CN105574653A - Supplier evaluation and selection method based on data warehouse - Google Patents
Supplier evaluation and selection method based on data warehouse Download PDFInfo
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- CN105574653A CN105574653A CN201510925233.7A CN201510925233A CN105574653A CN 105574653 A CN105574653 A CN 105574653A CN 201510925233 A CN201510925233 A CN 201510925233A CN 105574653 A CN105574653 A CN 105574653A
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Abstract
The invention relates to a data warehouse technique, solves the existing problem of having no integrated supplier evaluation and selection, and provides a supplier evaluation and selection method based on a data warehouse. The technical solution can be summarized as following steps: firstly, determining supplier evaluation indexes, an evaluation index system and basic data sources of each index, then determining service calculation logics of the supplier evaluation indexes and a scoring rule of each index, then extracting evaluation index service basic data to the data warehouse, with respect to the indexes without service system data, leading to the data warehouse according to a fixed template, then building an evaluation system model in the data warehouse according to the service calculation logics of the supplier evaluation indexes and the scoring rule of each index, calculating the integrated scores of each supplier, then generating an evaluation result according to the integrated scores of each supplier, wherein a service worker views and selects corresponding suppliers. The method of the invention is advantaged by that the method is convenient for a user to use and is applicable to supplier selection.
Description
Technical field
The present invention relates to data warehouse technology, particularly the supplier selection and evaluation technology of data warehouse.
Background technology
Along with the fast development of economy and electronic information technology, the management of supply chain plays an important role for the development of enterprise and competition.As the source of supply chain management and the terminal of supply chain circulation feedback, supplier plays a very important role in supplier management process, it affects quality, the technology of product, restrict the development of whole supply chain, therefore vendors' evaluating has very important meaning with selection to supply chain management.
But a lot of enterprise also rests on artificial subjective judgement to the overall evaluation of supplier at present, and result is subject to the impact of human factor, and supplier's relevant historical trading data is also scattered in each operation system, is not easy to carry out data centralization management.
Summary of the invention
The object of the invention is to solve the overall evaluation of current neither one to supplier and the problem of selection, provide a kind of supplier selection and evaluation method based on data warehouse.
The present invention solves its technical matters, and the technical scheme of employing is, based on the supplier selection and evaluation method of data warehouse, it is characterized in that, comprises the following steps:
Step 1, determine that supplier evaluation index, assessment indicator system and each index basic data are originated;
The score rule of step 2, the service computation logic determining supplier evaluation index and each index;
Step 3, extraction evaluation index service basic data to data warehouse, for the index without business system data, import data warehouse according to fixed form;
Step 4, build evaluation system model according to the score rule of the service computation logic of supplier evaluation index and each index at data warehouse, calculate the integrate score of each supplier;
Step 5, generate evaluation result according to the integrate score of each supplier, check for business personnel;
Step 6, business personnel, according to evaluation result and actual conditions, select corresponding supplier.
Concrete, in step 1, describedly determine that supplier evaluation index, assessment indicator system and each index basic data are originated, it is determined together with business personnel by technician.
Further, in step 1, described supplier evaluation index is divided into three grades, and be respectively: first class index, it refers to comprehensive evaluation; Two-level index, it comprises each one-level evaluation; Three grades of indexs, it comprises the specific targets under each two-level index.
Concrete, in step 2, the score rule of described each index refers to the score rule of each three grades of indexs.
Further, in step 3, described extraction evaluation index service basic data obtain the service basic data relevant to supplier evaluation and master data from each operation system.
Concrete, described each operation system comprises ERP system and/or supplier relationship management system.
Further, step 4 comprises the following steps:
Step 41, build evaluation system model according to the score rule of the service computation logic of supplier evaluation index and each three grades of indexs at data warehouse, calculate three grades of index scores of each supplier;
Step 42, utilization Fuzzy AHP obtain the weight of each three grades of indexs;
Step 43, use each three grades of index scores of each supplier calculated to be multiplied by the weight of corresponding index after the cumulative each two-level index score obtaining each supplier;
Step 44, each two-level index score of each supplier is added up obtain the first class index score of each supplier respectively, namely obtain integrate score.
Concrete, in step 42, the method that described utilization Fuzzy AHP obtains the weight of each three grades of indexs is: use Information Entropy to obtain the weight of each three grades of indexs, specifically comprise the following steps:
Step 42a, standardization is carried out to index, by heterogeneous index homogeneity;
Step 42b, calculating lower i-th supplier of jth item index account for the proportion of this index, and wherein, j and i is positive integer;
The entropy of step 42c, calculating jth item index;
The coefficient of variation of step 42d, calculating jth item index;
Step 42e, calculating weights.
Further, in step 5, the described integrate score according to each supplier generates in evaluation result, also divides supplier's grade, described supplier grade level Four altogether according to the integrate score of each supplier.
Concrete, in step 5, described evaluation result is shown by form or figure.
The invention has the beneficial effects as follows, in the present invention program, by the above-mentioned supplier selection and evaluation method based on data warehouse, by setting up the evaluation index of various dimensions, build evaluation system model, help enterprise's various dimensions, objective, transparent supplier is evaluated, for enterprise selects the supplier of more high-quality to provide real, objective, comprehensive one innings, and then help enterprise to occupy more favourable competitive edge at supply chain management center, and facilitate user.
Embodiment
Below in conjunction with embodiment, describe technical scheme of the present invention in detail.
Supplier selection and evaluation method based on data warehouse of the present invention is: first determine supplier evaluation index, assessment indicator system and each index basic data source, determine the service computation logic of supplier evaluation index and the score rule of each index again, then evaluation index service basic data to data warehouse is extracted, for the index without business system data, data warehouse is imported according to fixed form, evaluation system model is built at data warehouse again according to the service computation logic of supplier evaluation index and the score rule of each index, calculate the integrate score of each supplier, and then generate evaluation result according to the integrate score of each supplier, check for business personnel, last business personnel is according to evaluation result and actual conditions, select corresponding supplier.
Embodiment
The supplier selection and evaluation method based on data warehouse of the embodiment of the present invention, comprises the following steps:
Step 1, determine that supplier evaluation index, assessment indicator system and each index basic data are originated.
In this example, be supplier evaluation index, assessment indicator system and each index basic data source determined together with business personnel by technician, and supplier evaluation index can be divided into three grades, is respectively: first class index, it refers to comprehensive evaluation; Two-level index, it comprises each one-level evaluation, such as business assessment, quality assessment and reference evaluation etc.; Three grades of indexs, it comprises the specific targets under each two-level index.Such as, index under the business assessment index that to be the index under price rank, quality assessment be under a batch qualification rate, reference evaluation is supply of material promptness rate etc.
The score rule of step 2, the service computation logic determining supplier evaluation index and each index.
In this example, the score rule of each index refers to the score rule of each three grades of indexs, and the service computation logic of supplier evaluation index and the score rule of each index are exemplified below: price rank passes through purchase order settlement amounts divided by purchase quantity, draw material unit price, cheapest score is up to 100 points, the price that must be divided into the price/second place of 100* first place of second place, the price that must be divided into the price/third of 100* first place of third, by that analogy; Batch qualification rate=qualified batch of number/overall test batch number, score=qualification rate * 100; Supply of material promptness rate=delivery just-in-time amount/order total amount, score=promptness rate * 100.
Step 3, extraction evaluation index service basic data to data warehouse, for the index without business system data, import data warehouse according to fixed form.
In this example, extracting evaluation index service basic data can be obtain the service basic data relevant to supplier evaluation and master data from each operation system, and each operation system comprises ERP system and/or supplier relationship management system etc.
Step 4, build evaluation system model according to the score rule of the service computation logic of supplier evaluation index and each index at data warehouse, calculate the integrate score of each supplier.
In this example, this step can comprise following concrete steps:
Step 41, build evaluation system model according to the score rule of the service computation logic of supplier evaluation index and each three grades of indexs at data warehouse, calculate three grades of index scores of each supplier.
Step 42, utilization Fuzzy AHP obtain the weight of each three grades of indexs.
In this step, the method using Fuzzy AHP to obtain the weight of each three grades of indexs is: use Information Entropy to obtain the weight of each three grades of indexs, specifically comprise the following steps:
Step 42a, standardization is carried out to index, by heterogeneous index homogeneity;
Step 42b, calculating lower i-th supplier of jth item index account for the proportion of this index, and wherein, j and i is positive integer;
The entropy of step 42c, calculating jth item index;
The coefficient of variation of step 42d, calculating jth item index;
Step 42e, calculating weights.
Step 43, use each three grades of index scores of each supplier calculated to be multiplied by the weight of corresponding index after the cumulative each two-level index score obtaining each supplier.
Step 44, each two-level index score of each supplier is added up obtain the first class index score of each supplier respectively, namely obtain integrate score.
Step 5, generate evaluation result according to the integrate score of each supplier, check for business personnel.
In this example, generate in evaluation result according to the integrate score of each supplier, also divide supplier's grade according to the integrate score of each supplier, be such as level Four by supplier's grade classification: be more than or equal to 90 and be divided into A, be more than or equal to 80 points to be less than 90 and to be divided into B, be more than or equal to 70 points to be less than 80 and to be divided into C, be less than 70 and be divided into D, and evaluation result can be shown by form or figure.
Step 6, business personnel, according to evaluation result and actual conditions, select corresponding supplier.
Claims (10)
1., based on the supplier selection and evaluation method of data warehouse, it is characterized in that, comprise the following steps:
Step 1, determine that supplier evaluation index, assessment indicator system and each index basic data are originated;
The score rule of step 2, the service computation logic determining supplier evaluation index and each index;
Step 3, extraction evaluation index service basic data to data warehouse, for the index without business system data, import data warehouse according to fixed form;
Step 4, build evaluation system model according to the score rule of the service computation logic of supplier evaluation index and each index at data warehouse, calculate the integrate score of each supplier;
Step 5, generate evaluation result according to the integrate score of each supplier, check for business personnel;
Step 6, business personnel, according to evaluation result and actual conditions, select corresponding supplier.
2. as claimed in claim 1 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, in step 1, describedly determine that supplier evaluation index, assessment indicator system and each index basic data are originated, it is determined together with business personnel by technician.
3., as claimed in claim 1 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, in step 1, described supplier evaluation index is divided into three grades, and be respectively: first class index, it refers to comprehensive evaluation; Two-level index, it comprises each one-level evaluation; Three grades of indexs, it comprises the specific targets under each two-level index.
4. as claimed in claim 3 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, in step 2, the score rule of described each index refers to the score rule of each three grades of indexs.
5., as claimed in claim 4 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, step 4 comprises the following steps:
Step 41, build evaluation system model according to the score rule of the service computation logic of supplier evaluation index and each three grades of indexs at data warehouse, calculate three grades of index scores of each supplier;
Step 42, utilization Fuzzy AHP obtain the weight of each three grades of indexs;
Step 43, use each three grades of index scores of each supplier calculated to be multiplied by the weight of corresponding index after the cumulative each two-level index score obtaining each supplier;
Step 44, each two-level index score of each supplier is added up obtain the first class index score of each supplier respectively, namely obtain integrate score.
6. as claimed in claim 5 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, in step 42, the method that described utilization Fuzzy AHP obtains the weight of each three grades of indexs is: use Information Entropy to obtain the weight of each three grades of indexs, specifically comprise the following steps:
Step 42a, standardization is carried out to index, by heterogeneous index homogeneity;
Step 42b, calculating lower i-th supplier of jth item index account for the proportion of this index, and wherein, j and i is positive integer;
The entropy of step 42c, calculating jth item index;
The coefficient of variation of step 42d, calculating jth item index;
Step 42e, calculating weights.
7. as claimed in claim 1 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, in step 3, described extraction evaluation index service basic data obtain the service basic data relevant to supplier evaluation and master data from each operation system.
8., as claimed in claim 7 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, described each operation system comprises ERP system and/or supplier relationship management system.
9. as claimed in claim 1 based on the supplier selection and evaluation method of data warehouse, it is characterized in that, in step 5, the described integrate score according to each supplier generates in evaluation result, also divide supplier's grade, described supplier grade level Four altogether according to the integrate score of each supplier.
10. the supplier selection and evaluation method based on data warehouse as described in claim 1 or 2 or 3 or 4 or 5 or 6 or 7 or 8 or 9, is characterized in that, in step 5, described evaluation result is shown by form or figure.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107622420A (en) * | 2017-09-28 | 2018-01-23 | 浪潮通用软件有限公司 | A kind of supplier recommends method and device |
| CN108090602A (en) * | 2016-11-22 | 2018-05-29 | 浙江科技学院 | A kind of complicated supply chain network optimum design method based on uncalibrated visual servo supply grid cluster |
| CN108197816A (en) * | 2018-01-17 | 2018-06-22 | 吉林省吉好生活服务有限公司 | A kind of credit system evaluation method based on household services |
| CN108428037A (en) * | 2017-10-31 | 2018-08-21 | 平安科技（深圳）有限公司 | Electronic device, the method and storage medium for adjusting supplier |
| CN108492033A (en) * | 2018-03-26 | 2018-09-04 | 国家电网公司客户服务中心 | Power grid client, which concentrates, complains intelligent early-warning method |
| CN109242562A (en) * | 2018-08-31 | 2019-01-18 | 万翼科技有限公司 | Ranking method, device and the storage medium of supplier |
| CN109377114A (en) * | 2018-12-14 | 2019-02-22 | 万翼科技有限公司 | Appraisal procedure, server and the storage medium of supplier |
| CN109740036A (en) * | 2018-12-29 | 2019-05-10 | 北京创鑫旅程网络技术有限公司 | OTA platform hotel's sort method and device |
| CN110070244A (en) * | 2018-01-22 | 2019-07-30 | 北京京东尚科信息技术有限公司 | Supplier evaluation method, system, electronic equipment and computer-readable medium |
| CN112381349A (en) * | 2020-10-14 | 2021-02-19 | 浪潮软件股份有限公司 | Configuration method for terminal code scanning quality evaluation |
| CN112529449A (en) * | 2020-12-20 | 2021-03-19 | 大唐互联科技(武汉)有限公司 | Supplier quality evaluation method and system based on big data |
| CN112687473A (en) * | 2020-12-14 | 2021-04-20 | 安徽诚越电子科技有限公司 | Preparation method and device for improving yield of super capacitor |
| CN113537758A (en) * | 2021-07-13 | 2021-10-22 | 机械工业第六设计研究院有限公司 | Manufacturing industry high-quality development comprehensive evaluation method and system based on big data technology |
| CN114548631A (en) * | 2020-11-27 | 2022-05-27 | 国网电子商务有限公司 | Dynamic evaluation method and device |
-
2015
- 2015-12-14 CN CN201510925233.7A patent/CN105574653A/en active Pending
Cited By (16)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108090602A (en) * | 2016-11-22 | 2018-05-29 | 浙江科技学院 | A kind of complicated supply chain network optimum design method based on uncalibrated visual servo supply grid cluster |
| CN107622420A (en) * | 2017-09-28 | 2018-01-23 | 浪潮通用软件有限公司 | A kind of supplier recommends method and device |
| CN108428037A (en) * | 2017-10-31 | 2018-08-21 | 平安科技（深圳）有限公司 | Electronic device, the method and storage medium for adjusting supplier |
| CN108197816A (en) * | 2018-01-17 | 2018-06-22 | 吉林省吉好生活服务有限公司 | A kind of credit system evaluation method based on household services |
| CN110070244A (en) * | 2018-01-22 | 2019-07-30 | 北京京东尚科信息技术有限公司 | Supplier evaluation method, system, electronic equipment and computer-readable medium |
| CN108492033A (en) * | 2018-03-26 | 2018-09-04 | 国家电网公司客户服务中心 | Power grid client, which concentrates, complains intelligent early-warning method |
| CN109242562A (en) * | 2018-08-31 | 2019-01-18 | 万翼科技有限公司 | Ranking method, device and the storage medium of supplier |
| CN109377114A (en) * | 2018-12-14 | 2019-02-22 | 万翼科技有限公司 | Appraisal procedure, server and the storage medium of supplier |
| CN109740036A (en) * | 2018-12-29 | 2019-05-10 | 北京创鑫旅程网络技术有限公司 | OTA platform hotel's sort method and device |
| CN109740036B (en) * | 2018-12-29 | 2020-12-18 | 北京创鑫旅程网络技术有限公司 | Hotel ordering method and device for OTA platform |
| CN112381349A (en) * | 2020-10-14 | 2021-02-19 | 浪潮软件股份有限公司 | Configuration method for terminal code scanning quality evaluation |
| CN114548631A (en) * | 2020-11-27 | 2022-05-27 | 国网电子商务有限公司 | Dynamic evaluation method and device |
| CN112687473A (en) * | 2020-12-14 | 2021-04-20 | 安徽诚越电子科技有限公司 | Preparation method and device for improving yield of super capacitor |
| CN112687473B (en) * | 2020-12-14 | 2022-05-27 | 安徽诚越电子科技有限公司 | Preparation method and device for improving yield of super capacitor |
| CN112529449A (en) * | 2020-12-20 | 2021-03-19 | 大唐互联科技(武汉)有限公司 | Supplier quality evaluation method and system based on big data |
| CN113537758A (en) * | 2021-07-13 | 2021-10-22 | 机械工业第六设计研究院有限公司 | Manufacturing industry high-quality development comprehensive evaluation method and system based on big data technology |
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Application publication date: 20160511 |