IT Project Costs

The following is a collection of some of the more common installation issues.  If you have additional questions, concerns, or issues with any upgrade or installation, please call our Technical Support line anytime at:  1-800-43-PRICE.

Default Password Override

TP’s default password may not be strong enough based on your security policy.  Please review your specific requirements for passwords and follow the directions below to change the default:  When you get to the screen, uncheck the “Use Default Password” and enter a valid password based upon your specific security settings.  Then click next and continue the installation process.

Existing TruePlanning Installations

If TruePlanning 2008 SR2 is currently installed, it is recommended that users export their projects, then uninstall TruePlanning, making sure to backup their database when prompted to do so during the uninstall. The uninstall of TruePlanning can be initiated from the Control Panel.  Also, please select the option to uninstall MSDE when prompted during the uninstall.  Once this is complete, install the new version of TruePlanning, making sure to manually import the projects which were exported from the older release once the installation is complete.  Upgrades from TruePlanning 2009 and above do not require TruePlanning  to be uninstalled as the TruePlanning 2010 installation will automatically upgrade the projects in the database; however, it is recommended that users still export their projects manually and before the upgrade to be safe. 

Administrative Rights

The user installing TruePlanning requires administrator rights on the machine.  On Vista it is advisable to launch the installation of TruePlanning by navigating the “Setup.exe” file on the TruePlanning CD and initiating the installation using the “Run as Administrator” option. This option is available from the right click menu in Windows Explorer (My Computer). 

XmlLite

XmlLite is a resource provided by Windows to perform certain XML parsing abilities. It is a prerequisite for installing TruePlanning 2010. If TruePlanning 2010 is installed on a computer that does not have XmlLite, and error will occur when TruePlanning is launched.  The installation will not produce any errors or warnings. This error is Windows XP specific. Vista and Windows 7 contain the XmlLite natively. Normally XmlLite is installed when Internet Explorer 7.0 (or newer) or Windows XP SP3 are installed. Installing either of these resources should resolve the error.  Some customers are not able to install IE 7.0 or Windows XP SP3 and should therefore install XmlLite directly. It is available from Microsoft at: http://support.microsoft.com/kb/915865. It should be noted that TruePlanning 2010 has features that rely on Internet Explorer 7.0 or higher. Some of the Calculators contained in TruePlanning will not function properly without Internet Explorer 7.0 or higher.  Therefore, if possible, upgrading Internet Explorer is the preferred option. 

MSXML6 SP2

There is a known issue installing TruePlanning 2010 on computers that have Windows XP SP3 and MSXML6.0 SP2 installed.  The issue occurs because of an incompatibility between SQL Server 2005 Express and MSXML6.0 SP2. This issue is described by the following Microsoft Knowledge Base article: http://support.microsoft.com/kb/968749. MSXML6.0 SP2 is installed by the Windows XP Service Pack 3. This is not an issue on Vista.  The above MS KB article provides a fix for the issue. It is advisable to execute the fix before attempting to install TruePlanning 2010. It is possible to identify computers that have had MSXML6.0 SP2 installed by examining the “Add/Remove Programs” feature under the Control Panel. If the issue in encountered during the installation of TruePlanning it can be identified by the failure of SQL Server to install. The failure will be identified as pertaining to MSXML6. This can be ascertained after the installation has been exited, by examining the log of the SQL Server installation. The summary of the SQL Server 2005 Express installation can be found at the location defined by the following support page: http://msdn.microsoft.com/en-us/library/ms143702%28SQL.90%29.aspx. If the error has been encountered please contact PRICE System’s Support for help resolving the issue.

“I think we have an obligation to work with industry to ensure that our suppliers do not just remain world class in defence, but aspire to be world-class manufactures that can withstand comparison to other industries.”

Chief of Defence Procurement, Sir Robert Walmsley

Is this a practical proposition or is it a pipe dream?  The following excerpt from Dale Shermon’s Systems Cost Engineering attempts to make the case that this type of comparison is possible.


Many of the statements in proposals and marketing literature stating the superiority of a company are anecdotal or at best qualitative evidence. It has not been possible to quantify the productivity of industry to demonstrate that one manufacturer is more efficient than another.

In the ship building industry it is possible to benchmark commercial ship yards using a metric called Compensated Gross Tonnage (CGT). CGT measures the complexity of building a ship. It is calculated by multiplying the gross tonnage by the relevant CGT coefficient (calculated by the Organisation for Economic and Commercial Development [OECD]).  However, this is only applicable to this one industry. Other metrics exist in other industries, but what is really required is a single benchmarking technique and measure.

Benchmarking with Cost Normalization.  Forty years ago, PRICE Systems developed a metric that can be used to normalize cost and support the benchmarking practices needed to reach Sir Walmsley vision.  Manufacturing Complexity represents the normalized cost density of an item that has been manufactured. It has two dimensions: technology and productivity. Hence, more than one Manufacturing Complexity can exist. As aircraft are made using different technologies and by different companies, these have various complexity figures. However, if the technology is constant, the only dimension that changes is productivity. As a result, it is possible to compare the efficiency of companies that produce similar technologies.

Supplier Assessment.  One obvious and practical application of this technique is Supplier Assessment. This technique exploits the capability of parametric models to compare organization’s normalized cost density or Manufacturing Complexity. If, on paper, you have very similar proposals, how can you judge which organization will provide the best value for money? Heritage data will determine the level of development that is required and Operating and Support Cost will establish the Through Life Cost, but if these cannot differentiate the proposals perhaps the productivity of the companies should be considered. This is not a simple comparison, but with manufacturing complexity this can be achieved easily.

This process will lead to your suppliers knowing that you are able to control them; they will need more control on themselves. It will enable you to perfect your negotiation skill, leading to more success, as better negotiation material is utilised based on technology cost drivers. A parametric questionnaire is a possible tool to enable proposal validation in minutes.  All this information can be garnered at a very early stage in a project if required, providing better estimating accuracy for the purchased items. Normalization enables a bigger data sample as previous proposals received from the same companies can be compared. This in turn enables the establishing of trends. Are the suppliers becoming more or less efficient? Ultimately, these comparisons can be used to determine preferred suppliers.

Conclusion.  This method of benchmarking a project or company can be used for all environments. With the ability to move across environments it is possible to compare commercial and military organisations equally. Decisions and judgments can be made between Commercial and Military suppliers where no military competition exists.  It is possible to assess the productivity of an organisation or country at System, sub-system and equipment levels. The technique can be used to compare the whole cost or just the labour cost if that is the focus of your efficiency drive.

It is possible to determine preferred suppliers on a justified basis, or alternatively it is possible to demonstrate the efficiency of your organisation when the customer is skeptical about your productivity or your drive to improve productivity.

Finally, many organisations already have a license to use the PRICE models and over 8,000 people worldwide have been trained and are familiar with the PRICE methodology. This is not a new idea, PRICE has been established since 1975, but this new application of an established technique can help decision maker take the right decision regarding source selection cross industry and national companies. Alternatively, it can enable industry to demonstrate, with proof, that they are more effective than other solutions.

1. A round table peer review, where we describe and defend our parametric modeling approach as well as consistency across similar objects/ systems/ alternatives. 
2. Introduction of an independent 3^rd party, not part of the estimating team, who is an experienced modeler. This resource can take the client perspective in reviewing, say, procurement versus cost-of-ownership as well as comparables from similar program experiences.  
3. Take an agile approach where your project leader is the “product owner” who reviews all interim deliverables top-down.  
4. Another option is incorporating a client representative into your pre-release reviews for similar validation testing. 
5. Finally, we pair off internally to verifying each other’s work against the real-time documentation we keep per common templates.  (Available from PRICE Systems, for both hardware and software modeling inputs). They are great visualization tools for internal parameter-tracking, plus external pre/ post model review with customers.

...wear the worst shoes. The cobbler was a master at his craft; he was just too tired to practice it when he got home from the shop.  Sound familiar?

A disciplined approach to understanding (functional) requirements as well as analogous projects (with actuals) is our not-so-secret sauce. Why run the risk of creeping back up our career learning curve? There’s already enough scope creep to keep us busy. Plus, for you management types charged with prospecting, a consistent approach towards estimation is a great way to connect with people who've felt the pain of being the cobbler's kids.

I recently reconnected with a colleague who found himself immersed in an early-stage, large-scale federal software project. Discussion points ranged from parametrics utility to sizing to Earned Value Management. Not leaving my toolset at the shop translated into good conversation with followup request. A bad example is yours truly, a year ago, so immersed in a highly-featured personal project, that he neglected to find agreement on scope and cost with his team. Bad idea! Now my “shoes” (a one-off custom hot-rod) are way behind schedule and way over budget. Keeping on my professional cost estimation consulting hat would have saved on both… bigtime! 

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.

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.

True accuracy can only be determined after the project or effort has been completed and a post-audit analysis reconciles what was expected to happen with what did happen.  This is a very expensive, time consuming process that many preach about but few actually attempt. 

In my experience, when people ask about accuracy what they are really interested in is uncertainty.  They want a quantification of any uncertainty in the facts and processes that derived the estimate.  Because naturally, the more uncertainty the less accurate the estimate.   I am using Dale Shermon’s definition of uncertainty as explained in the book, Systems Cost Engineering. Uncertainty means ‘a possible event, the probability and the consequences of which are unknown’.   

Uncertainty about system or project scope, requirements stability, cost or effort drivers, the assumptions, and the range of possible answers all contribute to the individual’s assessment of how much doubt to apply to a response.

In an effort to describe the accuracy of estimates, the industry had added entire disciplines designed to generate all comforting statistics around someone’s approximate judgment.  Risk analysis, confidence levels, technology readiness levels are all valid and useful guides to help the consumer of the estimate understand the estimators assessment of their own accuracy…uncertainty.

What techniques or methods have you found useful to convey your estimate’s accuracy/uncertainty?

Have you experience the same relationship between Accuracy and Uncertainty? 

My June blog entry suggested the use of parametrics in real-options valuation. This month, I’d like to offer the generalized use of our type of modeling in valuing tangible assets. 

Typically, fundamental analysis evaluates the intrinsic value of securities. I won’t attempt to compete with Warren Buffet here. But it is certainly the case that a company, or portfolio of securities reflecting many companies, is based in part on the market value of its product assets and their potential for future earnings, as well as other objective and subjective considerations.

In parametric estimation, we take a top-down approach to developing models of estimating ultimate acquisition and ownership costs. In the case of the former, I’d argue that we can readily… and uniquely… estimate operating costs for companies developing and selling, say, technology-based products.  Marketing can determine pricing, based on their competitive landscape analyses and market-demand for unmet needs. 

We are in an excellent position to complete the forecasting of earnings (and hence, discounted cash flow) using our parametric methods to evaluate a product-system’s should/will costs. Anyone who does detailed bottoms-up budgeting for “go to market” expense, as well as production delivery, would find value in our modeling.  

And again, once estimated costs are subtracted from revenue forecasts, the netted estimate of earnings and cash flows will allow for traditional market value assessment of this asset or entity. For example, your organization needs to compare economic potentials of emerging new software products. There are no balance sheets. There are no income statements. Yet. 

Now your sales and marketing function has a good independent sense of revenue opportunity. So it’s left to you to estimate the costs of developing and delivering. Independent parametric estimation is the answer. No idea on sizing, either SLOC or function points? No problem. 

Data-driven True Planning has years of data modeling that allow you to run application-specific calculators. In addition, you can take advantage of calibrating actual data from similar projects. Likewise, this process of valuing assets holds true for IT infrastructure products as well. Cloud computing, SAAS and ERP are all further examples of where new IT/software products are emerging… and need estimating as well as financing via valuation.

I think parametric estimating has significant value commercially in the estimation of value of future product assets, and consequently their companies and associated securities.  What do you think?

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.

Recently a cost research project on missiles was completed. The research resulted in performance based equations for air-to-ground and surface-to-air missiles were developed. The performance based equations can be used for early concept estimation  on missile development and production costs. The question though is “What is the process for developing this type of estimating relationship?” This will be the first of a series of BLOGs on this topic. 

The first task is to define what is a “Performance Based Equation?” Bruce Fad covered this definition in a previous “Data Driven BLOG” so please review his post for the details. The second step is data collection of not only cost and technical data, but also collection of data for potential independent variables. I would recommend collecting data for several independent variables. This avoids starting over with the data collection effort, when the initial independent variable does not correlate with the dependent variable. In the case of the missile data, various potential independent variables were identified: Range, speed, payload, guidance system, and propulsion system. The independent variable data was not used for the next step. Rather the next step was to set up a calibration TruePlanning input file. The calibration results were for manufacturing complexity and were ported over to MS Excel for completing the analysis. This will be discussed in a follow-up post.

Jim Otte
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

Here’s a cool project.  The Bloodhound Project  is focused on building a land vehicle capable of breaking the 1000mph speed barrier.  The mission of the project is twofold.  The first is to “overcome the impossible using science, technology, engineering and mathematics”.  But the second is more interesting – this project is intended as motivation for the upcoming generation to embrace technology related fields.  Britain doesn’t have enough students interested in such fields and they are worried about their ability to compete in technological forays going forward.

But how much should something like this cost and how could they possibly figure it out?  There is no historical data on which to base an estimate – no one has ever done this before.  And of course, they are currently in trouble, expecting the cost to rise above the 6.6m (British Pounds) original estimate for researching, designing and building the vehicle   So just for fun I thought I would look at the project from a parametric perspective.  I did a quick search to determine the weight of the car (6 tonnes or 13228lbs), made some assumptions about the complexity and engineering difficulty, and ran the whole lot through the TruePlanning for Hardware Model.  While the technical information I was working with was scanty – I was able to come up with an estimate of 8.6m (British Pounds).  Hopefully, for the project team, my assumptions on complexity were overstated and the project completes successfully within the original estimate.  Regardless it certainly is a creative, if somewhat expensive, way to grow new engineers

Some of us remember taking the Iowa tests during our early school days. The Iowa Tests of Basic Skills (ITBS) are standardized tests provided as a service to schools by the College of Education of The University of Iowa. The tests, administered to students in grades K-8, became a national standard for measuring scholastic aptitude – I was educated in Pennsylvania.

Now out of Iowa comes another test of sorts, something called an Integrity Index Score based upon a proprietary algorithm of an organization called Iowa Live. Iowa Live calls itself, “a growing network of volunteer Citizens & professionals for improving Iowa.” The organization has addressed a variety of issues in the education, health, and government areas. In July, Iowa Live published its comparison of two commercially marketed parametric estimating software products, one of which was PRICE TruePlanning. The comparison was for both estimation of software projects and estimating hardware. If you’d like to see the results, visit the Iowa Live website, where you can also learn more about the theory and derivation of the Integrity Index.  

Bruce Fad
VP Professional Services, PRICE Systems

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.

Ahhhh, the 80s… a challenging (but often confusing) time in an evolving computing world.  Working in 1985 as a software estimator as well as SQA engineer in a quality assurance department that “audited” real-time projects using new concepts like OOD & OOP… well, you get the picture.  It was a great time to get immersed into great work.  And the good news:  that company’s process as well as its developers were bullish on a young estimation/ quality types asking plenty of questions… as long as they were of the Yes-No variety.  And ask I did.  Writing and using those checklists was great OJT, above & beyond adding their value of verifying/ enabling healthy development activities. 

Less than two years later, SEI’s Walt Humphrey formalized his Capability Maturity Model with its five levels of software process maturity.  These “CMM” levels are still used by many organizations and estimating tools, including within True Planning’s “Organizational Productivity Calculator.”  Could the CMM assessment be supplemented to include cost-driver questions for purposes of parametric estimation?  It worked in my SQA audit days. 

In fact many estimators (if only because they can’t get on an SME’s schedule twice) take the opportunity to ask qualitative and quantitative questions.  Integrating both lines into one interview should still be received as a healthy value-add.  Whether estimation is resident within a quality or financial function is moot.  We have the entrée to support both costing/ planning and productivity assessment.  A good example of an integrated approach is the David Group’s Project Profile Worksheet, cited in the text “Function Point Analysis” by David Garmus & David Herron.  Less comprehensive checklists are likely out there too, including methodologies proprietary to individual companies. 

The thought today is that the future is now and structured approaches, called audits or otherwise, will enable good practices as well as illuminate new approaches too.  In Wall Street, regulations are only good in controlling past (known) bad behaviors.  In just as creative Software, process rules help developers maximize their productivity towards current & future good behaviors.

The key cost driver when estimating software costs is the size of the product. The problem is that there is no perfect technique available to measure and quantify the size of software. The two major techniques in use today are Source Lines of Code and Function Points.  Today we will talk about Source Lines or Code or SLOC.

Source Lines of Code measures logical lines of code. It takes some of the uncertainty out of physical line of code measures by counting only complete statements (which can cross over more than on physical line). SLOC excludes comments and blank lines.

SLOC has several advantages:

·         Easily counted by automated tools, which can be configured with an organizations definition to produce consistent counts. Link to free tool from USC is provided below.

http://sunset.usc.edu/research/CODECOUNT/download/2010/UCC_Release_Notes_v.2010.07.pdf

·         Provide visibility into technical progress as projects proceed through design, code and testing.

·         Can be used to develop historical databases of past project size, which enable the more accurate prediction of size of future similar projects.

·         Design, Code and Test change to modified software can be specifically quantified

SLOC has several disadvantages:

·         It’s very difficult to predict SLOC on new programs prior to design

·         Different programming languages will require different amounts of SLOC to implement the same functions. This makes summary measures of size on multi-programming language products difficult

·         SLOC is difficult to map back to product features or requirements. Which makes usage of EVM difficult to apply to SLOC based SW projects. 

·         SLOC is a meaningless number to non Software Engineers (without detailed explanation)