AU2009235996A1 - A method for controlling the flow of commodities - Google Patents

Description

AUSTRALIA Patents Act 1990 ORIGINAL COMPLETE SPECIFICATION INVENTION TITLE: A METHOD FOR CONTROLLING THE FLOW OF COMMODITIES The following statement is a full description of this invention, including the best method of performing it known to us:- -2 A METHOD FOR CONTROLLING THE FLOW OF COMMODITIES Description 5 The invention relates to a method for controlling the flow of commodities from a main branch to one or a plurality of locally removed affiliates. In practice, such methods are conventionally implemented in order to supply an 10 affiliate with selected or previously-ordered commodities in a timely manner. This usually occurs through a previous telephonic or other form of order to the main branch on the part of the affiliate. That largely continues to be the case. In addition, document DE 202 07 903 UI, for example, discloses a system for selling 15 consumer goods. In this instance, tokens are worked with that a customer, after having paid, exchanges for the desired article in a piece of distributing equipment. In this manner, an attempt is made to counteract in particular a loss of the article concerned by, for example, theft. 20 The manners of proceeding that were adhered to in the past cannot be satisfactory all around. For, inasmuch as the control of the flow of commodities of, for example, perishable goods such as fruit or vegetables is concerned, improvements are required. Indeed, such perishable goods are characterised by both a very limited shelf life of sometimes merely one day and, also, the availability of such goods is closely linked 25 to customer satisfaction. One is thus confronted with the difficulty of ensuring a high degree of service, that is to say a high degree of availability of the product or commodity concerned throughout the entirety of the day and, at the same time, minimising the depreciation costs owing to a loss of the commodities. For this reason, approaches were already undertaken in the past, so-called order-amount 30 optimisations. The previous attempts cannot, however, be satisfactory all around. The invention accordingly addresses the following technical problem of providing a method and a device for controlling the flow of commodities from a main branch to one or a plurality of locally removed affiliates, by means of which method and 35 device a higher degree of service is achieved while depreciation costs are simultaneously minimised. 10/1 I/09,va 18350 speci.doc,2 -3 In order to solve this technical problem addressed, the subject matter of the invention is a method for controlling the flow of commodities from a main branch to one or a plurality of locally removed affiliates, according to which method selected commodities are evaluated by means of a commodity registration device in the 5 affiliate concerned with regard to their commodity-specific data and are converted into a disposition recommendation in connection with affiliate-specific data. Within the context of the invention, selected commodities are thus initially investigated in one or a plurality of affiliates, namely primarily with regard to the 10 type of product and sales amount. Commodity-specific data can be generated from the sales amount or from the sales numbers which are determined by means of the commodity registration device. These commodity-specific data thus reflect at least the type of product, that is to say the specific commodity concerned, and its sales amounts for a certain time period (for example an hour, a day, a week etc.). 15 Moreover, the commodity-specific data may optionally also contain an article number and the price of the selected commodity. In such an instance, it can be the purchase price and/or the selling price. Furthermore, the point of time of the sale of the selected product or of the selected 20 commodity and/or the service life of the selected commodities may also be integrated in the commodity-specific data. These collected commodity-specific data (type of product and sales amount as well as optionally article number and/or price and/or point of time of sale and/or service life) can be stored in a goods dataset. In order to generate this commodity dataset, the commodity registration device is available, 25 which preferably is a matter of one or a plurality of cash register machines in the main branch. Should a plurality of cash register machines be used in the respective main branch, all of the commodity-specific data, which belong to the selected commodity, for the main branch concerned are centralised and stored in the previously-mentioned commodity dataset. 30 The service life of the selected commodity represents not only service-life values, but also the seasonal availability of the commodity concerned. That is to say, in so far as the selected commodity is a perishable commodity, such as fruit or vegetables, the service life indicates how long the commodity concerned can be on sale in the 35 affiliate (for example, a day or a plurality of days). The seasonal availability conveys during which season the commodity is at all available, for example only in the summer or only in the spring etc. 10/ 11/09,va 18350 speci.doc,3 -4 The commodity dataset or the commodity-specific data in the affiliate concerned are now supported by affiliate-specific data. These affiliate-specific data are, as a rule, those that are generated by means of at least one (external) sensor as well as 5 optionally by an external input and stored in an affiliate dataset. The (external) sensors and the sensors associated with the respective affiliate can, in the simpler case, be a clock or a radio controlled clock and/or a temperature sensor (outdoor temperature and/or indoor temperature) and/or a time and attendance recording device and/or a humidity sensor and/or an external input unit and/or an affiliate 10 specific weather programme unit and/or an affiliate-specific calendar programme unit. By means of the external input, affiliate-specific data from, for example, a branch office manager can be generated that are intended to take into consideration the local 15 distinctions and are intended to be introduced into the disposition recommendation. It is thus conceivable during the course of a planned advertising campaign to increase the order amount of the selected commodity. Likewise, local distinctions can hereby be represented, for example, the unusual practice of being open for business on Sundays or regional holidays as well. The particular competitive position in 20 comparison with other purveyors can likewise be given consideration. By means of the clock or respectively the radio controlled clock as an external sensor, the individual sales of selected commodities with the desired point of time of sale are supported and can also be temporally synchronised with the individual cash 25 register machines. The temperature sensor provides information about the local weather at the location of the affiliate as likewise the humidity sensor indicates the probability of rain. In this manner, the invention utilises the recognition that certain commodities and their sales amounts depend on regional weather. In this connection, by means of the external input unit, a weather forecast for the coming days can be 30 incorporated into the affiliate-specific data. At this point, it is conceivable that a weather-forecasting unit or an affiliate-specific weather-programme unit is alternatively or additionally realised as an (external) sensor by means of which the regional weather that is to be expected at the location of the affiliate is taken into consideration within the coming days and incorporated into the affiliate-specific data. 35 The current weather data can hereby also just as well be retrieved from a database. An affiliate-specific calendar programme unit functions similarly. 10/1 I1/09,va 18350 speci.doc,4 -5 In the end, a time capturing device can also be used as an (external) sensor if necessary. This time capturing device accounts for the times at which the personnel are present or absent in the affiliate, which optionally can affect or has affected the disposition recommendation. This is because depending on available personnel, the 5 sale of selected commodities can, by means of special sales promotions, be stimulated or precisely the opposite. In any case, the affiliate-specific data and an affiliate dataset derived therefrom practically reflect all factors that affect or could affect the anticipated sales amount of 10 a selected commodity at that specific point in time and in the future. In such an instance, a quasi local calendar, in particular, can also contribute to the aforementioned and can be generated for the respective affiliate, either by means of the external input unit or by referring to the calendar programme unit that, as sensor, is fed the corresponding data (from the main branch or from a different database). 15 The main branch derives the disposition recommendation, which it returns to the individual affiliates as the result of the collection of data and of the processing of the data, from this comprehensive information, that is to say from the commodity specific data with respect to the commodity dataset and the affiliate-specific data 20 with respect to the affiliate dataset. The disposition recommendation correlates both of the datasets and calculates therefrom the anticipated requirement of the selected commodity for the specific affiliate and a selected time period (for example, for a day, a plurality of days, a week). That is to say, the disposition recommendation leads to a recommended order quantity for the selected commodity taking into 25 consideration the future sale time period. That is to say, the disposition recommendation regularly occurs as a function of the day of the week and also as a function of the calendar and is furthermore affiliate specific. The invention proceeds from the realisation that, for example, amounts sold of 30 selected commodities are generally greater on weekends than at the beginning of the week. As a consequence, the disposition recommendation must take into consideration the fluctuation of the amounts sold, which is dependent on the day of the week. Likewise, also included therein are the previously mentioned variable factors such as the weather at the location of the affiliate, calendar-date related 35 special events, the number of personnel at the affiliate, and the availability and shelf life of the selected commodity (useful life). Additional data, such as the price to be 10/l l/09.va 18350 speci.doc.5 -6 expected of the selected commodity or the local competition situation as well are also taken into consideration for the disposition recommendation. In any case, the disposition recommendation, which takes into consideration all of 5 these input parameters, serves to make it possible for an affiliate manager in the affiliate concerned to the able to optimise in some manner the purchase order quantity for the selected commodity, as has heretofore been considered impossible. Such an optimisation of purchase order quantity or the disposition recommendation dependent thereupon is also of importance insofar as it is the result of a base of 10 objective data and is essentially presented independently of all individuals. In this manner, the invention takes into consideration the current comprehensive shop opening hours and furthermore takes into consideration that, on the basis of the disposition recommendation, recommended orders of the respective affiliate no longer need or must be effected by an individual. 15 The respective decision maker will be provided a reliable orientation aide that said decision maker uses and also can use for making orders. The positioned recommendation also takes into particular consideration affiliate-specific distinctions that are taken into consideration in the recommended quantity ordered for the 20 respective selected commodity. In order to achieve this in detail, the respective commodity dataset and the affiliate dataset are transmitted to the main branch and evaluated there. The main branch then deduces from the affiliate dataset and from the commodity dataset the disposition 25 recommendation for the selected commodity and transmits this disposition recommendation back to the respective specific affiliate. That is to say, a disposition recommendation is submitted that varies not only depending on the day of the week, but also and in particular from affiliate to affiliate, while furthermore taking into consideration the respective local distinctions. Moreover, the disposition 30 recommendation naturally reflects the special availability situation, the price etc. of the respectively selected commodity. What is more, as a rule, the disposition recommendation takes into consideration surplus goods of the selected commodity dependent on the time of day and/or the 35 date. This surplus of goods is integrated in the level of service and conveys altogether the availability of the selected commodity at a certain time of day. Most often, percentages are worked with here that ultimately reflect the likelihood of the 10/l 11/09,va 18350 speci.doc.6 -7 selected commodity in a pre-determined amount correlating with a certain hour during the shop opening time. That is to say, the level of service is calculated from the number of days with an availability of the selected commodity up to a specific point in time (for example, an hour prior to the shop closing time) divided by the 5 number of days on which the commodity in question is sold at all. Whatever the case may be, the product surplus takes into consideration the desire of potential customers, for example, the ability to purchase a selected commodity still shortly before the shop closing time. The invention in this instance takes into 10 consideration the fact known from practice that commodity unavailability or insufficient availability leads to customer dissatisfaction and, in the end, to a customer possibly no longer visiting the affiliate. Whatever the case may be, the disposition recommendation takes into consideration such a product surplus of the selected commodity, which is dependent upon time of day and/or the date. 15 The product surplus that is dependent upon the time of day demonstrates, for example, with a one-day commodity that this commodity, which is given a use life of merely one day, must be seen throughout the day and, during the shop opening hours, must furthermore be available in a certain predicted amount in order to reach a pre 20 determined level of service. In contrast thereto, the disposition recommendation naturally ensures at the same time that the product surplus of the selected commodity is not too large so as to ensure that a loss incurred by unsold commodities is as little as possible. This can be mapped by means of the purchase price or the retail price of the commodity concerned which is reflected in the commodity-specific data or in the 25 product dataset. Moreover, the invention suggests comparing the commodity-specific data or the product dataset of a selected commodity with the commodity-specific data or the product dataset of a different selected commodity with regard to comparable, time 30 dependent sales volumes. That is to say, both of the respective product datasets are compared with regard to their time-dependent sales volumes as well as taking into consideration a pre-determined deviation. Should the deviation not reach a pre determined value, the commodities concerned can be combined into product clusters having similar sales patterns in the main branch. 35 For example, it has been shown with fruit and vegetables, that as selected commodities, oranges and herbs or also kiwi and pineapple exhibit a comparable 10/11 /09,va 18350 speci.doc.7 -8 sales volume pattern when regarded over the course of a day. Such so-called product clusters can be defined affiliate-wide in the main branch and determine or naturally can also be determined as a function of the affiliate. 5 In any case, the possible combination of individual, selected commodities into optionally affiliate-dependent product clusters owing to their largely corresponding, time-dependent sales volumes represents a facilitation in the generation of the disposition recommendation or makes it possible on a broader basis. 10 Moreover, it is possible to combine individual days with comparable sales volumes or with similar sales patterns regarded over time. In such an instance, day clusters, for example, are formed that are in turn defined either affiliate-wide or alternatively specific to an affiliate. Thus the sales patterns in a certain affiliate may be similar on the days Tuesday (Di) and Thursday (Do) in such a manner that relatively reliable 15 predictions can be derived therefrom. In any case, the days, commodities or even entire affiliates can be combined into day clusters, product clusters, affiliate clusters etc., which altogether considerably increases the precision of the disposition recommendation and thus of a prediction. 20 As a result, by means of the data generated according to the invention or respectively by means of the basis of the product dataset and of the affiliate dataset, a specific sales volume, which is anticipated, of a selected commodity can be predicted with a relatively high degree of precision for a specific affiliate on a previously determined (calendar) weekday. The decision maker is hereby provided with a suitable decision 25 making aid in order to execute on this basis the order for the following weekday, the following two weekdays or a different time period. In so doing, this model and the data to be considered therein have been discovered to be particularly advantageous in connection with perishable goods. Since such 30 perishable goods as, for example, fruit and vegetables are associated in part with large losses when the quantity ordered does not correspond with the quantity actually sold, resulting in the loss of a large product surplus. A quantity of such goods that is too limited is just as negatively assessed because it creates a drastic decline in customer satisfaction. 35 At any rate, the invention makes possible for the first time that, by means of the data obtained, a resilient disposition recommendation can be made and can be provided as 10/11 /09,va 18350 speci.doc,8 -9 a decision-making aid. The subject matter of the invention is also a device and how it can be used in a particularly advantageous manner to control the flow of commodities and, in particular, to carry out the described method. This device is described in claim 12, wherein advantageous embodiments of the device follow in 5 claims 13 et seq. In the following, the invention is described in greater detail using one drawing representing merely one exemplary embodiment. The single figure shows a device for controlling the flow of commodities from a main branch I to a plurality of 10 affiliates 2a, 2b, 2c, and 2d that are locally removed with regard to the main branch 1. Indeed, a main branch 1, which is configured as a centre of distribution for commodities 3 or contains such a centre of distribution, is recognisable in the figure. 15 The commodities 3 in the exemplary embodiment, that is to say they are not restrictive, are strawberries, wherein a certain standardised amount of strawberries is represented by a small box of the same size. The affiliates 2a to 2c are respectively displayed as shop locations. 20 It is furthermore recognisable that the main branch I and the affiliates 2a, 2b, 2c, and 2d are connected to one another by means of data and in terms of transportation as well. The data connection can, for example, take place over single lines 4 that may be telephone lines, Internet lines etc. It goes without saying that a wireless data connection between the main branch I and the affiliates 2a, 2b, 2c, and 2d is also 25 comprised by the invention. In the context of the example, selected commodities, strawberries 3 in the exemplary embodiment, are evaluated by means of a commodity registration device 5 in the affiliate 2a to 2d concerned with regard to their product-specific data. A commodity 30 registration device 5, which is merely indicated with reference to the affiliate 2d, is a cash register machine 5, which is customarily equipped with a scanner in order to be able to read a barcode affixed to the selected commodity, the strawberries 3 in the case of this example. It goes without saying that a plurality of cash register machines 5 per affiliate 2a to 2d can be realised to define the commodity registration device 5. 35 That, however, is not shown. 10/11/09.va 18350 speci.doc.9 - 10 In looking at the other affiliates 2a to 2c, one notes sensors 6 to 13 that are external, that is to say outside the commodity registration device, respectively the cash register machine 5, yet is realised within, respectively in proximity to the affiliate 2c concerned in the example case. The sensors 6 to 13 are a clock, respectively a radio 5 controlled clock 6 that, for example, serves to temporally synchronise a plurality of cash register machines 5 within one affiliate 2a to 2d. Furthermore, a temperature sensor 8 is provided, for example, outside the affiliate 2c in the example and a temperature sensor 7 is provided inside, by means of which the local temperature at the location of the affiliate 2c can be detected. A humidity sensor 9 furthermore 10 belongs to the sensors 6 to 13, by means of which humidity sensor the relative atmospheric humidity can be detected. Moreover, an input unit 10 is comprised therein by means of which initially the data of all of the sensors 6 to 13 can be collected and, additionally, these data can be 15 provided with flanking inputs. Furthermore, a time detection device 13 as well as a weather programme unit 11 and finally a calendar programme unit 12 belong to the sensors 6 to 13. The time detection device 13 serves to detect the times at which personnel are present and absent within the affiliate 2c concerned. The weather programme unit 11 makes available weather forecasting data for a certain period of 20 time, for example one day, two days or up to one week, or reports the local weather. The calendar programme unit 12 makes it possible to represent local calendar-related distinctions that are to be taken into account such as, for example, a regional holiday, the local school vacations, the Sundays on which the shop is open for business, distinctive regional festivities etc. 25 In this manner, the affiliate, which affiliate is considered 2c in the case of the example and is configured as at this location, makes the data material comprised thereby available at this considered affiliate-specific data and is furthermore input into an affiliate dataset 14. In addition to this affiliate dataset 14, which represents 30 the previously-mentioned affiliate-specific data that is detected by means of the sensors 6 to 13, a commodity dataset 15, which represents product-specific data, is also available in the affiliate 2c concerned. This product-specific data is the product type (strawberries 3, in the case of the 35 example) and the volume of sales per time units, for example the quantity of strawberries 3 sold per hour on a certain calendar day. Moreover, the product dataset 15 may have deposited in it the article number for the product concerned or for the 10/11/09.va 18350 speci.doc.10 - 11 selected commodity (strawberries 3). Furthermore, the price of the commodity as well as the point in time of the sale is specified by the clock 6 or is synchronized therewith. In the end, the commodity dataset 15 also provides information about the service life of the selected commodity or of the strawberries 3, in the case of the 5 example. This service life is, as a rule, flanked with two values, one for the length of life of the commodity concerned or of the strawberries 3, respectively their maximum possible duration of sale (one day in the case of the example). Moreover, the service life expresses the seasonal availability of the selected commodity (strawberries 3), for example, meaning that here, a residual availability of two weeks 10 is furnished because strawberry season will end very soon. Within the context of the invention, the commodity dataset 15 in conjunction with the affiliate dataset 14 is now transmitted to the main branch by the affiliate 2c concerned, in the instance of the example, by means of the associated line 4. Both of 15 the datasets 14, 15 are evaluated within the main branch 1 by using, for example, a stochastic position model. As a result of all of the described input data, a disposition recommendation 16 is transmitted from the main branch I to the affiliate 2c in the case of the example. This disposition recommendation 16 has been determined in an affiliate-specific manner as well as being dependent upon the day of the week and, of 20 course, in a calendar-specific manner. With respect to the selected commodity, that is to say the strawberries 3 in the instance of the example, this means that, for example, for Tuesday, the third of June, a sold quantity of selected commodities or strawberries 3 that is anticipated in the 25 affiliate 2c corresponds to the quantity of three "small boxes" of strawberries 3 in the figure. For the same day (Tuesday, the third of June), in taking into consideration the affiliate 2b, four "small boxes" of strawberries 3 may result as the anticipated sales volume. In the affiliate 2a, only one "small box" is anticipated on this day, whereas in contrast two "small boxes" may be anticipated for the affiliate 2b. In any case, the 30 main branch 1 transmits a respectively affiliate-specific and weekday-dependent recommendation to the respective affiliates 2a to 2d in the light of the selected commodity 3. This disposition recommendation 16 can now be converted by the decision maker in 35 the affiliate 2a to 2d concerned into an order placed with the main branch 1. This order can, for example, be transmitted by means of the input unit 10 to the main branch 1. For this input unit 10 is a computer or a computer unit that not only 10/I1/09,va 18350 speci.doc,I I - 12 receives all of the data of the sensors 6 to 13, but is also connected to the cash register machines 5 located in the affiliate 2c. That is to say, all commodity-specific and affiliate-specific data are collected and consolidated as well as transmitted to the main branch 1 by and in the input unit 10. Furthermore, the input unit 10 serves to 5 reproduce the disposition recommendation lb from the main branch I and therewith execute the order as described. Subsequent to the described ordering process, the anticipated sales volumes ("small boxes" of strawberries 3) are assembled in the main branch I for the calendar day 10 considered (Tuesday, the third of June) respectively per affiliate 2a to 2d and can then be directly delivered subsequent thereto to the affiliate 2a to 2d concerned. For the most part, this takes place on the eve of or during the night prior to the day considered (Tuesday, the third of June). 15 Throughout this specification and the claims which follow, unless the context requires otherwise, the word "comprise", and variations such as "comprises" and "comprising", will be understood to imply the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps. 20 The reference to any prior art in this specification is not, and should not be taken as, an acknowledgment or any form or suggestion that the prior art forms part of the common general knowledge in Australia. 10/l11/09.va 18350 speci.doc.12

Claims (15)

1. A method for controlling the flow of commodities from a main branch to one or a plurality of locally removed affiliates, according to which method selected 5 commodities are evaluated in the affiliate concerned by means of a commodity registration device with regard to their commodity-specific data and, in conjunction with the affiliate-specific data, are converted into a disposition recommendation.

2. The method as claimed in claim 1, wherein the type of product as well as 10 sales volume and optionally an article number and/or the price and/or the point in time of sale and/or the service life of the selected commodity are included as commodity-specific data and are stored in a commodity dataset.

3. The method as claimed in claim 2, wherein the service life of the selected 15 commodity as well as the lifetime values in addition to the seasonal availability are reflected.

4. The method as claimed in any one of claims I to 3, wherein one or a plurality of cash register machine(s) can be used in the affiliate as a commodity registration 20 device.

5. The method as claimed in any one of claims I to 4, wherein the affiliate specific data are generated by means of sensors as well as optionally by an external input and are stored in an affiliate dataset. 25

6. The method as claimed in any one of claims I to 5, wherein the commodity dataset and the affiliate dataset are transmitted to the main branch where they are evaluated. 30

7. The method as claimed in any one of claims 1 to 6, wherein the main branch derives the disposition recommendation for the selected commodity from the affiliate dataset as well as from the commodity dataset and transmits said disposition recommendation to the respective affiliate. 35

8. The method as claimed in any one of claims I to 7, wherein the disposition recommendation takes into consideration a product surplus, which is dependent upon the time of day and/or the calendar date, of the selected commodity. 10/11/09,va 18350 speci.doc,13 -14

9. The method as claimed in any one of claims 1 to 8, wherein the main branch establishes a respectively affiliate-specific and/or weekday-dependent disposition recommendation. 5

10. The method as claimed in any one of claims I to 9, wherein the commodity specific data of a selected commodity are compared with the commodity-specific data of a different selected commodity with respect to comparable time-dependent volumes of sales. 10

11. The method as claimed in claim 10, wherein depending on the correlation of the time-dependent volumes of sales of the commodities that are to be compared while taking into consideration a pre-determined deviation, individual commodities are combined into affiliate-dependent and/or time-dependent product clusters and/or 15 weekday clusters and/or affiliate clusters with similar sales patterns in the main branch.

12. A device for controlling the flow of commodities from a main branch to one or a plurality of locally removed affiliates, in particular for carrying out the method 20 as claimed in any one of claims 1 to 11, wherein the main branch and the affiliates are connected to one another by means of data and transportation, and wherein selected commodities are evaluated with regard to their product-specific data by means of a commodity registration device in the affiliate concerned and are furthermore subsequently converted into a disposition recommendation in connection 25 with affiliate-specific data.

13. The device as claimed in claim 12, wherein the commodity registration device is configured as one or a plurality of cash register machine(s). 30

14. The device as claimed in claim 12 or claim 13, wherein the affiliates have sensors, for example a clock, in particular a radio controlled clock, and/or a temperature sensor, and/or a time capturing device, and/or a humidity sensor, and/or an input unit, and/or an affiliate-specific weather programme unit, and/or an affiliate specific calendar programme unit in order to generate affiliate-specific data in this 35 manner. 10/1 1/09,va 18350 spcci.doc,14 - 15

15. The device as claimed in any one of claims 12 to 14, wherein the affiliates are configured as a local shops and the main branch is configured as a centre of distribution or contains such a centre of distribution. 5 10/1 1/09,va 18350 speci.doc,15