Cost Estimating Tools

My previous blog discussed a “Should Cost” methodology used by PRICE Systems to complete an analysis. In the article I included a chart depicting calibration results for manufacturing complexities for each weapon system (X-Axis). Manufacturing complexities are a major cost driver within the model. This parameter can be derived from model knowledge tables, generators or from calibration. Many times the calibrated results are simply averaged and used for predicting cost for the new system. This assumes that the new system is very similar in technology and performance as the systems used for calibration. In general this is not the case. Below I discuss how data driven cost estimating relationships (CER) can be developed between the calibration results and a selected independent variable. The CER will then be used to derive the manufacturing complexity, which then matches much closer to the new technology.

Figure 1. Calibration Results for each Weapon System

Since the data was already collected and calibrated within the model, the next step was to identify an independent variable. For manufacturing complexity for structure, thrust was selected. However, other variables could have been selected.  Maximum take-off weight, range, ceiling, empty weight, thrust per pound, or speed were all candidates for an independent variable. For manufacturing complexity for Electronics, frequency speed was selected as an independent variable. Again there are many potential candidates for an independent variable for electronics. 

The next step was to graph and complete regression analysis. Figure 2, depicts the results for manufacturing complexity for structure, and figure 3, depicts the results for manufacturing complexity for electronics.  I normally select a power function when regressing data. One could select any function except linear. Linear regression does not always work very well and as a practical matter technology advancements are rarely linear. 

Figure 2.  Manufacturing Complexity for Structure

Figure 3. Manufacturing Complexity for Electronics

Using the above equations now require information be collected on the aircraft thrust requirement for structure, and frequency speed for electronics. These requirements are then used to calculate the appropriate manufacturing complexity. This approach insures that the cost estimate now match up with the requirements. 

The next time you need to complete a cost analysis, talk to one of our expert PRICE Solutions consultants for help.

I consistently run into this idea of data driven estimating.  Yet, there is no clear explanation of this concept.  I am not trying to provide one here, however, I am interested in is what is at the root of this growing movement.  My take is that it is an attempt to scratch an itch.  But what’s the itch?

I believe it is related to my early post (Accuracy is Risky Business).  In the struggle to answer the accuracy question people have decided that understanding the data used in the estimating process is key to understanding its accuracy.  To a certain degree this makes sense.  It is useful to gain insight into the information upon which a cost estimation model was based.

• How much data was available?
• How current was the data?
• Was it relevant to the project being estimated?
• What statistical techniques were employed to analyze the data?

In terms of data, there are two general areas considered relevant: data quality and fit. Understanding how much data was used; how old it was; where the data came from sheds additional light on the results. Once the amount, age and source of the information is established, the next concern is how the information was analyzed. 

Descriptive statistics are often used to describe a collection of data in quantitative terms. They aim to quantitatively summarize a data set. Descriptive statistics include many measures including central tendency (mean, median, mode), dispersion (standard deviation, range, quartile) and association (correlation). Additionally, there is statistical inference, which makes propositions about populations, using data drawn from the population of interest via some form of random sampling. 

The industry is fraught with estimates backed by reams of data surrounded by all the necessary statistics. But does understanding descriptive statistics and statistical inference alone improve our understanding and confidence of an estimate?  If so, why then is expert opinion one of the most widely used forms of estimating?  Why do programs based on these data driven estimates continue to perform poorly?  Is data driven the answer?  What do you think?

The concept of the fuel cell was first published in 1938 by Christian Friedrich Schonbein.  Based on this publication Sir William Grove invented the precursor of the fuel cell in 1839. The Grove Cell created current by applying two acids to zinc and platinum electrodes separated by a porous ceramic pot.  In 1842 Grove developed the first actual fuel cell which produced electricity with hydrogen and oxygen, much like many fuel cells in use today.

Fuel cells remained an intellectual curiosity until the 1960’s when the US space program identified a requirement for extended life batteries for which fuel cells seem to offer a promising solution.  The focus on green technologies has increased interest in consumer uses of fuel cells for transportation, residential and commercial power supply, emergency backup power and portable power supplies for consumer and battlefield applications.  Increased usage of any technology begs the question of how to address the costs associated with that technology. 

A fuel cell is an electrochemical cell which converts some fuel, usually hydrogen, into electric current.  It does this through a reaction between the fuel and an oxidant in the presence of an electrolyte.  The waste product of this chemical process is water and heat.  Fuel cells, unlike conventional batteries, consume reactant from an external source rather than one stored in the battery. They do require a continuous supply of fuel, but given that this supply is available, they will not run out of charge like a conventional battery. 

Because fuel cells require neither flame nor combustion to convert fuel to electricity, there is much hope that they will become a viable power source of the future as we try to reduce our carbon footprint.  Fuel cells are very reliable and less likely to be effected by the environment as some more conventional power delivery systems are.  Because of this they are being adopted in industries such as the telecommunications where outages are particularly problematic.  They are often considered for power generation in remote areas where energy from the grid is expensive and outages are frequent.  Because heat is a waste product of the fuel cell electricity generation process, micro combined heat and power systems are gaining popularity for residential and small business needs.  Other interesting uses of fuel cell power include material handling, backup power systems and uninterruptable power supplies.

Despite increases in the use of fuel cells, they continue to evade wide spread use because they are expensive.  Certainly significant progress has been made through increases in efficiency and improvements in manufacturing processes, but it is still more expensive, in most domains, to get electricity from fuel cells than from more conventional methods. According to a report from the Department of Energy in May 2010, high volume automotive fuel cell stack cost has been reduced from $275/KW in 2002 to $61/KW in 2009 and appear to be on track to reach the $30/KW goal by 2015.   The same report indicates a 24% increase in system power density for stationary fuel cells making it possible to reduce the fuel stack volume, weight and cost.

PRICE recently conducted a research effort using publically available data to develop cost estimating relationships for various types of power systems utilizing fuel cell technology. For a white paper describing this project and the resulting cost estimating models email info@pricesystems.com with the code word FUEL in the subject line.

What follows is PRICE's interpretation of the DOD-HDBK-343, which addresses design, construction and testing requirements for a type of space equipment. Within the document are specified several levels of Class Definitions for space programs, space vehicles and space experiments. The classes are briefly described below.

• Class A - High Priority, Minimun Risk
• Class B - Risk with Cost Compromises
• Economically Re-flyable or Repeatable
• Minimum Acquisition Cost

HDBK-343, originally published in 1986, was reviewed and found to be still valid in 1992.  We can't due justice to the 79-page document in a blog, but we can give you a brief description of each class and PRICE's interpretation of the platform for those classes.
 

The PRICE Platform alters the cost estimating relationships (particularly in the development phase) between the groups of hours and cost within the model, and is used to describe the operating specification of the item being costed. For example, as the platform is increased, the amount of design hours (thus cost) changes to a higher proportion of the development cost. This reflects the extra specifications and tests needed to qualify the design for a given operating specification.  Electronic and structural complexities are also linked platform.  Thus, when considering the platform for a specific HDBK-343 Class, the estimator must also choose appropriate complexities.

Class and Platform Descriptions

• Class A:  Defined as high-priority, minimum risk effort. Characteristics usually involve some combination of: high national prestige, long Life, high complexity, high use of redundancy, soft failure modes, independent qualification items, complete flight spares, highest cost, and a critical launch time.  This class is considered to use a Platform of 2.0 for UNMANNED equipment; 2.5 for MANNED equipment.  NOTE:  It is possible that this Platform may have a higher value IF a number of conditions force higher quality components, longer testing, and other conditions above the HDBK-343 descriptions for this class.
• Class B:  Defined as a risk with cost compromises effort.  It is a high priority, medium-risk, with cost saving compromises made primarily in areas other than design and construction.  Characteristics usually involve a combination of: high national prestige, medium life, high complexity, soft failure modes, protoflight qualification, limited flight spares, limited use of redundancy, high cost, short schedule, and a critical launch time.         This class is considered to use a Platform of 1.9.  NOTE:   It is possible that this Platform may have a higher (or lower) value IF a number of conditions force different quality components, different testing, and other conditions varying the HDBK-343 descriptions for this class.
• Class C:  Defined as economically re-flyable or repeatable.  It is a medium or higher risk effort, that is economically re-flyable or repeatable.  Characteristics usually involve a combination of: medium to high national prestige, short life, low to medium complexity, small size, single string designs, hard failure modes, very limited flight spares, medium cost, short schedule, and a non-critical launch time.  This class is considered to use a Platform of 1.8.  NOTE:  It is possible that this Platform may have a higher (or lower) value IF a number of conditions force different quality components, different testing, and other conditions varying the HDBK-343 descriptions for this class.
• Class D:  Defined as a higher risk, minimum cost effort.  Characteristics usually involve a combination of: medium to low national prestige, short life, low complexity, small size, single string designs, simple interfaces, hard failure modes, and a non-critical launch time.    This class is considered to use a Platform of 1.7.  NOTE:  It is possible that this Platform may have a higher (or lower) value IF a number of conditions force different quality components, different testing, and other conditions varying the HDBK-343 descriptions for this class.

 If you need help with this or other aspects of parametric modeling, post a comment or reach out to our subject matter experts through help@pricesystems.com

As is often the case, there is a difference between definition and connotation. The intended meaning of consumerism at these events was the phenomena of the consumer goods infiltrating and influencing government IT policy.  The IPad was all too visible in the audience as were the comments from CIO staff about their user base wanting to integrate IPad-like products into the work domain.

Like it or not we are all consumers; and consumers are getting more tech savvy.  As the adoption of these products or services increase in our daily lives, the question becomes unavoidable – Why can’t I use these for work? It was clear that for the CIOs attending these conferences this question was top of mind.  While most of the U.S. government is attempting to identify, inventory, consolidate and remove redundancies of IT infrastructure in response to Mr. Kundra’s IT modernization plan, CIOs are also feeling pressure (and criticism) from users about their ability to support seemingly everyday applications.

I’m sure there are many reasons why these aren’t supported; my intention is not to address them here.  Instead I’d like to posit an opinion.  There are  tools supporting new paradigms in how we communicate, at work and home, which are becoming the norm.  They are no longer ‘toys’ for the younger crowd.  For those waiting for this social media fad to pass, I’d suggest another look.  Recent events in the Middle East are real illustrations of their significant impact.  The U.S. State Department is beginning to use a nation’s access to internet and social media as a barometer for civil liberties.  Yet, there is still much resistance in adoption or more fundamentally understanding and embracing these venues. 

I’m encountering resistance and sometimes denial of these forces on a daily basis.  I don’t think you need to have 500 Facebook friends or Tweet until thumbs bleed.  Nor do I think being a LinkedIn Pro replaces human interaction.  It is important though to recognize the shift in communication.  Take just a few minutes to understand the different tools.   You’ll find it’s not unlike a conversation you may have in a coffee room or a hallway if you still have a coffee room or a hallway.  Many don’t.  For those who are time, money or resource constrained, you can access industry experts, thought leaders and practical advice on your own time at no cost.  There are plenty of free introductory videos or articles on line.  You can decide which mediums work best for you. 

At PRICE, we are raising discussions, sharing product capabilities and answering questions about cost estimation models through our social media.  Because people have different preferences for certain outlets or certain restrictions at work, we repeat similar material across our social media networks.  You can check us out on Facebook, LinkedIn, Twitter or follow our blog.

PRICE Systems recently accepted an assignment to complete a "Should Cost" estimate for a U.S. ally on a weapon system. The estimate included not only analysis on production costs, but also should cost on various operations and support costs. The only information provided by the client was quantity and time frame for production. A major ground rule for the estimate was that all data specific to the weapon system must come from publicly available information.  For example, mass, manufacturing process, and learning curve information must come from the public domain. 

After reviewing the scope for the estimate, we decided to also collect data on four similar weapon systems. This would allow us to provide not only a “Should Cost” estimate, but additional information to support the estimate. 

The initial task was to collect data on each weapon system. Pertinent model inputs were collected from various public sources. Flyaway costs were collected for each weapon system and used as the cost input for calibration. Manufacturing complexity for structure and electronics were the key input values solved for via calibration. The calibration results are displayed in a line graph, depicted in Figure One below.

Figure One. Calibration Results for each Weapon System

We then translated all calibration input data and calibration results into a predictive input file. Estimates were completed for each weapon system. All results were reported in the form of a graph depicting average amortized production costs, average flying hour cost, and average operations and support costs for each weapon system. 

The assignment could not have been completed without the capability of the PRICE Models. Model calibration was a critical task. Only a few pieces of data were required: quantity produced, production schedule, and mass. 

The model’s capability to solve for values for manufacturing complexity and a graphical depiction of the results enabled the client to quickly understand the results even though some of their personnel were not familiar with the PRICE models. Do you have a question about should cost?  Post it and we'll do our best to answer your question.  Need help? Contact one of our experts for assistance.

PRICE Systems is currently developing a COM interface for TruePlanning. I know, I know…  What’s COM you say? COM stands for (Component Object Model) and it's a programmable interface which exposes the TruePlanning estimating brains for integration and analysis!  I know it sounds boring but it’s really cool because it allows anyone, including our users, to build “apps” for TruePlanning similar to the way “apps” are built for the iPhone.  Let me give you some examples of some apps that you can build:  Excel solution, sensitivity analysis,  project comparison, risk simulation, total cost of ownership (TOC) solution, calibrate multiple inputs, optimize maintenance concepts and more.  The apps can be developed using a host of tools including VBA which comes with Microsoft Office.  Expect some apps to be built by PRICE but anyone can do it.  If you have an idea for a creative TruePlanning “app” let us know about it because that will help us build the right COM interface for you.

TruePlanning 2010 SR1 estimation software is now available as an upgrade for existing PRICE customers. The most significant update to this version of TruePlanning is the capability to use both parametric estimating models as well as analogous data to produce estimates. This capability validates and increases the defensibility of estimates.

TruePlanning provides a framework that allows content driven parametric models to be estimated in one system. Most notably, hardware, software, IT and Systems of Systems (SoS). No other commercially available estimating tool can make that claim. However, whereas in previous versions estimates relied on parametric models which are based on industry benchmarks, now users can also incorporate their own data for analysis. Customers can import organizational data to TruePlanning, run regression analysis on that data, and further validate their estimates. So now estimates can be backed by internal organizational data as well as external benchmark data, which is a powerful way to defend an estimate.

To view complete details of this new feature as well as other enhancements visit our New Release Info page. 

Last week I gave a webinar which detailed the PRICE perspective on Should Cost & Will Cost Management. The responses I have received have been very positive and also informing. For those of you who could not attend you can view the recorded version of that webinar here.

Below is a brief summation of that presenation and some key takeaways.

The Under Secretary of Defense issued a memo late last year. The thrust of the memo was the current need for greater efficiency and productivity in defense spending. His guidance contained 23 principal actions for improving the efficiency of the department organized into five initiatives: (1) Target Affordability and Control Cost Growth; (2) Incentivize Productivity and Innovation in Industry; (3) Promote Real Competition; (4) Improve Tradecraft in Services Acquisition; and (5) Reduce Non-Productive Processes and Bureaucracy.

One of the principals outlined in the first initiative is the idea of driving productivity growth through Will Cost / Should Cost management. In my view, Should Cost is "the realm of the possible" and Will Cost is "the domain of the probable". Simply put Will Cost is a forecast of a program’s cost …” based upon reasonable extrapolations from historical experience.”[1] Whereas, Should Cost is an analysis of what the program ought to cost given concerted efforts in economy and efficiency by the contractor. “A should cost analysis results in an, …” Approximation of a contract-price, developed by the customer’s accounting, engineering, procurement, and other costing staff.” [2]

Should Cost analysis for DoD was first applied by the US Air Force in the early 1960s. Over time this practice matured to where in 1972 it was declared “A Multimillion-Dollar Savings” in an article written by Major David N. Burt in the Air University Review (September-October 1972). Major Burt describes the evolution of the practice commencing in a thorough discussion of a “new” alternative approach. He goes on to describe a five phase approach spanning one to four or more months consisting of a very large team which includes actual on-site (contractor) investigation of contractor practices and operations. There are issues associated with both of these concepts.
 
First, a Will Cost estimate is a business as usual view which contains all of the characteristics of both good and bad production and management practices. Estimates based on Will Cost have the effect of perpetuating previous inefficiencies by providing a flawed benchmark. Secondly, a Should Cost analysis as described by Major Burt is both time consuming and costly to implement. Furthermore, Secretary Carter, in his November 3, 2010 memorandum to Military Departments and Directors of Defense Agencies declared his desire …”to establish “Should Cost” targets as management tools for all ACAT I programs… and to establish by January 1, 2011 …”’Should Cost’ estimates for ACAT II and III programs… for component MS decisions.”

Clearly Secretary Carter is serious in regards to achieving productivity growth and soon. However, given the timelines, the cost of a traditional “Should Cost” analysis, and the problems associated with a “Will Cost” approach,  how can the Military Departments and Defense Agencies meet the “beyond objectives” outlined in the November 3rd memorandum?

One solution may be utilizing a parametric approach. A parametric estimating approach will reduce the time and resources required while also providing an external benchmark of industry standards for similar systems. Given the pace with which agencies are expected to move its probably an approach many should consider.

Bob Koury
Senior Research Analyst, PRICE Systems

In last month’s blog I wrote about Ash Carter’s (Under Secretary of Defense for Acquisition, Technology & Logistics) Memorandum for Acquisition Professionals, Better Buying Power: Guidance for Obtaining Greater Efficiency and Productivity in Defense Spending (14 September 2010).

I concluded the TruePlanning unified framework and comprehensive cost models, is a tool very well suited to provide the types of analysis outlined in the memorandum. In terms of Should Cost and Independent Cost Estimates (ICE), TruePlanning estimation software provides the industry standard capability to conduct Should Cost and calibration (actual program history) for ICE. Most interestingly and to the point of the Carter memo, TruePlanning has the capability of breaking the “self fulfilling” prophesy of business-as-usual.

On November 3^rd, Ash Carter issued a follow up memorandum outlining specific actions to implement the September 14^th Guidance. For this month’s post, I wanted to point out some specific comments about Milestone A and B actions and specifically how TruePlanning can help.

At Milestone A the memorandum specifics establishment of an “affordability target to be treated by the Program Manager (PM) like a Key Performance Parameter (KPP)…This analysis should show results of capability excursions around expected design performance points to highlight elements that can be used to establish cost and schedule trade pace.

At Milestone B, the memorandum requires ”a system engineering tradeoff analysis showing how cost varies as the major design parameters and time to complete are traded off against each other.” Thus, Integration between parametric cost models and performance models is needed to allow full exploration and optimization of the trade space, treating cost as another design parameter

Did you know that TruePlanning through its integration with Phoenix ModelCenter is a powerful tool to provide exactly this type of analysis? ModelCenter contains a native plug-in to interface with TruePlanning directly. Through the ModelCenter interface, analysis can easily perform Design of Experiments (DOE), Carpet Plot Analysis (trading performance KPP’s against cost) and Optimization Analysis.  If you are interested in seeing some examples, especially system engineering trade off analysis, please get in contact with me and I will send you a few presentations.

In his August blog-entry here, Zach Jasnoff outlined typical client perspectives for the different types of analyses that TruePlanning can accommodate. Working on a large project, we’ve experienced situations that, realistically, can happen where the initial intent and model structuring later have the boundaries of model appropriateness stretched. An Analysis of Alternatives (AoA), for example, is meant to measure deltas between baseline and its alternatives. If common costs “wash” then they can be excluded… which becomes an issue when treated as a Rough Order Magnitude for customer budgeting. 

Likewise, if a ROM or Independent Cost Estimate (ICE) of acquisition costs is extended to Program Lifecycle Costs, significant gap analysis is in someone’s future. TruePlanning can handle these tasks. But obviously it’s always best to establish use of an estimate and its underlying model, beyond initial application. TruePlanning has enormous flexibility. We analysts endeavor to do the same.  Clients, particularly those new to parametric cost estimation, just need coaching and synchronization up-front sometimes. They may think they have “the estimate” when it only covers certain configurations, activities, phases or cost-categories. Expanding a model is simple enough; creating and defending changes can be tough for the customer internally. 

I’m continuing to realize that when in doubt, make it clear what an estimate & model is meant for, and what it’s not.

John Swaren
Solutions Consultant, PRICE Systems

Yesterday I had the pleasure of speaking at the New England SCEA Chapter December luncheon  [link to Flyer .pdf].  The attendees were a great mix of experienced, seasoned cost estimators and young, new talent, eager to learn techniques to apply on the job. 

My topic was the program management value of combining estimating Rules of Thumb with more rigorous cost estimating models and databases [link to presentation .pdf].  Rule of Thumb estimating is used every day by program managers to help guide their projects.  Oversight authorities rarely have the resources to perform detailed program estimates, so they rely on simple Rule of Thumb-like models to ensure estimates are within the budget tolerance.  I stressed the importance of using external and internal benchmarks to aid model building.  One of my favorite examples of this is the Tailor Rule of Thumb.  

This is a simple approximation that was used by tailors to determine the wrist, neck, and waist circumferences of a person through one single measurement of the circumference of that person's thumb. The rule states that twice the circumference of a person's thumb is the circumference of their wrist, twice the circumference of the wrist is the circumference of the neck, and twice around the neck is the person's waist. This external benchmark uses average values (2x) for the wide population of the time.  I decided to update this with internal benchmarks, or measurements of my own.  I carried a tape measure for a week and measured everyone who agreed – friends, family, and co-workers.  Based my internal benchmarks, I discovered that a multiplier of 2.3 made the model extremely accurate – it is no secret that we eat more than average New Jersey.  In this way, I combined an external benchmark with internal benchmarks to determine an estimating Rule of Thumb with which I am comfortable. 

We empower our customers with models and tools to arrive at the same comfort level for complex projects.  Most of the luncheon attendees work every day with rigorous models and databases, so they left the luncheon for a new appreciation for the value of Rules of Thumb.

Unfortunately this is a true story.
 

I decided to have a couple of gold fish in a nice glass bowl, having done my sums I estimated the cost should be:

• Bowl £20.00
• Gravel £5.00
• Two gold fish £8.00
• Food £4.00

Making a total of £37.00, ok I can afford this, off I go to the pet shop.

The pet shop advised “fish don’t like bowls”, plus “it’s cruel to keep them in one”, but as a child I often won fish at the fun fair and they lasted years, so undeterred off I went and purchased a bowl and 2 lovely gold fish from somewhere else. All is good.

After two weeks I watched one gold fish do a fantastic somersault and then die, off to the pet shop and buy another fish, £4.00, not too bad.

Two weeks later while cleaning the much-cherished bowl it shattered and cut my finger so badly I end up lying on the kitchen floor, finger in the air to try and stop the flow of blood, the fish at this point are swimming in an old sandwich box.  Obviously needing help I phone my son to buy me another bowl, he arrives with an all singing all dancing tank, daylight, moon light, filters the lot. Cost £50.00 with the added insult of “You shouldn’t be trusted with glass or sharp objects”.
 

Next day my finger has swollen so badly I attend the A&E department to have my gold ring cut off, cost to have ring repaired £40.00.

All in all what should have cost £39.00 has now cost £131.00 but hey my gold fish now live in a palace! And yes, I do talk to them.

I do wonder what parametric cost estimating could have taken into account the cost drivers, risk and benefits of this venture.

By K.T. Price

UK

I was recently struck by Ash Carter’s (Under Secretary of Defense for Acquisition, Technology & Logistics) Memorandum for Acquisition Professionals, Better Buying Power: Guidance for Obtaining Greater Efficiency and Productivity in Defense Spending (14 September 2010). Within this broad sweeping memo, Ash Carter outlines 23 principal actions in five major areas aimed at increasing efficiency in Defense acquisition.  The first major area covered is “Target Affordability and Control Cost Growth”.

Within this major area, program managers must treat affordability as a requirement before milestone authority is granted to proceed (starting with Milestone A). This means developing affordability targets and treating cost as a Key Performance Parameter. 

What I find really interesting is the critique of Will Cost vs. Should Cost. The memo is critical of Will Cost, or Independent Cost Estimates (ICE). As Dr. Carter points out, “the ICE reflecting business-as-usual management in past programs, becomes a self fulfilling prophesy. The forecast budget is expected, even required, to be fully obligated and expended.” To combat this “vicious cycle”, the memorandum now requires “each major program to conduct a Should Cost analysis justifying each element of program cost and showing how it is improving year by year or meeting other relevant benchmarks for value.”

In my career experience, parametric estimating models such as TruePlanning play a major role in targeting affordability and controlling cost growth. In terms of affordability analysis, TruePlanning contains a unified framework of all elements of program cost (hardware, software, IT and Systems) and has built-in capacity to interface with engineering optimization tools such as Model Center. Through this interface cost can be treated as a Key Performance Parameter (KPP) for optimization and engineering trade off analysis.

In terms of Should Cost and ICE, TruePlanning provides the industry standard capability to conduct Should Cost and calibrated (actual program history) for ICE. Most interestingly and to the point of the Carter memo, TruePlanning has the capability of breaking the “self fulfilling” prophesy of business-as-usual. Using a calibrated TruePlanning model for ICE, estimators can change key engineering and programmatic parameters and see the impact on cost. For example, parameters such as requirements stability, engineering complexity and team composition can be quickly changed to assess a new program’s reality while still taking into account past performance history.

As the Carter memorandum points out … “the ability to understand and control future cost from a program’s inception is critical to achieving affordability requirements.” Because of TruePlanning unified framework and comprehensive cost models, it is a tool very well suited to provide the types of analysis outlined in the memorandum.

Zach Jasnoff
Solutions Architect, PRICE Systems

Margaret Wolfe Hungerford in 1878 in her book Molly Bawn coined the phrase …”Beauty is in the eye of the beholder”. This concept of the “value of beauty” has been expressed by others such as:

 

 Benjamin Frankin in Poor Richards Almanack 1741 when he wrote;

                “Beauty, like supreme dominion

                Is but supported by opinion”

David Hume in Moral and Political 1742

“Beauty in things exists merely in the mind which contemplates them.”

So what does this have to do with Cost Benefit? Well Merriam-Webster dictionary defines benefit as something that provides useful aid. Inherent in the term “useful” is the idea of value. Value in the context of useful only becomes meaningful when someone considers or contemplates it as being valuable. The degree to which something is evaluated as useful becomes a mental process of a stakeholder or user of the item. You might say that value is in the eye of the user! This becomes important in our efforts as cost estimators especially when we are involved in cost-benefit analysis. The mental evaluation of the stakeholder assigns meaning to the cost we calculate. Payback, and return on investment are related to this same mental evaluation. These kinds of metrics are a way of quantifying a stakeholders opinion about value and the usefulness of a program, project, or system. We as cost analysts should never lose sight of this truth.

Bob Koury
Senior Cost Research Analyst, PRICE Systems

The midterm elections are finally over. The themes of reduced spending and lower taxes showed up in force at the ballot box. But what does that mean for the defense industry?

The U.S. Secretary of Defense, Robert Gates, caused quite a stir when he announced his proposals for reigning in defense spending. There are the expected assortment of eliminations (U.S. Joint Forces Command and Business transformation Agency to name two), reductions (in service support contracts, number of senior civilian executive and general/admiral military officers, and funding for intelligence community advisory contracts), freezes (of automatic replacement of departing contractors with full-time government personnel and oversight reports), and consolidations (IT assets). All of these have created so much emotional reaction that I almost missed one component of his proposal that looks like an adder – to attach a cost estimate to every new initiative proposed hereafter. It’s hard to find more detailed explanation on this. I’m reading it as: let’s figure out what our ideas are likely to cost us before we fall in love with them. And that sounds like a fiscally good idea, as well as one that needs a community of smart cost estimators, capable of producing meaningful cost-benefit analyses.

When I glanced at the Washington Post on Sunday, the following headline screamed out:

Defense cuts could slow D.C. economy for years

The article basically covers how Defense Secretary Robert M. Gates is calling for reducing spending on "support contractors" by 10 percent each of the next three years as the Defense budget shrinks. As Washington DC is a hub for these types of companies, the impact is expected to be significant. According to the article, more than a quarter of national defense spending contains of outlays for service contracts. Among the largest companies affected are CACI, SAIC, Lockheed-Martin, Booz Allen Hamilton and ManTech.

As the Defense budget shrinks and more companies are chasing fewer projects, the need for greater accuracy in cost estimating increases. At the same time, the WSRA adds 20,000 new positions in cost estimating, contracts and oversight.

This is an interesting conundrum, cutting DoD service contracts 10% over three years while the government is adding 20,000 new positions in cost estimating, contract and oversight

One year after the WSRA was signed into law, an interesting observation from the National Defense Magazine Blog:

Nancy Spruill, director of acquisition resources and analysis at the office of the undersecretary of defense for acquisition, technology and logistics points outs “The long pole in the tent is the cost estimates,” she said. “There's a lot of programs that need cost estimates as they're moving through the process today. … Doing additional ones has been difficult, especially a while ago, when they didn't have the staff.”

Thus, in an era of shrinking defense budgets, greater oversight and more competition for fewer projects, parametric cost estimating models such as TruePlanning can play a major role in providing accurate cost and risk estimates for both government and contractors. This is especially true in Source Selection where determining the most cost-effective offering is critical. For more details on using TruePlanning for Source selection, see my previous two blog posts.