WO2002021853A2 - Outil de decision de gestion commande par des donnees en vue d'une gestion totale des ressources - Google Patents

Outil de decision de gestion commande par des donnees en vue d'une gestion totale des ressources Download PDF

Info

Publication number
WO2002021853A2
WO2002021853A2 PCT/US2001/027566 US0127566W WO0221853A2 WO 2002021853 A2 WO2002021853 A2 WO 2002021853A2 US 0127566 W US0127566 W US 0127566W WO 0221853 A2 WO0221853 A2 WO 0221853A2
Authority
WO
WIPO (PCT)
Prior art keywords
stage
data
inputting
determining
outputting
Prior art date
Application number
PCT/US2001/027566
Other languages
English (en)
Other versions
WO2002021853A3 (fr
Inventor
Dennis M. Baca
Michael J. Fanning
Original Assignee
United States Postal Service
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by United States Postal Service filed Critical United States Postal Service
Priority to AU2001288782A priority Critical patent/AU2001288782A1/en
Priority to US10/362,093 priority patent/US20040015382A1/en
Publication of WO2002021853A2 publication Critical patent/WO2002021853A2/fr
Publication of WO2002021853A3 publication Critical patent/WO2002021853A3/fr

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/10—Office automation; Time management

Definitions

  • This invention relates to systems and methods for management decision making, and, more particularly, to a data-driven management decision tool for use in total resource management processes.
  • Resources management is a business practice of managing resources by analyzing the various costs and savings associated with a resource to determine the best method for using, servicing, and replacing the resource.
  • Conventional approaches used for resource management decisions have relied on separate consideration and evaluation of a number of criteria, such as design, acquisition, deployment, operations and maintenance, and investment recovery.
  • the design criterion deals with the construction of the resource, such as ergonomics and possible litigation linked to flaws in the construction of a resource.
  • Acquisition deals with the method of acquiring the resource, such as purchase or lease.
  • Deployment deals with the method in which the resource will be implemented, such as location and storage space.
  • Operations and maintenance deals with the manner in which the resource will be serviced.
  • Investment recovery deals with determining the profitable method for implementing the resource.
  • NPV Net Present Value
  • ROI Return on Investment
  • investment recovery is a stage of total resource management analysis. It is dependent upon previous decisions; hence, investment recovery should not be used as the driver for the total resource management process. Total resource management is based on a combination of investment recovery and other key factors.
  • the present invention is directed to a multistage evaluation system and method which substantially obviates one or more of the limitations and disadvantages of the related art.
  • one embodiment of the invention is directed to a system and method for making data-driven management decisions for use in total resource management, which comprises inputting data into one or more evaluation stages, determining the cost associated with each evaluation stage based on the data input into each stage, and determining a total cost based on the aggregate of the costs of each evaluation.
  • Figure 1 illustrates a flow diagram of a method consistent with the present invention
  • Figure 2 illustrates a system for performing a method consistent with the present invention
  • Figure 3 illustrates steps of a multistage evaluation process using a TRMS Decision Tool consistent with the present invention
  • Figures 4 illustrates a sample screen shot of a program performing a data input step consistent with the present invention
  • Figure 5 illustrates a sample screen shot of a program performing a data analysis step consistent with the present invention
  • Figure 6 illustrates a sample screen shot of a program performing an assumption step consistent with the present invention
  • Figure 7 illustrates a sample screen shot of a program performing a base case results display step consistent with the present invention
  • Figures 8-13 illustrate sample screen shots of a program displaying graphical representations of results consistent with the present invention
  • Figure 14 illustrates a sample screen shot of a program performing a sensitivity analysis data entry step consistent with the present invention
  • Figure 15 illustrates a sample screen shot of a program performing a sensitivity analysis display step consistent with the present invention
  • Figures 16-19 illustrate sample screen shots of a program displaying graphical representations of sensitivity results consistent with the present invention.
  • a data-driven management decision tool for total resource management comprises a series of cross-functional stages which together form a multistage evaluation system 100.
  • the individual stages include a design and manufacturing stage 20, an acquisition stage 30, a deployment and training stage 40, an operations and maintenance stage 50, and an investment recovery stage 60.
  • relevant input data such as financial parameters relating to the activity defined at each stage
  • the financial parameter input into each stage can be classified as one of two types: decision variables and assumptions.
  • parameters such as asset life, deposition method, acquisition method, environmental material/liability, ergonomic design/litigation, and maintenance practices are typical decision variables.
  • Parameters such as asset design life, discount rate of Net Present Value (NPV) calculation, interest rate for leasing asset, escalation rate for replacement equipment, escalation rate for labor, escalation rate for energy, escalation rate for miscellaneous items, labor rates, rate of technological advancement, and rollover of depreciation from an asset being replaced are typical of assumptions.
  • NPV Net Present Value
  • Decision variables and assumptions can be further divided into sub-categories. For example, rollover of depreciation from an asset being replaced can be broken down into sub- categories including depreciation remaining, acquisition cost of replaced asset, salvage value of replaced asset, depreciation life of replaced asset, and method of depreciation.
  • a process consistent with the present invention starts with an input to a design and manufacturing stage 20, which is fed with any previously-determined decision data D5 as well as any previously-determined system state data (not shown).
  • a first output from design and manufacturing stage 20 is a parameter S5, representing the state of the system resulting from design and manufacturing stage 20.
  • Parameter S5 is input into acquisition stage 30.
  • Acquisition stage 30 also receives input D4, representing decision data made for stage 4.
  • a first output from acquisition stage 30 is a parameter S4, representing the state of the system resulting from acquisition stage 30.
  • Parameter S4 is input into deployment and training stage 40, which also receives a data input, D3, representative of decision data for stage 3.
  • an output parameter, S3, from deployment and training stage 40 is input into operations and maintenance stage 50.
  • Operations and maintenance stage 50 is also inputted with D2, representative of decision data for stage 2.
  • investment recovery stage 60 receives an output parameter, S2, from operation and maintenance stage 50 and a data input, D1 , representative of decision data for stage 1.
  • Additional outputs C5, C4, C3, C2 and C1 are taken, respectively, from design and manufacturing stage 20, acquisition stage 30, deployment and training stage 40, operations and maintenance stage 50 and investment recovery stage 60.
  • the sum of C5+ C4+ C3+ C2+ C1 is a minimum overall cost.
  • the multistage evaluation system 200 consists of a computer system 210.
  • Computer system 210 comprises a monitor, keyboard, and computer unit.
  • the computer unit contains the standard components required for inputting, outputting, manipulating, and storing data.
  • the computer unit may be comprised of a central processing unit (CPU), random access memory (RAM), video card, sound card, magnetic storage devices, optical storage devices, input output (I/O) terminals, and a network interface card (NIC).
  • Computer system 210 can optionally be connected to a printer 240 through the I/O terminals. Examples of the I/O terminals to which the printer can be connected are parallel, serial, universal serial bus, and IEEE 1394.
  • network 230 can be a local area network (LAN), wide area network (WAN), or wireless network.
  • remote computing devices to which computer system 210 may be connected are a remote server 220 and a remote printer 250.
  • a multistage evaluation process consistent with the present invention may be performed on the multistage evaluation system 200.
  • the different steps performed by the stages of the evaluation system may be performed by, for example, a computer program or a financial spreadsheet.
  • a computer program consistent with the present invention may be created using various programming languages or software suites.
  • the computer program can be a stand alone program coded in a language such
  • JavaTM JavaTM or C++, or it may be designed using a known spreadsheet program.
  • the multistage evaluation process may be performed entirely by, for example, computer system 210.
  • the computer program or spreadsheet for executing steps of the multistage evaluation process is stored at computer system 210.
  • the program can be stored, for example, on one of the magnetic storage devices or optical storage devices contained in computer system 210.
  • magnetic storage devices such as hard disk drives or floppy disk drives could be used to store the computer program or spreadsheet.
  • optical storage devices such as CD-ROM, DVD, CD-R, or CD-RW could be used to store the computer program or spreadsheet.
  • the computer program or spreadsheet is executed.
  • Various parameters are inputted into the computer program or spreadsheet by an analyst using the keyboard.
  • the program may also be linked to databases located at computer system 210.
  • the computer program or spreadsheet can query the database for values inputted into the different stages of the multistage evaluation system.
  • the computer program or spreadsheet performs a multistage evaluation process.
  • the results of the process can be displayed on the monitor of computer system 210.
  • the results can be displayed in either numerical or graphical form.
  • the operator can print the numerical or graphical results on printer 240.
  • the computer program or spreadsheet may also perform a sensitivity analysis.
  • the operator can change various parameters entered into the multistage evaluation system to determine what effect the change has on the results.
  • the results of the sensitivity analysis can be displayed on the monitor of computer system 210 in numerical or graphical form. Also, the operator has the option of printing a hard copy of the results of the sensitivity analysis on printer 240.
  • the method has been described as running locally on computer system 210.
  • a remote computer system may be used in combination with computer system 210.
  • the computer program or spreadsheet is functionally the same but the location of the program, spreadsheet, or inputted data may differ.
  • the program or spreadsheet instead of the computer program or spreadsheet being stored at computer system 210, the program or spreadsheet can be stored at remote server 220.
  • the computer program or spreadsheet would be stored on magnetic or optical storage devices located at remote server 220.
  • the computer program or spreadsheet would be transferred from remote server 220 across network 230 to computer system 210 for execution.
  • the computer program or spreadsheet can be remotely executed at remote server 220.
  • databases containing values inputted into the multistage evaluation system can be stored at remote server 220. Once the evaluation process is performed, the results can be transferred across network 230 for display at remote server 220 or printing on remote printer 250.
  • the example concerns the analysis of the replacement of manual flat mail sorting machines with Flat Sorting Machines (FSM) 1000 Keying using the United States Postal Service Total Resource Management System (TRMS) Decision Tool.
  • FSM 1000 Keying is a machine for processing mail.
  • TRMS Decision Tool is one example of the present invention implemented using a financial spreadsheet
  • FIG 3 is a flowchart illustrating the steps of a multistage evaluation using the TRMS Decision Tool.
  • An analyst begins a new analysis with data input step 310 of the TRMS Decision Tool.
  • a sample screen shot for this step is shown in Figure 4.
  • the analyst provides information about the resource to be analyzed, including characteristics of the resource and of the existing capital resource that it may replace.
  • the data input step includes the specification of the existing mail processing technology and the new technology that is to be installed.
  • the analyst provides information on various parameters concerning the old and new technologies. For example, the analyst enters the capital cost of the new technology, along with the disposition value for both the new and old technologies.
  • the parameter values that cannot be obtained from existing databases are included on the Data Input screen of Figure 4.
  • the parameter values may be obtained from various entities providing services related to the parameter. For example, the demolition cost per machine would be acquired from a company performing the demolition.
  • the analyst also specifies the location for the resource, which will allow the TRMS Decision Tool to locate appropriate location-specific parameters in available databases. In cases where a programmatic purchase is being considered, the analyst can indicate that the location is national in scope. If it would be useful to be able to analyze regional programmatic purchases as well, that capability could easily be added to the TRMS Decision Tool.
  • the second step is a data analysis 320.
  • Data analysis 320 takes place with the data review screen, an example of which is shown in Figure 5.
  • the data review screen summarizes the technical parameters of the new and old technologies.
  • This screen combines the information from data input step 310 with information taken from databases.
  • data analysis step 320 some preliminary calculations are also performed. For example, in the mail- processing example, values for the Direct Cost per Handling are calculated in data analysis step 320, using the Operator Wage Rate and the Productivity (per labor hour).
  • the source of the information in this step can be indicated by shading on the screen, with analyst-entered indicated in white, database- derived values indicated by light shading, and calculated values indicated by heavy shading.
  • the third step of the TRMS Decision Tool analysis is an assumption step 330, an example of which is shown in Figure 6.
  • This screen shows the general economic assumptions that are used to perform the economic calculations of NPV and ROI. These parameters can be taken directly from a handbook that specifies how the economic analysis should be performed. These parameters include the discount and hurdle rates, along with three escalation rates for labor, energy and other costs.
  • Other parameters entered in assumption step 330 may be new parameters that are being included in the TRMS Decision Tool.
  • the Realization Factor allows the analyst to specify whether the full projected savings from the new technology will be achieved. This parameter allows the analyst to consider the impact of unforeseen factors in the deployment of a new technology and to correct for levels of savings that may be overly optimistic.
  • a second example is the Rate of Technological Advance, which allows the analyst to specify how quickly technology is changing.
  • a third example is the Rate of Increase in Maintenance, which allows the analyst to specify how quickly maintenance costs will increase as the technology ages. For these latter two parameters, an analysis of existing data could be performed to show what range of parameter values is likely. The analyst can adjust any of these parameter assumptions on the assumptions screen shown in Figure 6. When the analyst is finished adjusting the parameters, pressing the button marked "Run Base Case Scenario" causes the TRMS Decision Tool to produce the Base Case results and advances the analyst to a results screen as shown in Figure 7.
  • the fourth step of the TRMS Decision Tool analysis is base case results step 340, an example of which is shown in Figure 7.
  • This screen summarizes the parameter values describing the new and old technologies, along with the general assumptions that are used in the analysis.
  • the results section shows the results for the base case analysis of the resource evaluated using the TRMS Decision Tool.
  • the length of the analysis is indicated by the Analysis Period output. In most cases, the analysis is performed for a 10-year period in accordance with the instructions for preparing an economic analysis. However, in cases in which the NPV peaks before 10 years - for example, if there is an especially fast increase in maintenance costs over time -, then the analysis period is reduced to the length of time that produces the maximum NPV.
  • the results section shows the NPV and ROI corresponding to the analysis period, along with the number of years to produce an ROI equal to the hurdle rate and the number of years until the resource becomes technologically obsolete.
  • the TRMS Decision Tool could also include measures of the changes in energy usage and emissions in the results section. These measures will allow the analyst to understand some of the environmental impact of the new resource that is not captured in the economic measures of NPV and ROI.
  • the NPV and ROI are determined by calculating the cash flow for each year up to the end year using standard accounting methods. A chart showing the cash flow for the mail processing example is described below with reference to Figure 13.
  • the cash flow is determined by the cash inflows and outflows inputted in the first three steps (310, 320, 330).
  • the NPV is calculated by using the imbedded NPV calculation function of the TRMS Decision Tool.
  • the NPV for each year can be determined by the following equation:
  • n is the number of cash flow
  • valuesi is value of a particular cash inflow or outflow
  • rate is the discount rate inputted in step 330.
  • Base case results step 340 also generates a number of charts that show the results in more detail.
  • Figures 8 and 9 are two sample charts showing the NPV and the ROI that result from keeping the new resource for different lengths of time up to the 10-year period specified for the analysis.
  • Figure 10 is a chart showing the undiscounted yearly cash flow for the new resource over a 10-year period.
  • Figure 11 is a chart showing how each year's cash flow contributes to the 10-year NPV of the resource. This chart illustrates how the primary NPV payoff of a new resource generally occurs in the early years of its use.
  • Figure 12 is a chart showing the projected 10-year ROI for the next-generation technology over the next 10 years. This chart illustrates how the economic value of the next-generation technology improves over time and eventually crosses the hurdle rate.
  • Figure 13 is a screen shot of a chart detailing the yearly cash flow calculation in a format that is consistent with the requirements of the invention.
  • the next step of the TRMS Decision Tool analysis is a sensitivity analysis parameters entry step 350.
  • a screen shot of a sample data entry form is shown in Figure 14. This screen is the control panel that allows the user to define both the automated and non-automated portions of the sensitivity analysis.
  • the TRMS Decision Tool automatically changes critical parameter values up and down, for example, by an equal percentage.
  • the analyst may control the size of this percentage change by altering the value in the Level of Uncertainty field.
  • the possible values for the Level of Uncertainty range from 10 to 30 percent.
  • the base case parameter values are shown in the Current Value column.
  • the Low Case column shows the parameter values after a percentage decrease from the base case, whereas the High Case column shows the parameter values after a percentage increase from the base case.
  • the automated portion of the sensitivity analysis may alter each of the parameter values individually, keeping all other parameter values at their base case values. Including both increases and decreases in values, this portion of the sensitivity analysis computes different scenarios to compare with the base case. These results are shown on the Sensitivity Analysis Results screen, which is described below with reference to Figure 15.
  • the automated portion of the sensitivity analysis allows the analyst to understand how the investment NPV and ROI calculations are affected by changes in each of these parameter values.
  • the analyst assigns values for the parameters. These changes can be applied simultaneously, thus allowing the analyst to explore the combined effect of the parameters on the resource NPV and ROI.
  • the non-automated parameter values are shown in the User-Defined column of the Sensitivity Analysis screen shown in Figure 14.
  • step 360 the TRMS Decision Tool calculates the sensitivity analysis results and advances the analyst to the sensitivity analysis screen shown in Figure 15, which gives the results. Note that in a typical analysis, the analyst may go back and forth several times between the Sensitivity Analysis Parameters and Sensitivity Analysis Results screens.
  • Sensitivity calculation and display step 360 of the TRMS Decision Tool analysis is shown by the Sensitivity Analysis Results screen, a sample of which is shown in Figure 15.
  • This screen shows the results for both the automated and non-automated portions of the sensitivity analysis.
  • the initial screen summarizes the parameter values that were chosen in step 360, along with the non-automated analysis comparing the Base Case results with the User-Defined results.
  • This portion of the screen also provides links to four charts, which are showN in Figures 16 through 19 that show the results for both the automated and non-automated portions of the analysis.
  • Figures 16 and 17 are sample charts providing the results for the automated portion of the sensitivity analysis.
  • Figure 16 shows the impact of the parameter value variation on the calculated NPV.
  • the chart shows the NPV when a low value is used for the parameter and when a high value is used for the parameter.
  • the parameter values may be changed individually, so that the values of all parameters are at their base case value except for the one parameter that is being changed.
  • Figure 17 is analogous to the first chart but shows the impact of the parameter value variation on the calculated ROI rather than on the calculated NPV.
  • Figures 18 and 19 are sample charts providing further information about the non-automated portion of the sensitivity analysis. These charts compare the Base Case and User-Defined results for keeping the new resource for different lengths of time, up to the 10-year period specified the analysis. Figure 18 shows the results for ROI, and Figure 19 shows the results for NPV.

Landscapes

  • Engineering & Computer Science (AREA)
  • Business, Economics & Management (AREA)
  • Strategic Management (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Human Resources & Organizations (AREA)
  • Operations Research (AREA)
  • Economics (AREA)
  • Marketing (AREA)
  • Data Mining & Analysis (AREA)
  • Quality & Reliability (AREA)
  • Tourism & Hospitality (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)
  • General Factory Administration (AREA)

Abstract

Un procédé servant à prendre des décisions de gestion commandées par des données et utilisé en gestion totale des ressources consiste à entrer des données de décision et des données d'état d'un système dans divers étages d'évaluation. On calcule le coût lié à chaque étage d'évaluation et on détermine la globalité des coûts en fonction de l'ensemble des coûts provenant de chaque étage d'évaluation. On peut réaliser une analyse de sensibilité en modifiant l'entrée des données de décision dans chaque étage d'évaluation.
PCT/US2001/027566 2000-09-07 2001-09-06 Outil de decision de gestion commande par des donnees en vue d'une gestion totale des ressources WO2002021853A2 (fr)

Priority Applications (2)

Application Number Priority Date Filing Date Title
AU2001288782A AU2001288782A1 (en) 2000-09-07 2001-09-06 Data-driven management decision tool for total resource management
US10/362,093 US20040015382A1 (en) 2001-09-06 2001-09-06 Data-driven management decision tool for total resource management

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US23079300P 2000-09-07 2000-09-07
US60/230,793 2000-09-07

Publications (2)

Publication Number Publication Date
WO2002021853A2 true WO2002021853A2 (fr) 2002-03-14
WO2002021853A3 WO2002021853A3 (fr) 2003-07-10

Family

ID=22866603

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2001/027566 WO2002021853A2 (fr) 2000-09-07 2001-09-06 Outil de decision de gestion commande par des donnees en vue d'une gestion totale des ressources

Country Status (2)

Country Link
AU (1) AU2001288782A1 (fr)
WO (1) WO2002021853A2 (fr)

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5311438A (en) * 1992-01-31 1994-05-10 Andersen Consulting Integrated manufacturing system
US5704045A (en) * 1995-01-09 1997-12-30 King; Douglas L. System and method of risk transfer and risk diversification including means to assure with assurance of timely payment and segregation of the interests of capital
US5737581A (en) * 1995-08-30 1998-04-07 Keane; John A. Quality system implementation simulator
US5892900A (en) * 1996-08-30 1999-04-06 Intertrust Technologies Corp. Systems and methods for secure transaction management and electronic rights protection
US6151582A (en) * 1995-10-26 2000-11-21 Philips Electronics North America Corp. Decision support system for the management of an agile supply chain
US6154731A (en) * 1997-08-01 2000-11-28 Monks; Robert A. G. Computer assisted and/or implemented process and architecture for simulating, determining and/or ranking and/or indexing effective corporate governance using complexity theory and agency-based modeling
US6256773B1 (en) * 1999-08-31 2001-07-03 Accenture Llp System, method and article of manufacture for configuration management in a development architecture framework
US20010034686A1 (en) * 1997-12-10 2001-10-25 Eder Jeff Scott Method of and system for defining and measuring the real options of a commercial enterprise

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5311438A (en) * 1992-01-31 1994-05-10 Andersen Consulting Integrated manufacturing system
US5704045A (en) * 1995-01-09 1997-12-30 King; Douglas L. System and method of risk transfer and risk diversification including means to assure with assurance of timely payment and segregation of the interests of capital
US5737581A (en) * 1995-08-30 1998-04-07 Keane; John A. Quality system implementation simulator
US6151582A (en) * 1995-10-26 2000-11-21 Philips Electronics North America Corp. Decision support system for the management of an agile supply chain
US5892900A (en) * 1996-08-30 1999-04-06 Intertrust Technologies Corp. Systems and methods for secure transaction management and electronic rights protection
US6154731A (en) * 1997-08-01 2000-11-28 Monks; Robert A. G. Computer assisted and/or implemented process and architecture for simulating, determining and/or ranking and/or indexing effective corporate governance using complexity theory and agency-based modeling
US20010034686A1 (en) * 1997-12-10 2001-10-25 Eder Jeff Scott Method of and system for defining and measuring the real options of a commercial enterprise
US6256773B1 (en) * 1999-08-31 2001-07-03 Accenture Llp System, method and article of manufacture for configuration management in a development architecture framework

Non-Patent Citations (2)

* Cited by examiner, † Cited by third party
Title
DATABASE ABI/INFORM(R) [Online] NOVACK ET AL.: 'Rethinking concept foundations in logistics management', XP002963511 Retrieved from DIALOG Database accession no. 92-60960 & JOURNAL OF BUSINESS LOGISTICS vol. 13, no. 2, 1992, pages 233 - 267 *
DATABASE BAMP [Online] SHARMAN: 'Activity/process budgets', XP002963510 Retrieved from DIALOG Database accession no. 00631869 & CMA MAGAZINE vol. 70, no. 2, March 1996, pages 21 - 24 *

Also Published As

Publication number Publication date
WO2002021853A3 (fr) 2003-07-10
AU2001288782A1 (en) 2002-03-22

Similar Documents

Publication Publication Date Title
US7603308B2 (en) Security analyst estimates performance viewing system and method
US8498917B2 (en) Systems and methods for providing migration and performance matrices
US8019734B2 (en) Statistical determination of operator error
US7930195B2 (en) Strategic management and budgeting tools
US20050278202A1 (en) Information technology transformation assessment tools
US20040015376A1 (en) Method and system to value projects taking into account political risks
US7747478B2 (en) Method of generating multiple recommendations for multi-objective available-to-sell (ATS) optimization problem
US20030033586A1 (en) Automated system and method for software application quantification
KR20090006489A (ko) 신용 위험 모형 구축용 툴 킷, 신용 위험 모형 구축을 통한신용 위험 관리 방법 및 이를 기록한 기록매체
JP2001125962A (ja) 企業診断及び経営意思決定支援システム
US20040015382A1 (en) Data-driven management decision tool for total resource management
US6651017B2 (en) Methods and systems for generating a quality enhancement project report
US20130035990A1 (en) Software solution for Visual Sales process simulation and management
CN115375474A (zh) 信息提示方法、装置及电子设备
US8606616B1 (en) Selection of business success indicators based on scoring of intended program results, assumptions or dependencies, and projects
WO2002021853A2 (fr) Outil de decision de gestion commande par des donnees en vue d'une gestion totale des ressources
KR100738899B1 (ko) 신용카드 결제 시스템을 이용한 창업 및 경영 지원 서비스제공 시스템
US20220351112A1 (en) System and method for obtaining audit evidence
Thompson et al. Multi-objective optimization for bridge management systems
JP2003280901A (ja) 見積評価支援プログラムおよび見積評価支援システム
WO2003019437A1 (fr) Evaluation des performances du commerce electronique
US20030120533A1 (en) Systems and methods for increasing business productivity and revenues by identifying critical interactions relating to customers
Denkena et al. Linking total costs and benefits of ownership (TCBO) and process chain simulation for integrated assessment of manufacturing technologies and processes
WO2000067169A1 (fr) Systeme d'evaluation d'un projet d'investissement
Ferrario et al. A framework for evaluating difficulties in ERP implementation

Legal Events

Date Code Title Description
AK Designated states

Kind code of ref document: A2

Designated state(s): AE AG AL AM AT AU AZ BA BB BG BR BY BZ CA CH CN CO CR CU CZ DE DK DM DZ EC EE ES FI GB GD GE GH GM HR HU ID IL IN IS JP KE KG KP KR KZ LC LK LR LS LT LU LV MA MD MG MK MN MW MX MZ NO NZ PH PL PT RO RU SD SE SG SI SK SL TJ TM TR TT TZ UA UG US UZ VN YU ZA ZW

AL Designated countries for regional patents

Kind code of ref document: A2

Designated state(s): GH GM KE LS MW MZ SD SL SZ TZ UG ZW AM AZ BY KG KZ MD RU TJ TM AT BE CH CY DE DK ES FI FR GB GR IE IT LU MC NL PT SE TR BF BJ CF CG CI CM GA GN GQ GW ML MR NE SN TD TG

WWE Wipo information: entry into national phase

Ref document number: 10362093

Country of ref document: US

REG Reference to national code

Ref country code: DE

Ref legal event code: 8642

DFPE Request for preliminary examination filed prior to expiration of 19th month from priority date (pct application filed before 20040101)
122 Ep: pct application non-entry in european phase
NENP Non-entry into the national phase in:

Ref country code: JP