MINISTÈRE DE LA DÉFENSE MOPSOS : predicting acquisition cost of armoured vehicles 11-1.

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Presentation transcript:

MINISTÈRE DE LA DÉFENSE MOPSOS : predicting acquisition cost of armoured vehicles 11-1

SDA/EC 11-2 CONTENTS I.INTRODUCTION II. COST ESTIMATE III.MOPSOS MODEL IV. MOPSOS SOFTWARE V.CONCLUSION

SDA/EC 11-3 COST FORECASTING IN DGA Cost analysis department : DPM/SDA/EC Cost estimators Purchasing and cost analysis departments (AEC) Aircraft (SPAé) Ships (SPN) Tactical missiles (SPMT) Ground (SPART) Space & electronics (SPOTI) Nuclear (SPNuc) Direction of Programs, acquisition Methods and quality Purchasing sub-direction

SDA/EC 11-4 COST ANALYSIS DEPARTMENT Purchasing In the Purchasing sub-direction Audit : companies general rates, post costing, audit of contractor proposals Procurement cost forecasting : for programs departments, parametric methods (universal and specific), analogy Cost databases : Structure, tools, contents

SDA/EC 11-5 Cost estimate principles Compute an accurate amount of money for a product 3 steps to estimate the cost of a new product To know the product and the acquisition environment To compare with similar known product To extrapolate from known product to new product 3 forecasting methods Analytic way : unit comparison : hours, material, … Analogy : global comparison Parametric way : use of statistical models

SDA/EC 11-6 PARAMETRIC METHODS Parametric methods Specific methods Universal methods CERs building models Ex : statistic tools, CCOStat, COST + Specific cost estimate models Ex : FACET, SCOPE, MAEVA... Cost Estimating Relationships (CERs) COST = F(specific parameters) Market cost estimate models Ex : PRICE, MAP General formulas Applicable for all type of products Universal parameters (weight volume, quantity, manufacturing difficulty …) Calibration process

SDA/EC 11-7 COST ESTIMATE RELIATIONSHIPS BUILDING COST = F (PARAMETERS) DATA COLLECTION COST, PARAMETER interview + documentation ANALYSIS, STANDARDIZATION QUANTITIES, RATES, SCHEDULES COST DEFINITION CHOICE OF COST DRIVERS :. weight. volume. range. power.... STATISTICAL TESTS & EXPERTISE Actual cost Estimated cost STATISTICAL METHODS CERs cost = bx cost = a+bx cost = a+bx 1 +dx 2 cost = ab x... CHOICE OF THE BEST CERs FF = c X b quantity unit cost

SDA/EC 11-8 COST ESTIMATE RELATIONSHIPS BUILDING Phase 1 : key phase, time-consuming, iterative process, database Phase 2 : cost normalisation, precise and definite, same monetary unit, same quantity and rate Phase 3 : data analysis, identify cost drivers, parameters that have measurable influence on cost Phase 4 : modelling (regression techniques) several formulas (linear, log-linear, …) Phase 5 : validation, statistical test, domain specialists expertise Phase 6 : Choice of CERs set, use rules

SDA/EC 11-9 Data issues for military governmental organisation Data collection : lack of data (small families), lost data, different sources for technical and cost data, confidentiality Precise definition of costs and parameters Confidence and validity of data Choice of family of products compromise : large family / homogeneous family consistency along time Correlation of parameters modelling troubles

SDA/EC Armoured vehicle Model (MOPSOS) Requirements Very beginning of a project Help tool for preparation or definition choice Quick budget estimate Parameters : linked with cost defined very early by users precise enough Easy and quick to use What-if analysis on parameters

SDA/EC THE MOPSOS MODEL Production cost forecasting tool of armoured vehicles for medium and long term purposes Production cost = F (technical parameters, performances) Historical data of all French Armoured vehicles : Database (50 technical parameters and performances) Set of CERs : A tool (excel) : quick and user friendly Forecasting of future vehicle cost based of technical description What-if analysis : variation of parameter, quantity...

SDA/EC MOPSOS SOFTWARE : INPUT DATA Technical data : main parameters : weight, volume, armament,... additional parameters (secondary) : specific components of the vehicle like type of telemetry, autonomy or equipment on ammunition All these data must be included in the interval of acceptance values derived from the armoured vehicles databases. A type of vehicles may be chosen among 3 (Tank, light armoured vehicle, undetermined)

SDA/EC Economical data : Economical updating can be done by three indices : - the indice steel armoured vehicle - the indice lighted alloy armoured vehicle - or the inflation rate observed in the country between 1989 and the year of updating All these indices are calculated from indices produced by French National Statistical Organisation (INSEE) Learning curve : quantity and rate can be chosen by the user MOPSOS SOFTWARE : INPUT DATA

SDA/EC SOFTWARE RESULTS Twenty results calculated by statistical and non statistical models are resulted from : cost 100 approach, cost per kilograms approach, cost of chassis, cost of turret approach, cost of chassis per kg, cost of turret per kg approach. Examples :Cost 100 = a(weight) b (number of persons) c Cost of chassis = h(horsepower) i Cost per kg = e(shell performance) f (number of persons) g

SDA/EC MOPSOS USE EXAMPLES This model was recently used for 2 programs : the VBCI (Armoured Vehicle for Combat and Infantry) and the PVP (Small Protected Vehicle) updating of MOPSOS model and software with VBCI data It will once again be utilised for the VBMO project (armoured vehicle for maintenance of law and order)

SDA/EC USE RULES AND PITFALLS Belonging to the family (huge technology change, interval of acceptance parameters) Consistency of technical definition - viability of the future product Model up to date evolving model Up dating rules : validity check of the model

SDA/EC FUTURE MODELLING Today : Acquisition cost forecasting models Tomorrow : Integration of ownership cost in MOPSOS model Possible research project : Life Cycle Cost modelling trough statistical techniques

SDA/EC This slide has been deliberately left blank Diapositive intentionnellement blanche

SDA/EC This slide has been deliberately left blank Diapositive intentionnellement blanche