edsgm99 white paper letter

1999 INFORMS Prize Nomination from GM Europe and EDS

Application and Value of PLANETSä

Value Chain Optimization Models in the

General Motors Europe (GME) Planning Processes

A White Paper prepared by: EDS:John Lucas - Consulting Principal, EDS Enterprise Planning Optimization

General Motors Europe AG:Hans Barth - Vice President Project & Production SupportKlaus Nuechter - Director, Production Schedules & Capacity PlanningHelmut Herzog - Manager, Assembly Schedules & Capacity Planning

June, 1999

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BUSINESS SUMMARY

In the most recent European Harbour Report1, GM Europe was ranked as the most effective capacity planning organization among the five highest volume European mass vehicle makers. One of the key reasons why GM Europe has maintained the highest facility and tooling utilization in the European industry is a successful management policy to strategically deploy complex capacity flexibility among its assembly and manufacturing operations. This policy maximizes product-market delivery flexibility over the planning horizon (typically 5-10 years) while minimizing dedicated facility investments. Optimal product-plant tooling allocations among multiple facilities can accommodate shifting product-market preferences that balance the utilization of facilities over the planning horizon. While this multi-flex policy involves a significantly increased level of analytical decision-making and reporting complexity, the strategic usage of MS/OR (Management Science / Operations Research) fully integrated with IT (Information Technology) has simplified the planning process and has made this multi-flex planning policy feasible. By developing and deploying reengineered GM Europe capacity planning processes that intentionally leverage MS/OR technologies and integrated IT, even the most complex evaluation of strategic alternatives through time are now routine. Without these technology enablers, adequate operations analysis to support this flexible capacity strategy would not be possible.

Manufacturing planning within GM Europe is an integral part of a larger, ongoing business planning process (Diagram 1.). The scope of any manufacturing planning activity can be described in the following terms: As product mix, product portfolio lifecycle timing, market demand, resource availability and costs, management policy, government legislation, labor agreements, and economic alternatives change through time, it is necessary to develop an optimum capital spending and manufacturing operations plan, spanning 5-10 years, to keep pace. The near-term years of this operations plan eventually become the basis for capital spending decisions, budgets, and production schedules.

Business Planning Process Summary

Capacity Restricted Product Forecasts /Market Diversions /

Allocation

Capital Plan /Resource Plans

ManufacturingPlan

Free DemandProductForecast

ProductProgram

PortfolioPlan

StrategicPlan

MarketingPlanning

Manufac-turing

Planning

Diagram 1.

1 James Harbour Associates is a globally recognized independent provider of comparative benchmarks of the automobile industry using standardized metrics.

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1999 INFORMS Prize Nomination from GM Europe and EDS The overall cross-functional, cross-product, cross-facility, and cross-geographic scope and complexity of the planning analysis conducted by GM Europe has been increasing annually as the automotive business has truly gone global. Beginning in 1993, the objective of the GM Europe and EDS team was reengineer improved multinational capacity planning processes to satisfy the increased global analysis and planning requirements. Detroit-based EDS planning consultants have assisted GM Europe Production Scheduling and Capacity Planning in the methodical and evolutionary deployment of MS/OR based technologies, other integrated decision support tools, and IT as technology enablers in this process reengineering effort. This GM Europe organization (located in Zurich, Switzerland and Ruesselsheim, Germany) has served as the focal point for GM non-North America manufacturing plan coordination and consolidation, involving the Europe, Latin America, and Asia Pacific regions; in addition to an international manufacturing planning coordination role, the GM Europe Production Scheduling and Capacity Planning group has actual responsibility for development of the GM Europe regional operations plan.

The core of the MS/OR technology leveraged by the GM Europe capacity planning process are optimization models that process relevant criteria and policy inputs provided by a complementary IT infrastructure (Diagram 2.). To optimize a model of a global or regional (European) enterprise across an interactive planning horizon requires both linear and mixed integer formulations. Mixed integer models are very effective in the long range planning domain where go/no-go policy decisions and investment evaluations are required; linear programming or network models are more than adequate for detailed volume and scheduling allocations from plants to markets once tooling and investments have been determined and to evaluate the short term planning horizon.

Planning Process Leverage ofMS/OR Technologies

MS / ORModels

(PLANETS)

OUTPUT

Long Term Free DemandVehicle Forecast

Material /Component SetRequirements

Existing / PotentialTooling Availability

Fixed / VariableCost Estimates

LogisticsCriteria

InternationalTrade

Constraints

Vendor Sourcing Alternatives

ProductionRules Production

CapacityAlternatives

Long Term RestrictedVehicle Forecast

Vehicle - Plant - MarketAllocations

Material Sourcing Plan

Financial Plan

INPUTINPUT

Manufacturing Plan

ProductProgram

Description

Stock / InventoryRules

ManagementPolicy

Capital Spending Plan

Diagram 2.

Changes in the product portfolio or market demand usually result in an “unmakeable” free demand forecast (free market demand volume may exceed installed capacity or there may be no installed capacity if the product is totally new). A manufacturing operating plan, that satisfies management objectives and results in some “makeable” production deliveries plan (the restricted volume demand forecast) is then developed.

Since the modeling scope involved in this planning activity spans the European, Asia-Pacific, and Latin America automotive business activities, numerous corporate and local databases have been integrated into the business planning process as I/O devices for the MS/OR models. For example, an Excel-based common global plant capacity database system (CapScan II) provides existing and potential production capacity information directly to the models. Actual plant data (workday/holiday calendars, shift patterns, manpower and tooling capacity) is maintained at the local level by globally dispersed plant managers and consolidated by GM Europe. Along with this capacity data, marketing forecasts and other data are automatically fed to the PLANETSä (Electronic Data Systems Inc.) decision support system which then generates unique mixed-integer and linear mathematical models to satisfy specific planning analysis situations.

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1999 INFORMS Prize Nomination from GM Europe and EDSTo develop this plan, models with two different output usages (manufacturing and marketing) are deployed (Diagram 3.):· The initial planning process sequence results in a mixed-integer mathematical model that optimizes

tooling selection and allocation while generating a “makable” production plan with product-plant production volume allocations/schedules, a product-plant-tooling production allocation plan, and an annual production stock/inventory determination, per year.

· Given buy-in to the above production plan, a more elaborate linear programming model then generates a detailed product-plant-market operation delivery shipment plan, which determines the volume of each product to be shipped from each plant to each specific market, per year.

· The resultant mathematical models have over 100,000 variables, including integers, representing global operational plans and alternatives involving plants in over 20 countries, over 120 types of product, vehicle markets in over 80 countries, product-time-market and product-plant-time diversion alternatives, with associated inbound, interplant, and outbound logistics, and a 10 year planning horizon.

System / Process Context Diagram

FREE DEMANDVEHICLE

FORECAST

FREE DEMANDPOWERTRAIN

FORECAST

GM Europe Production Scheduling & Capacity Planning

PLANETSOPTIMIZATION

MODEL(S)

VEHICLE ASSEMBLYPLANNING REPORTS

GMIO MGT. &CAPACITY

CONSTRAINTS

VIA EXCEL

VIA PLANETS,EXCEL

RESTRICTEDVEHICLE ASS’Y /MKT OPERATION

ALLOCATION /DELIVERIESFORECAST

POWERTRAINPLANNINGREPORTS

RESTRICTEDPOWERTRAIN

FORECAST

OTHER GM

PRODUCTIONINVENTORYFORECAST

MGT.ALTERNATIVES

RESTRICTEDVEHICLE ASS’Y /MKT OPERATION

ALLOCATION /PRODUCTION

FORECAST

MODEL#1

MODEL#2

Diagram 3.

In this joint GM Europe and EDS endeavor, EDS performs the role of suggesting and facilitating process change based on known capabilities of integrated decision support system enablers. This includes:

· assisting the process reengineering efforts, · developing, deploying, and integrating the technology enablers into the business process, including

· the EDS proprietary PLANETSä mathematical model building system which generates unique linear and/or mixed-integer programming models

· a common global plant capacity database definition and repository · documenting the resultant processes, · developing the initial MS/OR business model structure, · developing the custom input/output (I/O) interfaces (e.g., Visual Basic macros) between the tools and

other corporate databases, · and providing ongoing training and process improvement consulting assistance.

GM owns the business process and resultant unique MS/OR models, databases, and reports. This involves GM planners:

· executing the process and models directly;· maintaining and controlling all input;· establishing modeling objectives and policy;· conducting “What is?” queries and statistical analysis; · developing and evaluating “What if?” strategy alternatives;· generating and maintaining custom operational and executive summary reports;

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1999 INFORMS Prize Nomination from GM Europe and EDS· providing and enforcing process discipline and accountability;· routinely scheduling EDS provided PLANETSä business and mathematical model building training

of GM planning personnel around GM Europe personnel rotations in order to stabilize the planning process which is so heavily dependent upon these MS/OR enablers.

Planning / Modeling Scope

Diagram 4.

BENEFITS

This effort has enabled GM Europe to:· develop feasible and optimal manufacturing plans, short term schedules, and long term production

forecasts that maximize management’s capacity flexibility policy; this has resulted in:· industry leading plant and resource utilization (reference European Harbour Report) among the

top five European volume vehicle makers;· maintaining a more stable level of assembly and manufacturing manpower through time which

results in higher productivity through higher morale and increased learning;· significant capital cost avoidance (hundreds of millions of dollars since 1994).

· significantly reduce the cycle time to build and analyze an operations plan:· days instead of weeks

· conduct a greater number of higher quality manufacturing plan studies with significantly fewer staff; without the MS/OR and IT technology enablers:

· 50% more staff would be required to evaluate significantly fewer scenarios· it would be difficult, if not impossible, to fully leverage management’s capacity flexibility

policy · develop globally and/or regionally consolidated plans (Diagram 4.); · perform integrated planning across manufacturing, marketing, financial, and engineering functions;· deploy logical and repeatable analysis processes that guarantee quantitative optimization of the plan

while also adhering to executive policy constraints and objectives.

CRITICAL SUCCESS FACTORS

The critical success factors to this successful business solution deployment have been:· the transparent integration of sophisticated MS/OR modeling technologies into the business process;· development of well documented, flexible processes;· designated staff rotation plans to ensure long term process viability while considering routine staff

attrition and turnover;· designated staff training plans to ensure long term process viability;· automation of as many of the process input / model build / output reporting steps as possible;· inclusion of over-riding executive policy preferences and constraints to the resultant models; · routine process and system reviews to accelerate continuous improvement suggestions;· intimate knowledge of the manageable business process complexity by both the EDS solution

providers and the GM Europe process owners;· very strong GM Europe leadership and championing of new processes/solutions.

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1999 INFORMS Prize Nomination from GM Europe and EDSTECHNOLOGY SUMMARY ADDENDUM - PLANETSä While most business situations can be represented as a mathematical model given enough time, knowledgeable modeling resources, and modeling ingenuity using commercial optimization packages, a proprietary modeling aid that allows enterprise process owners to describe their business in terms they are familiar with has been developed by EDS. This modeling tool is called PLANETSä. In 1986, the EDS entry, “PLANETS: A Modeling Tool for Business Planning”, was a TIMS2 Edelman Award finalist.The current version is designed to operate on a stand-alone PC platform utilizing a 32-bit Windows environment (Diagram 5.).

Input Output

PLANETS for WindowsTM

MathPro 2000TM

XPRESS-MPTM

BUSINESS MODELCONCEPT

TOPRODUCTION

RESEARCH TO PLAN

ORDER TO CASH

SALESTO

REORDER

PLANETS Building Block Modeling ConstructsPLANETS Database

MATRIXGENERATOR

MATRIXSOLVER

Diagram 5.

As an integrated decision support system, PLANETSä has provided the GM Europe / EDS team with a singular framework and means to perform the following six modeling process steps:

· (Step 1) develop a detailed “living” business model of GM’s regional automotive operations using simple business terminology to describe people, places, things, objectives, and policy; these business terms and descriptions of the existing enterprise, supply chain, and potential operational alternatives are captured and represented by PLANETSä generic “building block” entities; the resultant mathematical model that is automatically generated by PLANETSä from this business model (Steps 4, 5, and 6) can literally generate an optimal representation of the enterprise’s detailed operating plan for every time period in the planning horizon; this representation can include the entire supply chain; no MS/OR background is required of the person defining the business model in PLANETSä.

· (Step 2) further define, maintain, and integrate supportive data describing this business model (via PLANETSä database browsers and/or external data import features);

· (Step 3) customize the business scope and objectives of each mathematical model to be built using the enterprise view assembled in Steps 1 and 2;

· (Step 4) automatically interpret and translate this “building block” representation and business modeling rules into a mathematical (matrix / network) representation of the business;

· (Step 5) automatically generate LP/MIP/network modeling code and solve the optimization model;· (Step 6) automatically convert the mathematical model output to business legible reports.

Steps 1-6 would be iterated as necessary to maintain and update the model(s) as a representation of the enterprise and perform various “What is?” and “What if?” analyses.

2 TIMS, The Institute for the Management Sciences6

1999 INFORMS Prize Nomination from GM Europe and EDSThe GM Europe modeling user operates within the PLANETSä input, output, and control screen hierarchy and is never exposed to PLANETSä internal database manipulations or its calls to third-party matrix building / solving technology. Since at no time does PLANETSä converse with the user in MS/OR terminology, no prior management science or operations research background or education is required of the GM Europe planners to use this tool and the resultant models; however, over time, the planners do gain a rich and satisfying appreciation and understanding of MS/OR’s capabilities and contribution to increased business process performance. In order to be an effective modeler, the user must understand his/her business enterprise since the models include significant cross-functional, cross-geographic, and cross-organizational criteria.

TECHNOLOGY SUMMARY ADDENDUM - BUSINESS MODEL

The business model is a description, in common business terminology, of the people, places, things, policy, and objectives to be modeled. Not only must an enterprise be represented cross-functionally and cross-geographically, it must also be represented “across time”. Real data varies over time and “optimal” solutions are not absolute but relative to a specific planning horizon and to changing existing and/or potential conditions (E.g. emerging markets, product introductions, facility/resource changes, market seasonality). There must be agreement upon the various definitions of the planning horizon scope and an understanding of the modeling opportunities and limitations of each.

At Gm Europe, this involved developing, building, and maintaining a “living model” of GM’s regional operations that transcends a significant, usually 5-10 year, rolling planning horizon (Diagram 6.). The business model is called a “living model” because, once built, it is intended to be maintained, updated, and modified continuously to mirror the actual enterprise.

The model is initially built as a “snapshot” view of the current enterprise and the enterprise’s current planned structure over the planning horizon. Modeling over a “rolling” planning horizon means that if today, during 1999, the updated and available model’s planning horizon spans a timeframe bounded by the current year +1 through the current year +10 (2000 through 2009), then next year’s model, used in 2000, will still span 10 years (2001 through 2010) since the previous first year will be dropped and a new year will be added to the model’s planning horizon. In this manner, the “living” model always represents a planning horizon spanning the next 10 years.

Model Planning Horizon

10 Interactive Decision-Making Calendar Years

Year 10TODAY YEAR 5

SCHEDULING

PLANNING

Diagram 6.

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1999 INFORMS Prize Nomination from GM Europe and EDSDuring the course of business, this “living model” can be accessed for a variety of “What is?” and “What if?” decision support analysis since it reflects the current enterprise view and most known strategic alternatives (Diagram 7.).

GLOBALCUSTOMER/ MARKETSTRATEGY

GLOBALPRODUCT &

TECHNOLOGYSTRATEGY

GLOBAL OPERATIONS &LOGISTICS STRATEGY

HOW MANY TOMAKE /

PURCHASE?

WHERE TOMAKE?

ALLIANCE?

SHOULD ITBE MADE?

HOW TO DESIGN?ENTERPRISE

BUSINESSMODEL

WHAT TOMARKET?

WHERE TODESIGN?

HOW TO DISTRIBUTE?

HOW TOPRICE?

WHICHMARKETS

TOSATISFY &

WHEN &HOW?

WHEN TO MAKE /PURCHASE?

WHETHER TOMAKE OR BUY?

WHEN TOENTER /LEAVE

MARKET?

WHEN TODESIGN?

HOW TOCAPITILIZE?

CONCEPTTO

PRODUCTION

RESEARCHTO PLAN

WHAT TOMAKE?

WHICH DESIGN?

HOW TOMANAGE

RESOURCES?

ORDER TOCASH

SALESTO

REORDER

Diagram 7.

In order for GM Europe to develop and deploy a usable operations business model, the following conditions were met:

· planning process accountability must be understood (E.G. Who are the decision makers?), documented, and supported by senior management;

· cross-functional participation in the model design, testing, and usage was committed to;· scope, objective(s), and planning horizon(s) were defined in simple terms;· the enterprise representation (people, places, policy, and things) must be understandable and

described in everyday business terms (Diagram 8.); · while a great deal of data may be needed to represent the enterprise, only relevant data should be

collected in earnest;· the model construction and solution must be feasible and timely.

Business Model View

Per CoreProcess,Define:

People

Places

Things

Alternatives

Strategies

Geo-PoliticalIssues

Scenarios

Objectives

Constraints

Rules

Interactions

Legistlation



TOPRODUCTION

RESEARCH TO PLAN

ORDER TO CASH

SALESTO

REORDER

.

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1999 INFORMS Prize Nomination from GM Europe and EDSThis “living” business model of the entire enterprise is easily structured in PLANETSä using the available generic “building block” modeling constructs (Diagram 9.).

Any enterprise can be represented since each “building block” modeling construct provides an additional sub-framework to further define mandatory and optional variable attributes (duration, availability, capacity, status, linkages, financials, quantity, efficiency, etc.).

Virtually all variables that PLANETSä can consider are time-based; this means that these variables have dependencies in all relative past, present, and future time periods; these variables can vary over time, across the model’s planning horizon, providing the ability to dynamically create and evaluate unique scenario combinations as they relate to current and future conditions or potential decisions (with independent, dependent, contingent, or mutually exclusive cross-dependencies). In addition, both calendar year and product (vehicle) model year issues are evaluated. This large, ongoing, reusable model of the GM Europe regional automotive operations is structured around interactive sub-models of core processes and is designed to evaluate all of the stated short term and long term planning issues

“Building Block”Modeling Constructs PLANETS

BuildingBlocks:

Time

Facility

Resource

Product

Routing

Material

Strategy

Geo-Political

Logistics


PLANETS Building Block Modeling Constructs



TOPRODUCTION

RESEARCH TO PLAN

ORDER TO CASH

SALESTO

REORDER

PLANETS Building Block Modeling Constructs

Diagram 9.

TECHNOLOGY SUMMARY ADDENDUM - MODEL INPUT

In describing an enterprise comprising the mammoth scope of GM’s regional automotive operations, a great deal of data is required to define and populate existing and potential products, facilities, tooling, resources, markets, etc.:

· More than 120 existing and potential vehicle products· More than 40 existing and potential manufacturing/assembly locations in over 20 countries· Multiple vehicle-plant assembly alternatives· Hundreds of capacity, flex capacity, manpower, and tooling alternatives· More than 80 country markets for finished product· Production startup / inventory stock / production shortfall analysis· Facility/tooling ramp up and ramp down issues· 100,000 facility-market outbound shipment allocation alternatives

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1999 INFORMS Prize Nomination from GM Europe and EDSBy design, most of this business model input (Diagram 10.) has been automated. Up to 100% of GM Europe’s quantitative input data and modeling scope issues (such as existing and future product program descriptions) which define the business model are maintained in common corporate databases or convenient local databases and are automatically imported into the PLANETSä modeling database when necessary; this includes:

· detailed existing and potential product program descriptions· vehicle product program code· vehicle style (2dr, 3dr, 5dr, etc.)· vehicle driver position (left hand drive, right hand drive)· vehicle brand

· existing and potential product program lifecycles· free market demand, per year for up to ten years, for each specific product description

· by market area / region (Asia-Pacific, North America, etc.)· by market operation / country (Germany, New Zealand, etc.)

· relevant assembly/manufacturing capacity detail, per dedicated assembly line per plant per country· detailed ten year calendar displaying full / partial assigned work days, national and religious

holidays, and other date specific operating assumptions· existing and alternative regular and overtime shift patterns, per calendar day throughout the planning

horizon; this includes complete calendar planning flexibility in defining the number of shifts per day and the number of hours per shift

· manpower availability per time period; this can vary for each time period in the planning horizon· per product line description, per time period, the technical capacity in units per hour for existing and

potential installed tooling· total plant < 75/hour· total line < 50/hour· specific product line flex capacity rates, per product tooling definition

- total Product A < 40/hour- total Product A-3dr < 40/hour- total Product A-5dr < 17/hour- total Product B < 50/hour- total Product B-3dr < 50/hour- total Product B-5dr < 45/hour- total Product A and Product B < 35/hour- total 3-dr < 40/hour- total 5-dr < 40/hour

· interference rates· ramp up / steady state / ramp down rate factors· local operating efficiencies

· cost to produce, per product-tooling-time combination· outbound pipeline stock targets, per product-market-time combination· inventory cost, per product-market-time combination, per activity level· outbound freight cost, per product-market-freight mode-time combination· product pricing is automatically calculated and imported by product-market-time combination

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Input

Input

Via:

PLANETSBrowser

Excel Import

ODBC

Other FileTransfer




TOPRODUCTION

RESEARCH TO PLAN

ORDER TO CASH

SALESTO

REORDER


Diagram 10.

Even though the data is imported into PLANETSä from numerous database sources, a common/shared data entity terminology protocol is enforced for this process to be manageable. In addition, all financial information (ABC-like costs, prices, investments) can be input in local currency for each specific manufacturing or market location referenced; PLANETSä will then perform currency conversion calculations to any base currency management chooses for reporting.

Additional input, such as management policy over-rides, preferences, and alternative strategies can be easily introduced (through PLANETSä modeling system browsers) for any range of time periods in the planning horizon; some examples are:

· specific product-plant-market allocation scenarios· labor agreement constraints / considerations· logic based or quantifiable government regulation impact· “ad hoc’ rules or preferences· specific plant utilization or inventory targets· specific market penetration allocations· timing and investment cost of tooling alternatives, in local country currency· independent, mutually exclusive, contingent, or dependent investment scenarios, scenario sets, or

strategy elements· any enforceable assignment (involving product, plant, resources, markets, and/or time)

TECHNOLOGY SUMMARY ADDENDUM - MODEL GENERATION

Once the business model is defined in the PLANETSä database, actual mathematical models can be generated for “What is?” and “What if?” query analysis. Dependent upon the analysis to conducted, not all of the business model data needs to be accessed. The planner may limit a specific analysis to only a sub-set of products, markets, or facilities. Every time an analysis is made, a unique mathematical model is generated by PLANETSä from the data, using only that portion of the business model data that has been specified for this analysis. So even though a model of the complete enterprise may reside within PLANETSä, only a portion of the data may be relevant for the analysis at hand. PLANETSä is very flexible; if there is a big problem to be analyzed, requiring lots of data, then PLANETSä will create a larger, always unique, mathematical model; if the problem is a sub-set of the enterprise or planning horizon, PLANETSä will generate a much smaller model. Prior to a model generation, the user has full control (through a check-list) of which

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1999 INFORMS Prize Nomination from GM Europe and EDSproducts, markets, facilities, resources, strategies, policies, linkages, and objectives to exclude/include in the analysis; for example, freight and logistics may be relevant for some analysis and unnecessary overhead in others. Likewise, the GM Europe planner controls the planning horizon for this specific model ; perhaps only 2001-2005 is to be analyzed, even though data resides for a complete 1999-2009 planning continuum. This modeling checklist also is where the objectives are set, whether to minimize costs, maximize production, maximize DCF/ROI; the GM Europe models frequently use maximize production and minimize unsatisfied demand as the primary optimization objectives. It is thus possible to run thousands of modeling alternatives from a given PLANETSä business model database.

After the checklist for this specific model generation is completed, the process of solving a PLANETSä for WINDOWS model simply requires the GM Europe planner to “click” on a PLANETSä Generate/Solve icon which automatically conducts the following internal data table generation / population, matrix file generation, matrix solving, and output capture procedures (Diagram 11.):

· The generation of the matrix data tables involves pulling the business model data from the PLANETSä for WINDOWS database and automatically putting it in a format that MathPro 2000ä (MathPro Inc.) can import to populate the tables in the Matrix Schematic.

· Once the MathPro 2000ä tables are populated, the Matrix Schematic is used to generate the matrix file to be read by an optimizer.

· PLANETSä for WINDOWS use the XPRESS-MPä optimizer (Dash Associates Ltd.), one of the best available commercial solvers. The XPRESS-MPä optimizer fully supports Mixed Integer Programming including binary variables, general integer variables, semi-continuous variables, and special ordered sets. It has state-of-the-art branch and bound search strategies modifiable by the user. It also has high performance Newton Barrier Interior Point linear and quadratic optimizers complementing the advanced Simplex Mixed Integer Programming solver.

· Using the MathPro 2000ä generator and the XPRESS-MPä optimizer, PLANETSä for WINDOWS has been able to generate and solve problems with the order of 100,000 continuous variables and 30,000 constraints, and hundreds of integer variables, in a few minutes. The ability to serve as a PC-based modeling platform to develop and solve mathematical representations of a global enterprise model is a reality.

· The initial optimization output solution is internally stored in an XPRESS-MPä output file.

Matrix Generator / Matrix Solver


MathPro 2000TM

XPRESS-MPTM


TOPRODUCTION

RESEARCH TO PLAN

ORDER TO CASH

SALESTO

REORDER


MATRIXGENERATOR

MATRIXSOLVER

Diagram 11.

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1999 INFORMS Prize Nomination from GM Europe and EDSTECHNOLOGY SUMMARY ADDENDUM - MODEL OUTPUT

After the optimal mathematical solution has been generated, PLANETSä automatically and internally directs MathPro 2000ä to interpret the solution provided by XPRESS-MPä and put it in a format that PLANETSä for WINDOWS can use to generate end-user business reports (typically in Excel).

Since an enormous amount of output data is available for review (Who made/shipped what? When?, Where?, In what quantity?, etc.), a great deal of the GM Europe and EDS effort has been targeted on communicating this information the best way possible, to different audiences. The output of the optimization models literally contains detailed operations planning information supporting all facilities, resources, products, and markets for each time period (usually annually) across the entire planning horizon. For this GM Europe application, EDS planning consultants further developed and integrated a series of Visual Basic macros to generate and format Excel reports, callable from within the PLANETSä decision support system, that are straightforward and easy to read by GM Europe planners and management (Diagram 12.). Some of these reports are of GM Europe fixed textual or graphical format, others leverage the flexibility of Excel pivot table formatting.

Output

Output

Via:

ExcelExport

CPS

ODBC

Other FileTransfer

Types:

Financials

Forecasts

Utilizations

Allocations

Diversions

OperatingPlans

StrategySelections

Timing

Capital Plan


MathPro 2000TM

XPRESS-MPTM


TOPRODUCTION

RESEARCH TO PLAN

ORDER TO CASH

SALESTO

REORDER


MATRIXGENERATOR

MATRIXSOLVER

Diagram 12.

Basically, the following types of operational planning reports are typically generated:

· Deliveries Retail volume, per product, per plant, per market, per time period· Production by market Per product, per market, per time period, (per plant)· Production by facility Per plant, per product, per time period· Production by tooling Per plant, per tooling/resource, per product, per time period· Resource utilization % % utilization, per plant, per resource center type, per time period· Diverted shortfalls Allocation of unsatisfied (unmakeable) market demand, by time

period· Adjusted demand Diverted volume, how much diverted from what (product-market-

time)to what (product-market-time) if production limits

· Strategies selected Policy and/or capital investment strategies selected, per time period;basically includes: What assets were added, deleted, or modified?When? What amount capital was required, by asset category?

· Financial reports - DCF Discounted cash flow, by facility, by time period· Financial reports - revenue Per product, per market, per time period· Financial reports - costs Fixed and variable costs, per facility, per product, per time period· Financial reports Transfer pricing, per product, per time period

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1999 INFORMS Prize Nomination from GM Europe and EDSIn addition to these types of reports, planning databases are also generated as output. Periodically, the GM Europe business planning process is focused on evaluating the impact of new product or market forecasts on the existing plan. This results in an analysis process to capacitize or productionize an unmakeable free market demand volume forecast into a makeable restricted volume market demand forecast; this process generates two distinct databases (one has a production focus, the other a marketing/sales focus):

· Output - A production forecast database· A mixed-integer mathematical model optimizes tooling selection and allocation while

generating a database containing a “makable” production plan with product-plant production volume allocations/schedules, a product-plant-tooling production allocation forecast, and an annual production stock/inventory determination, per year.

· Output - a marketing deliveries forecast database· Given buy-in to the above production plan, a more elaborate linear programming model

then generates another database containing the detailed product-plant-market operation delivery shipment plan, which stores the volume of each product to be shipped from each plant to each specific market, per year.

· These model output generated databases are currently used by different GM Europe functions, including manufacturing, planning, finance, and marketing sales.

CONCLUSION

The value of MS/OR to the GM Europe organization has been proven. The benefits are real and the methodologies and technologies have been intelligently integrated into the mainstream planning processes (Diagram 12.). These are not one-off modeling applications; they see duty week in and week out, year after year, with a continually changing cast of planners entering and leaving the scene. In essence, these sophisticated MS/OR applications, developed and delivered by EDS, have become institutionalized within the GM Europe business processes.

In the future, the modeling and planning process experience gained by GM Europe and EDS offers the opportunity for additional MS/OR activity and improved decision making in the areas of:

· Powertrain and component planning· Short term schedules and materials management· Capital planning· Product portfolio development· “Ad hoc” studies such as facility site selections, make-versus-buy analyses, resource allocations, etc.

Support relevant cross-functional and cross-geographic impact analysis processes thatdevelop optimal operational plans across thetotal planning horizon

VALUE OF MS/OR

TIME

Diagram 12.

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15


16


17


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