Business data driving method for work decomposition based on data transmission

Abstract

The invention discloses a business data driving method for work decomposition based on data transmission. According to the method, business work decomposition is carried out, data driving is formed, and business digitization and digital business are realized; the business digitization comprises the steps of S1, decomposing a task into a work order corresponding to delivery data; s2, defining key indexes; s3, collecting, analyzing, querying and counting the data; s4, real-time monitoring and adjustment based on data; the digital business comprises S1 and the following steps of S5-S7 and S5: realizing data productization, and converting data collected from the worksheet into a data product through data fusion, data analysis and visualization means; s6, realizing data servitization; and S7, realizing data capability service. According to the business data driving method for work decomposition based on data transmission, effective business data are comprehensively collected in a specific mode of business digitization and digital business, so that business data driving and intelligent management and efficient operation of businesses are realized.

Description

Technical Field

[0001] The present invention relates to the fields of data management and business digitization, and in particular to a business data driven method for work decomposition based on data transfer. Background Art

[0002] With the rapid development of big data and Internet technology, data has become a core element of enterprise decision-making and operation. However, in traditional work decomposition, work orders are often not oriented towards delivery data, but are decomposed in a way that contains data and task actions. Its biggest flaw is that "data transfer" is blocked by non-data work orders, so that the clear path of "data transfer" cannot be seen. As a result, problems such as data islands, missing data, invalid data, poor data transfer, and unclear work decomposition have led to inefficient business decision-making and serious waste of resources. Therefore, how to effectively use the data transfer mechanism to optimize the work decomposition process has become a key challenge for modern enterprises to transform to digitalization. Summary of the invention

[0003] To solve the above problems, the present invention provides a business data-driven method for work decomposition based on data transmission, which comprehensively collects effective business data through specific methods of business digitization and digital businessization, thereby realizing business data-driven, intelligent management and efficient operation of the business.

[0004] According to one aspect of the present invention, a business data-driven method for work decomposition based on data transmission is provided, which performs business work decomposition according to the direction of data transmission, forms data drive, and realizes business digitization and digital businessization;

[0005] Business digitization includes the following steps S1 to S4

[0006] S1: Decompose the task into work orders corresponding to the delivery data according to the direction of data transmission, where each work order corresponds to one delivery data;

[0007] S2: Define key indicators;

[0008] S3: collect, analyze, query and count data;

[0009] S4: Real-time monitoring and adjustment based on data;

[0010] Digital service includes step S1 and the following steps S5 to S7

[0011] S5: Realize data productization, transform the data collected from the work order into data products through data fusion, data analysis and visualization;

[0012] S6: Realize data service;

[0013] S7: Implement data capability services;

[0014] Among them, step S1 further includes the following steps

[0015] A: Define the business categories in the task, where the business categories include business category 1 to business category N;

[0016] B: In business category 1, break down the work order 1-1 formed with data 1-1 as the delivered data. When data 1-1 is to be referenced by data 1-2, break down the work order 1-2 formed with data 1-2 as the delivered data, and so on, until the work order 1-N formed with data 1-N as the delivered data is broken down.

[0017] C: In business category 2, when data 1-1 in business category 1 is to be referenced by data 2-1 in business category 2, break down the work order 2-1 formed with data 2-1 as the delivered data. When data 2-1 is to be referenced by data 2-2, break down the work order 2-2 formed with data 2-2 as the delivered data, and so on, until the work order 2-N formed with data 2-N as the delivered data is broken down.

[0018] D: By analogy with steps B) and C), until the work order N-N formed with data N-N as the delivered data is broken down.

[0019] In some embodiments, the data delivered in the work order can be transferred within the same business category and can also be transferred to other business categories. The advantage is that it describes the transfer methods that data can achieve through work orders, and the transfer paths and logics are very clear.

[0020] In some embodiments, in step S2, the key indicators include design quality indicators, design progress indicators, and design efficiency indicators, and each indicator is designed according to the business nature. The advantage is that it describes the main content of the key indicators.

[0021] In some embodiments, in step S3, the data includes delivered data and attribute data. The advantage is that it describes the main content of the data for collection, analysis, query, and statistics.

[0022] In some embodiments, in step S4, the methods of real-time monitoring and adjustment include business and its data visualization and key indicator visualization. The advantage is that it describes the main specific methods of real-time monitoring and adjustment.

[0023] In some embodiments, in step S5, it includes fusing the model data collected from each business category to generate an electronic sand table file as a visualized data product. The advantage is that it describes a specific step to achieve data productization.

[0024] In some embodiments, in step S6, the items of data service-ification include drawing mounting and sub - items. The advantage is that the main item content of data service-ification is described.

[0025] In some embodiments, in step S7, the items of data capability services include construction simulation and progress management, providing model version comparison services, optimizing data transfer and business processes, and data synchronization services. The advantage is that the main item content of data capability services is described. Description of the Drawings

[0026] Figure 1 It is a flowchart of a business data - driven method for work breakdown based on data transfer according to an embodiment of the present invention;

[0027] Figure 2 is Figure 1 The flowchart of work breakdown based on data transfer shown. Detailed Embodiments

[0028] The present invention will be further described in detail below with reference to the drawings.

[0029] As Figure 1 shown, a business data - driven method for work breakdown based on data transfer in the present invention mainly includes two parts: business digitalization and digital business - ization. The data mentioned herein is a general reference, and in this embodiment, a BIM three - dimensional design project of a highway engineering is taken as an example for illustration.

[0030] Business digitalization can be achieved through the content of each of the following steps S1 - S4.

[0031] S1: Work breakdown based on data transfer.

[0032] The work breakdown of tasks is multi - dimensional. In the present invention, it refers to different business categories, and all are based on the "data" as the deliverable and the process of "data transfer" for work breakdown, decomposing the task into work orders corresponding to the deliverable data, where each work order corresponds to a deliverable data.

[0033] As Figure 2 shown, the specific steps of work breakdown are as follows:

[0034] 1. First, clarify the business categories in the task (such as road, bridge, tunnel specialties, etc.). Let the business categories include business category 1, business category 2... business category N.

[0035] 2. In business category 1 (road specialty), decompose the "work order 1 - 1" formed with "(route design) data 1 - 1" as the deliverable data;

[0036] When "(Route Design) Data 1-1" is to be referenced by "(Subgrade Design) Data 1-2", a "Work Order 1-2" formed with "(Subgrade Design) Data 1-2" as the delivery data can be decomposed, that is, the data transfer path is from "Data 1-1" to "Data 1-2".

[0037] And so on, until when "(Route) Data 1-1, (Subgrade Design) Data 1-2..." etc. are to be referenced by "(Earthwork Calculation) Data 1-N", a "Work Order 1-N" formed with "(Earthwork Calculation) Data 1-N" as the delivery data can be decomposed, that is, the data transfer path is from "Data 1-1", "Data 1-2" until "Data 1-N".

[0038] 3. In Business Category 2 (Bridge Specialty), when "(Route Design) Data 1-1" is to be referenced by "(Bridge Design) Data 2-1" in Business Category 2 (Bridge Specialty), a "Work Order 2-1" formed with "(Bridge Design) Data 2-1" as the delivery data is decomposed, that is, the data transfer path is from "Data 1-1" to "Data 2-1", and when "(Bridge Design) Data 2-1" is to be referenced by other "Data 2-2", a "Work Order 2-2" formed with "Data 2-2" as the delivery data is decomposed, and so on. Thus, Business Category 2 (Bridge Specialty) also completes the work breakdown according to the internal data transfer requirements, that is, the data transfer path is from "Data 2-1" and "Data 2-2" until "Data 2-N".

[0039] 4. And so on, until the work breakdown of all businesses is completed, until a "Work Order N-N" formed with "Data N-N" as the delivery data is created.

[0040] It can be seen that a business is composed of multiple work orders containing delivery data, and multiple work orders form the work order tree of this business. Among them, the work order is an additional description of each delivery data, and all data (except the delivery data) on it are the attribute data of this delivery data.

[0041] In addition, the delivery data in the work orders decomposed by a certain business category can be transferred within the same business category (for internal business use), or transferred between different business categories (for external business use).

[0042] In this step, by performing work breakdown according to the "data transfer" process, all delivery data and their attribute data can be collected, ensuring the high effectiveness of the collected data, not only forming data-driven business digitization, but also the collected data laying a foundation for digital businessization.

[0043] S2: Define key indicators.

[0044] Taking a design project as an example, a series of metrics are usually used to ensure design quality, schedule, cost, and resource utilization efficiency, etc. For the data supporting the key metrics, it must be incorporated into the work order attribute data before it can be collected, mined, and utilized.

[0045] The present invention is based on "data transfer" as the basis for work (process) decomposition, is not restricted by business categories, the collected data covers data of all businesses, and can support the definition of global control metrics across businesses.

[0046] Taking a highway design project as an example, its key business metrics can be defined as (but not limited to):

[0047] 1. Design quality metrics, such as:

[0048] Design error rate: The proofreading opinion data can be extracted from the proofreading work order for error quantity statistics, and compared with the total design quantity extracted from the attribute data of the work order;

[0049] Number of design changes: The number of design changes can be determined by using data such as the "version number" of the delivery data in the work order, the number of changes in the "status" of the work order, and the number of times submitted for proofreading;

[0050] Design review passing rate: It can be calculated by using statistics on data such as the "status" of internal or external review work orders and the total number of review work orders.

[0051] 2. Design schedule metrics, such as:

[0052] Design cycle completion rate: That is, the ratio of the actual completed design workload to the planned workload, which can be automatically statistically calculated by extracting the attribute data in the relevant work orders, namely the completed quantity and the planned completed quantity;

[0053] Milestone node achievement rate: That is, whether the key design nodes are completed on time. The task start and end time data of the work order can be used to automatically generate a task visual plan chart, and the node achievement rate can also be statistically calculated;

[0054] Number of design delay days: That is, the difference between the actual completion time and the planned time of the design work. It can be automatically calculated by comparing the "completion time" data and the "work status" data of the tasks in the work order, and an early warning can be pushed based on this result.

[0055] 3. Design efficiency metrics, such as:

[0056] Per capita output of design personnel: That is, the design workload completed by each design personnel within a unit time. The data such as "executor, total number of work orders, completed quantity, start / completion time" in the real-time collected work orders can be extracted, analyzed, and calculated to obtain the result of this metric;

[0057] Drawing output efficiency of design drawings: That is, the number of design drawings completed per unit time. Data such as "total number of work orders, completed quantity, start / complete time" in the collected work orders can be extracted, analyzed, and calculated to obtain the result of this indicator;

[0058] Collaboration efficiency of design (across different specialties): That is, the response speed and collaboration effect of collaborative design among multiple specialties. Data such as "version", "submission time", "access statistics", etc. of the delivery data in the collected work orders can be extracted, analyzed, and calculated to obtain the result of this indicator;

[0059] 4. Other indicators, such as:

[0060] Application rate of new technologies: That is, the proportion of new technologies and new processes adopted in the design.

[0061] Proportion of green design: That is, the proportion of green and environmental protection technologies adopted in the design.

[0062] For the above two indicators, they can both be obtained by extracting, analyzing, and calculating data such as "work tags" and "mounted data" from the attribute data of the collected work orders.

[0063] Design communication frequency: That is, the number and quality of communications between the design team and external units such as customers and construction parties. It can be obtained by extracting the data in the "communication window" of the work order and conducting statistics.

[0064] On-time delivery rate of design results: That is, whether the design results are delivered to the customer or the construction party on time. Data such as "completed quantity, start / complete time" in the collected work orders can be extracted, analyzed, and calculated to obtain the result of this indicator.

[0065] The above key indicators are all visually displayed, facilitating real-time monitoring of the progress of the business, and timely adjustment of business strategies, feeding back business data to the business, so as to achieve data-driven refined operation.

[0066] S3: Collect, analyze, query, and statistically process the data.

[0067] Using the real-time data in the collected business processes, including full-volume data of the entire process such as work status, working hours, planned workload, and completed workload, through data fusion, extraction, and analysis, these data are mined and parsed to form an analysis and insight of the entire business process, providing support for business decision-making.

[0068] Such as Figure 2 As shown, the full-volume data of the entire business mainly includes data generated in the entire business category, all work orders, and the entire business process. Specifically, it includes:

[0069] 1. Delivery data, which is the outcome data of the business and drives business digitization.

[0070] 2. Attribute data.

[0071] Among them, the work order is an additional description of each delivery data, and all data (except delivery data) on it are the attribute data of this delivery data, including but not limited to: work order number, work order name, work label, work scope, work type, work status, start / end time, work executor, total work volume, completed volume, creator, work description, work studio design, delivery data version, mounted data, work attachments, work members, suggestion box, this order configuration, message configuration, review order number, review order name, review process, creator, processor, creation time, update time, etc.; it also includes editable types, such as submission instructions, submission results, review comments, attachment list, communication window, etc.

[0072] Among them, both delivery data and attribute data are dynamic and will be recorded and collected in real time.

[0073] It can be seen that all the delivery data collected by using the method of the present invention is effective, and at the same time, it can also ensure a high efficiency of the corresponding attribute data.

[0074] In terms of data analysis, query and statistics, based on the data-driven method of the present invention, there is more detailed information data, and it has stronger data traceability ability, and can support multi-dimensional correlation data analysis. Among them. Through applications such as analysis, query, and statistics of the collected full-service data, the production plan and actual execution situation in any concerned scope can be compared and analyzed to find out the problems and bottlenecks in the production plan, and realize real-time monitoring and scientific decision-making driven by data.

[0075] For data analysis, it includes but is not limited to the following methods: fusing and plotting the collected time-related attribute data to draw a business Gantt chart, comparing and analyzing the production plan and actual execution situation through a data analysis tool, and using colors (data-driven) to identify the businesses that do not meet the plan, which is convenient for finding out the bottlenecks of business lag and making decisions on resource allocation; and fusing the collected model delivery data to generate project-level sand table file data, comparing and analyzing the model data with the specification data through a data analysis tool, generating a comparison result report, and feeding it back to the data maintenance personnel to maintain the data accordingly.

[0076] In data query and statistics, the data-driven method of the present invention can support multi-dimensional accurate queries. Attribute data categories, keywords, etc. can all be used as query conditions to adapt to queries and statistics on business progress, quality, etc. based on any dimension of the whole. The query methods include but are not limited to the following: Through accurate data, the time and responsible person of each business link can be tracked. In the custom query tool, setting the "planned completion time", "completion time" of the work, and the "executor" of the work order as query conditions can count and visualize all the work orders of this employee during the query time period. In this way, when analyzing business delays, the problem can be located more quickly, and clicking on the problematic work order can lead to the details of the work for problem handling, while the traditional method may only show the overall delay rate and cannot go into details.

[0077] S4: Real-time monitoring and adjustment based on data.

[0078] In the present invention, since global and full-scale business data can be collected, key business indicators can be tracked and evaluated in real time. Once business problems and opportunities are found, the business strategy can be adjusted immediately to ensure the continuous growth and optimization of the business. Among them, the ways of real-time monitoring and adjustment include business and its data visualization and key indicator visualization.

[0079] For business and its data visualization, in the present invention, work breakdown is carried out based on the data transfer process, and the data transfer logic is clear. It can not only visualize the business but also visualize the business data, facilitating real-time monitoring of the work, promptly discovering problems and making adjustments to the business and resources.

[0080] For key indicator visualization, on the basis of collecting all business data, a data extraction, analysis, and application mechanism is established. The business data is fused and transformed into business key indicators, and visualization is achieved by means of charts, etc., in order to facilitate real-time monitoring and adjustment of the production plan and ensure the accuracy rate and on-time rate of the production plan.

[0081] Digital business transformation means using the collected data, on the basis of data integration, packaging the data into a product, and upgrading it to a new business segment, which is commercially promoted and operated by a professional team in a productized manner.

[0082] Among them, digital business transformation can be achieved through the content of S1 and the following steps S5 to S7.

[0083] S5: Realize data productization.

[0084] Data productization means converting the data collected from work orders into data products, such as Web sand table files, through data fusion, data analysis, and visualization means. Among them, the Web sand table file can change with the change of the source data, so as to provide services such as decision-making support for the business in a timely manner.

[0085] By fusing the BIM model data of each business category (specialty) collected and generating an electronic sand table file, a visual data product can be obtained, which can be applied to the display, reporting, etc. of the three-dimensional model data of the entire project design result;

[0086] S6: Implement data serviceization.

[0087] Data serviceization means integrating the data precipitated in the business system, finding rules from the data, and using the data to drive the development of each business, infiltrating the data into the operation of each business, enabling the data to feed back to the business, and finally releasing the data value to complete the operation closed-loop of the data value.

[0088] Taking the highway design project as an example, the relevant data serviceization projects mainly include drawing mounting and work breakdown.

[0089] In the drawing mounting service, mounting the drawing data to the model data of the component is a data service provided to external users. Among them, the specific generation method of the drawing mounting service is: import BIM model data (into the tool) - import drawing data - identify (model attributes + drawing attributes) data - data matching - generate the "drawing mounting" data service.

[0090] In the work breakdown service, by using data analysis, conversion, and data docking means, the collected engineering quantity data is docked by work breakdown according to the bill of quantities of the construction stage, and the engineering quantity data is transferred from the upstream to the downstream application through data conversion. Especially when design changes occur, after the upstream data changes, the downstream data will follow the change in a timely and error-free manner, avoiding the frequent errors in traditional manual data updates and improving the efficiency of manual data correction.

[0091] Among them, the specific generation method of work breakdown is: import model, material information, material quantity, work breakdown information, ebs code - import the target work breakdown list standard - change (iteratively) - generate the "work breakdown" engineering quantity ledger - dock with the downstream data platform - generate the "work breakdown" data service.

[0092] S7: Implement data capability service.

[0093] Data capability service means building digital capabilities related to the main business based on the organization's relevant data resources and knowledge, such as digital capabilities services like intelligent analysis, simulation verification, and construction management.

[0094] Taking a highway design project as an example, the relevant data service capabilities mainly include the following items.

[0095] 1. Construction simulation and progress management, that is, associating the BIM model with the construction progress plan (4D) to simulate key nodes. The specific real-time steps are as follows: extracting BIM model data - associating the construction progress plan - dynamically visualizing the simulation - conflict detection and optimization - progress tracking and comparison - deviation warning - simulation iterative optimization (adjusting the progress, comparing multiple options) - result release (for construction disclosure, reporting, etc.).

[0096] 2. Providing model version comparison service, that is, maintaining the accuracy and consistency of data through the model version comparison function provided by the data capability service. The specific real-time steps are as follows: determining the data version numbers to be compared - selecting and extracting the BIM model data of the corresponding versions - using the model comparison tool - generating a visual comparison result.

[0097] 3. Optimizing data transfer and business processes, that is, extracting the data problems and improvement suggestions feedback by team members during the project execution from the attribute data, and continuously optimizing the data transfer process and business processes. The specific real-time steps are as follows: extracting data such as "communication window", "suggestion box", "key indicators", etc. - integrating relevant data - multi-party collaboration to identify problems - using visual means to analyze and evaluate problems - generating optimization opinions and releasing them.

[0098] 4. Data synchronization service, that is, real-time synchronizing data changes in the project to ensure that all team members can obtain the latest data version in a timely manner. The specific real-time steps are divided into two methods:

[0099] (1) Data change - triggering the "automatic update" mechanism - the delivery data of the studio is automatically updated to the latest version;

[0100] (2) Data change - triggering the "automatic detection" mechanism - sending a message to the data reference personnel - the option to update the reference data is available.

[0101] A business data-driven method based on work breakdown through data transfer in the present invention mainly has the following beneficial effects:

[0102] 1. The method of work breakdown based on "data transfer" can make the goals of work breakdown very clear and not easy to miss items. The "data transfer" path is clear. Moreover, it can not only precipitate all the data of the business process, but also break the data islands between businesses, realize the integration and interconnection of upstream and downstream data, and at the same time ensure the efficient operation of the business process through the comprehensive digitalization of the business process, laying a data foundation for the overall optimization of the business process;

[0103] 2. Taking 'data transfer' as the basis for work (process) breakdown, it is not limited by business, thus breaking through the data barriers between businesses and helping to control the entire business scope;

[0104] 3. For the work orders after work breakdown based on data transfer, the process data is recorded and captured in real time throughout the whole link, which can be used for data analysis and as the decision-making basis for management;

[0105] 4. For the work orders after work breakdown based on data transfer, the delivery data has been classified, defined, and planned since it starts to be produced, and all of them are valid data and can be directly used;

[0106] 5. Enabling the business data to be accurately and fully collected through work orders, it can realize more and more advanced data services that can be provided externally, such as drawing mounting, sub - item division, etc.

[0107] The above are only some embodiments of the present invention. For those of ordinary skill in the art, without departing from the inventive concept of the present invention, several modifications and improvements can still be made, and these all belong to the protection scope of the present invention.

Claims

1. A business data driven method for work decomposition based on data transfer, characterized in that: Decompose business work according to the direction of data transmission, form data-driven, and realize business digitization and digital business; Business digitization includes the following steps S1 to S4 S1: Decompose the task into work orders corresponding to the delivery data according to the direction of data transmission, where each work order corresponds to one delivery data; S2: Define key indicators; S3: collect, analyze, query and count data; S4: Real-time monitoring and adjustment based on data; Digital service includes step S1 and the following steps S5 to S7 S5: Realize data productization, transform the data collected from the work order into data products through data fusion, data analysis and visualization; S6: Realize data service; S7: Implement data capability services; Wherein, step S1 also includes the following steps A: Clearly define the business category in the task, where the business category includes business category 1 to business category N; B: In business class 1, work order 1-1 formed by data 1-1 as delivery data is decomposed, and when data 1-1 will be referenced by data 1-2, work order 1-2 formed by data 1-2 as delivery data is decomposed, and so on, until work order 1-N formed by data 1-N as delivery data is decomposed; C: In business class 2, when data 1-1 of business class 1 will be referenced by data 2-1 in business class 2, work order 2-1 formed with data 2-1 as delivery data is decomposed, and when data 2-1 will be referenced by data 2-2, work order 2-2 formed with data 2-2 as delivery data is decomposed, and so on, until work order 2-N formed with data 2-N as delivery data is decomposed; D: According to step B) and step C), and so on, until the work order NN formed with data NN as the delivery data is decomposed.

2. The business data driven method for work decomposition based on data transfer according to claim 1, characterized in that: The data delivered in the work order can be passed within the same business class and can be passed to other business classes.

3. The business data driven method for work decomposition based on data transfer according to claim 1, characterized in that: In step S2, the key indicators include design quality indicators, design progress indicators and design efficiency indicators, and each indicator is designed according to the nature of the business.

4. The business data driven method for work decomposition based on data transfer according to claim 1, characterized in that: In step S3, the data includes delivery data and attribute data.

5. The business data driven method for work decomposition based on data transfer according to claim 1, characterized in that: In step S4, the real-time monitoring and adjustment methods include business and data visualization and key indicator visualization.

6. The business data driven method for work decomposition based on data transfer according to claim 1, characterized in that: In step S5, the collected model data of each business category are integrated to generate an electronic sandbox file as a visual data product.

7. The business data driven method for work decomposition based on data transfer according to claim 1, characterized in that: In step S6, the data service items include drawing mounting and sub-items.

8. The business data driven method for work decomposition based on data transfer according to claim 1, characterized in that: In step S7, the data capability service items include construction simulation and progress management, model version comparison service, optimization of data transmission and business processes, and data synchronization service.

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