Certified Professional Logistician LIFE CYCLE COST (LCC) REDUCTION FROM RAM AND SUPPORTABILITY ANALYSES IN ACQUISITIONS This topic will emphasize Life Cycle Cost (LCC) reduction using Reliability, Availability, Maintainability (RAM) and supportability analyses in acquisitions. Use of a supportability optimization model in cost estimates helps to analyze the impact of RAM and Supportability on LCC. Bernard Price Certified Professional Logistician

Notional System LCC Overview 100 LIFE CYCLE COST (LCC) DETERMINATION 80 APPROX 90% OF LCC DETERMINED 60 Cumulative Percent 40 ACTUAL FUNDS SPENT This chart notionally shows how Life Cycle Costs (LCC) are accumulated over the system’s life cycle versus how Life Cycle Costs are determined by product design and supportability decisions made much earlier in the system’s life cycle. By the time Milestone B is reached, about 70% of the Life Cycle Costs are determined by decisions already made. The use of the ASOAR model helps to determine RAM requirements, which should help to influence some cost effective decisions prior to Milestone B. By the time Milestone C is reached about 90% of the LCC has been determined by decisions already made while approximately 10% of the LCC has been spent. The use of COMPASS and SESAME to optimize supportability helps to make cost effective decisions prior to Milestone C. Most of the actual LCC spending occurs after Milestone C, where money is spent to pay for production items and the many years of recurring support costs after fielding the systems. 20 APPROX 10% OF TOTAL COST Milestones A B C PRODUCTION OPERATION & SUPPORT

Total Ownership Cost Categories Identified Logistics Costs & Non-Logistics Costs Regardless of Fund Type “It’s all green” OPA RDTE OMA MPA In developing a Logistics Cost Estimating Tool that tied closely to Logistics community needs, Total Ownership Cost (TOC) categories had to be defined. The numerous DoD Life Cycle Cost (LCC) elements were condensed down to 25 logistics costs categories and 15 non-logistics costs categories, regardless of fund type or budget appropriation. DoD LCC estimates are based on an analysis by fund appropriation. However, by counting money as money because it is all green, equipment LCC can be minimized. Optimization models can be then be used to support decisions that reduce LCC. Managing by appropriations will not yield an optimal LCC results. For instance, if a small investment in R&D or Procurement funds will yield a large savings in O&S funds, budget constraints in the R&D or Procurement appropriations may preclude a cost effective decision that dramatically lowers LCC. The total ownership cost categories were cross referenced to DA LCC elements to assure that all Life Cycle Costs were covered. Cross Referenced to DA LCC Elements 1.09, 2.02, 2.05, 4.01, 5.01, 5.04...

Non-Logistics Cost Categories Non-Logistics Cost Categories (Potential Investment Cost Areas) Development Engineering Producibility Engineering & Planning Development Tooling Prototype Manufacturing Systems Engineering & Project Management System Test & Evaluation Data/Reports Development Facilities Software Development Non-Recurring Production Recurring Production Production Engineering Changes Other Development Costs Other Production Costs Military Construction This chart lists 15 Non-Logistics cost categories. Non-Logistics costs support the development and production of the equipment. Some of these costs may apply as investment costs for a design improvement.

Logistics Cost Categories Logistics Cost Categories (Initial Costs - Red & Recurring Costs - Black) Operators Energy (POL & Batteries) Field Support Repair Labor Contractor Logistics Support Warranty Costs Scheduled Maintenance /Overhaul Initial Provisioning Replenishment Spares Inventory Holding Costs Support Equipment Test Program Sets System Specific Training Training Materials Post Production Software Support Technical Documentation Transportation Integrated Material Management Post Production Systems Engineering/Project Management System Hardware Changes Facilities/Sites Activation System Specific Base Operations Lease Operations & Maintenance Demilitarization/Disposal Industrial Readiness This chart lists the 25 Logistics Cost categories. Logistics costs support equipment use and readiness. Most logistics costs are recurring Operating and Support (O&S) costs that repeats as yearly or annual expenses. However, some of the listed logistics cost categories highlighted in red are investment costs in production dollars needed for setting up equipment supportability to maintain readiness. Those categories that are predominantly investment costs may include Initial Fielding Support, Warranty Costs, the Initial Provisioning of spares, Support Equipment or Test Program Set Development, New Equipment Training and Materials, Technical Documentation and Facilities or Sites Activation.

Supportability Costs Impacted by RAM Warranty Costs Level of Repair Analysis: Organic Repair Costs Contractor Logistics Support Costs Initial Provisioning of Spares & Repair Parts Replenishment of Spares & Repair Parts Inventory Holding Costs of Spares Transportation Costs for Forward & Retrograde Shipments Source of Repair Analysis: Support Equipment – Common & System Specific Test Program Sets Technical Documentation for Repairs Supportability costs impacted by Reliability, Availability and Maintainability (RAM) are listed on this slide. COMPASS will cover all the Level of Repair Analysis (LORA) and Source of Repair Analysis (SORA) listed costs. The worth of a warranty is the only reliability dependent cost not estimated by COMPASS. Equipment RAM in a LORA computes organic repair costs, contractor logistics support costs, the initial provisioning of spares and repair parts, the replenishment of items washed out or replaced rather than repaired; inventory holding costs associated with the stocking of spares; and transportation costs associated with the shipping of spares forward and the retrograde shipping of items removed from the equipment. A SORA computes costs associated with how an item should be repaired. Equipment RAM impacts support equipment costs. Some support equipment options may include using common test equipment, developing system specific test equipment or developing Test Program Sets (TPS). All these alternatives have different investment costs and RAM related recurring costs. Those alternatives with higher investment costs like special test equipment development or TPS development need to be used in many repair actions to generate enough savings to justify their development. Technical documentation for repairing can also vary based on the test equipment selected.

Types of Analyses to Support Decisions Best Value Analysis – Rates & Weights Multiple Factors to Evaluate the Benefits & Cost of Each Alternative (Source Selections & Pre-MS B) Logistics Support Optimization Analyses –Lowest Net Present Value Total Cost among Support Alternatives to Achieve the Same Ao (Pre-MS C) Economic Analysis - Evaluates the Return on Investment of an Alternative to Status Quo (After Design Frozen & Level of Repair Established) Alternatives should be evaluated before a business decision is typically made. This slide lists some types of analysis methodologies that may be applied to support decisions. A typical Best Value Analysis (BVA) often weights and rates multiple performance factors to evaluate the benefits along with the cost of each alternative. This type of BVA is used in competitive source selections and is a good methodology to apply when performance capabilities may significantly differ among alternatives, which may make it a recommended methodology for Performance Based Logistics (PBL) Business Case Analyses (BCAs) prior to Milestone B. Logistics Support Optimization (LSO) analyses apply models using a consistent quantitative basis of comparison. It determines the lowest net present value total support cost among supply and maintenance concept alternatives to achieve the same system Operational Availability (Ao) performance level. Since item level data is needed for LSO analyses, they are best applied after Milestone B until the design is frozen. A key outcome of an economic analysis is the Return On Investment (ROI) of the improvement compared to the status quo. An economic analyses is best applied after the equipment design is frozen or after the Level of Repair is established by the Logistics Support Optimization analysis.

Return on Investment (ROI) ROI = Net Present Value Savings of Improvement / Net Investment Cost for Improvement Net Present Value Savings from Recurring Cost Differences of Improvement vs. the Status Quo Net Investment Costs covers Improvement Initial Costs less any Remaining Status Quo Initial Costs Alternatives with the Highest ROI are typically worth funding the Improvement Investment Costs A Return on Investment (ROI) is equal to the net present value savings of the reliability or maintainability improvement divided by the net investment cost for accomplishing the candidate improvement. The net investment cost covers the improvement’s initial costs minus and remaining non-sunk status quo initial costs. Alternatives with the highest ROI ratio are typically worth funding to lower the equipment’s Life Cycle Cost.

Reasons for Estimating Life Cycle Costs (LCC) Design Tradeoffs Yield LCC Differences that Aids Decision Making Decisions Made Early Drive Future Supportability and Support Costs Project Managed Acquisition Programs Require Cost Estimates for Financial Planning & Budgeting Quantifying LCC Helps to Identify Drivers This chart explains the main reasons for estimating Life Cycle Costs (LCC). First, design tradeoff analysis yield LCC differences that aid cost effective decision making. Also, decisions made early in the acquisition cycle drive future supportability and support costs. Additionally, project managed acquisition programs require LCC estimates for financial planning and budgeting. Computing the LCC helps to identify cost category drivers. However, if the LCC is and estimated from reliability, availability, maintainability (RAM) factors using supportability optimization modeling, then life cycle costs can be managed and reduced. Using RAM driven Logistics Support Optimization modeling in the LCC estimate helps to identify which items and product support factors are cost drivers and can measure their LCC impacts. This permits performance of supportability analysis to be an integral part of systems engineering. If RAM LCC impacts are measured, LCC can be managed and reduced

Army LCC Management Models to be Discussed COMPASS* LOGSA Computerized Optimization Model for Predicting & Analyzing Support Structures ACE IT* DASA(CE) Automated Cost Estimating Integrated Tools LCET* CE LCMC Logistics Cost Estimating Tool (Includes Time Phased COMPASS) * TOOLS ARE LINKED FOR INTEGRATED LCC ESTIMATING The Army Simulation and Modeling for Acquisition, Requirements and Training (SMART) initiative emphasizes using models to improve collaboration, improve readiness and reduce Total Ownership Costs. This chart lists names and acronyms of three related, generic Army Life Cycle Cost management models to be discussed. These models can be provided to contractors at no cost. The Computerized Optimization Model for Predicting and Analyzing Support Structures (COMPASS) and Automated Cost Estimating Integrated Tools (ACEIT) are Army standard models. The Logistics Cost Estimating Tool (LCET), developed by the CE LCMC Systems Analysis Division, is also downloadable from the web. The LCET was developed to provide full logistics support cost estimating and the capability to electronically link the Army standard models. As linked models, COMPASS, ACEIT and LCET can be used together to provide an integrated approach to optimize supportability and concurrently compute life cycle costs.

ACE IT Usefulness Integrates Cost Estimates or Data From Other Computer Programs Often Used for Program Office Estimates & LCC Estimates Provides Credible Estimates for Time Phased Non-Logistics Acquisition Costs This slide introduces the usefulness of Automated Cost Estimating Integrated Tools (ACEIT). ACEIT is an Army standard model for Life Cycle Cost (LCC) estimating. It has the capability to integrate cost estimates or data from other computer programs. ACEIT is the tool of choice by the Air Force and Army Cost Analysis communities used for generating Program Office Estimates or LCC Estimates for Project Managers. ACE IT use by Cost Analysts tend to provide credible estimates for equipment development or production acquisition costs. However, the Cost Analysis community use of ACEIT has yielded less credible logistics support cost estimates. For instance, initial provisioning sparing typically applies a simple cost estimating relationship based on a percent of the end item cost. This type of cost estimate lacks correlation to equipment’s reliability or its readiness performance. The Deputy Assistance Secretary of the Army for Cost & Economics (DASA(CE)) is the Army proponent of this tool.

LCET Model Usefulness More Credible Logistics Costs in LCC Estimates Time-Phased COMPASS Module Results Yield Highest Fidelity Support Cost Estimates Relates Item Reliability to Readiness & Support Costs Adjusts Results for Worth of Warranty Logistics Cost Spreadsheet Module Covers Macro-Level Logistics Costs w/o Item Level Reliability Non-COMPASS Logistics Costs After Items Known Merges Multiple Runs of Different Time Frames Links COMPASS & ACE IT to Permit Concurrent Supportability Optimization & LCC Estimation This slide introduces the usefulness of the Logistics Cost Estimating Tool (LCET). The LCET model was developed to provide more credible logistics costs estimates in the Life Cycle Cost (LCC) estimate. LCET contains two distinct modules. The Time Phased COMPASS module electronically imports a selected COMPASS run and computes its annual support costs accounting for the time phased fielding of systems. This yields high fidelity support cost estimates that relates item reliability to readiness and optimized support costs. LCET also computes the worth of a warranty to adjust Time Phased COMPASS results. The LCET also contains a user friendly Logistics Cost Spreadsheet module with built-in help and computations. Since this module does not rely on item level data, its built-in computations may be used early in the acquisition cycle to estimate logistics costs. LCET also provides logistics cost estimates not covered in COMPASS. LCET has the capability to merge multiple COMPASS runs to permit separate analyses over different time frames in the life cycle. Besides linking to COMPASS, LCET results can also be electronically exported into ACEIT to permit concurrent supportability optimization and more credible LCC estimation.

Logistics Costs Coverage Since COMPASS is a Level of Repair Analysis model, costs that do not vary by maintenance policy are not estimated. The right hand side of this table covers the COMPASS supportability cost categories impacted by Reliability, Availability, Maintainability (RAM). Logistics costs covered in the Logistics Cost Spreadsheet are listed on the left hand side of this table. The Time Phased COMPASS module in LCET covers just 10 of the 25 logistics cost categories, but it covers these costs with more equipment design breakdown fidelity than the Logistics Cost Spreadsheet estimates. This fidelity in COMPASS permits a RAM analysis of the detailed design to reflect the cost impacts associated with each item in the equipment. A reliability improvement being considered to the design can also be compared to baseline design to assess its potential impact to reduce life cycle support costs. Time Phased COMPASS Covers 10 of 25 Logistics Cost Categories With More Fidelity Than the Logistics Cost Spreadsheet Module

What Each Model in Integrated Tool Set Determines COMPASS - Optimizes Viable Support Concepts to Ao Least Cost Initial Provisioning 2-Level vs. 3-Level Maintenance Return LRU vs. SRU Organic vs. Contractor Repair vs. Throwaway Time Phased COMPASS - Annual COMPASS Costs LCET Spreadsheet - Adds in Other Logistics Costs ACEIT – LCC Tool Adds in Non-Logistics Costs The integration of COMPASS, LCET and ACE IT provides a generic, structured approach to optimize supportability and compute LCC concurrently. This chart lists what each model in the integrated tool set determines. COMPASS optimizes among viable support concepts to achieve an inputted Ao goal. It determines the least cost initial provisioning associated with each potential maintenance concept. COMPASS also optimizes among maintenance tradeoffs to determine whether it is more cost effective to use 2-level or 3-level maintenance support, whether the Line Replaceable Unit (LRU) or its Shop Replaceable Units (SRUs) should be returned to depot for repair, whether depot repair should be organic or contractor, and whether an item should be economically thrown away instead of repaired. The Time Phased COMPASS module in LCET can be used to estimate COMPASS support costs on an annual basis based on end item fielding schedules and the support concepts considered. The Logistics Cost Spreadsheet module in LCET adds in estimates of other logistics costs not covered by COMPASS. Finally, ACEIT becomes the LCC tool that adds in estimates of the non-logistics acquisition costs. Optimizes Supportability & Computes LCC Concurrently

Improving Supportability Analysis & LCC Estimating Concurrently Logistics Cost Estimating Non-Logistics Cost Estimating Supportability Analysis ACEIT N/A Red Green* COMPASS Green Yellow N/A LCET N/A Green N/A This chart recaps the big picture for using the electronically linked models as one integrated tool. The ACEIT is providing the Cost Analysis community with a capability to do a good job in estimating non-logistics development and production costs, but is weak in estimating logistics costs. The COMPASS model does a good job with supportability analysis, but only covers the steady state, RAM driven logistics costs. The Time Phased COMPASS module in LCET improves the cost estimating portion of COMPASS. The Logistics Cost Spreadsheet module in LCET improves on the logistics cost estimates not covered by COMPASS. This integration of analyses and cost estimates provides a significant improvement over any Government model existing today for evaluating product support and design tradeoffs to life cycle costs. Integrated/Linked Models Green Green Green*

Acquisition Policies Supported by Integrated Tools DoD Policies: Perform Design & Supportability Tradeoffs to LCC Perform Supportability Analysis Integral to Systems Engineering Aid Performance Based Logistics Implementation for Product Support Army Policies: Manage TOC Reduction Evaluate TOC as a Factor in Source Selection Makes Supportability Co-Equal to Cost, Schedule & Performance This chart highlights Department of Defense (DoD) and Department of Army (DA) acquisition policies supported by the integrated tools. The integration of support concept optimization with LCC cost estimating helps to implement the performance of design and supportability tradeoffs to LCC. The use of COMPASS and LCET also permits the performance of supportability analysis to be integrated with systems engineering. Since COMPASS optimizes the cost of logistics support functions to maintain an Operational Availability/Readiness goal, it aids Performance Based Logistics implementation in acquisitions for Product Support. Army policies emphasize Total Ownership Cost (TOC) reduction management in acquisitions. The integrated models can help to assess and manage cost drivers or improve TOC reduction decisions with comparative LCC assessments of the present design and a potential change. Army policy even looks for the potential to evaluate TOC as a factor in source selections. Using the integrated models in the systems engineering process is a good way to make supportability a co-equal to cost, schedule and performance in acquisitions.

Source Selection Example Is “Outstanding” Product Support Worth $5M? Offeror A Offeror B Product Support Past Performance This chart provides an example to show why it may be worth the extra effort to evaluate Product Support Costs or Total Ownership Costs (TOC) during the Source Selection process. In this particular example, Offeror A has an Outstanding product support proposal and Offeror B has a Good product support proposal. However, the contract cost of Offeror A is $25M and the contract cost of Offeror B is $20M. The leads to the bottom line question that asks “Is an ‘Outstanding’ product support proposal worth the $5M difference?” Technical Contract Cost $25M $20M

Source Selection Example Is “Outstanding” Product Support Worth $5M? Offeror A Offeror B Product Support Past Performance By modeling Product Support Costs and projecting its impact on TOC, the answer to the bottom line question as to whether an “Outstanding” product support proposal is worth the $5M difference becomes apparent. Since some Product Support Cost estimates are not part of the Contract Costs, it is possible to count those softer cost estimates as being worth some percentage of harder Contract Cost bids. Regardless, in this example, it shows the weighted TOC of Offeror A to be significantly less than Offeror B. Therefore, Offeror A can be found to have the Best Value proposal. The modeling and evaluation of Product Support Costs or TOC becomes more significant if ratings for all the other source selection factors are close. Yes! Technical TOC $50M $60M

Source Selection Modeling Alternatives Advantages Disadvantages Easy For Bidders/Contractor Can Be Used Over Life Cycle Common Baseline Encourages Meeting Modeling Objectives Ease Of Evaluation Proven/Validated Technique Govt. Needs To Validate/Understand Prolongs Evaluations Lack Source Selection Common Baseline More Upfront Work for Bidder/Contractor Chance of Initial User Error Everybody Uses Their Own Model One way to quantify and estimate Product Support Costs or TOC is to use generic models or tailored spreadsheets. Both the Government and industry have existing models available to perform this type of analysis during source selection in competitive acquisitions. This chart lists the advantages and disadvantages of each bidder or contractor using the models of their choice or requiring the bidders/contractors to use the same Government furnished model. One main problem with every offeror using their own model is that the Government needs to understand each model. This could significantly prolong evaluation time. Another key disadvantage is that the lack of a common evaluation methodology baseline can lead to successful protests. If the Government provides the selected model and uses an evaluator that knows how to apply the tool, these key disadvantages are overcome. Also, using Government furnished model encourages the bidders or contractors to meet the customer’s modeling objectives to reduce TOC or optimize supportability. Using a common analytical methodology leads to better teaming and communications within Government and between Government and industry. To minimize initial user errors, the Government may provide training and a help desk for the free tools being furnished. Based on the advantages and disadvantages, it becomes apparent that it is better for the Government to furnish their evaluation tool rather than having each bidder or contractor use their own model. Use Govt. Selected Model

Reasons Contractors Should Use Integrated Tools in Acquisitions Provides a Common Evaluation Baseline among Bidders Expedites Evaluation by Government After Data or Analyses are Obtained Improves Government/Industry Teaming with Common Analyses Permits Contractor to Determine an Optimum Support Effectiveness/Logistics Chain Structure & LCC Baseline Permits Contractor to Evaluate the Impact of Proposed Changes to a LCC Baseline This chart lists some reasons why contractors and the Government should use the integrated tools in acquisitions. Besides being available to all Army contractors at no cost, these tools provide one common evaluation baseline among all bidders in competitive source selections. Since the Government evaluator should know the models used, this will expedite evaluations after data or model runs are obtained from the bidders or contractor. Additionally, common analyses may help the Government to update its own Life Cycle Cost (LCC) estimate and improve Government and industry teaming to make better acquisition support decisions. Using the integrated tools provides a RAM driven LCC baseline estimate. This also permits the contractor and Government to evaluate the impact of a proposed Reliability, Maintainability or Supportability change to the LCC baseline to quickly assess whether this potential change is worthwhile to implement.

Data Required to Analyze TOC Appropriate Data is Needed to estimate Government & Contractor Responsible Costs Data Depends on Proposed Contractor Support When contractor fixes end items, only end item level data needed When Govt fixes end items & Contractor fixes LRUs, need to know how often LRUs are removed and costs for LRU repair When Govt fixes LRUs with SRUs, need to know how often LRUs & SRUs are removed and costs for their repair or replacement The data required to analyze TOC estimates depends on who repairs the equipment to estimate the Government and contractor responsible costs, and not just the cost of the contract. The level of detail needed and tool use for modeling depends on proposed contractor support. When the contractor fixes end items, only end item level data is needed. When the Government fixes end items and the contractor repairs Line Replaceable Units (LRUs), information about how often LRUs will be removed and costs associated with end item and LRU repair are needed. When the Government fixes LRUs with SRUs, that is when all the detailed data for each LRU and the high failure rate SRUs will be required.

When A Tailored Spreadsheet Is A Good Evaluation Alternative Contractor Repaired End Item Small Number of Known TOC Driver LRUs that are Contractor Repaired Legacy End Item where Maintenance is Not a TOC Driver These are instances where the use of generic Army models can become an overkill for a source selection evaluation. For those cases where a standard model requires more inputs than necessary, a tailored spreadsheet is a good evaluation alternative. For the case of a contractor repaired end item, the maintenance concept is known and only one item has to be analyzed. Data below the end item level of indenture is not needed. This is when a tailored spreadsheet becomes ideal for estimating the Total Ownership Cost (TOC) in a solicitation. The Defense Advanced GPS Receiver (DAGR) solicitation potentially used a tailored spreadsheet for this type of source selection evaluation. A spreadsheet may be appropriate when there are a small number of known TOC driver items that are all contractor repaired or thrown away. For this case, the maintenance concept is known and the costs of just a few items have to be analyzed. For a legacy end item with maintenance costs not being a significant TOC driver, a tailored spreadsheet is also appropriate because item level repair costs and the initial provisioning spares cost of items are not important to capture. The AN/PRC-112 Radio modification, with a few key TOC drivers needing evaluation, successfully used a tailored spreadsheet for this type of source selection evaluation.

Which Integrated Tool Combo to Use for TOC Evaluation ACEIT & LCET - In Development Prior to Knowing LRUs ACEIT, LCET & COMPASS – In Development or LRIP When LRUs Known & Government Repairs End Item LCET & COMPASS – In Production or Re-Procurement If Maintenance is a TOC Driver This slide covers which integrated tool combination to use for Total Ownership Costs (TOC) evaluation. Since ACEIT and LCET do not require LRU level data, these models may be used together earlier in development prior to knowing the equipment’s LRUs. ACE IT, LCET and COMPASS are typically recommended for evaluating the Life Cycle Costs (LCC) during Engineering Development or Low Rate Initial Production (LRIP) when LRUs become known and the Government repairs the end items. The ACE IT is not typically needed to estimate LCC in Production or later because the non-logistics development and production costs are either sunk, known or proposed. Therefore, LCET and COMPASS may be recommended for use in Production or end item re-procurements if their maintenance or initial provisioning spares costs are a TOC driver.

Source Selection Plan Evaluating Total Ownership Costs TECHNICAL PRAG TOC* COST/PRICE FACTORS CONTRACT COSTS/PRICES GOVT COSTS CONTRACTOR COSTS MANAGEMENT SUBFACTOR SUBFACTOR COST REALISM (if not Fixed Price) This chart pictures one potential way for evaluating Total Ownership Cost (TOC) in competitive solicitations. TOC evaluation goes beyond the evaluation of contract price by considering Government organic costs and downstream contractor costs beyond the contract period. If these costs are evaluated separately from contract costs, then contract costs may be given a different weighting factor. By law, the contract price is quantitatively evaluated. However, estimating TOC with the contract price is a more effective way to establish best value. The source selection evaluation may separately require each bidder to offer a plan for reducing TOC or sharing data with the Government under a management sub-factor. It can also be priced out separately if covered by optional data items while still in competition. This is recommended if it is desired to continue improving the system design after contract award. Contractor data sharing of the TOC factors that they control is recommended if the Government wants to manage TOC reduction. The Thermal Weapon Sight and Enhanced Night Vision Goggle source selection evaluations used both the COMPASS and LCET to evaluate logistics support cost. ACEIT was not needed because the production acquisition costs were proposed by the bidders precluding the need to estimate the non-logistics costs. TOC REDUCTION PLAN DATA SHARING PLAN COST ADJUSTMENTS TECHNICAL INPUT RISK FACTORS COST INPUT RISK FACTORS * TOC EVALUATION RESULTS IN AN ESTIMATED AMOUNT OF DOLLARS

Costs that Tend to be Drivers in Many Systems Non-Logistics Costs: Software Development Recurring Production Cost Logistics Costs: Post Deployment Software Support Replenishment Spares Contractor Logistics Support - or - Organic Repair Before identifying some typical cost drivers that tend to be Life Cycle Cost drivers in many systems, it must be stressed that TOC drivers vary on a system by system basis. However, there are some cost drivers that may apply to many systems. These drivers may be non-logistics acquisition costs as well as logistics costs. The costs for Software Development and Post Production Software Support are often significant. The Recurring Production cost for equipment is frequently a major cost. Replenishment Spares, Organic Repair and/or Contractor Logistics Support costs also tend to be TOC drivers on many systems.

Logistics Cost Drivers that Tend to Vary by System Systems with Platforms Operators System Specific Training Energy – POL Man-pack Equipment/ Some Sensors Energy - Batteries Low Reliability or High Operational Availability Initial Provisioning Inventory Holding Costs (Frequent Item Upgrades) Long Term, Failure Free Warranties Warranty Costs This chart lists some cost drivers generally applicable to specific types of systems or scenarios. For systems with platforms, Operators will typically be a cost driver. System specific training may also become significant. Petroleum, Oil and Lubrication (POL) will often be a cost driver for moving platforms and generators. Man-pack equipment and some sensors often have batteries as a cost driver. Low reliability or high operational availability systems tend to have Initial Provisioning and Inventory Holding costs as major costs; especially when these systems have frequent item upgrades causing a high obsolescence rate for spares. For programs with long term, failure free warranties, warranty costs can be significant.

Logistics Cost Drivers that Tend to Vary by System Low Density, Highly Complex Equipment System Engineering/Program Management Integrated Material Management High Density, Highly Complex Systems System Specific Training Training Material Development & Maintenance Some Secure, Sensitive Systems Facilities/Site Activations System Specific Base Operations This chart continues to list some cost drivers generally applicable to specific types of systems or scenarios. For low density, highly complex systems, personnel costs associated with Systems Engineering, Program Management and Integrated Material Management are major costs. For high density, highly complex systems, system specific training and training material development & maintenance tend to be major costs. Some secure, sensitive systems may require expensive Facility or Site Activations and System Specific Base Operations.

Source Selection Plan Evaluating Total Ownership Cost Drivers COST/PRICE TECHNICAL PRAG FACTORS MANAGEMENT SUBFACTOR TOC DRIVER METRICS* CONTRACT COSTS/PRICES TOC REDUCTION PLAN DATA SHARING PLAN This chart pictures an alternative Source Selection Plan for evaluating TOC in competitive solicitations. This alternative emphasizes the evaluation of TOC drivers and considers their evaluation under the technical evaluation factor. Since this factor applies a qualitative or adjectival rating, threshold quantities for unacceptable, acceptable, good and outstanding ratings must be established. This optional plan is much simpler because it evaluates the TOC driver metric rather than estimating the TOC. For example, when the FIREFINDER was to be redesigned, the Government wanted to know the bidder’s proposed design impact on the number of operators needed because Military Operator Costs drove the FIREFINDER system TOC. COST REALISM (if not Fixed Price) TECHNICAL INPUT RISK FACTORS COST INPUT RISK FACTORS * TOC EVALUATION RESULTS IN AN ADJECTIVAL RATING FOR QUANTITATIVE THRESHOLDS

How Current Acquisition Practices Can Improve Analyze System Reliability and Operational Availability Requirements Use Government Ao Driven LCC Models for Best Value Decisions & Plan to Encourage Industry to Use Them Use TOC and/or Ao as an Evaluation Factor in Source Selection Provide Incentives to Industry for TOC Reduction Establish a Shared Data Environment To summarize what was discussed involves some changes to current acquisition practices within the acquisition process to make supportability a co-equal to cost, schedule and performance. First, system reliability and/or operational availability (Ao) should be used as a Performance Based Logistics (PBL) approach in acquisitions to help optimize product support supply and maintenance concepts prior to fielding. The Government should plan to furnish their Ao driven supportability optimization models and LCC estimating tools for best value decision making while improving the teaming across different communities. Using TOC or Ao as an evaluation factor in Source Selections should be pursued in acquisitions where appropriate. In addition to competitive source selection, the Government can consider using contract incentives for reducing TOC or improving reliability during the contract. Finally, establishing a shared data environment between the contractor and Government is important for analyzing and managing product reliability and TOC reduction because both the Government and industry contribute to factors that drive the equipment’s LCC and readiness.

Influence of RAM and LCC Reduction on System Cost Effectiveness Probability System Performs Appropriately In Mission (A) Product Effectiveness Probability System Lasts Mission Without Failing (B) System Effectiveness Probability System is Available to Accomplish Mission (C) Support Effectiveness System Cost Effectiveness Design Product to Reduce Life Cycle Costs (Relates to A, B & C) This diagram provides a macro-level view of the influence of RAM and Life Cycle Cost (LCC) reduction on System Cost Effectiveness. System effectiveness depends on the provability the system will perform appropriately in a mission, the probability the system will last the mission duration without failing, and the probability the system will be available for accomplishing missions. The probability that a system last the mission without failing depends on its reliability. The probability that a system is available to accomplish missions is its Ao or operational readiness rate. Cost effectiveness reduces the system’s LCC. Designing the product to reduce LCC introduces product design tradeoffs with regards to system performance factors, reliability or maintainability. For Performance Based Logistics (PBL) acquisitions, a Business Case Analysis (BCA) is applied to designing the system to reduce LCC. Determining the LCC savings and Return On Investment impacts of improved reliabilities may be one form of BCA. A logistics support effectiveness optimization maybe another form of BCA. Both system effectiveness and cost effectiveness impact system cost effectiveness. Cost Support Effectiveness Optimization (Relates to B & C) Effectiveness Basically Contractor Responsibility Typically Government and Contractor Responsibility