Supplier performance reporting
A system and method is provided for improved reporting of supplier performance. A system receives and processes data to enable reporting of on-time performance relative to a plurality of order start points and a plurality of order end points. Buyers and suppliers report on-time performance for system processing using the delivery start points and end points collected in the normal course of their business operations. System users may obtain supplier on-time performance reports indicating the on-time performance of suppliers relative to the plurality of start point/end point pairs reflected in the collected data. A system and method is also provided for improved reporting of reject performance. A system stores collected information predictive of whether an order reject was supplier caused or buyer caused. The predicted cause of order rejects is reflected in supplier reject performance as reported to system users.
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This invention relates to a system and method for reporting supplier on-time performance and a system and method for reporting supplier reject performance.
Supplier on-time performance is typically reported as a percentage of orders that are delivered within a specified period of time with respect to a standardized start point and end point. In order to measure the amount of time that a supplier takes to deliver product in response to an order, a “start point,” i.e. an event triggering the start of a time period used to measure delivery time, must be identified. An “end point,” i.e., an event triggering the end of the time period used to measure delivery time, must also be identified. Typically, the possible start points used for measuring delivery time include: the time at which the buyer placed the order (“order sent” or “OS”), the time at which the supplier received the order (“order received” or “OR”), and the time at which the supplier confirmed the order with the buyer (“order confirmed” or “OC”). Possible end points that might be used for measuring delivery time are, for example, the arrival time of the supplier shipment at one of the following: the customer's receiving dock (“CRD”) (note, the terms “customer” and “buyer” are used interchangeably herein); the customer's final destination (“CFD”, e.g. customer storeroom, customer assembly line, customer mail stop); the origin transport on board (“OTO”, i.e., loaded onto the shipping vehicle at the origin); destination transport onboard (“DTO”, i.e. when the shipping vehicle arrives at its destination country); destination customs inbound (“DCI”, i.e. arrival at customs in the destination country prior to customs processing); destination customs outbound (“DCO”, i.e., point at which customs processing in the destination country is completed); or the supplier shipping dock (“SSD”).
Existing supplier performance reporting systems generally pick a single start point and a single end point to use as the standardized start and end points for determining the time period against which to measure whether or not a delivery is “on time.” Such systems require users to report on time performance using a standardized start and end point. This approach has at least two disadvantages. First, the customers that are providing on-time delivery data for use by such systems may not ordinarily track delivery times using the standardized start point and end point required by the system. Thus, customers may have to adjust existing internal procedures in order to report delivery time data that is useable by such systems. A second disadvantage of such systems is that customers whose businesses place an importance on delivery times using start and end points different from those used by the reporting system will not be able to gauge the performance of suppliers in a manner that is consistent with the particular business needs of such customers.
Existing supplier performance reporting systems also typically report the percentage of orders that are returned. However, existing systems simply report “reject performance” as a percentage of total orders that are returned without distinguishing between whether the return was supplier caused or customer caused. In some contexts, it may be useful for users of a supplier performance reporting system to know how many returns were caused by the supplier and how many were caused the customer.
SUMMARY OF THE INVENTIONThe present invention addresses some of the problems of prior supplier performance reporting systems. An aspect of a present embodiment receives and processes data to enable reporting of on-time performance relative to a plurality of order start point/end point pairs. Customers and suppliers report on-time performance for system processing using the delivery start and end points collected in the normal course of their business operations. System users may obtain supplier on-time performance reports indicating the on-time performance of suppliers relative to the plurality of start point/end point pairs reflected in the collected data.
Another aspect of a present embodiment collects transaction information predictive of whether an order reject was supplier caused or customer caused. The predicted cause of order rejects is reflected in supplier reject performance as reported by a system implementing this aspect of the present invention.
BRIEF DESCRIPTION OF THE DRAWINGSThe novel features of the invention are set forth in the appended claims. However, for purpose of explanation, several aspects of an embodiment of the invention are described by reference to the following figures.
In the following description, numerous details are set forth for purpose of explanation. However, one of ordinary skill in the art would realize that the invention may be practiced without the use of these specific details. In other instances, well-known structures and devices are shown in block diagram form in order not to obscure the description of the invention with unnecessary detail.
System 10 is communicatively connected (either periodically or continuously) to computer systems at various subscribers including buyers and/or suppliers including systems 11a, 11b, and 11c. System 10 is also be communicatively connected to web portal 12. Web portal 12 is a computer or group of computers that makes information from system 10 available over the Internet to one or more subscribers. Although
Blocks 10-1 to 10-7 and associated arrows indicate the processing and data flow of system 10. At block 10-1, data is received relevant to either basic purchase order data or summarized purchase order data (see
A subscriber may transmit requests to system 10 through web-portal 12. Requests are received at block 10-7. At block 10-5, a response to the user request is generated. This generation of a response involves requesting and retrieving information from data storage block 10-3 as indicated by the arrows between blocks 10-5 and 10-3, and involves performing the processing necessary to generate a suitable data view for display. At block 10-6, the response is returned to the used through web-portal 12.
In step 3-3, sub-subsets of Basic Data 20 records are identified from the subsets identified in step 3-2. In other words, in step 3-3 subsets are identified within each subset identified in step 3-2. The sub-subsets of step 3-3 each share the same purchase order number. Note that Basic Data 20 can have multiple records for a single purchase order (e.g. records 1 and 2 in Basic Data 20).
In step 3-5, the “# of POs” field in Summary Data 25 is populated by, for each subset identified in step 3-2, adding up the number sub-subsets identified in step 3-3, and putting the total in the record of Summary Data 25 that corresponds to the step 3-2 subset of Basic Data 20 whose step 3-3 sub-subsets were totaled. For example, Records 20R-1, 20R-2, and 20R-3 of Basic Data 20 is a subset identified in step 3-2 and thus corresponds to a record in Summary Data 25 (record 25R-1). That subset in turn has two subsets (or “sub-subsets”): (20R1, 20R2 corresponding to one purchase order number) and (20R-3 corresponding to another purchase order number). Therefore, the # of POs in record 25R-1 is 2. Of course, this step could also be phrased in terms of identifying the number of unique purchase order numbers in each subset of records identified in step 3-2.
In step 3-6, the “# of line items” field in Summary Data 25 is populated by adding up the number of line unique line items in each corresponding subset identified in step 3-2. Note that since Basic Data 20 has one record for each line item number, the results of step 3-6 in this instance will simply be the number of records in each subset identified in step 3-2 (note the number “2” in the “Line Item Number” field of record 20R-2 of Basic Data 20 is an identification number, not a number of line items in that record; each record in Basic Data 20 contains a single line item). In step 3-7, the “Orders On Time” field in Summary Data 25 is populated by adding up the total number of sub-subsets identified in step 3-3 for which every record in the sub-subset has a “Received Date” value that is earlier that its “Due Date” value. In other words, an order is defined as on time if every line item in the order was delivered on time. In step 3-8, the “Line Items On Time” field in Summary Data 25 is populated by, for each corresponding step 3-2 subset, summing together all the records in which the. “Received Date” is equal to or earlier than the “Due Date.”
Those skilled in the art will recognize that process 30 represents just one example of a series of steps that might be used to convert Basic Data 20 to Summary Data 25. Also, those skilled in the art will recognized that first executable code used to carry out a first step in process 30 might be the same code as second executable code used to carry out a second step in process 30. For example, a single piece of executable code might direct a computer to, for each record in Summary Data 25, store in the “# of POs” field 25F-5, the value obtained by counting the records in Basic Data 20 that have the same the same supplier name, start point, end point, and buyer name as the corresponding Summary Data 25 record and that also have identical purchase order numbers. Such a piece of code would be performing step 3-5 of process 30, but would also implicitly be performing step 3-3 and 3-2. Thus, such a piece of code could be said to be first code for performing step 3-2, second code for performing step 3-3, and third code for performing step 3-5. Those skilled in the art will recognize therefore that executable code may be organized in a variety of ways without departing from the spirit and scope of the present invention.
Furthermore, while process 30 works to convert Basic Data 20 into Summary Data 25, customer/buyers and suppliers might have basic purchase order data that is organized differently from the example of Basic Data 20. In such instances, those skilled in the art will recognize that executable code may, without undue experimentation, be written that will implement processes different that process 30 in order to convert basic data that is organized differently than Basic Data 20 into summary data similar to Summary Data 25.
It may also be noted that because the “Order Status” values in field 20F-10 of Basic Data 20 are “Closed” for each record, other data (e.g. received date) is available for each record. However, process 30 can be easily modified to handle the addition of data that includes some records that are incomplete because the “Order Status” value is “Open”. As one example, process 30 might be modified to operate only on records whose status is “Closed.” As one other example, process 30 might be modified to leave blank place holders in Summary Data 25 for records that cannot currently be completed (e.g., if all of the records in a subset identified in step 3-2 are “open”, a place holder such as “—” might be inserted into Summary Data 25 fields that cannot be properly completed for the corresponding record in Summary Data 25, and then those records may be ignored or at least partially ignored when creating reports from Summary Data 25). In this manner, basic purchase order data such as Basic Data 25 may be processed without having to first remove records for unclosed orders.
Display table 40b reports on time performance for orders placed with supplier S1 by customer/buyer C1. Table 40b displays data for on time performance with respect to a plurality of start point/end point pairs. Table 40b includes records 40bR-1, 40bR-2, 40bR-3, and 40bR-4, corresponding to, respectively, the following indicated start point/end point pairs in field 40bF-1. In addition to start point/end point field 40bR-1, table 40b also includes field 40bF-2 (“No. of orders”), field 40bF-3 (“% on time”), field 40bF-4 (“No. of line items”), and field 40bF-5 (“% on time”).
Those skilled in the art will recognize that process 50 represents just one example of a series of steps that might be used to convert Summary Data 51 into Supplier Report 52. Also, those skilled in the art will recognized that first executable code used to carry out a first step in process 50, might be the same code as second executable code used to carry out a second step in process 50.
Although process 50 shows steps for creating display data from summary data with respect to a particular supplier across all customer orders (i.e. display data analogous to table 40a of
Although the examples disclosed in
Beginning at the top of the flow diagram, if the item was not returned, the result of block 71 is “no.” If the item was not returned, but payment was less than the invoice, the system indicates that the order has, in a sense, been “rejected” in that the customer refused to pay the full amount. In such a case, the result of block 71a is “yes” and, as reflected by the arrow from block 71a to block 78, the system predicts and reports this rejection as supplier caused. If the payment was not less than the invoice and the item was not returned, than the result of block 71 a is “no” and the system reports the order as not rejected as indicated by the arrow from block 71a to block 71b.
If the order was returned, then the result of block 71 is “yes” as reflected by the arrow from block 71 to block 72. If the order was cancelled, the result of block 72 is “yes” and the reject is predicted and reported to be customer caused as indicated by the yes arrow from block 72 to block 77. If the answer is no, then, as illustrated by the arrow from block 72 to block 73, the system next considers whether or not the same item that was ordered was reshipped after the return. If the item was reshipped, then the result of block 73 is “yes” and the reject is predicted and reported to be supplier caused as indicated by the arrow from block 73 to block 78. If the result of block 73 is “no”, then, as illustrated by the arrow from block 73 to block 74, the system next considers whether or not the delivery was late. If the delivery was late, the result of block 74 is “yes” and, as indicated by the arrow from block 74 to block 78, the reject is predicted and reported to be supplier caused. If the result of block 74 is “no”, then, as illustrated by the arrow from block 74 to block 75, the system next considers whether or not there was a purchase order (“PO”)/invoice mismatch. If there was a PO/Invoice mismatch, then the result of block 75 is “yes” and, as indicated by the arrow from block 75 to block 78, the reject is predicted and reported as supplier caused. If the result of block 75 is “no”, then; as illustrated by the arrow from block 75 to block 76, the system next considers whether or not an item shipped was defective. If an item shipped was defective, then the result of block 76 is “yes” and, as indicated by the arrow from block 76 to block 78, and the return is predicted and reported as supplier caused. If, however, the item shipped was not defective, then the result of block 76 is “no” and, as indicated by the arrow from block 76 to block 77, the return is predicted and reported as customer caused.
The order of blocks 72-76 may be varied. Note that if, for example, block 76 were not the last block, its “No” arrow would simply point to the next block rather than to block 77. If information is not available from either the supplier or customer to make a determination for one or more of the blocks 72-76, a “No” answer is delivered for those blocks with insufficient information and the remaining blocks are used to make a reject determination.
Executable code may instruct one or more computers to perform the processing steps illustrated in
Although particular embodiments have been described in detail, various modifications to the embodiments described herein may be made without departing from the spirit and scope of the present invention, thus, the invention is limited only by the appended claims.
Claims
1. In a system for reporting supplier performance, the system including reporting of order rejections, a method of reporting a reason for order rejections comprising:
- collecting from a first customer predictive data elements about at least one of a plurality of orders made by the first customer to a first supplier, the predictive data elements being predictive of whether a rejection of items in the at least one of the plurality of orders was customer caused or supplier caused;
- making a prediction based on the predictive data elements about whether the rejection of items in the at least one of the plurality of orders was customer caused or supplier caused; and
- reporting the rejection as either supplier caused or customer caused based on the prediction.
2. The method of claim 1 wherein a one of the predictive data elements is whether or not the at least one of the plurality of orders was cancelled and wherein if the at least, one of the plurality of orders was cancelled, then the prediction indicates that the rejection was customer caused.
3. The method of claim 1 wherein a one of the predictive data elements is whether or not an item in the at least one of the plurality of orders was re-shipped and wherein if the item was re-shipped then the prediction indicates that the rejection was supplier caused.
4. The method of claim 1 wherein a one of the predictive data elements is whether or not items in the at least one of the plurality of orders were delivered late and wherein if the items in the at least one of the plurality of orders were delivered late, then the prediction is that the rejection was supplier caused.
5. The method of claim 1 wherein a one of the predictive data elements is whether or not a PO/Invoice mismatch exists with respect to the at least one of the plurality of orders and wherein if a PO/Invoice mismatch exists, then the prediction is that the rejection was supplier caused.
6. The method of claim 1 wherein a one of the predictive data elements is whether or not a payment was less than an invoice amount with respect to the at least one of the plurality of orders and wherein if a payment was less than an invoice amount, then the prediction is that the rejection was supplier caused.
7. The method of claim 1 wherein a one of the predictive data elements is whether or not an item in a one of the plurality of orders was defective, and wherein if the item was defective, then the prediction is that the rejection was supplier caused.
8. A system for reporting supplier performance comprising:
- at least one computer;
- first executable code for storing data collected from a first customer including predictive data elements about items in at least one of a plurality of orders made by the first customer to a first supplier, the predictive data elements being predictive of whether a rejection of items in the at least one of the plurality of orders was customer caused or supplier caused;
- second executable code for making a prediction based on the predictive data elements whether the rejection was customer caused or supplier caused; and
- third executable code for assembling a report including indication of the rejection as either supplier caused or customer caused based on the prediction;
- wherein the first, second, and third executable code is in an electronically readable medium accessible to the at least one computer.
9. The system of claim 8 wherein a one of the predictive data elements is whether or not the at least one of the plurality of orders was cancelled and wherein if the at least one of the plurality of orders was cancelled, then the prediction indicates that the rejection was customer caused.
10. The system of claim 8 wherein a one of the predictive data elements is whether or not an item in the at least one of the plurality of orders was re-shipped and wherein if the item was re-shipped, then the prediction indicates that the rejection was supplier caused.
11. The system of claim 8 wherein a one of the predictive data elements is whether or not the items in the at least one of the plurality of orders were delivered late and wherein if the items in the at leas tone of the plurality of orders were delivered late, then the prediction is that the rejection was supplier caused.
12. The system of claim 8 wherein a one of the predictive data elements is whether or not a PO/Invoice mismatch exists with respect to the at least one of the plurality of orders and wherein if a PO/Invoice mismatch exists, then the prediction is that the rejection was supplier caused.
13. The system of claim 8 wherein a one of the predictive data elements is whether or not a payment was less than an invoice amount with respect to the at least one of the plurality of orders and wherein if a payment was less than an invoice amount, then the prediction is that the rejection was supplier caused.
14. The system of claim 8 wherein a one of the predictive data elements is whether or not an item in a one of the plurality of orders was defective, and wherein if the item was defective, then the prediction is that the rejection was supplier caused.
15. A system for reporting supplier performance comprising:
- means for collecting from a first customer predictive data elements about at least one of a plurality of orders made by the first customer to a first supplier, the predictive data elements being predictive of whether a rejection of items in the at least one of the plurality of orders was customer caused or supplier caused;
- means for making a prediction based on the predictive data elements about whether the rejection of items in the at least one of the plurality of orders was customer caused or supplier caused; and
- means for reporting the rejection as either supplier caused or customer caused based on the prediction.
Type: Application
Filed: Jan 3, 2006
Publication Date: May 25, 2006
Applicant: Accenture Global Services GmbH (Schaffhausen)
Inventor: Alvin Wong (Monterey Park, CA)
Application Number: 11/322,348
International Classification: G06F 17/30 (20060101);