MXPA97010161A - System and method for driving available to prom - Google Patents

Abstract

A computer program system is provided to manage available for promise and make promises to satisfy customer orders. The computer program system includes a supply chain model representing a supply chain. The supply chain model includes site models that represent sites that have capacity and that manage the flow of material. The supply chain model also includes vendor models that represent vendor and that handle projections and buy. The commitments between the sites are modeled by the requests and promises, and sellers can piner periciones on behalf of the sites in anticipation of the future orders of the sites.

Description

SYSTEM AND METHOD FOR DRIVING AVAILABLE TO PROMISE TECHNICAL FIELD OF THE INVENTION This invention relates in general to the fields of demand management, supply chain management, and handling capacity. More particularly, the present invention relates to a system and method for managing available-to-promise (ATP) and making promises to satisfy customer demands.

BACKGROUND OF THE INVENTION Manufacturers produce products to be sold to customers. In the sales process, customers place orders with manufacturers. A customer order can consist of a request regarding a particular quantity of a product on a specific date. This date and quantity information may be collectively referred to as the "customer order" or the "requested information".

Manufacturing and distribution facilities have limited resources (capacity) and limited inventories (materials). Therefore, each customer order may not be satisfied in the sense that some may not receive a promise, and others may receive an inadequate one. The planning and management of which customer orders to promise and satisfy, is called "demand management" and is a fundamental and critical activity of most manufacturing and distribution organizations.

Due to material, capacity and other limitations, a manufacturer may not be able to satisfy a particular customer order. In this situation, the manufacturer typically negotiates with the customer to deliver a quantity of product on one or more acceptable dates to the customer. This date and quantity information may be referred to as the "manufacturer's promise" or "the promise information". Based on the manufacturer's promise, the manufacturer creates operational plans to implement the promise information. Manufacturers can use a combination of diverse program tools in negotiation and planning processes.

Traditional methods for demand management have several problems. First, such methods and systems are not integrated. Several different tools may be required to implement the full demand management strategy. Second, such systems and methods are not dynamic. Once a plan is in place, it is difficult for the manufacturer to react to change the circumstances and update the plan. Third, the promise of order to customers is often made based on an unfeasible plan. Subsequent attempts to find a feasible plan that satisfies the promises are often useless.

The current environment requires more and more answers. Customers require a significant diversity of products and want promises made to their requests or orders immediately, even by phone. The traditional way of promising in configuration environments to order or manufacturing to order involves submitting the order to the planners, and then, a few days after or weeks after the planners have gone through a planning cycle. They receive a promise or rejection.

Many manufacturing and distribution organizations have several sales offices associated with each manufacturing facility. Each sales office independently promises to supply the products from the factory to the customers. This is mentioned as a "distributed organization". Each vendor in each of the sales organizations needs to be able to make instant promises, simultaneously with other vendors who are doing the same. In addition, each of these promises requires that it be possible to comply with a feasible plan.

To better understand the customer's demand, the manufacturer must build products and / or intermediate items before receiving the orders from the customer. This production is based on projections called "projected orders". A product produced based on projected orders is referred to as "available to promise" or "ATP". The ATP consists of quantities of products with associated dates that the products are scheduled to be available for delivery to the customer.

In distributed organizations a sales office may require approval from the factory before an ATP can be promised to satisfy a customer order. This approval process can take up to a week under current practices. This delay is unacceptable in the current business environment.

SYNTHESIS OF THE INVENTION In accordance with the present invention, a system and method for handling ATP is provided that eliminates or substantially reduces the disadvantages and problems associated with previously developed systems and methods.

More particularly, one embodiment of the present invention provides a method for managing ATP in a distributed organization. The distributed organization comprises at least one supply facility such as a factory.

Additionally, the distributed organization comprises a plurality of ordering facilities for each supply facility. The ordering facilities may include, for example, the sales offices. Ordering facilities and supply facilities can be coupled through a computer network.

In this mode, the ordering facilities each store projected orders in a memory of a computer in the order installation. The projected orders include the order information. As previously defined, the order information includes the quantity (or range of quantities) of a product ordered by the supply facility and the date (or range of dates) on which it is required. A master program computer program system can be used to selectively plan the use of, for example, the manufacturing capability of the supply facility to fill the projected orders selected based on predetermined criteria. If a feasible and desirable plan can be designed to satisfy the request, then the provider can make a promise to the customer that the supplier will satisfy the request. Promises to fill selected projected orders can be transmitted directly to clients in a computer network.

In environments where customers do not agree to wait for a plan to be developed to obtain a promise, the supply facility must create promises in advance that are available for immediate transfer to a customer. In this modality, future orders can be projected and a plan can be made to satisfy and promise those projected requests. When a real customer order is received they can instantly reallocate one or more (or a part) of the promises made to the projected orders for the customer's order.

A technical advantage of the present invention includes the ability in a distributed organization with distributed vendors to allocate some of the promises made to projected orders to certain vendors, thus preventing them from simultaneously using the same promises projected as a promise to a customer, without require them to verify with each other before making promises. In this environment, each sales organization or sales person can be modeled and each promise / projected order can be assigned to one of these sales entities.

Another technical advantage of the present invention is that the allocation of promises can also be done for business management reasons. For example, a sales organization can be assigned promises based on how much they agree to commit to sell. This modality allows each sales entity to create its own projection of what it will sell and establish the level that it agrees to commit to sell. Projected orders are generated from the committed levels. Promises made to those requests are assigned to the sales entity to be used to form promises to the customer's orders.

A further technical advantage of the present invention is that it allows these sales entities to organize into hierarchies (e.g., a salesperson within a sales office within a marketing organization). Promises that are assigned to a sales organization can be used by salespeople within that organization. Coordination is required in such cases to ensure that two sellers do not consume the same promises. But where such coordination is possible, it is typically desirable to have some assignments that are common among them.

Another technical advantage of the present invention is that the customer orders that can not currently be promised are queued. When conditions change, queued orders have the first opportunity to be promised. Without such a queuing mechanism, orders that can not be promised are forgotten. When new capacity is released, the next customer placing an order gets that new capacity released.

A further technical advantage of the present invention is that the complete distributed organization of the providers and of the clients can be modeled together with the requests and promises placed between them. In this way, planners can see, manage, and plan the activity of a complete network where the interconnections between the elements must be formal (separate societies).

Another technical advantage of the present invention is that each sales entity can define the "products" it sells, where a product is an article whose price is based on the article, the quantity, the order time (time since acceptance). of the order to the requested date), and the client. For each product, an independent projection and commitment can be made, independent projected requests can be issued, and independent promises can be received. In this way, promises can be assigned for requests with particular characteristics. For example, a product can sell an item for $ 5 if the front order time is greater than six weeks. Another product can sell the same item for $ 10 if the time is as short as one week. Therefore, a customer request with a lead time of the order of six weeks can be received when all assignments for that product have been consumed. However, if all assignments for the lead time product of the order of a week have not been consumed, then the customer can be given a choice: the next available pledge for the lead time product of the order of six weeks will be of two weeks later than your due date, or alternatively you can choose to pay $ 10 for the lead time product of the order of a week and receive it on time. Such product management can avoid future higher profits that are sold at lower profits because these are promises served based on the first is the first.

An additional technical advantage of the present invention is that the projected requests can specify when they expire. Some may change over time if they are not consumed; others may expire and disappear if they are not consumed. Such self-support of projected requests can be very valuable in maintaining accurate projections and assignments for hundreds or thousands of products.

BRIEF DESCRIPTION OF THE DRAWINGS A more complete understanding of the present invention and the advantages thereof can be obtained with reference to the following description taken in conjunction with the accompanying drawings in which the like reference numbers indicate like characteristics, and wherein: Figure 1 is a block diagram of a mode of a supply chain model, including site models and vendor models, and prompts and promises between them.

Figure 2 illustrates a mode of a projection entry for one of several projection periods for one of the various products within a vendor; Figure 3 illustrates a mode of a time horizon with projected requests and current requests showing the time horizon moving as time passes and projected requests adjusting in response; Y Figure 4 illustrates a modality of a vendor model hierarchy and a product group hierarchy within a vendor.

DETAILED DESCRIPTION OF THE INVENTION Models of Supply Chain, Site and Seller Figure 1 is a block diagram of a mode of a supply chain model, including site models and seller models, and requests and promises between them. Figure 1 provides an exemplary supply chain according to the teachings of the present invention. The supply chain model of Figure 1 comprises 12 site models 12, 14, 16, 18, 20, 22, 24, 30, 32, 34, 36, and 38. These site models represent organizational units that may have the ability and materials to produce or consume items. Each site can place requests for articles on other sites. The requests are generally indicated in Figure 1 by triangles 52, 62, 72, and 74. For each request 52, 62, 72 and 74, the site 12, 14, 16, 18, 20, 22, 24, 30 , 32, 34, 36, and 38 being asked can make a promise to fill (totally or partially) that request. The promises are generally indicated by inverted triangles 54, 64 and 76.

Other primary members of a supply chain model are vendor models. The model of a supply chain of Figure 1 consists of a single vendor model 50. The vendor model 50 is partially shown in Figure 2 and consists of a list of products 110 that vendor 50 offers for sale. A product model 110 defines the supplier's site, the article on that site, a minimum order priority time, a minimum quantity, and the assigned customer sites. If a customer request meets these criteria for a product, then that request is eligible to be filled by that product, at the price specified by that product.

Figure 2 illustrates one mode of a projection entry for one of several projection periods for one of several products within a vendor. For each product 110, a projection horizon 112 is set. The projection horizon 112 can be arbitrarily broken. In this modality, three periods of a week (the first being 114) are followed by three periods of 1 month. For each projection period for each product, a projection input 116 is generated. The "projected" and "promised" values can be filled. The "projected" value is the vendor's estimate of how much can be sold for that product during that period. The value "committed" is the amount that the seller agrees to commit to sell.

The amount committed results in requests "projected" that are generated in an amount equal to the amount committed, spread over the corresponding projected period according to a projection policy specified by product 110. In the modality of figure 2, the amount committed results in generation of petitions 120 and 124, spaced in period 114. The site upon which petitions 120 and 124 were placed (specified by product 110) can then issue promises. Assuming promises 122 and 126 are made for requests 120 and 124, respectively, the value of "assigned" in projection input 116 for period 114 will be the total sum of the promised quantities.

The amount allocated is the presumed amount that the seller has available to promise the customer's requests. When the customer's order 128 reaches the vendor for the product 110 during the period 114, the vendor can take one or both promises (or part of one or both) that he has already received, break them or combine them to form a promise for the order of the client. Projected orders are simultaneously accepted down by the amount of the customer's order. Thus, for example, if the committed value of the projected entry 116 was 500 units, the two projected orders 120 and 124 were for 250 units each, the two promises 122 and 126 were received for 200 units, and the order of customer 128 was 300 units, then the two projected orders 120 and 124 will be adjusted to a total of 200 (for example 200 and 0 or 100 and 100 or some other combination, depending on the product's projection policy). The two promises 122 and 126 will be adjusted to a total of 100 and a new promise 130 will be created for 300 units to satisfy the order 128. The "committed" and "assigned" values of the projection input 116 do not change as a result, but the "ordered" and "promised" values do. When "promised" is equal to "assigned", then there are no more promises available to promise the customer's orders.

This process is also shown in the supply chain model of the example of Figure 1. In Figure 1, vendor 50 generates a projected order 52 on site 22 for delivery to site 30 (which does not need to be a physical site). ). The order 52 results in the site 22 generating operation 56 to carry out the activity involved in the delivery of the items ordered at site 30. If operation 56 is possible to be carried out, then site 22 may choose to create the promise 54 for the seller 50 that the item can be delivered as ordered for the order 52.

The site 34 then places the order 62 through the seller 50 for the same product as the order 52. If the customer's order 62 is consistent with what the seller 50 was projecting, then the seller 50 can reduce the order 52, the promise 54 and operation 56 for the order quantity 62, and then add the promise 64 and the operation 66 to satisfy the order 62. This simple action does not require re-planning through the site 22. Indeed, the ability of the site 22 to satisfy Order 62 has been pre-computed in the form of promise 54. Therefore, that promise 54 can be divided in order to form the promise 64.

A primary intimation is that the load and times of operation 56 may be valid when it is divided into operation 66. For example, if operation 56 involves using a truck to transport the items, then dividing operation 66 may result in which an additional truck is being used. If none is available, then operation 66 may have to wait. To compensate for this, each product defines criteria for dividing promises, which may include an amount of time with which to quilt the aforementioned due dates.

Of the site models that constitute a supply chain model (as in Figure 1), some of the sites may be under the control of that supply chain model, while others may be modeling sites which are planned independently. A field of the site model called "managed" indicates which sites are managed by this supply chain model and which are not.

Two sites that are both managed do not require making formal promises one from another - the request will generate an operation and all changes to the requests are immediately passed through the operation to the other site. Requests between a managed site and an unmanaged site require formal promises. Promises must be made explicitly, and once accepted, constitute a rigid agreement between two sites.

Changing that agreement requires the agreement of the two sites.

Adjust when the time passes Projections are frequently, by their nature, incorrect. Therefore, as time passes and when the client's requests arrive more quickly or more slowly than expected, it is desirable to modify the projections as appropriate. Given the large number of products and the numerous projection periods, automated adjustment is highly desirable.

Therefore, the product projection policy can specify how the projected and promised quantities should be adjusted over time and whether or not actual requests or orders are received.

Figure 3 illustrates a mode of a time horizon with projection requests and real requests showing the time horizon moving as time passes and projected orders adjusting in response. Timeline 200 represents the initial state. The projected orders 202, 204, 206 and 208 have been made in those respective projection periods. The sales orders are indicated with triangles as shown. The two customer requests 222 correspond to the projected request 202. The three customer orders 224 correspond to the projected request 204.

Time passes and no more orders are received. Timeline 210 represents the last state. The time has advanced beyond the projected period of the projected request 202. The requests or customer order 222 received during that period were less than the projected request. One option is to assume that the projection was very high and simply expire the remaining projection. Another option is to assume that the projected amount is correct, but that the time is out - that the total amount will be requested soon. In the latter case, the projected order must move forward in time and be reduced in quantity. This is shown as projected order 212. There are many other options for how to expire, reduce or increase projected orders based on the arrival rate of customer orders that can be encoded in the product projection policy.

Assignment to Sellers Figure 4 illustrates a modality of a vendor model hierarchy and a product group hierarchy within a vendor. Figure 4 shows two vendor hierarchies. The seller 410 represents a division of Commercialization of Industrial Products and the seller 420 represents a commercialization division of products to the consumer. Within the industrial products 410 there are three sales offices, each one managing a region: the North is managed by the vendor 412; the South is handled by vendor 414; the West is handled by vendor 416. Each sales office is made up of numerous vendors, each of whom is represented by a vendor (for example, Joe is vendor 418 and Sally is vendor 419).

In many organizations sellers can own their own allowances against which they can promise their customers without consulting the company. However, sellers do not require owning any assignments. For example, Joe 418 and Sally 419, along with other sellers in the South 414 sales office, can each project what they are trying to sell. These projections are added to the sales office salesperson 414 when they are used as a ticket. Seller 414 can project independently for the entire sales office. Therefore, in turn, it is assigned to division 410 of Industrial Products.

Clearly, projected orders should not be generated for projections at all three levels - which would result in tripling the appropriate orders.

Instead, each vendor can independently commit to selling part or all of the production.

Through commitment, projected orders are created in order to obtain promises that can be used to promise their clients. Those promises are preferred by (or controlled by) the seller who is committed to selling that amount.

However, it may be that some sellers do not commit at all. For example, none of the vendors, including Joe 418 and Sally 419 commit to anything planned. Instead, the South Sales Office 414 is committed as a whole. This results in assignments to the South 414 seller. These assignments can be used by any of the sub-sellers such as Joe 418 and Sally 419. However, such collective use of the assignments requires coordination. They must reserve the amount they require before they can actually promise it since other sellers may consider using the same allowances.

A seller is committed to anything to which his sub-sellers commit. However, the seller can commit to something additional beyond what their sub-sellers undertook. For example, each sales person can make a conservative commitment. The sales office will know that some of the vendors will most likely sell on their commitment, but it is not clear who these vendors are. In this way the Sales Office can commit to sell additional and those additional assignments will be available to the first sales person that exceeds their personal allocation.

Product Groups Projections tend to be more accurate in aggregate. A monthly projection will generally be more accurate than a weekly projection. A screening for North America will generally be more accurate than a screening for Texas. Similarly, a projection for milk will generally be more accurate than for skim milk in pint containers.

Therefore, it is important to be able to add projections, modify aggregate projections, and propagate changes back to individual products. The product group model supports this functionality.

Product groups form hierarchies. A product group can have at most one parent product group, and therefore it can be at most a product group hierarchy.

Products, on the other hand, can appear in numerous product groups; however, only in a product group of any hierarchy. A group of products defines a consistent hierarchy for aggregation. However, sellers will need to add the products in many different ways. For example, milk products can be added by their container size (gallon, half gallon, quarter, pint), by their fat content (full, 2%, 1%, skim) by the customer grouping ( store, restaurant, convenience store) or by brand (ECONO-COW, PUREWHITE).

The product groups are shown in Figure 4. The products 450, 452, 454, 456 are grouped into two product group hierarchies, based on product groups 430 and 440. Product group 430 is divided into product groups 432, 434 and 436.

Available for Advanced Promise (ATP) Each vendor has assigned (promises) available for the various products sold. When a customer order arrives at a seller, there may be numerous products that match that order. If the lowest cost product can completely satisfy the order (it has enough by the requested due date), then the request can simply be pledged. Otherwise, a decision may be required. For example, the customer may be able to choose to have a low price for a week later than the one requested, or for the requested date but at a 10% higher price. It may be that half of the order can be completed on time at a lower price, but the other half can be either delivered later or at a higher price, and so on. Therefore, the ATP can be a list of different products (prices) with different order priority times, minimum quantities, availability dates and availability quantities.

Extendable Product Model The product model type has a projection policy extension selector that allows additional fields and semantics to be added to a product model. The extension selectors are described in greater detail in the patent application of the United States of America series No. 08 / 491,153 filed on June 16, 1995 and entitled "System of Representation of Network of Extended Model for Process Planning", (Attorney's Case No. 020431.0136), the description of which has been incorporated herein by reference.

In this manner, additional projection information such as projection error or projected variation in any amount or time or both can be included and used. Additional fields for the expected course during the month can affect how the committed amount is divided into projected orders. The expected variation or order arrival rates can affect how projected orders expire or adjust over time, based on the sales orders that have been received.

Although the present invention has been described in detail, it should be understood that various changes, substitutions and alterations may be made without departing from the spirit and scope of the invention as defined by the appended claims.

Claims (10)

R E I V I ND I C A C I O N S

1. A computer program system to manage available to promise and make promises to fill customer orders, the program system comprises: at least one vendor model representing a vendor that is selling at least one product, the vendor model operable to project for at least one product and operable to choose commitment levels by creating projected orders; projected orders receive promises made by provider sites; Y the promises available to the selling entity to promise the actual customer orders.

2. The computer program system, as claimed in clause 1, characterized in that at least one vendor model can compromise a hierarchy so that assignments to a vendor can be used by the vendor or any sub-vendors and such that the commitments made by a seller also commit to the related sellers.

3. The computer program system, as claimed in clause 1, characterized in that the computer program system is located at and is executed by a digital computer, the digital computer comprising: a data storage device; an operable execution memory for containing the computer program system; Y a processor coupled to the data storage device and execution memory, the processor is operable to run the computer program system.

4. A computer program system to manage available for promise and make promises to fulfill customer orders, the computer program system comprises: A supply chain model that represents a supply chain, the supply chain model comprises: site models that represent sites that have capacity and that handle material flow; and seller models that represent sellers and that handle projections and purchases; where the commitments between sites are modeled by orders and promises; Y where sellers can place orders on behalf of sites in anticipation of future orders of the sites.

5. The computer program system, as claimed in clause 4, characterized comprises a queue that allows rejected orders to be queued for consideration when the capacity is released.

6. The computer program system, as claimed in clause 4, characterized in that the computer program system is located at and is executed by a digital computer, the digital computer comprising: a data storage device; an operable execution memory for containing the computer program system; and a processor coupled to the data storage device and execution memory, the processor is operable to run the computer program system.

7. A computer program system to manage available for promise and make promises to fulfill customer orders, the computer program system comprises: a product model representing a product, the product model specifies a supplier site, an article produced by that site, a minimum quantity, a minimum order priority time, a list of customers assigned for purchase, and a price for the product product; where a customer order having the desired characteristics matching the product can be filled by a promise of the product; so that a list of all available products and associated promises that are matched can be displayed as available to be promised for the order.

8. The computer program system, as claimed in clause 7, characterized in that the product model specifies a different projection information allowing an extension to be recorded and used to compute and distribute projected orders.

9. The computer program system, as claimed in clause 8, characterized in that the product model specifies expiration semantics and adjustment for projections over time and upon arrival of actual customer orders faster or slower than expected.

10. The computer program system, as claimed in clause 7, characterized in that the computer program system is located at and is executed by a digital computer, the digital computer comprising: a data storage device; an operable execution memory for containing the computer program system; Y a processor coupled to the data storage device and execution memory, the processor is operable to run the computer program system. SUMMARY A computer program system is provided to manage available for promise and make promises to meet customer orders. The computer program system includes a supply chain model representing a supply chain. The supply chain model includes site models that represent sites that have capacity and that manage the flow of material. The supply chain model also includes vendor models that represent sellers and that handle projections and purchases. The commitments between the sites are modeled by requests and promises, and sellers can place requests on behalf of the sites in anticipation of future orders from the sites.