, it can more comprehensively and intuitively determine the specific impact of different cost items on profits, and then make adaptive adjustments, thereby avoiding the impact of unreasonable cost control on the basic necessary expenditures of cost items, thereby avoiding the negative impact of unreasonable cost control on enterprise operations and development, and providing accurate and reliable data reference for enterprise cost optimization control.

[0009] As a possible implementation method, the cost and income data of the enterprise is obtained, and a cost impact analysis on the profit is conducted to determine the important control cost items, including: determining the change data of different cost items in the time dimension sequence based on the cost and income data, and forming the cost item change information corresponding to the different cost items; determining the change data of the profit in the time dimension sequence based on the cost and income data, and forming the profit change information; combining the cost item change information and profit change information corresponding to different cost items, conducting a cost item importance analysis on the profit change, and determining different important control cost items.

[0010] In the present invention, to optimize the cost of an enterprise reasonably, it is necessary to determine the cost items that really need to be optimized and controlled, so as to achieve reasonable optimization of costs and avoid the adverse effects of cost optimization such as affecting the development and operation of the enterprise. It can be understood that for the cost of an enterprise, the purpose of optimizing it is to avoid excessive cost expenditures from having a relatively large impact on the profit of the enterprise. Therefore, when confirming the cost items that need to be optimized, it is necessary to combine the change data of the cost items with the change data of the profit to determine the important control cost items that really affect the profit.

[0011] As a possible implementation method, the cost item change information and profit change information corresponding to different cost items are combined to conduct a cost item importance analysis for profit changes to determine different important control cost items, including: matching the cost item change information corresponding to different cost items with the profit change information in the time dimension sequence; setting an analysis time period, and continuously dividing different cost item change information and profit change information according to the analysis time period to extract different analysis period change information; performing a logical comparison analysis on all analysis period change information for changes in non-all cost items to determine important control cost items.

[0012] In the present invention, it can be understood that the original big data information corresponding to the different cost items obtained is the change data within a wider time range, and this change data has different change situations or time periods of the cost items. Therefore, in order to facilitate the determination of whether the cost items are objects that really need to be controlled and have an impact on profits, it is necessary and reasonable to divide the original big data of the cost items into time periods based on the time dimension. In this way, reasonable cost item analysis can be performed for each time period, avoiding the inability to efficiently complete the determination of important control costs due to a large amount of data formed due to a large time span.

[0013] As a possible implementation method, a logical comparative analysis is performed on all analysis period change information in which not all cost items have changed to determine the important controlling cost items, including: a logical comparative analysis is performed on all analysis period change information in the following manner to determine the important controlling cost items: for analysis period change information in which only one cost item has changed during the analysis period, if the change in the cost item causes the profit to change asynchronously in the same direction, then the changed cost item is determined as a negative important controlling cost item; for analysis period change information in which only one cost item has changed during the analysis period, if the change in the cost item causes the profit to change asynchronously in the opposite direction, then the changed cost item is determined as a positive important controlling cost item; for analysis period change information in which only one cost item has changed during the analysis period, if the change in the cost item causes the profit to remain unchanged, then the changed cost item is determined as a constant important controlling cost item; for all analysis period change information in which multiple cost items have changed during the analysis period, multiple cost items are calibrated. The analysis period change information in which the profits change synchronously and in the same direction due to the simultaneous changes in the same direction is identified, and the corresponding changed cost items in the analysis period change information are determined as stable impact cost items, and the remaining analysis period change information is analyzed as follows: If there is only one cost item that has changed in the analysis period change information that is not a stable impact cost item, and the profits do not change synchronously and in the same direction when all the changed cost items change in the same direction, then the changed non-stable impact cost item will be determined as a negative important controlling cost; if there is only one cost item that has changed in the analysis period change information that is not a stable impact cost item, and the profits do not change synchronously and in the opposite direction when all the changed cost items change in the same direction, then the changed non-stable impact cost item will be determined as a positive important controlling cost item; if there is only one cost item that has changed in the analysis period change information that is not a stable impact cost item, and the profits do not change when all the changed cost items change in the same direction, then the changed non-stable impact cost item will be determined as a constant important controlling cost item.

[0014] In the present invention, the determination of important control cost items needs to consider three aspects. On the one hand, the impact of important control costs on profits needs to be expressed intuitively, and the cost items that can be expressed intuitively are relatively independent in themselves. After all, the cost items are basically independent of each other in terms of cost expenditure. Therefore, when conducting important cost control analysis, the determined cost items should all be independent, and for independent cost items, their impact on profits is also relatively intuitive and obvious. Therefore, when confirming important control costs, judgments can be made based on independence, which is an important way to judge important control cost items. The second aspect is that for different important control cost items, there may be three situations in which their impact on corporate profits. One is that the increase in the cost of important control cost items will cause profits to increase in the same direction at the same time. For example, the increase in the cost of important control cost items will also increase corporate profits at the same time, which shows that the impact of important control cost items on corporate profits is positive. The second is that the increase in important control costs does not lead to a significant increase in corporate profits, but it can indeed maintain the company's profits. The contribution of this kind of important control costs to corporate profits is also relatively obvious and important. The third is that the change in important control costs leads to a reverse change in corporate profits. This change is a common category of cost items that affect corporate profits in most companies. Important control cost items in these three situations need to be analyzed and considered in order to achieve a more comprehensive and comprehensive optimization control of corporate costs. Of course, when judging important control cost items, the impact of a single cost item change on corporate profits is the easiest to judge. For the situation where multiple cost items change during the analysis period, consider the impact of the same or partially identical cost item changes on corporate profits during different analysis periods to conduct a comprehensive analysis and judgment of important control cost items.

[0015] As a possible implementation method, cost impact analysis is performed based on cost item change information corresponding to different important control cost items and combined with profit change information to form cost item impact data, including: for different important control cost items, the corresponding relationship between the changes in important control cost items and profits is extracted from the change information of the analysis period determined to be important control cost items to form change impact relationship information corresponding to the important control cost items; based on the change impact relationship information corresponding to different important control cost items, an impact comparison is performed to determine the cost impact data.

[0016] In the present invention, since the direction and magnitude of the impact of three different types of important control cost items on corporate profits are different, the three different types should be analyzed and judged separately to determine the order of the impact of each type on corporate profits.

[0017] As a possible implementation method, for different important control cost items, the corresponding relationship between the important control cost items and the profit changes is extracted from the analysis period change information of the important control cost items, and the change impact relationship information corresponding to the important control cost items is formed, including: for negative important control cost items: extract the negative cost change amount of the negative important control cost items according to the corresponding analysis period change information and negative relative change in profit And according to the negative cost change and negative relative change in profit The corresponding relationship in the time dimension sequence forms a negative control change influence relationship Where n represents the number of different negative important control cost items. Indicates the total negative change in profit of the negative important control cost item numbered n as the negative important control cost changes in the analysis period change information that is judged to be an important control cost item; for the constant important control cost item: determine the analysis period change information that can directly quantify the impact of the change of the constant important control cost item on the profit, and extract the constant control value range A of the constant important control cost based on the determined analysis period change information m , m represents different constant important control cost items; for positive important control cost items: extract the positive cost change of positive important control cost items according to the corresponding analysis period change information and the positive relative change in profit And according to the positive cost change and the positive relative change in profit The corresponding relationship in the time dimension sequence forms a positive control change influence relationship Among them, k represents the number of different positive important control cost items, It represents the total positive change in profit of the positive important control cost item numbered k in the analysis period change information that is judged to be an important control cost item as the profit changes with the positive important control cost.

[0018] In the present invention, it can be understood that the changes in corporate profits caused by the cost changes of important control cost items have an independent corresponding relationship, so the relationship analysis between the cost change amount and the profit change amount can be performed based on the determined analysis period change information, so that the corresponding important control cost items can be provided. The predicted relationship of the impact on corporate profits can also be provided for the subsequent adaptive cost optimization control of different important control cost items. It should be noted that for constant important control cost items, since they have the direct compensation of cost consumption, their impact on corporate profits can be directly expressed in terms of cost consumption, and based on big data, it can be determined within what cost consumption range different constant important control cost items can maintain this immediate direct compensation.

[0019] As a possible implementation method, the impact degree is compared according to the change impact relationship information corresponding to different important control cost items to determine the cost impact size data, including: for different negative important control cost items, according to the corresponding negative relative change amount of profit Integrate the information of changes in the analysis period in the time dimension, and sort the different negative important control cost items in descending order according to the integral value to form a negative important control cost impact sequence set; for different constant important control cost items, according to the corresponding constant control value range A m The maximum values ​​of the constant important control cost are sorted from large to small to form a constant important control cost impact sequence set; for different positive important control cost items, according to the corresponding positive relative change in profit The information on changes in the analysis period is integrated in the time dimension, and different positive important control cost items are sorted in descending order according to the integral value to form a positive important control cost impact order set.

[0020] In the present invention, for different types of important control cost items, the ranking order formed is determined based on the impact of the change in each cost on the enterprise's profit. It can be understood that for negative and positive important control costs, the total amount of profit change corresponding to the change in cost over the same time span can well determine the degree of its impact on the enterprise's profit. For constant important control costs, the corresponding scope of application can be established based on big data.

[0021] As a possible implementation method, cost control optimization analysis is performed on different important control cost items based on cost item impact data to form cost control optimization data, including: according to different types of important control cost items, impact-based allowable limit analysis is performed on different important control cost items to determine the allowable control optimization limit values ​​corresponding to the important control cost items; the allowable control optimization limit values ​​corresponding to different important control cost items are determined as the corresponding cost optimization control targets.

[0022] In the present invention, after obtaining the influence relationship of different important control cost items on enterprise profits, the optimization of enterprise costs can be adaptively analyzed based on the influence relationship, and then the optimization restriction characteristics can be used to achieve reasonable optimization of enterprise costs. It should be noted that the obtained optimization restriction characteristics are mainly to provide an optimization guide for subsequent cost budgeting, and according to this guide, real-time control of subsequent actual cost use can achieve reasonable optimization control of costs.

[0023] As a possible implementation method, according to different types of important control cost items, different important control cost items are subjected to allowable limit analysis based on the degree of influence, and the allowable control optimization limit values ​​corresponding to the important control cost items are determined, including: For negative important control cost items: according to the arrangement order of different negative important control cost items in the sequence of negative important control cost influence, the negative reduction control rate of different negative important control cost items is determined. in: i represents the sequence number of different negative important control cost items determined according to the arrangement order of the negative important control cost impact sequence set, It represents the integral value of the negative relative change in profit corresponding to the negative important control cost item with sequence number i in the time dimension of the change information of the analysis period; for constant important control cost items: according to the arrangement order of different constant important control cost items in the constant important control cost impact sequence set, the constant expansion control rate of different constant important control cost items is determined in: t represents the sequence number of different constant important control cost items determined according to the arrangement order of the constant important control cost impact sequence set, Indicates the maximum value of the constant control value range corresponding to the constant important control cost item with sequence number t; for positive important control cost items: according to the arrangement order of different positive important control cost items in the positive important control cost impact sequence set, determine the positive reduction control rate of different positive important control cost items in: z represents the sequence number of different positive important control cost items determined according to the arrangement order of the positive important control cost impact sequence set, It represents the integral value of the positive relative change in profit corresponding to the positive important control cost item with sequence number z in the time dimension of the change information in the analysis time period.

[0024] In the present invention, since different important control cost items have different impacts on corporate profits, the optimization restriction characteristics established are also different. For negative important control cost items, since their impact on corporate profits is negative, it is hoped that they will be reduced to a certain extent during optimization, so the optimization restriction characteristics obtained are the reduction control ratio of the cost budget, and this ratio is determined according to the proportion of all negative important control costs on corporate profits. Similarly, for positive important control cost items, a certain cost increase can be allowed, and this increase is determined by the ratio of the impact of different positive important control cost items on corporate profits. For constant important control cost items, considering that they have the characteristic of maintaining a flat profit for the company, an allowable cost increase is also provided, and the increase is determined by the ratio of the maximum cost values ​​that can be obtained by different constant important control cost items.

[0025] In a second aspect, the present invention provides an enterprise cost optimization system based on big data, which is configured to: obtain the enterprise's cost-benefit data, and conduct a cost impact analysis on profits to determine important control cost items; conduct a cost impact analysis based on cost item change information corresponding to different important control cost items and in combination with the profit change information to form cost item impact data; based on the cost item impact data, conduct a cost control optimization analysis on different important control cost items to form cost control optimization data.

[0026] In the present invention, the system configures an overall system that can adaptively realize reasonable optimization control of cost items by acquiring the impact of different cost items on profits from the enterprise's cost-benefit data, thereby ensuring the efficient realization of reasonable and comprehensive optimization control of enterprise costs, and is an important material basis for completing and realizing enterprise cost optimization control.

[0027] The beneficial effects of the enterprise cost optimization method and system based on big data provided by the present invention are as follows:

[0028] This method uses the company's historical cost-revenue data to analyze the impact of different cost items on profits to identify cost items with greater impact on profits, and then determines the optimization control direction and specific quantitative data of different cost items based on the quantitative relationship between the degree of impact of cost items on profits, thereby achieving reasonable enterprise cost optimization control based on the different degrees of impact on enterprise profits. Compared with the traditional manual control and analysis of a single cost item, this method is more efficient, and because it combines big data information, it can more comprehensively and intuitively determine the specific impact of different cost items on profits, and then make adaptive adjustments, avoiding the impact of unreasonable cost control on the basic necessary expenditures of cost items, thereby avoiding the negative impact of unreasonable cost control on enterprise operations and development, and can provide accurate and reliable data reference for enterprise cost optimization control.

[0029] The system configures an overall system that can adaptively realize reasonable optimization control of cost items by obtaining the impact of different cost items on profits from the enterprise's cost-revenue data, ensuring the efficient realization of reasonable and comprehensive optimization control of enterprise costs. It is an important material basis for completing and realizing enterprise cost optimization control. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for use in the embodiments of the present invention are briefly introduced below. It should be understood that the following drawings only show certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without creative work.

[0031] Figure 1 A step diagram of a method for enterprise cost optimization based on big data provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0032] The technical solutions in the embodiments of the present invention will be described below in conjunction with the accompanying drawings in the embodiments of the present invention.

[0033] In order to obtain better profits, enterprises not only need to promote the growth of income sources, but also need to reasonably control the costs of the enterprise, and ensure that the enterprise forms a good operating system by reducing costs and increasing efficiency. Of course, with the intensification of market competition, it is more difficult for enterprises to expand and develop their business in the market and to increase their profit growth points to a greater extent. Therefore, more reasonable cost control for enterprises is particularly prominent in increasing corporate benefits.

[0034] At present, the cost control of enterprises is usually achieved by re-evaluating and tracking specific cost items, and it is impossible to comprehensively consider cost expenditures, resulting in some cost reduction control methods having a significant side effect on the operation and even development of the enterprise. With the progress of science and society, big data technology is becoming more and more mature, and it is possible to use big data to conduct a comprehensive and comprehensive analysis of relatively large enterprise cost data to achieve reasonable optimization and cost control of cost items.

[0035] refer to Figure 1 The embodiment of the present invention provides an enterprise cost optimization method based on big data. The method determines the cost items with greater impact on profits by analyzing the impact of different cost items on profits from the historical cost-revenue data of the enterprise, and then determines the optimization control direction and specific quantitative data of the optimization control of different cost items according to the quantitative relationship between the impact of the cost items on profits, thereby realizing reasonable enterprise cost optimization control based on the different degrees of impact on enterprise profits. Compared with the traditional manual control analysis of a single cost item, it is more efficient, and because it combines big data information, it can more comprehensively and intuitively determine the specific impact of different cost items on profits, and then make adaptive adjustments, thereby avoiding the impact of unreasonable cost control on the basic necessary expenses of the cost items, thereby avoiding the negative impact of unreasonable cost control on the operation and development of the enterprise, and providing accurate and reliable data reference for the cost optimization control of the enterprise.

[0036] The enterprise cost optimization method based on big data specifically includes the following steps:

[0037] S1: Obtain the enterprise's cost-benefit data, conduct a cost impact analysis on profits, and identify important control cost items.

[0038] Obtain the enterprise's cost and income data, and conduct a cost impact analysis on profits to determine the important control cost items, including: determining the change data of different cost items in the time dimension sequence based on the cost and income data, and forming cost item change information corresponding to different cost items; determining the change data of profits in the time dimension sequence based on the cost and income data, and forming profit change information; combining the cost item change information and profit change information corresponding to different cost items, conduct a cost item importance analysis on profit changes, and determine different important control cost items.

[0039] To optimize the cost of an enterprise reasonably, it is necessary to determine the cost items that really need to be optimized and controlled, so as to achieve reasonable optimization of costs and avoid the adverse effects of cost optimization such as affecting the development and operation of the enterprise. It can be understood that for the cost of an enterprise, the purpose of optimizing it is to avoid excessive cost expenditures from having a greater impact on the profit of the enterprise. Therefore, when confirming the cost items that need to be optimized, it is necessary to combine the change data of the cost items with the change data of the profit to determine the important control cost items that really affect the profit.

[0040] Combine the cost item change information and profit change information corresponding to different cost items, conduct a cost item importance analysis for profit changes, and determine different important control cost items, including: matching the cost item change information corresponding to different cost items with the profit change information in time dimension sequence; setting an analysis time period, and continuously dividing the different cost item change information and profit change information according to the analysis time period to extract different analysis period change information; conducting a logical comparison analysis of changes in not all cost items for all analysis period change information to determine important control cost items.

[0041] It is understandable that the original big data information corresponding to the different cost items obtained is changing data within a wider time range, and this changing data includes different changing situations or time periods of the cost items. Therefore, in order to facilitate the determination of whether the cost items are objects that really need to be controlled and have an impact on profits, it is necessary and reasonable to divide the original big data of the cost items into time periods based on the time dimension. In this way, reasonable cost item analysis can be carried out for each time period, avoiding the inability to efficiently determine important control costs due to a large amount of data formed due to a large time span.

[0042] Performing a logical comparative analysis on all analysis period change information in which not all cost items have changed, and determining the important controlling cost items, including: performing a logical comparative analysis on all analysis period change information in the following manner to determine the important controlling cost items: for analysis period change information in which only one cost item has changed during the analysis period, if the change in the cost item causes the profit to change asynchronously in the same direction, then the changed cost item is determined as a negative important controlling cost item; for analysis period change information in which only one cost item has changed during the analysis period, if the change in the cost item causes the profit to change asynchronously in the opposite direction, then the changed cost item is determined as a positive important controlling cost item; for analysis period change information in which only one cost item has changed during the analysis period, if the change in the cost item causes the profit to remain unchanged, then the changed cost item is determined as a constant important controlling cost item; for all analysis period change information in which multiple cost items have changed during the analysis period, mark the multiple cost items that change in the same direction at the same time. The analysis period change information that causes the profit to change synchronously in the same direction is identified, and the corresponding changed cost items in the analysis period change information are determined as stable impact cost items, and the remaining analysis period change information is analyzed as follows: If there is only one cost item that has changed in the analysis period change information that is not a stable impact cost item, and the profits do not change synchronously in the same direction when all the changed cost items change in the same direction, then the changed non-stable impact cost item will be determined as a negative important controlling cost; if there is only one cost item that has changed in the analysis period change information that is not a stable impact cost item, and the profits do not change synchronously in the opposite direction when all the changed cost items change in the same direction, then the changed non-stable impact cost item will be determined as a positive important controlling cost item; if there is only one cost item that has changed in the analysis period change information that is not a stable impact cost item, and the profits do not change when all the changed cost items change in the same direction, then the changed non-stable impact cost item will be determined as a constant important controlling cost item.

[0043] The determination of important control cost items needs to consider three aspects. On the one hand, the impact of important control costs on profits needs to be expressed intuitively, and cost items that can be expressed intuitively are relatively independent. After all, cost items are basically independent of each other in terms of cost expenditure. Therefore, when conducting important cost control analysis, the determined cost items should be independent, and for independent cost items, their impact on profits is also relatively intuitive and obvious. Therefore, when confirming important control costs, judgments can be made based on independence, which is an important way to determine important control cost items. The second aspect is that for different important control cost items, there may be three situations in which their impact on corporate profits may exist. One is that the increase in the cost of important control cost items will cause profits to increase in the same direction at the same time. For example, the increase in the cost of important control cost items will also increase corporate profits at the same time, which shows that the impact of important control cost items on corporate profits is positive. The second is that the increase in important control costs does not lead to a significant increase in corporate profits, but it can indeed maintain the company's profits. The contribution of this kind of important control costs to corporate profits is also relatively obvious and important. The third is that the change in important control costs leads to a reverse change in corporate profits. This change is a common category of cost items that affect corporate profits in most companies. Important control cost items in these three situations need to be analyzed and considered in order to achieve a more comprehensive and comprehensive optimization control of corporate costs. Of course, when judging important control cost items, the impact of a single cost item change on corporate profits is the easiest to judge. For the situation where multiple cost items change during the analysis period, consider the impact of the same or partially identical cost item changes on corporate profits during different analysis periods to conduct a comprehensive analysis and judgment of important control cost items.

[0044] S2: Based on the cost item change information corresponding to different important control cost items and combined with the profit change information, the cost impact analysis is carried out to form the cost item impact data.

[0045] Based on the cost item change information corresponding to different important control cost items and combined with the profit change information, the cost impact size analysis is performed to form cost item impact data, including: for different important control cost items, the corresponding relationship between the changes in important control cost items and profits is extracted from the change information of the analysis period judged to be important control cost items, to form the change impact relationship information corresponding to the important control cost items; based on the change impact relationship information corresponding to different important control cost items, the impact is compared to determine the cost impact size data.

[0046] The impact of important control cost items on corporate profits. Since the three different types of important control cost items have different directions and magnitudes of impact on corporate profits, the three different types should be analyzed and judged separately to determine the order of the impact of each type on corporate profits.

[0047] For different important control cost items, the corresponding relationship between the important control cost items and the profit changes is extracted from the analysis period change information of the important control cost items, forming the corresponding change impact relationship information of the important control cost items, including: For negative important control cost items: extract the negative cost change amount of the negative important control cost items according to the corresponding analysis period change information and negative relative change in profit And according to the negative cost change and negative relative change in profit The corresponding relationship in the time dimension sequence forms a negative control change influence relationship Where n represents the number of different negative important control cost items. Indicates the total negative change in profit of the negative important control cost item numbered n as the negative important control cost changes in the analysis period change information that is judged to be an important control cost item; for the constant important control cost item: determine the analysis period change information that can directly quantify the impact of the change of the constant important control cost item on the profit, and extract the constant control value range A of the constant important control cost based on the determined analysis period change information m , m represents different constant important control cost items; for positive important control cost items: extract the positive cost change of positive important control cost items according to the corresponding analysis period change information and the positive relative change in profit And according to the positive cost change and the positive relative change in profit The corresponding relationship in the time dimension sequence forms a positive control change influence relationship Among them, k represents the number of different positive important control cost items, It represents the total positive change in profit of the positive important control cost item numbered k in the analysis period change information that is judged to be an important control cost item as the profit changes with the positive important control cost.

[0048] It can be understood that the changes in corporate profits caused by the cost changes of important control cost items have an independent corresponding relationship. Therefore, the relationship between the cost change and the profit change can be analyzed based on the determined analysis period change information. In this way, the corresponding important control cost items can provide a predicted relationship for the impact on corporate profits, and also provide data reference for subsequent adaptive cost optimization control for different important control cost items. It should be noted that for constant important control cost items, since they have the direct compensation of cost consumption, their impact on corporate profits can be directly expressed in terms of cost consumption, and based on big data, it can be determined within what range of cost consumption different constant important control cost items can maintain this immediate direct compensation.

[0049] According to the change impact relationship information corresponding to different important control cost items, the impact degree is compared to determine the cost impact size data, including: for different negative important control cost items, according to the corresponding negative relative change in profit Integrate the information of changes in the analysis period in the time dimension, and sort the different negative important control cost items in descending order according to the integral value to form a negative important control cost impact sequence set; for different constant important control cost items, according to the corresponding constant control value range A m The maximum values ​​of the constant important control cost are sorted from large to small to form a constant important control cost impact sequence set; for different positive important control cost items, according to the corresponding positive relative change in profit The information on changes in the analysis period is integrated in the time dimension, and different positive important control cost items are sorted in descending order according to the integral value to form a positive important control cost impact order set.

[0050] For different types of important control cost items, the ranking order formed is determined based on the impact of their respective cost changes on corporate profits. It can be understood that for negative and positive important control costs, the total amount of profit changes corresponding to the cost changes over the same time span can well determine the extent of their impact on corporate profits. For constant important control costs, the corresponding scope of application can be established based on big data.

[0051] S3: Based on the cost item impact data, cost control optimization analysis is performed on different important control cost items to generate cost control optimization data.

[0052] Based on the cost item impact data, cost control optimization analysis is performed on different important control cost items to form cost control optimization data, including: based on the different types of important control cost items, an allowable limit analysis based on the impact is performed on different important control cost items to determine the allowable control optimization limit values ​​corresponding to the important control cost items; the allowable control optimization limit values ​​corresponding to different important control cost items are determined as the corresponding cost optimization control targets.

[0053] After obtaining the influence of different important control cost items on enterprise profits, the optimization of enterprise costs can be adaptively analyzed based on the influence relationship, and then the optimization restriction characteristics can be used to achieve reasonable optimization of enterprise costs. It should be noted that the obtained optimization restriction characteristics are mainly to provide an optimization guide for subsequent cost budgeting. According to this guide, real-time control of subsequent actual cost use can achieve reasonable optimization control of costs.

[0054] According to the different types of important control cost items, the allowable limit analysis based on the impact degree is carried out on different important control cost items to determine the allowable control optimization limit value corresponding to the important control cost items, including: For negative important control cost items: According to the arrangement order of different negative important control cost items in the negative important control cost impact sequence set, the negative reduction control rate R of different negative important control cost items is determined. i opp ,in: i represents the sequence number of different negative important control cost items determined according to the arrangement order of the negative important control cost impact sequence set, U i opp It represents the integral value of the negative relative change in profit corresponding to the negative important control cost item with sequence number i in the time dimension of the change information of the analysis period; for constant important control cost items: according to the arrangement order of different constant important control cost items in the constant important control cost impact sequence set, the constant expansion control rate of different constant important control cost items is determined in: t represents the sequence number of different constant important control cost items determined according to the arrangement order of the constant important control cost impact sequence set, Indicates the maximum value of the constant control value range corresponding to the constant important control cost item with sequence number t; for positive important control cost items: according to the arrangement order of different positive important control cost items in the positive important control cost impact sequence set, determine the positive reduction control rate of different positive important control cost items in: z represents the sequence number of different positive important control cost items determined according to the arrangement order of the positive important control cost impact sequence set, It represents the integral value of the positive relative change in profit corresponding to the positive important control cost item with sequence number z in the time dimension of the change information in the analysis time period.

[0055] Since different important control cost items have different impacts on corporate profits, the optimization restriction characteristics established are also different. For negative important control cost items, since their impact on corporate profits is negative, it is hoped that they will be reduced to a certain extent during optimization. Therefore, the optimization restriction characteristics obtained are the reduction control ratio of the cost budget. This ratio is determined according to the proportion of the impact of all negative important control costs on corporate profits. Similarly, for positive important control cost items, a certain cost increase can be allowed. This increase is determined by the proportion of the impact of different positive important control cost items on corporate profits. For constant important control cost items, considering that they have the characteristic of maintaining a flat impact on corporate profits, an allowable cost increase is also provided. The increase is determined by the ratio of the maximum cost values ​​that can be obtained by different constant important control cost items.

[0056] The present invention also provides an enterprise cost optimization system based on big data, which is configured to: obtain the enterprise's cost-benefit data, and conduct a cost impact analysis on profits to determine important control cost items; conduct a cost impact analysis based on cost item change information corresponding to different important control cost items and in combination with the profit change information to form cost item impact data; based on the cost item impact data, conduct a cost control optimization analysis on different important control cost items to form cost control optimization data.

[0057] The system configures an overall system that can adaptively realize reasonable optimization control of cost items by obtaining the impact of different cost items on profits from the enterprise's cost-revenue data, ensuring the efficient realization of reasonable and comprehensive optimization control of enterprise costs. It is an important material basis for completing and realizing enterprise cost optimization control.

[0058] In summary, the enterprise cost optimization method and system based on big data provided by the embodiments of the present invention have the following beneficial effects:

[0059] This method uses the company's historical cost-revenue data to analyze the impact of different cost items on profits to identify cost items with greater impact on profits, and then determines the optimization control direction and specific quantitative data of different cost items based on the quantitative relationship between the degree of impact of cost items on profits, thereby achieving reasonable enterprise cost optimization control based on the different degrees of impact on enterprise profits. Compared with the traditional manual control and analysis of a single cost item, this method is more efficient, and because it combines big data information, it can more comprehensively and intuitively determine the specific impact of different cost items on profits, and then make adaptive adjustments, avoiding the impact of unreasonable cost control on the basic necessary expenditures of cost items, thereby avoiding the negative impact of unreasonable cost control on enterprise operations and development, and can provide accurate and reliable data reference for enterprise cost optimization control.

[0060] The system configures an overall system that can adaptively realize reasonable optimization control of cost items by obtaining the impact of different cost items on profits from the enterprise's cost-revenue data, ensuring the efficient realization of reasonable and comprehensive optimization control of enterprise costs. It is an important material basis for completing and realizing enterprise cost optimization control.

[0061] In the embodiments of the present application, "indication" may include direct indication and indirect indication, and may also include explicit indication and implicit indication. The information indicated by a certain information is called information to be indicated. In the specific implementation process, there are many ways to indicate the information to be indicated, such as but not limited to, the information to be indicated can be directly indicated, such as the information to be indicated itself or the index of the information to be indicated. The information to be indicated can also be indirectly indicated by indicating other information, wherein there is an association between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while the other parts of the information to be indicated are known or agreed in advance. For example, the indication of specific information can also be achieved by means of the arrangement order of each piece of information agreed in advance (for example, specified by the protocol), thereby reducing the indication overhead to a certain extent. At the same time, the common parts of each piece of information can also be identified and indicated uniformly to reduce the indication overhead caused by indicating the same information separately.

[0062] In addition, the specific indication method may also be various existing indication methods, such as but not limited to the above-mentioned indication methods and various combinations thereof. The specific details of the various indication methods can refer to the prior art and will not be repeated herein. As can be seen from the above, for example, when it is necessary to indicate multiple information of the same type, different indication methods may be used for different information. In the specific implementation process, the desired indication method can be selected according to specific needs. The embodiment of the present application does not limit the selected indication method. In this way, the indication method involved in the embodiment of the present application should be understood to cover various methods that can enable the party to be indicated to obtain the information to be indicated.

[0063] It should be understood that the information to be indicated can be sent as a whole, or divided into multiple sub-information and sent separately, and the sending period and / or sending time of these sub-information can be the same or different. The specific sending method is not limited in the embodiment of the present application. Among them, the sending period and / or sending time of these sub-information can be pre-defined, for example, pre-defined according to a protocol, or can be configured by the sending end device by sending configuration information to the receiving end device.

[0064] "Pre-definition" or "pre-configuration" can be implemented by pre-saving corresponding codes, tables or other methods that can be used to indicate relevant information in the device, and the embodiments of the present application do not limit the specific implementation method. Among them, "saving" can mean saving in one or more memories. The one or more memories can be set separately or integrated in an encoder or decoder, a processor, or a communication device. The one or more memories can also be partially set separately and partially integrated in a decoder, a processor, or a communication device. The type of memory can be any form of storage medium, which is not limited by the embodiments of the present application.

[0065] The "protocol" involved in the embodiments of the present application may refer to a protocol family in the communication field, a standard protocol with a similar protocol family frame structure, or a related protocol used in future communication systems, and the embodiments of the present application do not make specific limitations on this.

[0066] In the embodiments of the present application, descriptions such as "when...", "in the case of...", "if" and "if" all mean that the device will make corresponding processing under certain objective circumstances. It does not limit the time, nor does it require the device to have a judgment action when implementing it, nor does it mean that there are other limitations.

[0067] In the description of the embodiments of the present application, unless otherwise specified, " / " indicates that the objects associated before and after are in an "or" relationship, for example, A / B can represent A or B; "and / or" in the embodiments of the present application is only a description of the association relationship of the associated objects, indicating that there can be three relationships, for example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural. In addition, in the description of the embodiments of the present application, unless otherwise specified, "multiple" refers to two or more than two. "At least one of the following" or its similar expression refers to any combination of these items, including any combination of single items or plural items. For example, at least one of a, b or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple. In addition, in order to facilitate the clear description of the technical solution of the embodiments of the present application, in the embodiments of the present application, the words "first" and "second" are used to distinguish the same or similar items with basically the same functions and effects. Those skilled in the art will appreciate that words such as "first" and "second" do not limit the quantity and execution order, and words such as "first" and "second" do not necessarily limit the difference. At the same time, in the embodiments of the present application, words such as "exemplary" or "for example" are used to indicate examples, illustrations or explanations. Any embodiment or design described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a concrete way for easy understanding.

[0068] It should be understood that the processor in the embodiments of the present application may be a central processing unit (CPU), and the processor may also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), field programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc.

[0069] It should also be understood that the memory in the embodiments of the present application may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memories. Among them, the non-volatile memory may be a read-only memory (ROM), a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), or a flash memory. The volatile memory may be a random access memory (RAM), which is used as an external cache. By way of example and not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic random access memory (DRAM), synchronous DRAM (SDRAM), double data rate synchronous dynamic random access memory (DDR SDRAM), enhanced synchronous dynamic random access memory (ESDRAM), synchronous link DRAM (SLDRAM), and direct rambus RAM (DR RAM).

[0070] The above embodiments can be implemented in whole or in part by software, hardware (such as circuits), firmware or any other combination. When implemented using software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (such as infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (for example, a floppy disk, a hard disk, a tape), an optical medium (for example, a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0071] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0072] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0073] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0074] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0075] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0076] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0077] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0078] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0079] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0080] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for enterprise cost optimization based on big data, characterized in that: include: Obtain the cost-benefit data of the enterprise, conduct cost impact analysis on profits, and identify important cost control items; According to the cost item change information corresponding to the different important control cost items, and combined with the profit change information, the cost impact size analysis is performed to form the cost item impact data; According to the cost item impact data, cost control optimization analysis is performed on different important control cost items to form cost control optimization data.

2. The enterprise cost optimization method based on big data according to claim 1 is characterized in that: The acquisition of the enterprise's cost-benefit data, and the analysis of the cost impact on profits, determine the important control cost items, including: According to the cost-benefit data, determining the change data of different cost items in the time dimension sequence, and forming the cost item change information corresponding to the different cost items; According to the cost-benefit data, determining the profit change data in the time dimension sequence to form profit change information; By combining the cost item change information and the profit change information corresponding to different cost items, an importance analysis of the cost items for profit changes is performed to determine different important control cost items.

3. The enterprise cost optimization method based on big data according to claim 2 is characterized in that: The combining the cost item change information and the profit change information corresponding to different cost items, performing a cost item importance analysis for profit changes, and determining different important control cost items, includes: Matching the cost item change information corresponding to different cost items with the profit change information in the order of time dimension; Setting an analysis time period, and continuously dividing the cost item change information and the profit change information according to the analysis time period, and extracting the change information of different analysis periods; A logical comparison analysis of changes in non-all cost items is performed on all the analysis period change information to determine the important control cost items.

4. The enterprise cost optimization method based on big data according to claim 3 is characterized in that: The logical comparison analysis of changes in non-all cost items on all the analysis period change information to determine the important control cost items includes: Perform logical comparison and analysis on all the analysis period change information to determine the important control cost items in the following manner: For the analysis period change information in which only one cost item changes during the analysis period, if the change of the cost item causes the profit to change asynchronously in the same direction, the changed cost item is determined as a negative important controlling cost item; For the analysis period change information in which only one cost item changes during the analysis period, if the change of the cost item causes an asynchronous reverse change in profit, the changed cost item is determined as a positive important controlling cost item; For the analysis period change information in which only one cost item changes during the analysis period, if the change in the cost item results in no change in profit, the changed cost item is determined as a constant important controlling cost item; For all the analysis period change information in which multiple cost items change during the analysis period, the analysis period change information in which multiple cost items change in the same direction at the same time, resulting in synchronous and same-direction changes in profits, is identified, and the corresponding changed cost items in the analysis period change information are determined as stable impact cost items, and the following analysis is performed on the remaining analysis period change information: If there is only one cost item that has changed in the analysis period change information that is not the stable impact cost item, and when all the changed cost items change in the same direction, the profits do not change in the same direction synchronously, then the changed cost item that is not the stable impact cost item is determined as a negative important control cost; If there is only one cost item that has changed in the analysis period change information that is not the stable impact cost item, and when all the cost items that have changed change in the same direction, the profit does not change in the opposite direction synchronously, then the changed cost item that is not the stable impact cost item is determined as a positive important control cost item; If there is only one cost item that has changed in the change information during the analysis period that is not the stable impact cost item, and the profit does not change when all the changed cost items change in the same direction, then the changed cost item that is not the stable impact cost item will be determined as a constant important controlling cost item.

5. The enterprise cost optimization method based on big data according to claim 4 is characterized in that: The cost item change information corresponding to the different important control cost items is combined with the profit change information to perform cost impact analysis to form cost item impact data, including: For different important control cost items, extract the change correspondence between the important control cost items and profits from the analysis period change information determined to be the important control cost items, and form the change impact relationship information corresponding to the important control cost items; According to the change impact relationship information corresponding to different important control cost items, impact degree comparison is performed to determine cost impact size data.

6. The enterprise cost optimization method based on big data according to claim 5 is characterized in that: For different important control cost items, extracting the change correspondence between the important control cost items and the profit from the analysis period change information determined to be the important control cost items, and forming the change impact relationship information corresponding to the important control cost items, including: For the negative significant control cost items: Extract the negative cost change of the negative important control cost item according to the corresponding analysis period change information and negative relative change in profit And according to the negative cost change and the negative relative change in profit The corresponding relationship in the time dimension sequence forms a negative control change influence relationship Wherein, n represents the number of different negative important control cost items, Indicates the total negative change in profit of the negative important control cost item numbered n in the analysis period change information determined to be the important control cost item as the negative important control cost changes; For the constant important control cost items: Determine the analysis period change information that can directly quantify the impact of the change of the constant important control cost item on the profit, and extract the constant control value range A of the constant important control cost based on the determined analysis period change information m , m represents different important control cost items of constants; For the positive important control cost items: Extract the positive cost change of the positive important control cost item according to the corresponding analysis period change information and the positive relative change in profit And according to the positive cost change and the positive relative change in profit The corresponding relationship in the time dimension sequence forms a positive control change influence relationship Wherein, k represents the number of different positive important control cost items, It represents the total positive change in profit of the positive important control cost item numbered k as the profit changes with the positive important control cost in the analysis period change information determined to be the important control cost item.

7. The enterprise cost optimization method based on big data according to claim 6 is characterized in that: The step of comparing the impact degrees according to the change impact relationship information corresponding to different important control cost items and determining the cost impact magnitude data includes: For different negative important control cost items, according to the corresponding negative relative change in profit Integrating the change information of the analysis time period in the time dimension, and sorting the different negative important control cost items in descending order of the integral value to form a negative important control cost influence order set; For different important constant control cost items, according to the corresponding constant control value range A m The maximum values ​​of are sorted from large to small to form a sequence set of the influence degree of constant important control costs; For different positive important control cost items, according to the corresponding positive relative change in profit The information on the change in the analysis time period is integrated in the time dimension, and different positive important control cost items are sorted in descending order according to the integrated values ​​to form a positive important control cost influence order set.

8. The enterprise cost optimization method based on big data according to claim 7 is characterized in that: The cost control optimization analysis is performed on different important control cost items according to the cost item impact data to form cost control optimization data, including: According to different types of the important control cost items, an allowable limit analysis based on the impact degree is performed on different important control cost items to determine the allowable control optimization limit values ​​corresponding to the important control cost items; The allowable control optimization limit values ​​corresponding to the different important control cost items are determined as corresponding cost optimization control targets.

9. The enterprise cost optimization method based on big data according to claim 8 is characterized in that: According to the different types of the important control cost items, the allowable limit analysis based on the impact degree is performed on different important control cost items to determine the allowable control optimization limit values ​​corresponding to the important control cost items, including: For the negative significant control cost items: According to the arrangement order of different negative important control cost items in the negative important control cost impact sequence set, the negative reduction control rate of different negative important control cost items is determined. in: i represents the sequence number of different negative important control cost items determined according to the arrangement order of the negative important control cost impact sequence set, Represents the integral value of the negative relative change in profit corresponding to the negative important control cost item with sequence number i in the time dimension of the change information of the analysis time period; Important control cost items for the constants are: According to the arrangement order of different constant important control cost items in the constant important control cost influence order set, the constant expansion control rate of different constant important control cost items is determined. in: t represents the sequence number of different constant important control cost items determined according to the arrangement order of the constant important control cost impact sequence set, Indicates the maximum value of the constant control value range corresponding to the constant important control cost item with sequence number t; For the positive important control cost items: According to the arrangement order of different positive important control cost items in the positive important control cost impact sequence set, the positive reduction control rate of different positive important control cost items is determined. in: z represents the sequence number of different positive important control cost items determined according to the arrangement order of the positive important control cost impact sequence set, It represents the integral value of the positive relative change in profit corresponding to the positive important control cost item with sequence number z in the time dimension of the change information during the analysis time period.

10. An enterprise cost optimization system based on big data, characterized in that: is configured as: Obtain the cost-benefit data of the enterprise, conduct cost impact analysis on profits, and identify important cost control items; According to the cost item change information corresponding to the different important control cost items, and combined with the profit change information, the cost impact size analysis is performed to form the cost item impact data; According to the cost item impact data, cost control optimization analysis is performed on different important control cost items to form cost control optimization data.

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