TWI900071B - Operating dimension management system - Google Patents

Abstract

The present invention discloses an operating dimension management system applicable for execution on a computer of an enterprise. The operating dimension management system includes an internal operating data collection module, an external operating data collection module, an industry data collection module, a calculation program, and an output interface. Through the value-added rate prediction step, profitability prediction step, market demand prediction step, capital expenditure prediction step, and classification step of the calculation program, coupled with the design of the high-value product field and low-value product field of the output interface, the operating dimension management system allows enterprise operators to clearly identify which products are high-value products and which are low-value products. This can assist enterprise operators in more easily adopting a fourth-dimension management approach to running their business and focusing on the correct path of developing high-value products.

Description

Operational Dimension Management System

The present invention relates to a management system, in particular to a business dimension management system.

Through years of practical experience in large-scale corporate management, the inventor discovered that from a business management perspective, business dimensions can be divided into four: Dimension 1: Execution by Order, Dimension 2: Sticking to Conventions, Dimension 3: Strategic Operations, and Dimension 4: Transcending Time and Space.

Companies operating in the first dimension generally follow this pattern: managers and subordinates carry out their work according to established SOPs or directives from senior management, without any deep reflection on the instructions or the work. This approach typically presents few major problems with profitability and operations, especially if the company's industry is booming and its products are hot sellers.

Even if a company operates in a 1st-dimension mode, profits may continue to increase if its industry is booming and its products are hot sellers. In this scenario, senior management believes the current operating strategy is on the right track and the company will continue to operate with the same strategy. During this phase, the company may have few competitors, and market demand for the product is only just beginning to emerge, though this demand remains largely unsatisfied.

As mentioned above, as the industry and products continue to sell well, a company's profits will continue to increase, and the company will easily enter the second dimension of operations: that is, the company will continue to operate with the same strategy and will not easily modify the current strategy. Some companies may even believe that the current strategy is the best strategy and stick to it regardless of changes in the industry or market demand. At this point, the company's operations will easily fall into a state of rut.

With these two operational dimensions, if the industry continues to thrive, the company's operations generally won't encounter major problems. Consequently, based on past profits, senior management can easily fall into a rigid mindset, clinging to existing products and strategies. Companies with this rigid mindset are less likely to recognize the gradual decline of their industry, or even if they do, they're reluctant to confront the issue. They only realize the crisis when profits plummet, or even when their products have been almost completely replaced by alternatives. However, by the time a company realizes the crisis, it's often too late; the old product is no longer competitive and no longer meets market demand.

Companies like the one described above have no history of developing or researching other products. Therefore, even if they finally discover a crisis, they will struggle to catch up when they want to develop and manufacture the most popular or in-demand products. Furthermore, in this scenario, profits have already significantly declined. Even if they are able to produce the current best-selling product, they will likely face difficulties in producing new products due to insufficient funds, let alone developing new ones. Ultimately, such companies are prone to bankruptcy.

The third dimension of operations involves incorporating a warlike concept into the business process. This means that the company's top management always maintains a sense of warfare during operations. These management members conduct situation analysis, formulate strategies, execute tactics, and evaluate results, enabling the company to win in the marketplace.

Although the third-dimensional business model mentioned above is obviously superior to the first and second-dimensional business models mentioned above, if a company continues to operate in a third-dimensional way, it will be able to maintain its competitiveness in the market and prevent the company from easily going extinct.

The aforementioned third-dimensional management approach still has flaws in practice. Specifically, it still focuses on short-term (e.g., 3-5 years) operating performance and product development. Therefore, it still has limitations for the long-term development of a company.

The fourth dimension of operations builds on the third dimension of business thinking, incorporating a time dimension. Specifically, in addition to focusing on the company's short-term development (e.g., 3-5 years), business operators or senior management must also consider the possible development direction of the company, the entire industry, and even other industries over the next 10 or 20 years. This requires retrospective consideration of whether the company's current products and operations are aligned with the industry's expected development direction over the next 10 or 20 years, or whether the company's current products or capabilities can meet the needs of, or provide services for, industries that are likely to flourish in the next 10 or 20 years.

For example, the recent launch of Open AI's ChatGPT has unlocked limitless possibilities for AI applications for consumers, creating boundless business opportunities. For plastics processors, if they adopt the fourth-dimensional approach and consider the time horizon when considering their future development, they would have been more likely to anticipate, even before the launch of Open AI's ChatGPT, that with the growth of Open AI and the advancement of artificial intelligence, AI could be widely applied in various consumer scenarios. Before this widespread adoption, technology companies would have purchased large quantities of servers and chips to develop AI-related technologies. This, in turn, would have led to a surge in orders from chipmakers, necessitating expansion. Because semiconductor factories have high requirements for plastic tubes, the unit price and profit margin of plastic tubes are also relatively high. In addition, there are usually certain entry barriers to entering the semiconductor factory supply chain, such as relevant verification mechanisms of relevant manufacturers.

Therefore, for plastic processing companies, if they think about the future development direction of the company in a fourth-dimensional way, it will be easy for them to start planning to increase the company's sales volume and sales channels for plastic tubes in semiconductor factories at the starting point of the AI wave, or even before the AI wave begins.

Large companies, especially those producing a wide variety of products, often fall prey to the trap of focusing on quantity. That is, they desperately pursue sales volume and market share, but overlook the value of their products to the company. Take poplar, pine, and cypress, for example. Poplar can only be used as firewood and has a very low value; pine can be used as general building material and has a medium value; cypress can be used to make high-end furniture and has the highest value. Even if you planted a mountain of poplar trees, their value would still be less than that of a few cypress trees.

In other words, business operators must break the "quantity" trap in the process of running a business and get rid of the misconception of chasing high sales. If a company has a large sales volume but very little profit, or even suffers long-term losses, it will eventually go bankrupt.

The present invention discloses a business dimension management system, which is primarily used to improve existing technologies, as there is no system that can assist business operators in focusing on developing high-value products.

One embodiment of the present invention discloses a business dimension management system, which is suitable for execution in a computer of an enterprise. The business dimension management system includes: an internal business data collection module, an external business data collection module, an industry data collection module, a calculation program and an output interface. The internal business data collection module is used to collect internal business information of each product produced by the enterprise, and the internal business information includes a value-added rate and a profit rate; the external business data collection module is used to collect the capital expenditure of at least one product of at least one industry; the industry data collection module is used to collect the total market sales volume of the sales market corresponding to each product produced by the enterprise; the calculation program can be automatically executed at a predetermined time interval to calculate When the program is executed, it performs the following steps: 1. Value-added rate prediction step: using the value-added rate of each product in multiple historical records, calculate the corresponding value-added rate of each product after a predetermined time period; 1. Profit rate prediction step: using the profit rate of each product in multiple historical records, calculate the corresponding profit rate of each product after a predetermined time period; 1. Market demand prediction step: using the overall market sales volume of each product in multiple historical records , calculate the corresponding forecasted total market sales volume and forecasted total market sales volume growth rate for each product after a predetermined time period; the forecasted total market sales volume growth rate is the forecasted total market sales volume divided by the most recent historical total market sales volume; a capital expenditure forecasting step: using multiple historical industry capital expenditures, calculate the industry's forecasted industry capital expenditure and forecasted industry capital expenditure growth rate for each product; a classification step: Products with a predicted value-added rate greater than or equal to 20%, a predicted profit margin greater than 20%, a predicted overall market sales volume increase rate greater than 20%, and a predicted industry capital expenditure increase rate greater than 10% are labeled as high-value products. Products with a predicted value-added rate less than 15%, a predicted profit margin less than 10%, a predicted overall market sales volume increase rate less than 0%, and a predicted industry capital expenditure increase rate less than 5% are labeled as low-value products. The output interface is provided for viewing by a business operator, and includes the following fields: a high-value product field, which displays a list of high-value products marked as high-value products and a research option corresponding to each high-value product in the high-value product list; a low-value product field, which displays a list of low-value products marked as low-value products and a discussion option corresponding to each low-value product in the low-value product list. When any research option is selected, the business dimension management system will search for the contact information of a product manager responsible for the high-value product in a contact database based on the high-value product corresponding to the research option. It will also schedule a to-do item for the research report in the calendar of the product manager of the high-value product and a research meeting in the calendar of the business operator. The time of the research meeting is the date of the to-do item for the research report plus a preset time. When any discussion option is selected, the business dimension management system will search the contact database for the product manager responsible for the low-value product corresponding to the discussion option, and schedule a discussion meeting in the calendars of the business operator and the product manager responsible for the low-value product.

In summary, the business dimension management system of the present invention, through the calculation program's value-added rate prediction step, profit rate prediction step, market demand prediction step, capital outflow prediction step, and classification step, combined with the design of high-value product fields and low-value product fields on the output interface, can allow business operators to clearly understand which products currently produced by the company are high-value products and which products are low-value products. Furthermore, through the design of research options and discussion options, business operators can easily request relevant product managers to submit research reports on high-value products, or schedule discussion meetings with managers of low-value products. Therefore, the business dimension management system of the present invention can help business operators more easily walk on the right path of operating the business in a fourth-dimensional business manner and focusing on developing high-value products.

To further understand the features and technical contents of the present invention, please refer to the following detailed description and drawings of the present invention. However, such description and drawings are only used to illustrate the present invention and are not intended to limit the scope of protection of the present invention.

In the following description, if a specific figure is mentioned or indicated, this is merely to emphasize that the relevant content described in the subsequent description appears primarily in that specific figure, but does not limit the subsequent description to reference only that specific figure. The profit margin mentioned in the following description refers to the operating profit margin.

Based on their years of experience operating large enterprises, the inventors of this invention have discovered that before business operators, using a fourth-dimensional approach, can make decisions about the company's future core product development, they must first clarify which of their current products are high-value and which are low-value. Once they clearly understand which of their company's products are high-value, they can more easily determine the company's future core product development using a fourth-dimensional approach.

Please refer to Figures 1 and 2 together. Figure 1 shows a block diagram of a first embodiment of the business dimension management system of the present invention, and Figure 2 shows a schematic diagram of the output interface of the business dimension management system of the present invention. The business dimension management system 100 of the present invention is suitable for execution on a computer in an enterprise. Business dimension management system 100 includes: an internal business data collection module 1, an external business data collection module 2, an industry data collection module 3, a calculation program 4, and an output interface 5. Business dimension management system 100 can be presented as a website or an application.

The internal operating data collection module 1 is used to collect internal operating information 11 for each product produced by the enterprise. Internal operating information 11 includes a value-added rate 111 and a profit rate 112. In actual applications, the internal operating data collection module 1 can be, for example, a program that automatically and regularly retrieves the internal operating information 11 from an internal database within the company (e.g., an accounting database). In various embodiments, the internal operating data collection module 1 can also include an operation interface for allowing relevant personnel to upload the internal operating information 11.

Assuming that the value-added rate 111 and profit rate 112 of each product are X and Y, respectively, then X = ((X1 + X2) / X3) * 100%, and Y = (X1 / X3) * 100%. Here, X1 is the product's operating profit, X2 is the corresponding depreciation value, and X3 is the product's operating income. Operating profit, depreciation value, and operating income are all covered in learned accounting and will not be discussed here.

The external operating data collection module 2 is used to collect the interbank capital expenditure 21 of at least one product of at least one peer. In practical applications, the external operating data collection module 2 may, for example, include a web crawler program that regularly retrieves operating reports from the peer's official website and parses these reports to identify the interbank capital expenditure 21 of at least one product of the peer (e.g., a competitor). The method for parsing operating reports may, for example, utilize a generative AI model, which is not limited herein. In practice, the format and wording of each manufacturer's operating reports generally conform to general accounting review rules. Therefore, the external operating data collection module 2 may also include a parsing program that can locate the capital expenditure field for a specific product in the operating report to obtain the inter-industry capital expenditure 21. In various embodiments, the external operating data collection module 2 may also include an operating interface for allowing a user to input the inter-industry capital expenditure 21 for at least one product of each inter-industry.

The industry data collection module 3 is used to collect the overall market sales volume 31 for each product produced by the enterprise. Similar to the above description, the industry data collection module 3 may include a web crawler and a parsing program. These programs automatically and regularly obtain industry reports from specific websites (such as the website of the National Bureau of Statistics, the website of an industry association, the website of a market research organization, etc.) and parse the industry reports to obtain the overall market sales volume 31 for specific products. Of course, in different embodiments, the industry data collection module 3 may also include an operating interface for allowing users to input the overall market sales volume 31 for each product produced by the enterprise.

Calculation program 4 can be automatically executed at predetermined intervals (e.g., every month). When calculation program 4 is executed, it performs the following steps:

A value-added rate prediction step S11: using multiple historical value-added rates of each product, a predicted value-added rate 41 corresponding to each product after a predetermined time period is calculated;

A profit rate prediction step S12: using the multiple historical profit rates of each product, a predicted profit rate 42 corresponding to each product after a predetermined time period is calculated;

A market demand forecasting step S13: Utilizing the multiple historical total market sales of each product, a predicted total market sales volume 43 and a predicted total market sales volume increase rate 44 corresponding to each product after a predetermined time period are calculated; the predicted total market sales volume increase rate is the predicted total market sales volume divided by the most recent historical total market sales volume;

A capital expenditure forecasting step S14: using a plurality of historical interbank capital expenditures, a forecast interbank capital expenditure 45 and a forecast interbank capital expenditure increase rate 46 corresponding to each product of the interbank are calculated; the forecast interbank capital expenditure increase rate is the forecast interbank capital expenditure divided by the most recent historical forecast interbank capital expenditure;

Classification step S15: Products with a predicted value-added rate greater than or equal to 20%, a predicted profit margin greater than 20%, a predicted overall market sales volume increase rate greater than 20%, and a predicted industry capital expenditure increase rate greater than 10% are labeled as high-value products. Products with a predicted value-added rate less than 15%, a predicted profit margin less than 10%, a predicted overall market sales volume increase rate less than 0%, and a predicted industry capital expenditure increase rate less than 5% are labeled as low-value products.

In practice, the relevant information corresponding to each product (i.e., the aforementioned value-added rate, predicted value-added rate, profit rate, predicted profit rate, overall market sales volume, predicted overall market sales volume, predicted overall market sales volume increase rate, peer capital expenditure, predicted peer capital expenditure quality, predicted peer capital expenditure increase rate, etc.) can be stored in a database in an array data format. When the calculation program 4 executes the classification step S15, the calculation program 4 can store 0 or 1 in one of the preset addresses in the array of each product to mark the product as a high-value product or a low-value product.

In the aforementioned classification step S15, a predicted value-added rate greater than or equal to 20% and a predicted profit margin greater than 20% indicate that the product is highly profitable for the company. A predicted overall market sales volume growth rate greater than 20% indicates that future market demand for the product is likely to increase. A predicted industry capital expenditure growth rate greater than 10% indicates that the industry is likely to invest more resources in the product, indicating that the industry is optimistic about the product's future development prospects.

In the aforementioned classification step S15, a predicted value-added rate of less than 15% and a predicted profit margin of less than 10% indicate that this product is a low-profit product for the company internally; a predicted overall market sales volume growth rate of less than 0% indicates that this product may no longer be a mainstream product in the market; and a predicted industry capital expenditure growth rate of less than 5% indicates that the industry may invest less resources in this product in the future and that the industry may not be optimistic about the future development prospects of this product.

The calculation method used in the value-added rate prediction step S11, the profit rate prediction step S12, the market demand prediction step S13, and the capital outflow prediction step S14 can be selected based on actual needs. For example, the calculation can be performed using statistical linear regression or a machine learning algorithm. The calculation of relevant future forecast data using a machine learning algorithm using relevant real-time and historical data can be achieved, for example, using software and interfaces provided by existing data prediction companies (such as ^Amazon® Web Services and ^SAP® ), which is conventional technology.

In the above classification step S15, the products produced by the enterprise are classified into high-value products and low-value products based on three aspects: internal enterprise, overall industry and peers. In the classification step S15, predicted values (i.e., future values) are used, namely: predicted value-added rate, predicted profit rate, predicted overall market total sales volume, predicted overall market total sales volume growth rate, predicted peer capital expenditure and predicted peer capital expenditure growth rate, rather than using current values. Since the business dimension management system 100 of the present invention is used to assist business operators to develop in the direction of focusing on producing high-value products using the fourth-dimensional business method, the above-mentioned classification step S15 must use future values to assist business operators in operating the enterprise using the fourth-dimensional business method.

Capital expenditures for a specific product represent the amount of money a company has invested in that product. Therefore, by observing the capital expenditures and capital expenditure growth rates of each product across peers, we can understand peers' views on the future development of each product. For example, in the semiconductor industry, assuming the most advanced process is 2nm and the most mature process is 5nm, for companies ranked second or higher in market share, by observing the capital expenditures and capital expenditure growth rates of the company with the largest market share (i.e., the industry leader) for 2nm, 5nm, and 1nm processes, we can understand the leader's views on future product development trends. Assuming that the leading company's capital expenditure growth rate for 2nm and 1nm processes increases annually, and its capital expenditure growth rate for 5nm processes decreases annually, managers of companies ranked second or below in market share will know that the leading company has gradually shifted its focus to developing 1nm and 2nm processes. Consequently, managers of non-leading companies can determine their future product development direction based on their own capabilities, such as whether to focus on developing 2nm processes or competing for 5nm orders. Therefore, incorporating a filter based on predicted capital expenditure growth rates of competitors in the classification step S15 ensures that the high-value products ultimately selected are also products that the industry is optimistic about in the future.

By incorporating market data (i.e., the predicted overall market sales growth rate) into the classification step S15, we can ensure that the high-value products ultimately selected are products that the market will need in the future. If market data is not included in the classification step S15, the high-value products identified may not generate significant revenue for the company in the future due to low market demand.

As described above, the classification step S15 of the present invention simultaneously utilizes the company's internal data (i.e., predicted value-added rate and predicted profit rate) of each product, market data (i.e., predicted overall market sales volume growth rate) and capital expenditure data of peers (i.e., predicted peer capital expenditure growth rate) to classify all products produced by the company, so that business operators can clearly know which of the products currently sold by the company are high-value products and which are low-value products. Therefore, it can effectively assist business operators to more easily find out which high-value products the company needs to focus on developing in the future when operating in a fourth-dimensional business model.

Although some existing management systems can use historical sales data for each company's products to predict future sales data and provide business operators with information for formulating strategies, these management systems only use historical data to predict future data and do not include technical features such as the classification step S15 of the present invention. Therefore, these management systems cannot effectively assist business operators in moving towards a fourth-dimensional business model and focusing on producing high-value products.

Continuing from the above, in current practical applications, if business managers simply use the forecast data provided by existing management systems to formulate strategies for the company's future development direction, they will easily fall into a first-dimensional or second-dimensional business model. Taking the aforementioned example of the semiconductor wafer foundry company, for non-leading companies, if they only use the forecast data provided by existing management systems to formulate strategies for the company's future development direction, business managers will easily see the continued improvement in the predicted sales data of 5nm process products and formulate a corporate strategy that focuses on the development of 5nm process. As a result, they may ignore the development of 1-3nm.

As mentioned above, as companies (the aforementioned non-leading companies) focus on developing 5nm processes, their managers may indeed see a short-term increase in sales of 5nm products, and they may easily conclude that focusing on 5nm is the right path for their business strategy. However, any sales increase they see is likely due to the production capacity released by leading companies. Over time, the number of companies capable of manufacturing 5nm products may gradually increase, and even the demand for 5nm products from the leading companies' main customers may gradually decrease. However, the managers of these non-leading companies may not realize that mainstream customers no longer need 5nm products until they notice a significant decline in sales and market prices for 5nm products. Instead, they primarily want 3nm or 2nm products. At this point, because their pre-defined strategy is to focus on 5nm development, they may not be able to, or may find it difficult to, keep up with the 3nm process, let alone the 2nm process. Consequently, these companies will face relatively difficult operational challenges.

The output interface 5 is provided for viewing by a business operator. The output interface 5 may include a high-value product field and a low-value product field.

The high-value product column displays a list 521 of high-value products labeled as high-value products and a research option 522 corresponding to each high-value product in the high-value product list 521. In actual applications, the high-value product column may include relevant data for each high-value product, such as the predicted value-added rate, predicted profit rate, predicted overall market sales volume growth rate, predicted industry capital expenditure growth rate, etc., without limitation.

The low-value product column displays a list 531 of low-value products labeled as low-value products and a discussion option 532 corresponding to each low-value product in the low-value product list 531. In actual applications, the low-value product column may include relevant data for each low-value product, such as the predicted value-added rate, predicted profit rate, predicted overall market sales volume growth rate, predicted industry capital expenditure growth rate, etc., without limitation.

When any research option 522 is selected, a default program of the business dimension management system 100 will search for the contact information of a product manager responsible for the high-value product in a contact database based on the high-value product corresponding to the research option 522, and schedule a to-do item for preparing a research report in the calendar of the product manager of the high-value product, and schedule a research meeting in the calendar of the business operator. The time of the research meeting is the date of the to-do item for preparing the research report plus a preset time (for example, 2 weeks). For example, as shown in FIG2 , when a business operator clicks on the research option 522 labeled “Research” next to Product C in the output interface 5 , the default program will add a to-do item for producing a research report to the calendar of the product manager of Product C, and will also add a research meeting to the calendars of the business operator and the product manager, with the time for the research meeting being two weeks later.

In practical applications, a business operator may view multiple high-value products from the high-value product column in the output interface 5. Based on his or her own experience and observation of the broader environment, the business operator may select one or more research options 522 to enable the corresponding product manager to conduct research on the high-value product. Furthermore, since the business dimension management system 100 directly schedules the research meeting, there will be no problem of the product manager not receiving the assigned tasks.

When formulating their company's development strategy, business managers must consider the fourth dimension of business. Specifically, they must consider whether specific high-value products will be in high demand in future industries and societies. However, for businesses that produce a wide variety of products, it can be difficult to grasp the development status of all of their high-value products and the future development prospects of their customers. Therefore, when business managers view multiple high-value products in output interface 5, they can click on the research option 522 to request the relevant product managers to conduct in-depth research on the high-value products.

When any discussion option 532 is selected, the business dimension management system 100 will search the contact database for the product manager responsible for the low-value product corresponding to the discussion option 532, and schedule a discussion meeting in the calendars of the business operator and the product manager responsible for the low-value product.

In one embodiment, the business dimension management system 100 may further include an option display program 6. When the output interface 5 is displayed, the output interface 5 will execute the option display program 6. When the option program 6 is executed, the following steps will be performed:

A calculation step S21: Calculating a profit ratio of each low-value product, where the profit ratio is the ratio of the profit of the low-value product to the overall profit of the enterprise;

A discussion option display step S22: In the low-value-added product list, the low-value-added products are sorted according to their profit ratio so that the low-value-added product with the highest profit ratio is arranged first, and in the low-value-added product column, a discussion option 532 is displayed around each low-value-added product with a profit ratio higher than 30%.

In actual applications, business operators of companies that produce a variety of different types of products (such as plastic processing companies) may see multiple low-value products in the low-value product column of the output interface 5. Therefore, through the design of the above-mentioned option display program 6, business operators can only see the discussion option 532 around low-value products that account for more than 30% of the overall profit in the output interface 5. In this way, business operators can see a relatively simple screen in the low-value product column, and business operators can better focus on discussing low-value products that account for more than 30% of the overall profit.

The business dimension management system of this invention is primarily designed to assist business operators in operating their businesses using a fourth-dimensional approach, focusing on developing high-value products. By categorizing high-value and low-value products, researching options, and discussing their design, business operators can better formulate their short-, medium-, and long-term business strategies. For example, suppose a business operator sees in output interface 5 that the company currently produces many low-value products, and these low-value products account for the majority of the company's overall profits. The company also currently produces high-value products. In this scenario, after viewing output interface 5, the business operator can relatively easily formulate a short-term goal: maintain the profits of low-value products, a medium-term goal: find OEM manufacturers for low-value products, and a long-term goal: enhance the development of high-value products. In contrast, without the assistance of the business dimension management system of the present invention, business operators will easily set short-, medium-, and long-term goals based on low-value products that currently account for the largest share of overall profits. This strategy formulation method may cause the company to fall into the dilemma of continuing to focus on producing low-value products in the future. These low-value products may be in a red ocean market with many competitors and low quotes.

As shown in FIG2 , the business dimension management system of the present invention is mainly used to assist business operators to operate in the direction of focusing on developing high-value products using a fourth-dimensional business model. Therefore, in one of the variations of the present invention, each time the calculation program 4 is executed, after the classification step S15, for example, a proportion calculation step S16 may also be included. The proportion step S16 is to calculate a proportion value, which is the ratio of the quantity marked as high-value products to the quantity marked as low-value products; the output interface 5 also includes a current proportion value 54 and a historical proportion value 55. The current proportion value 54 is the proportion value calculated by the most recent calculation program 4, and the historical proportion value 55 is the proportion value calculated by the previous calculation program 4.

As shown in Figure 2, when business operators view output interface 5, they can simply view the current share value 54 and the historical share value 55 of output interface 5 to clearly understand whether the company is continuing to focus on developing high-value products.

In addition, the business dimension management system 100 may also include a monitoring program 7, which will be automatically executed every quarter. When the monitoring program 7 is executed, it performs the following steps:

A calculation step S31: using the historical percentage values, calculate a first quarter percentage trend line 56;

A first judgment step S32: determining whether the slope of the quarterly proportion trend line is positive;

If the slope of quarterly share trend line 56 is negative, a warning message is displayed on output interface 5 to inform the business operator that the slope of quarterly share trend line 56 is negative. In actual applications, if the output interface 5 displays a warning message, the business operator may, for example, see a prompt such as "Quarterly high-value product share trend line is negative" (i.e., the warning message) on output interface 5.

The design of the aforementioned monitoring program 7 allows business operators to clearly understand, when viewing the output interface 5, whether the company is progressing towards a focus on developing high-value products. Without the aforementioned monitoring program 7, business operators would be unable to quickly grasp the proportion of high-value products in the company's output each quarter through the output interface 5, and would be unable to quickly determine whether the company is gradually progressing towards a focus on developing high-value products.

As shown in FIG1 and FIG3, in one embodiment of the present invention, the external business data collection module 2 can also be used to collect the sales volume 22 of at least one product of at least one peer. After the discussion option display step S22, the following steps are also included:

A sales volume forecasting step S23 for a product in the same industry: using a plurality of historical sales volumes of each product in the same industry, a forecasted sales volume increase rate 47 for each product in the same industry is calculated;

First-generation manufacturer screening step S24: Based on each low-value product with a profit ratio greater than 30%, search a database for at least one first-generation manufacturer. The selected first-generation manufacturers have a predicted sales volume increase rate of greater than 5% for the corresponding low-value products.

A display step S25: In the low-value product column, first-generation manufacturer options 533 are displayed around each low-value product for which a corresponding OEM manufacturer has been found;

When any OEM option 533 is selected, the business dimension management system 100 will display a list of OEMs 5331. The OEM list 5331 includes OEMs found in the OEM screening step S24 for low-value products.

When any OEM option 533 is selected, at least one OEM name and a OEM contact option 5332 are displayed in the OEM list 5331. When the OEM contact option 5332 is selected, the business dimension management system 100 will reserve a to-do item for contacting the OEM on the to-do list of the product manager of the corresponding low-value product.

In the OEM screening step S24, a OEM with a predicted sales volume increase rate 47 of its peer product greater than 5% indicates that the manufacturer's sales volume for the product is gradually increasing. This may also mean that the quality of the low-value products produced by this manufacturer has reached a certain level and that the low-value products produced by this manufacturer have gradually been recognized by the market.

Based on years of practical experience in large-scale enterprise management, the inventors have discovered that large enterprises must cultivate a philosophy of coexistence and shared prosperity with other manufacturers in order to achieve long-term success. If business operators consistently view competitors as enemies, the company will ultimately be unable to achieve long-term success. Based on this business philosophy, combined with the aforementioned design of the sales volume forecasting step S23 for competing products, the OEM screening step S24, and the display step S25, business operators can clearly understand in output interface 5 which OEMs are likely to be selected for production of the company's current low-value products.

If a company has established a strong brand value over the years, its low-value products will continue to be favored by the market, and these products can still generate a certain amount of revenue for the company. In this scenario, the company still needs to focus on developing high-value products, but it does not need to abandon the production of low-value products. Instead, the company can provide guidance or support to other excellent manufacturers in the same industry so that they can produce low-value products of the same quality. In this way, the company can transfer a large number of orders for low-value products to other excellent manufacturers for OEM production, and the company can establish an ODM (Original Design Manufacturer) relationship with the manufacturer. This will not harm the rights of customers, can maintain the company's interests, and can also benefit the development of other manufacturers, thus creating a win-win-win situation.

Through the designs of the aforementioned peer product sales volume forecasting step S23, the OEM screening step S24, and the display step S25, the business operator can quickly determine which of the company's current low-value products may be transferred to other manufacturers for production. Furthermore, the business operator can click on the OEM option 533 and the OEM contact option 5332 in turn to add a to-do item for negotiation with the OEM to the calendar of the person in charge of the low-value product.

Please refer to Figures 4 and 5 . Figure 4 is a block diagram of a second embodiment of the operating dimension management system of the present invention, while Figure 5 is a diagram illustrating an example of a plant interface of the operating dimension management system of the present invention. In actual applications, the operating dimension management system 100 may also include a plant interface 8 and a plant calculation program 9. The plant interface 8 includes multiple plant fields, each of which displays a plant name and a plant capacity utilization rate.

When the plant interface 8 is displayed, the plant calculation program 9 will be executed. When the plant calculation program 9 is executed, the following steps are performed:

Calculating the high-value-added product ratio for a plant (S41): Calculate the high-value-added product ratio for each plant and display the high-value-added product ratio in the corresponding plant column. The high-value-added product ratio is the ratio of the total quantity of high-value-added products produced by the plant to the total quantity of all products produced by the plant.

A marking step S42 is performed: a plant with a high-value product capacity utilization rate of less than 70% and a high-value product ratio of less than 30% is marked as a low-value plant, and low-value plant information 811 is displayed in the corresponding plant column. A plant with a high-value product capacity utilization rate of more than 70% and a high-value product ratio of more than 30% is marked as a high-value plant, and high-value plant information 812 is displayed in the corresponding plant column. In practice, in each plant field, the user may see the words "high-value-added plant" or "low-value-added plant", which are the high-value-added plant information 812 and the low-value-added plant information 811.

Each plant column also displays the capacity utilization rate and total output of high-value products for all high-value products produced by the plant, as well as the capacity utilization rate and total output of low-value products for all low-value products produced by the plant.

As shown in Figure 5, specifically, a business operator can see in Factory Interface 8, for example, that Factory A's factory capacity utilization rate is 80%, the proportion of high-value products is 80%, and the proportion of low-value products is 20%. The high-value product capacity utilization rate of high-value products produced by Factory A is 95%, and the low-value product capacity utilization rate of low-value products produced by Factory A is 65%, and Factory A is recognized as a "high-value factory." For Factory B, the factory capacity utilization rate is 62%, the proportion of high-value products is 10%, and the proportion of low-value products is 90%. The high-value product capacity utilization rate of high-value products produced by Factory B is 60%, and the low-value product capacity utilization rate of low-value products produced by Factory B is 70%, and Factory B is identified as a "low-value factory".

Through the design of the aforementioned factory interface 8 and factory calculation program 9, business operators can easily see the attributes of the products produced by each factory, the factory capacity utilization rate of each factory, and the capacity utilization rates corresponding to the low-value products and high-value products produced by each factory. In this way, business operators can more clearly understand whether each factory can have a better production configuration. Specifically, in a scenario where a business operator wants to develop the company towards the production of high-value products, when the business operator views the factory interface 8, the business operator can easily know that he can discuss with his subordinates whether to transfer the demand for low-value products produced by Factory A to Factory B for production, and transform Factory A into a factory dedicated to the production of high-value products. In this way, not only can the factory capacity utilization rate of Factory B be improved, but the space or capacity originally used to manufacture low-value products in Factory A can also be converted to the production of high-value products, thereby transforming Factory A into a factory dedicated to the production of high-value products.

In addition, the factory interface 8 may also display a regional map 813, which indicates the location of each factory of the enterprise. The regional map 813 also indicates the location 8131 of at least one factory in the same industry and information about the main products of the factory in the same industry 8132. The main product information 8132 of the factory in the same industry is used to display the main products produced by the factory in the same industry. By displaying data on the total output of high-value products and low-value products in each factory column, combined with the design of the location of peer factories 8131 and the main product information of peer factories 8132, business operators and their subordinates can quickly discuss or evaluate whether the production capacity of low-value products of high-value factories can be transferred to peer factories for OEM production, allowing high-value factories to focus on producing high-value products.

In a preferred embodiment, in the regional map 813, a contract manufacturer contact option 8133 may be displayed around each of the corresponding factory locations 8131. When the contract manufacturer contact option 8133 is selected, the business dimension management system 100 will add a to-do item to the calendar of the corresponding factory manager to contact the manufacturer. In an example where the business dimension management system 100 is implemented as a website, each contract manufacturer contact option 8133, when selected, may trigger a default program. Each default program will add a to-do item to the calendar of the corresponding factory manager to contact the manufacturer.

Continuing from the above, it is important to emphasize that, in traditional business management thinking, business operators only view competitors as enemies. Therefore, in traditional business management interfaces, at most the relevant sales figures of competitors will appear, but the factory locations of competitors will not be displayed in the relevant interfaces, let alone the main products produced by specific factories of competitors (i.e., the main product information 8132 of the aforementioned factories). This is because, for traditional business operators, the location of competitors' factories and the products produced by each factory are not important.

However, the inventors of the present invention have broken away from the rigid mindset of traditional business operators. In addition to marking the location of the company's own factory, the regional map 813 of the factory interface 8 of the present invention also shows the locations of other companies' factories and the products they produce. This is to break away from the traditional mindset and move towards shared prosperity and coexistence with other companies.

As described above, through the design of the factory interface 8, business operators and their subordinates can quickly know whether there are any products produced by each factory that may need to be adjusted. This can greatly improve meeting efficiency and allow relevant personnel to quickly focus on the factory that needs adjustment.

It should be emphasized that the information displayed on the aforementioned factory interface 8 is designed to encourage business operators to develop towards the production of high-value products. Furthermore, the definitions of high-value and low-value products were designed by the inventors based on their long-term business practices. Therefore, the information displayed on the aforementioned factory interface 8 is not simply displayed on the interface. Instead, the inventors have carefully designed and selected which factory-related data to display on the factory interface 8. Specifically, factory-related operating data includes not only capacity utilization and output, but also raw material utilization rate, inventory turnover rate, product yield rate, energy consumption per unit, equipment downtime, and more. Displaying all of this data in the factory interface 8 would be of no help to business operators.

In conventional technology, the classification of high-value and low-value products of the present invention does not exist in the relevant management systems of enterprises. Therefore, in the management system, enterprise operators will only see that the plant capacity utilization rates of Plants A and B are 80% and 62%, respectively. Enterprise operators may therefore conclude that, aside from the potential for further capacity utilization, there is no other area that needs improvement in Plants A and B. In other words, for those with ordinary knowledge in the relevant technical field, because the classification of high-value and low-value products of the present invention does not exist in existing enterprise management systems, even if relevant technical personnel refer to the interface that records the capacity utilization information of each plant, they still cannot easily think of the technical features of the present invention, such as the plant interface.

In actual application, when the factory calculation program 9 is executed, after the marking step S42, the following steps may also be included:

A statistical step S43: calculating the monthly average output of a main low-value product of each high-value-added plant, and calculating the monthly average output difference of a main low-value product of each low-value-added plant; the monthly average output difference is the total monthly production capacity of a plant corresponding to the main low-value product of the low-value-added plant, minus the monthly average output of the main low-value product of the low-value-added plant; the main low-value product of the high-value-added plant refers to the low-value product with the largest total output among all low-value products produced by the high-value-added plant; the main low-value product of the low-value-added plant refers to the low-value product with the largest total output among all low-value products produced by the low-value-added plant;

A capacity concentration determination step S44: determining whether the monthly average output of the main low-value products of each high-value-added plant is less than or equal to the monthly average output difference of the main low-value products of a transferable low-value-added plant; the main low-value products of the transferable low-value-added plant are the same as the main low-value products of the high-value-added plant, and the capacity utilization rate of the main low-value products of the transferable low-value-added plant is less than 80%;

In the capacity concentration judgment step S44, if it is determined that the monthly average output of the main low-value products of the high-value-added plant is less than or equal to the monthly average output difference of the main low-value products of the transferable low-value-added plant, then a suggestion information 91 is displayed in the plant interface 8. The suggestion information 91 includes the name of the transferable low-value-added plant. The suggestion information 91 is used to prompt the business operator to transfer the main low-value products of the high-value-added plant to the transferable low-value-added plant with the said name for production.

For example, as shown in Figure 5, assume that Plant A is a high-value-added plant and Plant B is a low-value-added plant, and the main low-value-added products produced by Plant A and Plant B are both L products. In the capacity concentration judgment S44, it is determined that the monthly average output of L products produced by Plant A (15 tons) is less than the monthly average output of L products produced by Plant B. (35 tons), therefore, the business operator will see text such as "Suggestion: Transfer the production of Product L (low-value product) of Factory A to Factory B" in the factory interface 8. Such text is the suggested information 91, and the business operator and his subordinates can quickly focus on the suggested information 91 for discussion by viewing the factory interface 8.

As mentioned above, if product L from Factory A is transferred to Factory B for production, the plant capacity utilization rate of Factory B and the capacity utilization rate of low-value products (product L) can be improved. The capacity or equipment originally used to produce product L in Factory A can be converted to produce high-value products (such as product Q), thereby improving the plant capacity utilization rate of Factory A and the capacity utilization rate of high-value products.

Please refer to Figure 6, which shows another embodiment of the plant interface of the business dimension management system of the present invention. In actual application, in the production capacity concentration determination step S44, if it is determined that the difference in the monthly average output of the main low-value products of two or more low-value plants is greater than or equal to the monthly average output of the main low-value products of the high-value plant, the following steps will be executed:

A distance determination step S45: Calculate the distance between each low-value-added plant and the high-value-added plant, and use the name of the low-value-added plant closest to the high-value-added plant as the name in the recommendation information.

Specifically, as shown in Figure 6, in the capacity concentration determination step S44, the difference in the monthly average production volume of Product L for Plant B and Plant C, respectively, is greater than the average production volume of Product L for Plant A. This means that the production of Product L in Plant A can be transferred to either Plant B or Plant C. In the distance determination step S45, since Plant C is closer to Plant A, the final recommendation generated is to transfer the production of Product L in Plant A to Plant C.

Please refer to Figure 7, which shows a schematic diagram of another embodiment of the plant interface of the business dimension management system of the present invention. If, in the production capacity concentration determination step S44, it is determined that the monthly average output of the main low-value products of the high-value plant is greater than the monthly average output difference of the main low-value products of each transferable low-value plant, the following steps are executed:

A capacity dispersion determination step S45: determining whether the monthly average output of the main low-value products of each high-value production plant is less than or equal to the sum of the monthly average output differences of the main low-value products of two or more of the transferable low-value production plants;

If, in the capacity dispersion determination step S45, it is determined that the monthly average output of the main low-value products of each high-value-added plant is less than or equal to the sum of the monthly average output differences of the main low-value-added products of two or more of the transferable low-value-added plants, then a suggestion information is displayed in the plant interface 8, and the suggestion information includes the names of at least two transferable low-value-added plants; the suggestion information is used to prompt the business operator to transfer the main low-value-added products produced by the high-value-added plant to the two transferable low-value-added plants for production.

For example, as shown in Figure 6, assume that Plant A is a high-value-added plant, and Plants B and C are low-value-added plants. The main low-value-added products produced by Plants A, B, and C are all L products. Moreover, the average monthly output of L products (main low-value-added products) at Plant A (15 tons) is the same as the sum of the difference between the average monthly output of Plant B (10 tons) and the average monthly output of L products at Plant C (8 tons). In this case, the enterprise manager can view a recommendation message 91 in the plant interface 8, such as "It is recommended to transfer the production of L products produced by Plant A to Plants B and C."

It should be emphasized that the aforementioned statistical steps, capacity concentration determination steps, distance determination steps, and capacity dispersion determination steps are all performed after the labeling step. That is, before generating the recommended information, each plant must be classified through the labeling step to distinguish it as a high-value plant or a low-value plant. In other words, the statistical steps, capacity concentration determination step, distance determination step, and capacity dispersion determination step are not simply about concentrating products produced in different plants in a specific plant. Instead, the original intention of designing these steps is to allow high-value plants to focus on producing high-value products, while allowing low-value products to be concentrated in low-value plants.

In other words, without considering the marking steps described above, technicians would have no incentive to transfer a specific product from one plant to another. In practice, each plant produces different products, a result of years of experience (such as serving customers in the surrounding area). Therefore, technicians would not easily change the product range of a plant unless there was a strong motivation.

It should be noted that the various steps included in the plant calculation program of the present invention are based on the principle of focusing the enterprise on producing specialized value-added products. This is why the program includes features such as the capacity concentration and capacity decentralization determination steps. In contrast, in traditional management thinking, the product categories produced by each plant are typically determined by business operators based on various historical factors. Therefore, for traditional business operators, if the capacity utilization rate of each plant is good, they generally do not consider changing the product types produced by each plant.

In summary, the business dimension management system of the present invention, through the calculation program's value-added rate prediction step, profit rate prediction step, market demand prediction step, capital outflow prediction step, and classification step, combined with the design of high-value product fields and low-value product fields on the output interface, can effectively assist business operators and more easily develop towards the direction of focusing on the production of high-value products through a fourth-dimensional business model.

Through years of practical experience in large-scale business operations, the inventor discovered that business operators can enhance their own energy to help improve the dimension of business operations. For example, business operators can enhance their own energy by simply listening to scriptures. By enhancing their own energy, they may be able to stimulate their own observation, integration, creativity and execution capabilities. In this way, it will be easier to operate the business in a fourth-dimensional way, allowing the company to develop towards a better future.

It is worth mentioning that in the 2021 version of the Review Criteria, Part II, Chapter 12, Section 3.4, “Information processing with the aid of computer software is specifically implemented using hardware resources”, it is stated that “the requirement of ‘information processing with the aid of computer software is specifically implemented using hardware resources’ means that a specific information processing device or method is constructed according to the purpose of information processing through the coordinated operation of computer software and hardware resources. In making this determination, the examiner should refer to common knowledge at the time of application and, with respect to the specific technical means or steps for the coordinated operation of computer software and hardware resources set forth in the claim, determine whether specific information processing or calculation is achieved in accordance with the purpose of information processing. This is used to determine whether the invention related to computer software meets the aforementioned requirements and is a "creation of technical ideas utilizing the laws of nature" in order to meet the definition of an invention. " According to the patent examination standards, if the application's claim clearly states that a specific information processing device or method is constructed by "specific technical means or steps" implemented through the coordinated operation of computer software and hardware information based on the "purpose of information processing," then the claim meets the definition of an invention and complies with the provisions of Article 21 of the Patent Act.

As can be seen from the uploaded instructions, the "information processing purpose" of the "operational dimension management system" defined in claim 1 of this invention is to enable business operators to know which of the company's products are high-value products and which are low-value products. Furthermore, the technical features defined in claim 1 of this invention, such as the "internal operating data collection module, external operating data collection module, industry data collection module, calculation program, and output interface," are already the "specific technical means or steps" that can achieve this information processing purpose. Therefore, each claim of this invention clearly meets the definition of an invention in the patent examination criteria and complies with the provisions of Article 21 of the Patent Law.

The above description is merely a preferred embodiment of the present invention and does not limit the patent scope of the present invention. Therefore, any equivalent technical changes made by applying the contents of the description and drawings of the present invention are included in the scope of protection of the present invention.

100: Business Dimension Management System 1: Internal Business Data Collection Module 11: Internal Business Information 111: Value-Added Rate 112: Profitability 2: External Business Data Collection Module 21: Comparable Capital Expenditure 22: Comparable Product Sales Volume 3: Industry Data Collection Module 31: Overall Market Sales Volume 4: Calculation Program 41: Forecast Value-Added Rate 42: Forecast Profitability 43: Forecast Overall Market Sales Volume 44: Forecast Overall Market Sales Volume Increase Rate 45: Forecast Comparable Capital Expenditure 46: Forecast Comparable Capital Expenditure Increase Rate 47: Forecast Comparable Product Sales Volume Increase Rate 5: Output Interface 521: List of High-Value Products 522: Research Options 531: Low-Value Product List 532: Discussion Options 533: OEM Options 5331: OEM List 5332: OEM Contact Options 54: Current Market Share 55: Historical Market Share 56: Quarterly Market Share Trend 6: Option Display Program 7: Monitoring Program 8: Factory Interface 811: Low-Value Factory Information 812: High-Value Factory Information 813: Regional Map 8131: Competing Factory Locations 8132: Competing Factory Main Product Information 8133: OEM Contact Options 9: Factory Calculation Program 91: Suggested Information

FIG1 is a block diagram of a first embodiment of the business dimension management system of the present invention.

FIG2 is a schematic diagram of the output interface of the business dimension management system of the present invention.

FIG3 is another schematic diagram of the output interface of the business dimension management system of the present invention.

FIG4 is a block diagram of a second embodiment of the business dimension management system of the present invention.

Figure 5 is a schematic diagram of the factory interface of the second embodiment of the business dimension management system of the present invention.

FIG6 is a schematic diagram of another embodiment of the plant interface of the business dimension management system of the present invention.

Figure 7 is a schematic diagram of another embodiment of the factory interface of the business dimension management system of the present invention.

100: Operational Dimension Management System

1: Internal business data collection module

11: Internal business information

111: Value-added Rate

112: Profitability

2: External business data collection module

21: Interbank capital expenditure

22: Sales volume of peer products

3: Industry data collection module

31: Total market sales volume

4: Calculation Program

41: Estimated Value Added Rate

42: Predicted Profit Rate

43: Forecast overall market sales volume

44: Predicted overall market sales growth rate

45: Forecasting industry capital expenditures

46: Forecasted capital expenditure growth rate of peers

47: Forecast sales growth rate of peer products

5: Output Interface

6: Option display program

7: Monitoring Program

Claims (11)

A business dimension management system, adapted for execution on a computer within an enterprise, comprises: An internal business data collection module for collecting internal business information for each product produced by the enterprise, wherein the internal business information includes a value-added rate and a profit rate; An external business data collection module for collecting industry capital expenditures for at least one product of at least one industry; An industry data collection module for collecting overall market sales figures for each product produced by the enterprise; A calculation program, which is automatically executed at predetermined time intervals, and when executed, performs the following steps: A value-added rate prediction step: using the multiple historical value-added rates of each of the products, calculate a predicted value-added rate corresponding to each of the products after the predetermined time period; A profit rate prediction step: using the multiple historical profit rates of each of the products, calculate a predicted profit rate corresponding to each of the products after the predetermined time period; A market demand prediction step: using the multiple historical overall market sales volumes of each of the products, calculate a predicted overall market sales volume and a predicted overall market sales volume growth rate corresponding to each of the products after the predetermined time period; the predicted overall market sales volume growth rate is the predicted overall market sales volume divided by the overall market sales volume of the most recent historical transaction; A capital expenditure forecasting step: Utilizing multiple historical industry capital expenditures, calculate a forecast industry capital expenditure and a forecast industry capital expenditure growth rate corresponding to each product. A classification step: Labeling products with a forecast value-added rate greater than or equal to 20%, a forecast profit margin greater than 20%, a forecast overall market sales volume growth rate greater than 20%, and a forecast industry capital expenditure growth rate greater than 10% as high-value products. Labeling products with a forecast value-added rate less than 15%, a forecast profit margin less than 10%, a forecast overall market sales volume growth rate less than 0%, and a forecast industry capital expenditure growth rate less than 5% as low-value products. An output interface for a business operator to view, the output interface comprising the following fields: A high-value product field, which displays a list of high-value products marked as high-value products and a research option corresponding to each high-value product in the high-value product list; A low-value product field, which displays a list of low-value products marked as low-value products and a discussion option corresponding to each low-value product in the low-value product list; When any of the research options is selected, the business dimension management system will search a contact database for the product manager responsible for the high-value-added product corresponding to the research option. The system will then schedule a research report preparation task in the calendar of the product manager and a research meeting in the calendar of the business operator. The time of the research meeting is the date of the research report preparation task plus a preset time. When any of the discussion options is selected, the business dimension management system will search the contact database for the product manager responsible for the low-value product corresponding to the discussion option, and schedule a discussion meeting in the calendars of the business operator and the product manager responsible for the low-value product. An operating dimension management system as described in claim 1, wherein each time the calculation program is executed, after the classification step, it further includes a proportion calculation step: calculating a proportion value, wherein the proportion value is the ratio of the quantity marked as the high-value-added products to the quantity marked as the low-value-added products; the output interface further includes a current proportion value and a historical proportion value, wherein the current proportion value is the proportion value calculated by the calculation program most recently, and the historical proportion value is the proportion value calculated by the calculation program last time. The operating dimension management system of claim 2, further comprising a monitoring program that is automatically executed each quarter. When executed, the monitoring program performs the following steps: A calculation step: Calculating a quarterly share trend line using the share values of the plurality of historical records; A determination step: Determining whether the slope of the quarterly share trend line is positive; If the slope of the quarterly share trend line is negative, displaying a warning message on the output interface to inform the business operator that the slope of the quarterly share trend line is negative. The business dimension management system of claim 1, wherein when the output interface is displayed, the output interface executes an option display program. When the option program is executed, the following steps are performed: A calculation step: calculating a profit ratio for each of the low-value products, wherein the profit ratio is the ratio of the profit of the low-value product to the overall profit of the enterprise; A step of displaying discussion options: sorting the low-value-added products in the low-value-added product list according to their profit ratios so that the low-value-added product with the highest profit ratio is ranked first, and displaying the discussion options around each low-value-added product with a profit ratio greater than 30% in the low-value-added product column. The operating dimension management system as described in claim 4, wherein the external operating data collection module is further configured to collect the sales volume of at least one product of at least one of the peers; and after the discussion and display step, the module further comprises the following steps: A peer product sales volume forecasting step: Calculating a predicted peer product sales volume growth rate for each of the peer products using multiple historical sales volumes of the peer products; A first-generation manufacturer screening step: Searching the database for at least one first-generation manufacturer for each of the low-value products having a profit ratio greater than 30%; the selected first-generation manufacturers having a predicted peer product sales volume growth rate greater than 5% for the low-value products; A display step: In the low-value product column, first-tier manufacturer options are displayed around each low-value product for which a corresponding found OEM manufacturer is identified. When any of the OEM options is selected, the business dimension management system displays a list of first-tier manufacturers. The OEM list includes the OEM manufacturers identified for the low-value product in the OEM screening step. The operating dimension management system as described in claim 5, wherein, when any of the OEM options is selected, at least one OEM name and a OEM contact option are displayed in the OEM list; when the OEM contact option is selected, the operating dimension management system will reserve a contact item with the OEM on the to-do list of the product manager of the corresponding low-value product. The operating dimension management system of claim 1, wherein the operating dimension management system further comprises a plant interface and a plant calculation program, wherein the plant interface comprises a plurality of plant fields, each of the plant fields displaying a plant name and a plant capacity utilization rate; and when the plant interface is displayed, the plant calculation program is executed, and when the plant calculation program is executed, the following steps are performed: Calculating the high-value product ratio for a plant: Calculate the high-value product ratio for each plant and display the high-value product ratio in the corresponding plant column; the high-value product ratio is the ratio of the total quantity of high-value products produced by the plant to the total quantity of all products produced by the plant. A marking step: marking a plant with a high-value product capacity utilization rate of less than 70% and a high-value product ratio of less than 30% as a low-value plant, and displaying the low-value plant information in the corresponding plant column; marking a plant with a high-value product capacity utilization rate of more than 70% and a high-value product ratio of more than 30% as a high-value plant, and displaying the high-value plant information in the corresponding plant column. The operating dimension management system as described in claim 7, wherein each of the factory columns further displays a high-value product capacity utilization rate and a total output of high-value products corresponding to all the high-value products produced by the factory, a low-value product capacity utilization rate and a total output of low-value products corresponding to all the low-value products produced by the factory, and the factory interface further displays a regional map, on which the location of at least one factory in the same industry, information on the main products of the factory in the same industry, and a first-party manufacturer contact option are also marked; when the first-party manufacturer contact option is selected, the operating dimension management system will add a to-do item for contacting the manufacturer to the calendar of the person in charge of the corresponding factory. The operating dimension management system as described in claim 7, wherein, after the marking step, the following steps are further included: A statistical step: calculating the monthly average output of a main low-value product of each high-value-added plant, and calculating the monthly average output difference of a main low-value product of each low-value-added plant; the monthly average output difference is the total monthly production capacity of a plant corresponding to the main low-value product of the low-value-added plant, minus the monthly average output of the main low-value product of the low-value-added plant; the main low-value product of the high-value-added plant refers to the low-value product with the largest total output among all the low-value products produced by the high-value-added plant; the main low-value product of the low-value-added plant refers to the low-value product with the largest total output among all the low-value products produced by the low-value-added plant; A capacity concentration determination step: determining whether the monthly average output of the main low-value products of each high-value-added plant is less than or equal to the monthly average output difference of the main low-value products of a transferable low-value-added plant; the main low-value products of the transferable low-value-added plant are the same as those of the high-value-added plant, and the capacity utilization rate of the main low-value products of the transferable low-value-added plant is less than 80%; If the monthly average output of the high-value-added plant's main low-value-added product is determined to be less than or equal to the monthly average output difference of the main low-value-added product of the transferable low-value-added plant, a suggestion message will be displayed on the plant interface. The suggestion message includes the name of the transferable low-value-added plant. The suggestion message is used to prompt the business operator to transfer the main low-value-added product of the high-value-added plant to the transferable low-value-added plant with the name for production. The operating dimension management system of claim 9, wherein, in the capacity concentration determination step, if it is determined that the difference in the monthly average output of the main low-value-added products of two or more of the transferable low-value-added plants is greater than or equal to the monthly average output of the main low-value-added products of the high-value-added plant, the following steps are performed: A distance determination step: Calculating the distance between each of the transferable low-value-added plants and the high-value-added plant, and using the name of the transferable low-value-added plant closest to the high-value-added plant as the name in the recommendation information. The business dimension management system of claim 9, wherein, in the capacity concentration determination step, if the determination is that the monthly average output of each low-value product in each high-value plant is the same as the sum of the monthly average output differences of two or more low-value plants producing the same low-value product; If the monthly average output is the same, a suggestion is displayed on the plant interface, prompting the business operator to transfer at least a portion of the low-value products produced by the high-value plant to two or more of the low-value plants.