CN102542520A - Supplier cluster analysis management and customer allocation method - Google Patents
Supplier cluster analysis management and customer allocation method Download PDFInfo
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- CN102542520A CN102542520A CN2011104458922A CN201110445892A CN102542520A CN 102542520 A CN102542520 A CN 102542520A CN 2011104458922 A CN2011104458922 A CN 2011104458922A CN 201110445892 A CN201110445892 A CN 201110445892A CN 102542520 A CN102542520 A CN 102542520A
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Abstract
The invention discloses a supplier cluster analysis management and customer allocation method, which is characterized in that: firstly, the cluster analysis is carried out on suppliers, and then, the customer allocation is carried out according to the analysis result. The supplier cluster analysis management and customer allocation method comprises the following steps of: carrying out cluster analysis on all the suppliers by utilizing an attribute-oriented induction algorithm according to a first type of selected inductive attribute and a second type of selected inductive attribute; setting assessment rules through a control system according to the description; extracting all the suppliers in supplier types when grade values in the supplier types pocessing of first type of description are lower than scheduled lower threshold values, retrieving grade values attributed by second type of description corresponding to the first type of description and judging whether the grade values are still lower than the scheduled lower threshold values or not; and putting supplier data into a spare supplier database when the grade values of the suppliers passing through the first type of description are lower than the scheduled lower threshold values and the grades values of the suppliers passing through the second type of description are still lower than the scheduled lower threshold values. Through the method, the suppliers can be fairly selected.
Description
Technical field
The present invention relates to a kind of supplier management-control method, especially relate to a kind of supplier cluster analysis management and client's distribution method.
Background technology
The merchant runs the field with mobile telecommunication service, and along with the explosive increase of service content, supplier's reasonable management and control more and more becomes the indispensable means of modern commerce.Common operator's management and control need could be accomplished through numerous links, and artificial Subjective Intervention property is stronger, causes substantial unfairness.
Summary of the invention
The present invention is directed to the drawback of prior art; A kind of supplier cluster analysis management and client's distribution method are provided; This method can utilize computer system that supplier's situation is analyzed automatically, and distributes customer resources, realizes efficient fair management and allocation scheme.
The present invention provides a kind of supplier cluster analysis management and client's distribution method, it is characterized in that, at first supplier is carried out cluster analysis, and carry out the client according to analysis result again and distribute,
Specifically may further comprise the steps:
1) utilizes towards the attribute inductive algorithm,, whole suppliers are carried out cluster analysis, first kind of class description of every type of supplier after the generation cluster based on first kind of selected conclusion attribute;
2) utilize once more towards the attribute inductive algorithm,, whole suppliers are carried out cluster analysis, second kind of class description of every type of supplier after the generation cluster based on second kind of selected conclusion attribute;
3) control system is provided with first kind of assessment rules based on first kind of class description, based on second kind of class description second kind of assessment rules is set, and respectively whole provider-class is carried out ranking based on said first kind of assessment rules and second kind of assessment rules respectively;
All suppliers that 4) will have in the provider-class that grade point in the provider-class of first kind of class description is lower than predetermined lower threshold value extract; Retrieve the affiliated grade point of its second kind of corresponding class description, judge whether its grade point still is lower than predetermined lower threshold value;
5) with being lower than predetermined lower threshold value and putting into subsequent use supplier database through first kind of its grade point of class description among the supplier, all the other supplier data data are put into available supplier database through the supplier data data that second kind of its grade point of class description still is lower than predetermined lower threshold value;
6) parameters among the available supplier is carried out data and excavate, excavate out the degree of association between the parameters, and the relevance level of evaluation parameters;
7) utilize the allocation process center to receive client's information, client's information decomposition is become two types of demand information and contact details, and demand information and contact details are encrypted respectively, and generation safe key separately;
8) excavate data in the demand information, the parameters among these datas and the available supplier is mated, and according to the relevance level of the parameter on mating, for this coupling is provided with weight, wherein, weighted value is directly proportional with relevance level;
9) numerical value according to the parameters among weighted value and the corresponding available supplier calculates, and result of calculation is sorted, and selects the high person of result of calculation as choosing supplier;
10) demand information is passed to corresponding safe key choose supplier, and record should transmission information simultaneously, and should transmission information pass to server and put on record with contact details and safe key accordingly.
Preferably, in described supplier cluster analysis management and the client's distribution method, said first kind of selected conclusion attribute comprises the combination of supplier's scale merit, hazard rate, field deflection index and supply of goods index.
Preferably, in described supplier cluster analysis management and the client's distribution method, said second kind of selected conclusion attribute comprises arrival promptness rate index, service positive rating index, geographical area information, logistics speed information and technological R&D strength index.
Preferably, in described supplier cluster analysis management and the client's distribution method, said predetermined lower threshold value be in the grade point in all provider-class minimum 10% as node, the numerical value of being got.
Preferably, in described supplier cluster analysis management and the client's distribution method, the relevance level of a certain parameter is directly proportional with quantity with related other parameter of this parameter generating.
Supplier disclosed by the invention cluster analysis management and client's distribution method can utilize computer system that supplier's situation is analyzed automatically, and distribute customer resources, realize efficient fair management and allocation scheme.
Embodiment
Below the present invention is done further detailed description, can implement according to this with reference to the specification literal to make those skilled in the art.
The invention discloses a kind of supplier cluster analysis management and client's distribution method, at first supplier is carried out cluster analysis, carry out the client according to analysis result again and distribute, its objective is result, realize fair allocat the order client through cluster analysis.
Specifically may further comprise the steps:
1) utilizes towards the attribute inductive algorithm,, whole suppliers are carried out cluster analysis, first kind of class description of every type of supplier after the generation cluster according to first kind of selected conclusion attribute; Divide according to the attribute of appointment towards attribute inductive algorithm AOI, whole suppliers are classified, be distinguished into a plurality of classifications.
2) utilize once more towards the attribute inductive algorithm,, whole suppliers are carried out cluster analysis, second kind of class description of every type of supplier after the generation cluster according to second kind of selected conclusion attribute; That is to say and use two kinds of logics instead, whole suppliers are classified, is to take a part for the whole in order to avoid to the maximum limit like this.
3) control system is provided with first kind of assessment rules based on first kind of class description, based on second kind of class description second kind of assessment rules is set, and respectively whole provider-class is carried out ranking based on said first kind of assessment rules and second kind of assessment rules respectively; Because sorting technique is different, so assessment rules certainly exists difference.
All suppliers that 4) will have in the provider-class that grade point in the provider-class of first kind of class description is lower than predetermined lower threshold value extract; Retrieve the affiliated grade point of its second kind of corresponding class description, judge whether its grade point still is lower than predetermined lower threshold value; Confirming and can confirming according to number percent of this lower threshold value also can be confirmed according to numerical value itself.
5) with being lower than predetermined lower threshold value and putting into subsequent use supplier database through first kind of its grade point of class description among the supplier, all the other supplier data data are put into available supplier database through the supplier data data that second kind of its grade point of class description still is lower than predetermined lower threshold value; So just available supplier and subsequent use supplier have been distinguished.Subsequent use supplier distributes the client by the mode of artificial appointment, and available supplier assigns the client by the mode that system assigns automatically.
6) parameters among the available supplier is carried out data and excavate, excavate out the degree of association between the parameters, and the relevance level of evaluation parameters; Through degree of association evaluation, that can establish different parameters does not wait the status.
7) utilize the allocation process center to receive client's information, client's information decomposition is become two types of demand information and contact details, and demand information and contact details are encrypted respectively, and generation safe key separately;
8) excavate data in the demand information, the parameters among these datas and the available supplier is mated, and according to the relevance level of the parameter on mating, for this coupling is provided with weight, wherein, weighted value is directly proportional with relevance level; The degree of association is different, and weight is different.For example, shipment rate index is agree ability, and just the degree of association with other parameter is more, so its weight is answered Gao Genggao.
9) numerical value according to the parameters among weighted value and the corresponding available supplier calculates, and result of calculation is sorted, and selects the high person of result of calculation as choosing supplier;
10) demand information is passed to corresponding safe key choose supplier, and record should transmission information simultaneously, and should transmission information pass to server and put on record with contact details and safe key accordingly.
Preferably, in described supplier cluster analysis management and the client's distribution method, said first kind of selected conclusion attribute comprises the combination of supplier's scale merit, hazard rate, field deflection index and supply of goods index.
Preferably, in described supplier cluster analysis management and the client's distribution method, said second kind of selected conclusion attribute comprises arrival promptness rate index, service positive rating index, geographical area information, logistics speed information and technological R&D strength index.
Preferably, in described supplier cluster analysis management and the client's distribution method, said predetermined lower threshold value be in the grade point in all provider-class minimum 10% as node, the numerical value of being got.That is to say, grade point is ranked according to order from big to small, be subdivided into subsequent use supplier sequence coming last 10%.
Preferably, in described supplier cluster analysis management and the client's distribution method, the relevance level of a certain parameter is directly proportional with quantity with related other parameter of this parameter generating.Also many with regard to saying with other more parameters of this parameter association, the relevance grades of this parameter is high more.
Although embodiment of the present invention are open as above; But it is not restricted to listed utilization in instructions and the embodiment; It can be applied to various suitable the field of the invention fully, for being familiar with those skilled in the art, can easily realize other modification; Therefore under the universal that does not deviate from claim and equivalency range and limited, the legend that the present invention is not limited to specific details and illustrates here and describe.
Claims (5)
1. supplier's cluster analysis management and objective
The family distribution method is characterized in that, at first supplier is carried out cluster analysis, carry out the client according to analysis result again and distribute,
Specifically may further comprise the steps:
1) utilizes towards the attribute inductive algorithm,, whole suppliers are carried out cluster analysis, first kind of class description of every type of supplier after the generation cluster based on first kind of selected conclusion attribute;
2) utilize once more towards the attribute inductive algorithm,, whole suppliers are carried out cluster analysis, second kind of class description of every type of supplier after the generation cluster based on second kind of selected conclusion attribute;
3) control system is provided with first kind of assessment rules based on first kind of class description, based on second kind of class description second kind of assessment rules is set, and respectively whole provider-class is carried out ranking based on said first kind of assessment rules and second kind of assessment rules respectively;
All suppliers that 4) will have in the provider-class that grade point in the provider-class of first kind of class description is lower than predetermined lower threshold value extract; Retrieve the affiliated grade point of its second kind of corresponding class description, judge whether its grade point still is lower than predetermined lower threshold value;
5) with being lower than predetermined lower threshold value and putting into subsequent use supplier database through first kind of its grade point of class description among the supplier, all the other supplier data data are put into available supplier database through the supplier data data that second kind of its grade point of class description still is lower than predetermined lower threshold value;
6) parameters among the available supplier is carried out data and excavate, excavate out the degree of association between the parameters, and the relevance level of evaluation parameters;
7) utilize the allocation process center to receive client's information, client's information decomposition is become two types of demand information and contact details, and demand information and contact details are encrypted respectively, and generation safe key separately;
8) excavate data in the demand information, the parameters among these datas and the available supplier is mated, and according to the relevance level of the parameter on mating, for this coupling is provided with weight, wherein, weighted value is directly proportional with relevance level;
9) numerical value according to the parameters among weighted value and the corresponding available supplier calculates, and result of calculation is sorted, and selects the high person of result of calculation as choosing supplier;
10) demand information is passed to corresponding safe key choose supplier, and record should transmission information simultaneously, and should transmission information pass to server and put on record with contact details and safe key accordingly.
2. supplier as claimed in claim 1 cluster analysis management and client's distribution method is characterized in that, said first kind of selected conclusion attribute comprises the combination of supplier's scale merit, hazard rate, field deflection index and supply of goods index.
3. according to claim 1 or claim 2 supplier's cluster analysis management and client's distribution method; It is characterized in that said second kind of selected conclusion attribute comprises arrival promptness rate index, service positive rating index, geographical area information, logistics speed information and technological R&D strength index.
4. supplier as claimed in claim 1 cluster analysis management and client's distribution method is characterized in that, said predetermined lower threshold value be in the grade point in all provider-class minimum 10% as node, the numerical value of being got.
5. supplier as claimed in claim 1 cluster analysis management and client's distribution method is characterized in that, the relevance level of a certain parameter is directly proportional with quantity with related other parameter of this parameter generating.
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| CN2011104458922A CN102542520A (en) | 2011-12-27 | 2011-12-27 | Supplier cluster analysis management and customer allocation method |
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Cited By (5)
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| CN104574127A (en) * | 2013-10-21 | 2015-04-29 | 北京中海纪元数字技术发展股份有限公司 | Innovative marketing platform |
| CN105808921A (en) * | 2016-02-29 | 2016-07-27 | 四川长虹电器股份有限公司 | Supplier supply timeliness ratio data processing method |
| CN107122425A (en) * | 2017-04-07 | 2017-09-01 | 广东精点数据科技股份有限公司 | The method and system evaluated corporate client |
| CN109214772A (en) * | 2018-08-07 | 2019-01-15 | 平安科技（深圳）有限公司 | Item recommendation method, device, computer equipment and storage medium |
| CN112288375A (en) * | 2020-11-19 | 2021-01-29 | 南京岁卞智能设备有限公司 | Big data-based intelligent supply chain coordination management system |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104574127A (en) * | 2013-10-21 | 2015-04-29 | 北京中海纪元数字技术发展股份有限公司 | Innovative marketing platform |
| CN104574127B (en) * | 2013-10-21 | 2018-07-06 | 北京中海纪元数字技术发展股份有限公司 | innovative marketing platform |
| CN105808921A (en) * | 2016-02-29 | 2016-07-27 | 四川长虹电器股份有限公司 | Supplier supply timeliness ratio data processing method |
| CN105808921B (en) * | 2016-02-29 | 2018-03-02 | 四川长虹电器股份有限公司 | The data processing method of supplier's supply of material promptness rate |
| CN107122425A (en) * | 2017-04-07 | 2017-09-01 | 广东精点数据科技股份有限公司 | The method and system evaluated corporate client |
| CN109214772A (en) * | 2018-08-07 | 2019-01-15 | 平安科技（深圳）有限公司 | Item recommendation method, device, computer equipment and storage medium |
| WO2020029400A1 (en) * | 2018-08-07 | 2020-02-13 | 平安科技（深圳）有限公司 | Project recommendation method and apparatus, and computer device and storage medium |
| CN109214772B (en) * | 2018-08-07 | 2024-01-16 | 平安科技（深圳）有限公司 | Project recommendation method, device, computer equipment and storage medium |
| CN112288375A (en) * | 2020-11-19 | 2021-01-29 | 南京岁卞智能设备有限公司 | Big data-based intelligent supply chain coordination management system |
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Application publication date: 20120704 |