KR20110026094A - System and method for optimizing organization - Google Patents

Abstract

A knitting optimization system and method are disclosed. Embodiments of the present invention can derive a scheme for obtaining the maximum sales performance when selling items through TV, Internet, radio or other broadcasting media, and the expected performance calculated by the average contribution benefit based on past performance. By correcting this to reflect the promotion effect and seasonality, it is possible to derive an optimized programming plan.

Description

Organizing optimization system and its method {SYSTEM AND METHOD FOR OPTIMIZING ORGANIZATION}

Embodiments of the present invention relate to a programming system and a method thereof, and more particularly, to a system and method for optimizing and organizing an item in a broadcasting time slot when selling an item through a TV, the Internet, a radio, or other broadcasting media. .

Recently, the number of items sold through TV, Internet, radio and other broadcasting media is increasing. In addition, you can listen to detailed descriptions of items comfortably at home, as well as giveaways, interest-free installments, ARS discounts, and direct delivery to your home. The frequency of customer use is also increasing.

In the case of broadcast media, technologies for information exchange and communication between both broadcasters and viewers have been developed and developed, but information transmission by unilateral broadcasting time scheduling of broadcasters is still common. Therefore, even if a viewer wants to purchase an item through home shopping, it is inconvenient that it is difficult to purchase the item through home shopping if the sales broadcast of the desired item is not provided at the time of viewing.

The organization optimization system according to an embodiment of the present invention is a time value calculation unit for calculating time value information corresponding to the performance compared to the past time, an item derivation unit for deriving the item to be organized based on the calculated time value information, A predictive performance calculation unit that calculates an expected performance corresponding to the derived target item, a predictive performance correction unit that corrects the calculated expected performance by applying a correction variable to the calculated expected performance, and based on the corrected expected performance As such, it may include a draft proposal derivation unit for deriving an optimized draft plan.

In accordance with an embodiment of the present invention, a method for optimizing knitting comprises calculating time value information corresponding to past performances, deriving a knitting target item based on the calculated time value information, and obtaining the knitting target item. Calculating an expected performance corresponding to, correcting the calculated expected performance by applying a correction variable to the calculated expected performance, and deriving an optimized programming plan based on the corrected expected performance. Can be.

Embodiments of the present invention can derive a scheme for obtaining the maximum sales results when selling items through TV, Internet, radio or other broadcasting media.

In addition, the embodiments of the present invention may derive an optimized programming plan by correcting the expected result calculated as the average contribution benefit based on the past results, reflecting the promotion effect and seasonality.

Hereinafter, with reference to the contents described in the accompanying drawings will be described in detail an embodiment according to the present invention. However, the present invention is not limited or limited by the embodiments. Like reference numerals in the drawings denote like elements.

As used herein, the term 'organization' refers to not only organizing a broadcasting time for selling items in TV home shopping, but also organizing a broadcasting time for selling and advertising items in radio, internet broadcasting, department stores and other broadcasting media and retailers. Include.

In addition, the term 'item' as used herein refers to any item that is intended to be broadcasted for sale and advertising without limitations in the form of products (eg furniture, soy crab), service provision (eg insurance).

Hereinafter, exemplary embodiments of the present invention will be described in detail with reference to the accompanying drawings.

1 shows a configuration of a knitting optimization system according to an embodiment of the present invention.

Referring to FIG. 1, the organization optimization system 100 according to an embodiment of the present invention includes a time value calculation unit 110, an item extraction unit 120, an expected performance calculation unit 130, and an expected performance correction unit 140. ) And knitted eye relief 150.

The time value calculation unit 110 calculates time value information corresponding to past performance.

According to an embodiment, the time value calculation unit 110 may calculate time value information as an average contribution benefit for each time period based on past performance.

According to an embodiment of the present invention, 'contribution benefit' may be sales revenue per time slot / item. That is, the contribution profit may be sales revenue per time slot / item, which is sales revenue obtained by arranging arbitrary items at any time.

In addition, the 'average contribution contribution by time period' according to an embodiment of the present invention may be the sales revenue of all items organized in any time zone without division of the items.

In addition, the 'average contribution benefit per item' according to an embodiment of the present invention may be sales revenue obtained in any time zone in which any item is organized without time zone division.

According to an embodiment, the time value calculation unit 110 may calculate the contribution benefit and the average contribution benefit for each time zone by dividing the time zone by one hour unit and one minute unit.

According to an embodiment, the 'time value information' may be a percentage of the sales revenue and the increase or decrease of the sales volume compared to other time zones. For example, the time value information may be information that profits of 20 million won or more occur between 20 o'clock and 21 o'clock without item classification, or that 150% of sales volume can be obtained between 19 o'clock and 21 o'clock. have.

According to an embodiment, the time value calculation unit 110 may calculate time value information based on the performance of the last one year.

In addition, the time value calculation unit 110 may calculate time value information by distinguishing weekdays from weekends, separately calculating time value information of holidays, and excluding items subject to special contracts and flat-rates. Time value information can be estimated.

In addition, the time value calculation unit 110 may exclude a program whose actual broadcast amount is 15 minutes or less in order to calculate reliable time value information.

The item deriving unit 120 may derive a knitting target item based on the calculated time value information. That is, the item deriving unit 120 may primarily select and derive an item (that is, a knitting target item) that is an object of organization among all items that are desired to be broadcast for sale and advertisement.

According to an exemplary embodiment, the item derivation unit 120 may derive a knitting target item based on the calculated time value information. For example, the item deriving unit 120 may derive an item corresponding to a season or a season (Season) good item compared to other items in the time period as the item to be organized.

In addition, according to an embodiment, the item deriving unit 120 may derive new and planned items of the sourcing team as the item to be organized. In this case, the item deriving unit 120 may receive a knitting target item which is arbitrarily selected from the knitting manager because the past performance does not exist in the case of a new item, and may derive the knitting target item.

The expected performance calculator 130 calculates an expected performance corresponding to the derived knitting target item. Hereinafter, the expected performance calculation unit 130 will be described in more detail with reference to FIG. 2.

2 is a predicted performance chart showing the predicted performance calculated by the predictive performance calculation unit according to an embodiment of the present invention for each time zone / item.

Referring to FIG. 2, the predicted performance diagram 200 showing the predicted performance calculated by the predictive performance calculator 130 by time zone / item has a time zone on the horizontal axis 210, an item on the vertical axis 220, and a vertical axis. An expected result corresponding to the organization target item derived based on the time value information is indicated at 230. The predictive performance calculator 130 according to an embodiment of the present invention may output and display the predictive performance chart 200 so that the predicted performance by time / item can be easily understood.

In this case, the expected performance calculator 130 may list the knitting target items derived by the item extractor 120 on the vertical axis 220. According to an exemplary embodiment, the predictive performance calculator 130 may divide the time zone in units of 1 hour and 1 minute and display the time zone on the horizontal axis 210.

The expected performance calculation unit 130 according to an embodiment of the present invention may calculate the expected performance as the contribution profit (sales by time / item). According to an embodiment of the present invention, 'contribution profit' may be sales revenue per time slot / item, which is a sales revenue obtained by arranging any item at any time.

The expected performance calculator 130 according to an embodiment of the present invention may calculate the expected performance by reflecting at least one of a customer characteristic, a channel characteristic, and an item characteristic.

According to an embodiment, the customer characteristics may include i) customer satisfaction with the surveyed item based on the customer's testimonial and the result of the survey on the item satisfaction, and ii) whether the customer continues to use the item. Customer loyalty to the item and iii) customer's A / S claims / counts and complaints received about the item. For example, if the customer satisfaction and customer loyalty of a certain item is high and there are few or no customer requests, the predictive performance calculation unit 130 not only contributes profits based on past performance of the item but also the customer characteristics. By reflecting this, the expected performance can be calculated higher than the expected performance when considering only the contribution profit.

Depending on the embodiment, the channel characteristics may be i) broadcast organization of competitor channels and ii) viewer ratings. For example, if a competitor's channel broadcasts an item with a high sales rate (sales of an item corresponding to the season, application of a promotion, etc.) in an organizing time of an arbitrary item, the predictive performance calculating unit 130 may determine the item. Reflecting the channel characteristics as well as the contribution results based on the past results, the expected performance can be calculated lower than the expected performance when only the contribution profit is considered.

According to an embodiment, the item characteristic may be a product life cycle. For example, if the life cycle of any item is determined to be two years, and two years have passed since the item was placed on the market, the predictive performance calculator 130 may not only contribute the profit based on the past performance of the item. By reflecting the characteristics of the item, it is possible to calculate the expected performance lower than the expected performance when considering only the contribution profit.

The customer characteristic, the channel characteristic and the item characteristic are not limited thereto, and the predictive performance calculator 130 according to an exemplary embodiment of the present invention considers various characteristics that may affect the predicted performance. Expected performance can be calculated.

If the item to be knitted is an existing item that has been organized and sold in the past, the expected performance calculator 130 may calculate the expected performance as a contribution based on the past performance of the derived item to be knitted. According to an embodiment, the predictive performance calculation unit 130 may calculate the predicted performance as a contribution based on the performance of the past year.

If the item to be organized is a new item that has not been organized and sold in the past, since the historical performance data does not exist, the expected performance calculation unit 130 may calculate the expected performance based on time-based average contribution profit based on the past performance. have. According to an embodiment of the present invention, the time-based average contribution benefit may be the sales revenue of all items organized in any time zone without division of the items. According to an embodiment, the predictive performance calculation unit 130 may calculate the predicted performance as a contribution based on the performance of the past year.

Referring back to FIG. 1, the predictive performance correction unit 140 corrects the calculated predicted performance by applying a correction variable to the predicted performance calculated by the predictive performance calculating unit 130.

According to an embodiment of the present invention, the 'calibration variable' may mean a factor that has not been considered that may affect the calculated expected performance, and the 'calibration variable' refers to the effect of promotion, seasonality Or recent performance.

According to an embodiment, the predictive performance correction unit 140 may analyze the promotion effect on the organization target item and correct the expected performance by reflecting the analyzed promotion effect.

'Promotion' according to an embodiment of the present invention may mean an promotion of an item, and may mean an item additional configuration, interest-free installment, ARS discount, price discount, and premium.

In addition, the 'promotion effect' according to an embodiment of the present invention may refer to the degree of influence on the sales performance (contribution profit-time sales period / item sales revenue) when the promotion is applied to the item to be organized.

In addition, according to an embodiment, the predictive performance correction unit 140 may analyze the promotion effect by regressing the promotion level and the promotion performance.

According to an embodiment of the present invention, the 'promotion level' may include a degree that may affect the promotion of the sale of the item of any promotion, and according to the embodiment, the level of promotion that the customer can feel It can be decided in terms of monetary value.

For example, the predictive performance correction unit 140 may measure a high monetary value that a customer can feel when the bedding unit is made of a high-priced quilt as an additional component, and the unit price is low when the vacuum cleaner is sold. If you use the dust filter as an additional component, you can lower the monetary value that the customer can feel.

According to an embodiment of the present invention, 'promotional performance' may include a promotion rate according to a promotion level. In other words, the promotion result is the increase or decrease of the specific sales result when the promotion is applied, while the promotion effect is the degree of influence on the sales performance when the promotion is applied, and both can be distinguished.

For example, if a vacuum filter is added to the vacuum cleaner and the sales performance is increased by 5%, the promotion performance is 5%, but the effect of the promotion on the overall sales performance is insufficient, so the promotion effect can be classified as nonexistent or weak. have.

In addition, the predictive performance correction unit 140 may classify the item to be organized according to the strength information of the promotion effect analyzed through the regression analysis.

For example, the predictive performance correction unit 140 may classify the item to be organized under the category of i) presence of effect ii) weak effect iii) unconfirmed effect. If there is an effect, the predictive performance correction unit 140 may correct the predicted performance calculated by reflecting the intensity information of the promotion effect (that is, the information on the degree of the effect of the promotion effect on the sales performance). However, if the effect is weak or unconfirmed, the predictive performance correction unit 140 may not reflect the intensity information of the promotion effect.

Hereinafter, the predictive performance correction unit 140 for correcting the predicted performance by reflecting the promotion effect will be described in more detail with reference to FIG. 3.

3 is a table showing the promotion effect analyzed by the predictive performance correction according to an embodiment of the present invention.

Referring to FIG. 3, the promotion effect analysis table 300 shows a promotion level (in thousand won) on the horizontal axis and a promotion performance (%) on the vertical axis. In the case of the promotion effect analysis table 310 for mackerel, since the mackerel is a product with a relatively low selling price, even if the promotion level converted into monetary value is small (less than 50) or increases in a small amount, the performance of the promotion is increased. Is high (performance increases by 7.9% at 1,000 won). In the case of the promotion effect analysis table 320 for the pants 123, since the pants are products having a relatively medium selling price, the ratio of the promotion performance to the promotion level is smaller than △△ mackerel and higher than the abc sofa (when the increase is 1,000 won). Performance growth is 2.2%). In the case of the promotion effect analysis table 330 for the abc sofa, since the sofa is a product having a relatively high selling price, there is no promotion result when the promotion level converted into monetary value is 100 or less. In addition, the ratio of promotion performance to promotion level is also the smallest compared to △△ mackerel and 123 pants (increased by 1,000 won, the performance increase rate is 0.5%).

At this time, △△ mackerel may be classified as a high intensity of the promotion effect, abc sofa may be classified as a promotion effect is absent at the promotion level of 100 or less, the promotion effect may be classified as weak at 100 or more. Therefore, in the case of △△ mackerel, the expected performance correction due to the promotion effect can be widened.

Referring back to FIG. 1, according to an embodiment, the predictive performance correction unit 140 may correct the predicted performance by reflecting seasonality.

According to an embodiment of the present invention, the 'seasonality' is influenced by the sales volume and profit according to the season (season, season) of items (eg, seasonal fruits, air conditioners, fans, boilers) closely related to the season It can refer to the property receiving. According to an embodiment, when the average monthly contribution of any item exceeds the annual average contribution, the predicted performance correction unit 140 may determine that the item is seasonal. Alternatively, according to the embodiment, when the average monthly sales quantity of any item exceeds the annual average sales quantity, the predictive performance correction unit 140 may determine that the item is seasonal.

According to an embodiment, the predictive performance correction unit 140 reflects the difference between the monthly average contribution profit and the annual average contribution profit when the monthly average contribution profit of the item to be organized exceeds the annual average contribution profit. You can then correct the expected performance. At this time, according to an embodiment of the present invention, 'contribution profit' may be sales revenue per time slot / item.

According to an embodiment, the predictive performance correction unit 140 may correct the predicted performance by reflecting recent performance. That is, the predictive performance compensation government 140 may correct the predicted performance by reflecting the recent performance if there is a significant difference from the past performance. For example, the predictive performance compensation unit 140 may calculate the expected performance by reflecting the average performance of the last five times, rather than the annual average, if the performance of the last three times and five times has a significant difference from the previous broadcast.

The organization drafting unit 150 derives an optimized organization plan based on the corrected expected performance. According to an embodiment of the present invention, the 'optimized programming plan' may include a programming plan in which items are organized to obtain a maximum sales performance.

According to an embodiment, the knitting derivation unit 150 may include the fixed knitting target item at least one of a predetermined knitting date and a specific knitting time zone which are predetermined so as not to be affected by the knitting optimization system according to an embodiment of the present invention. Can be organized at

According to an embodiment of the present invention, the 'fixed organization target item' may include an item in which at least one of an organization date and a time zone of the items is predetermined. Similarly, according to an embodiment of the present invention, the 'non-fixed organization target item' may include an item in which both the organization date and the time zone are not predetermined.

In addition, the organizational drafting unit 150 may sort and organize the non-fixed knitting target items according to the priority of the calculated expected performance. According to an exemplary embodiment, when the calculated expected outcomes are the same, the knitted derivation unit 150 may arrange and organize the unfixed knitting target items according to the priority of the handling amount. That is, the organizational drafting unit 150 may organize the items so that the expected performance of the entire organization is high by organizing the items first in order of high expected performance (when the expected performance is the highest).

In addition, when the knitted non-fixed knitting target item is organized in a time zone close to the same non-fixed knitting target item, the knitted non-fixing knitting item 150 may reorganize the knitted non-fixed knitting target item. Through this, the knitting derivation unit 150 may arrange the same item at the farthest time zone with the knitted item.

In addition, when the knitted non-fixed knitting target item is organized in a time zone in which the knitted non-fixed knitting target item is organized in the past, the knitted non-fixed knitting target item may be reorganized. Through this, the knitted guide portion 150 may prevent the knitting fixation. For example, when an item is organized in a time zone in which any item has been organized in the past, the item guider 150 may reorganize the item in a time zone about 1 hour from the time zone.

Hereinafter, the knitted guide portion 150 will be described in more detail with reference to FIGS. 4 and 5.

4 and 5 illustrate an example of organizing an item to be knitted by a knitting guider according to an embodiment of the present invention.

Referring to FIG. 4, the first knitting table 410 displays a fixed knitting target item on at least one of a predetermined knitting date and a specific knitting time zone which are predetermined so as not to be affected by the knitting optimization system according to an embodiment of the present invention. The organized knitting table is shown. For example, if ○○ phone is set to be arranged on Monday 09 o'clock and Wednesday 10 o'clock, and □□ shoes are organized at 12 o'clock on Tuesday, the Knitting Departure Unit 150 is the ○○ phone and □□ shoes during the above time. Can be organized.

The sorting table 420 according to the priority of the predicted performance shows the sorting table in which the abc sofa has the highest predicted performance and is sorted first, and xx TV, 123 pants, and △△ mackerel are sequentially arranged. According to the embodiment, if the expected performance of the pants 123 and ΔΔ mackerel is the same, and the handling liquid of the 123 pants is high, the knitted desorption unit 150 may sort the 123 pants before the ΔΔ mackerel.

The second knitting table 430 shows a knitting table in which the non-fixed knitting target items are sequentially arranged in the sorted order in the knitting table in which the fixed knitting target item is first knitted. For example, the knitting derivation unit 150 may first organize ○○ phone and □□ shoes, which are fixed knitting target items, and randomly arrange abc sofas, which are non-fixed knitting target items, in an empty time zone. have. Thereafter, the knitting derivation unit 150 may sequentially arrange xx TV, 123 pants, and ΔΔ mackerel which are unfixed knitting target items at random in an empty time period.

According to the embodiment, since the non-fixed knitting target items are randomly arranged in the empty time slot, the knitting guide 150 may derive the optimized knitting plan by repeating the knitting process. For example, the knitting process may be simulated 1000 times to derive a knitting plan for obtaining a maximum sales performance.

Referring to FIG. 5, xx TVs are organized in the first programming table 510 at 10 o'clock Monday and 12 o'clock Monday. That is, since the xx TVs are organized in the adjacent time zone, the programming guide 150 may reorganize the xx TVs. The second programming table 520 shows a programming table in which xx TVs, which were organized at 12:00 on Monday, are reorganized at 13:00 on Wednesday.

For example, when the abc sofa organized at Wednesday 11 o'clock of the first knitting table 510 has been organized at Wednesday 11 o'clock in the past, the knitted security guide 150 may organize the abc sofa to prevent knitting fixation. You can regroup at 10 o'clock Wednesday, one hour before your time zone.

Referring back to FIG. 1, when the knitted non-fixed knitting target item has a knitting constraint, the knitted drafting unit 150 may reorganize the unfixed knitting target item that is knitted to satisfy the knitting constraint. The programming constraints may be, for example, that abc sofas can be organized only in a time zone of 20 to 24, xx TV must be organized at least three times per week, and 123 pants cannot be organized for two consecutive days.

According to an embodiment, when the knitting constraint is a condition relating to the time that the knitting should be minimum (ie, the minimum knitting time condition), the knitting derivation unit 150 may satisfy the minimum knitting time condition so as to satisfy the minimum knitting time condition. The second non-fixed knitting target item having the smallest expected outcome among the first non-fixed knitting target item and the knitted non-fixed knitting target item which do not satisfy the level may be replaced and reorganized.

Hereinafter, referring to FIG. 6, a knitting guide unit 150 that reorganizes an unfixed knitting target item to satisfy a minimum knitting time condition will be described in more detail.

6 illustrates an example of organizing an item to be knitted so as to satisfy a knitting constraint by a knitting guider according to an embodiment of the present invention.

Knitting unit 150 may derive an optimized knitting plan 610 without consideration of knitting constraints. However, for example, when there is a minimum knitting time condition that requires xx TV to be organized at least three times per week, and does not satisfy the minimum knitting time condition, the programming guide 150 may satisfy the minimum knitting time condition. The organization target item can be reorganized. The sorting table 620 according to the priority of the expected performance indicates that the best eraser has the smallest expected performance. Therefore, the knitting derivation unit 150 is the XX TV (the first non-fixed target item) and the organized non-fixed target item that does not meet the minimum knitting time conditions, the smallest expected performance of the eraser (second non-fixed pair) Can be reorganized by replacing the target item). The organization drafting unit 150 may derive the optimized programming plan 630 that satisfies the minimum programming time condition by reorganizing xx TVs on Wednesday 09 of the optimized programming plan 610 without consideration of the programming constraints. have.

In accordance with an embodiment of the present invention, a method for optimizing knitting comprises: calculating time value information corresponding to past performances, deriving a knitting target item based on the calculated time value information, and the derived knitting target Calculating an expected performance corresponding to the item, correcting the calculated expected performance by applying a correction variable to the calculated expected performance, and deriving an optimized programming plan based on the corrected expected performance. . In the knitting optimization method according to an embodiment of the present invention, since the contents described with reference to FIGS. 1 to 6 may be applied as it is, a detailed description thereof will be omitted.

Embodiments according to the present invention can be implemented in the form of program instructions that can be executed by various computer means can be recorded on a computer readable medium. The computer readable medium may include program instructions, data files, data structures, and the like, alone or in combination. Program instructions recorded on the media may be those specially designed and constructed for the purposes of the present invention, or they may be of the kind well-known and available to those having skill in the computer software arts. Examples of the computer-readable recording medium include magnetic media such as a hard disk, a floppy disk, and a magnetic tape; optical media such as CD-ROM and DVD; magnetic recording media such as a floppy disk; Magneto-optical media, and hardware devices specifically configured to store and execute program instructions such as ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

As described above, the present invention has been described by way of limited embodiments and drawings, but the present invention is not limited to the above embodiments, and those skilled in the art to which the present invention pertains various modifications and variations from such descriptions. This is possible.

Therefore, the scope of the present invention should not be limited to the described embodiments, but should be determined not only by the claims below but also by the equivalents of the claims.

1 shows a configuration of a knitting optimization system according to an embodiment of the present invention.

2 is a predicted performance chart showing the predicted performance calculated by the predictive performance calculation unit according to an embodiment of the present invention for each time zone / item.

3 is a table showing the promotion effect analyzed by the predictive performance correction according to an embodiment of the present invention.

4 and 5 illustrate an example of organizing an item to be knitted by a knitting guider according to an embodiment of the present invention.

6 illustrates an example of organizing an item to be knitted so as to satisfy a knitting constraint by a knitting guider according to an embodiment of the present invention.

Claims (19)

A time value calculation government that calculates time value information corresponding to past performance; An item deriving unit deriving a knitting target item based on the calculated time value information; An expected performance calculator configured to calculate an expected performance corresponding to the derived target item; An expected performance correction unit for correcting the calculated expected performance by applying a correction variable to the calculated expected performance; And Organizing plan derivation unit to derive an optimized programming plan based on the revised expected performance Organizational optimization system comprising a. The method of claim 1, wherein the time value calculation unit Organizing optimization system for calculating the time value information based on the past contribution based on time-based average contribution. The method of claim 1, wherein the expected performance calculation unit, When the derived knitting target item is an existing item, And a calculation optimization system for calculating the expected performance based on the contribution results based on past results of the derived knitting target item. The method of claim 1, wherein the expected performance calculation unit, When the derived knitting target item is a new item, A programming optimization system that calculates the expected performance based on the past contribution based on time-based average contribution. The method of claim 1, wherein the expected performance calculation unit, And calculating at least one of a customer characteristic, a channel characteristic, and an item characteristic of the derived knitting target item to calculate the expected performance. The method of claim 1, wherein the predictive performance correction unit, And analyzing the promotion effect on the derived knitting target item and correcting the calculated expected performance by reflecting the analyzed promotion effect. The method of claim 6, wherein the predictive performance compensation, And a regression analysis of a promotion level and a promotion result to analyze the promotion effect, and classify the derived knitting target item according to the intensity information of the analyzed promotion effect. The method of claim 7, wherein the predictive performance compensation, A programming optimization system for converting a promotion into a monetary value to determine the promotion level. The method of claim 7, wherein the predictive performance compensation, And a system for optimizing the calculated expected result by reflecting the intensity information of the promotion effect. The method of claim 1, wherein the predictive performance correction unit, When the average monthly contribution profit of the derived knitting target item is larger than the annual average contribution profit of the derived knitting target item, the calculation is performed by reflecting a difference between the monthly average contribution profit and the annual average contribution profit. Organizing optimization system to correct predicted performance. The method of claim 1, wherein the knitted ophthalmic portion, A knitting optimization system for organizing a fixed-organization target item on at least one of a specific organization date and a specific organization time zone. The method of claim 1, wherein the knitted ophthalmic portion, An organization optimization system for sorting and organizing non-fixed organization target items according to priorities of the calculated expected results. The method of claim 12, wherein And reorganize the knitted non-fixed knitting object item when the knitted non-fixed knitting object item is organized in a time zone close to the same non-fixed knitting object item. The method of claim 12, wherein And the non-fixed knitting target item is sorted and organized according to the priority of the handling amount when the calculated expected outcome is the same. The method of claim 12, wherein And when the organized non-fixed knitting object item is organized in a time zone in which the past organized experience is organized, reorganizing the knitted non-fixed knitting object item. The method of claim 12, wherein And if the knitted non-fixed knit object has a knitting constraint, reorganize the knitted unfixed knit object to satisfy the knitting constraint. The method of claim 16, wherein When the knitting constraint is a minimum knitting time condition, the calculated non-fixed knitting target item that does not satisfy the minimum knitting time condition and the knitted non-fixed knitting target item are satisfied to satisfy the minimum knitting time condition. A knitting optimization system that replaces and reorganizes a second unfixed knitting target with the smallest expected performance. Calculating time value information corresponding to past performance; Deriving a knitting target item based on the calculated time value information; Calculating an expected result corresponding to the derived knitting target item; Correcting the calculated expected performance by applying a correction variable to the calculated expected performance; And Deriving an optimized programming plan based on the corrected expected performance Organizing optimization method comprising a. A computer-readable recording medium having recorded thereon a program for performing the method of claim 18.

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