Estimation . Analysis . Planning . Control
Updated: 11 hours 9 min ago
IT Project Failure Warning Signs
This list was adapted from ITBusinessEdge
Lack of governance: Project criteria, roles, processes & outcomes not used or accepted by management. Not understanding project risk.
Internal politics: Territorial fights. Its not my job, or “they” messed up.
Communication issues between the business and IT: IT talking with the business stakeholders about bandwidth and blobs rather than end user oriented benefits.
Unclear expectations: Bad estimates and ambiguous expectations.
Lack of fact based analysis: Plans not based on facts but on opinions. Studies have shown, for example, that projects of any magnitude can’t produce a viable estimate without a model like SEER.
Lack of input from users: IT may know how to do it but users probably know what they need better.
Changes in project without re-planning
Unplanned changes in key personnel
Unrealistic schedules: Projects on death marches.
Unanticipated operations costs: These must be estimated well up-front
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Off Topic: Estimating the Occurence of Phantom Traffic Jams
Estimating the slowdown on the freeway. Interesting article from Wired quantifies and estimates the occurrence of phantom traffic jams. You all know them… traffic slows to a crawl. There must be an accident. But no, it is just a phantom traffic jam. Living in Los Angeles I find this really interesting.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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New Code Counter Update Available from USC
The University of Southern California has been developing and updating line of code counters for a number of years. Such code counters can be very handy when using lines of code as a size measure. I know, many object to using lines of code, but when used correctly they can work well. We see users who have just as much success with lines of code as they do with function points, use cases, etc.
Even if you are a functional size user, knowing the SLOC for legacy can be useful, rather than counting the function points, etc. Here is the announcement from USC:
We are pleased to announce that a new version of the Unified CodeCount (UCC) tool is now available to the public at http://sunset.usc.edu/research/CODECOUNT/. This Release 2010.07 supports new programming languages (e.g., Fortran, Python, ColdFusion, Bash and C-Shell script) and the CSV output format among other enhancements and bug fixes. Please refer to the release notes document for further details at http://sunset.usc.edu/research/CODECOUNT/download/2010/UCC_Release_Notes_v.2010.07.pdf
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Cost To Recover from an IT Business Interruption
Aberdeen group published some interesting information regarding the time and cost to recover from business interruptions. This is the time to recover 90% of functionality. I recommend getting the complete report. They found that best in class recovered 6.5 times faster than laggards and had an average cost of $72,000 versus laggards with an average cost of $2,880,000.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Software Estimating: Sources and Uses of Data and Data Driven Estimates Intro
These days software estimation vendors are competing to have the largest repositories of completed software projects, and the customer is encouraging this competition, which is fundamentally good. However, there is more to insuring the accuracy of an estimation model than just having a lot of data points sitting on the proverbial shelf.
Where Data Comes FromThe first question asked of a vendor is, where does your data on completed software projects come from? Early on, much of it came from Government agencies, who in turn collected from contractors. Over time, public sources have emerged that contain voluntarily submitted information from private companies worldwide; the prime example of this being the International Software Benchmark Standards Group (ISBSG). Galorath has obtained software project data over the years through numerous private and public sources. The data comprises many thousands of total observations that have passed data quality tests. Most observations contain size and effort information, thousands more do not contain all the desired fields.
What is Done With DataWhile plain-vanilla data can reveal a lot, it has its limitations. For this reason, Galorath maintains extensive surveillance of industry trends, including third-party analyses. These can reveal insight into changes in modern practices such as Agile development, the productivity gained by the latest IDEs, and many other ongoing evolutions. The company is a member of numerous industry consortiums – in part to obtain access to the latest research available.
At Galorath, once data is acquired, it is processed into a form that is usable for analysis. This involves normalization so that the data points are comparable, i.e., include the same activities from early requirements through testing and the same types of labor, including programmers, testers, management, etc. We also try to find and understand “outliers” – those projects that are so different that they are not useful. At numerous conferences and in webinars, we have described our normalization process and compared our results against other methods.
Using the collected data we update SEER for Software in several ways. A key method is to run our model against various stratifications (specific subsets such as “Business” and “Client-Server”) that are defined by SEER for Software’s knowledge bases. Simply put, we compare the model’s estimates to observed outcomes. Based on these results, knowledge bases are re-calibrated when necessary. In fact, data sets are not uniform in terms of the information observed. Some completed project records may include peak staff, development activities, and software language used, while others don’t. We account for this by performing a separate analysis of various factors: language productivity, development proportions, productivity variation by application or development method, and so on. These analyses are done first, and the model is adjusted, before gross analysis is begun.
SEER for Software’s core model is configured to a particular circumstance by a set of knowledge bases, and it’s these knowledge bases that are calibrated based on new industry information and trends. Each knowledge base is defined in terms of a set of parameters, some visible to users, and others normally hidden. When a knowledge base is updated the visible parameters, such as Modern Development Practices, may be modified and some underlying calibration factors may be adjusted. These knowledge base adjustments occur every few years as evidence warrants.
ProjectMiner, Analogy Based Estimation, Metrics and Benchmarking Can Use Raw as Well as Processed DataWhile SEER for Software includes numerous data driven functions (such as ProjectMiner data driven estimates, Metrics and Benchmarking data driven analysis, and more) the overall evolution of SEER for Software is best called “innovation-driven.” While data analysis is a very important part of how we maintain SEER for Software, we also continually enhance the model’s ability to estimate real world projects. These enhancements have often been industry firsts: flexible project staffing, off-the-shelf (COTS) integration modeling, translation of estimates into detailed project plans having intricate interdependencies, extended schedule and small schedule estimating, cloud computing solutions, to name only a few. All these innovations, alongside data-driven updates, serve an important role in insuring the model’s precision. SEER uses data in a number of ways including, but not limited to:
- Refine knowledge bases and Equations
- Provide Trend Lines on Metrics and Benchmarking
- Plot Your Estimate compared to actual completed projects
- Apply to ProjectMiner (AKA SEER Independent Crosscheck & Verification) which provides a completely data driven estimate either as a crosscheck or primary estimate
- Provide sizing for systems
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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SEER 2010 International User Conference Papers Are Available
http://www.galorath.com/index.php/library/estimating-united-conference/
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Interesting ROI Spreadsheet for Software Process
Shows ROI of inspections, PSP, tsp, and more http://davidfrico.com/roi-book.htm
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Addressing the Need for More Female Computer Science Graduates
Gender equity in computing has long been a national goal advanced by those concerned with fairness and by those who know that the female point of view improves the design and development of software systems. Unfortunately, the percentage of young women entering computing-related majors keeps falling, and the female dropout rate is higher than the very high male dropout rate.
The Bureau of Labor Statistics predicts a large increase in the need for B.S. and M.S. computing graduates in the next decade. The largest untapped pool of potential computing majors and, eventually, computing professionals, is science- and math-talented high school students, but only about 10% of entering undergraduate majors in computing majors are female. Despite the many initiatives aimed at attracting young women, the number of female computing majors keeps dropping…
Prof David Klappholz is involved in the Real Projects for Real Clients Courses (RPRCC) initiative, a K-12 and college level ACM-W project aimed at recruiting young women into, and retaining them in, computing-related majors. The initiative’s approach is based upon a 35-year-long psychological study that followed hundreds of mathematically- and scientifically-talented youth from middle school to middle age and elucidates gender differences in career choice.
Galorath’s head of development is female, as is nearly half our development staff. And so naturally from us, three cheers for RPRCC!
From http://users.drew.edu/ftrees/TECS/Session_Descriptions.htm
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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New “Bid To Win” Book Available For Download
Galorath’s Evin Stump and SEER customer Bill Vitaliano wrote an excellent book on preparing winning bids. While Evin did this on his own time, he has given Galorath permission to distribute it.
I am pleased to recommend this book covering the right things to produce winning proposals. It saddens me when people equate price to win with lying or low-balling since price to win can be a viable engineering approach for defining the best product or service for a client while ensuring it is also affordable. While this book is written with larger proposals in mind I believe many of its principles are applicable to both bidding and internal development. Bid To Win Book
In addition to the basic book, the authors have written a bid to win novel, Saving SEIC: An Industrial Love Story, to bring the points home (if you have read “The Goal,” you will be familiar with this approach.)
For a succinct summary of the costing part of price to win, I also recommend Galorath’s Bob Hunt’s price to win briefing found elsewhere on this site.
PS: I am at the APMP conference where I heard a rave review of the book and the process. Hats off to both Evin and Bill.
PS2: Someone asked me today why they didn’t charge for the book. Evin said they just wanted to make it available to the community.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Live From UK Williams Formula 1: How SEER Made IRS Projects Successful
The US Internal Revenue Service used SEER for Software and SEER for IT to plan a major portfolio upgrade. They were able to catalog different types of systems in SEER-IT. Mitchell said if they could have done the estimates without SEER (and he didn’t think they could), it would have taken at least 10 times the effort.
This presentation will be available on www.galorath.com in a few days.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Live from UK Williams Formula 1: Euroclear Bank IT Support With SEER
SEER has become the keystone of Euroclear Bank’s project review process. They implemented independent estimation in addition to the project leaders’ SEER estimate and are providing support to negotiations with outsourcers.
Initially they had difficulties since project managers could not understand function points.
IT management then mandated SEER for all projects and also mandated an independent estimate.
They now have both internal function point counters and outsourced function point consultants.
Today the external team can explain the function points to the project leaders.
Euroclear found the following were the key drivers in their projects and limit usage to these in most cases:
- Size
- Team capabilities
- Location of IT management
- Development platform (knowledge base)
They are now using SEER for estimates and for monitoring project growth, at the end of the design phase and at the end of the project. This now allows them to estimate based on high level requirements.
They also collect software key performance indicators monthly.
Their lessons learned include:
- Start with a few parameters. Refine later.
- Calibrate function point counts and SEER
- Collect Final Actuals
- Must have management support
This presentation will be available on www.galorath.com in a few days
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Live From UK Williams Formula 1: The Virtual Composites Company
Kevin Potter discussed how he teaches students using SEER within the aerospace engineering department of University of Bristol.
They use SEER in design project work where students design an airplane. They use SEER to quantify affordability as well as what are the cost drivers of the engineering work they do.
He pointed out how SEER for Manufacturing is really a design for manufacturing (DFM) application, allowing affordability trade-offs for a variety of designs.
He focused on composites materials. He pointed out that many in composites have over-emphasized the impact of touch labor versus other components of cost.
This briefing will be available on www.galorath.com in the next few days.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Live From UK Williams Formula 1: DSTL Estimating Future Unmanned Air Systems
DSTL uses SEER and Galorath’s new CostIQ (Case based reasoning estimation) to rapidly generate estimates of Unmanned Air Vehicles. They are looking to reduce costs and increase the viability of estimates.
They need to understand the trade space of different system concepts and cost them to see how far they have to relax the capability until it is affordable.
CostIQ is allowing them to generate a complete estimate and detailed Work Breakdown Structure by describing performance based characteristics of a system. In UAVs, for example, reusability or not, range, payload, etc. are key drivers.
The paper will be available at www.galorath.com in the next few days.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Live From UK Williams Formula 1: Ford Motor Company Europe Uses SEER for Software and IT
This morning Ford Motor Company’s European operation presented their development process, how estimating is improving their developments and how they tie IT infrastructure and IT services into the estimate with SEER to see the complete costs, make trade-offs and produce successful solutions. They have several gates where estimates are required and a lessons learned post mortem. In an excellent talk the speaker pointed out that even when the requirements are known, there is requirements growth. This is modeled with the SEER “requirements volatility” parameter.
The presentation will be available at www.galorath.com in the next few days.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Possibilistic Versus Probabilistic Estimates
I was in a cost task force meeting this morning, looking for ways to improve cost analysis in outsource environments, both from the customer and the offerer sides. These have been interesting meetings in many regards. Today the discussion focused on outsourcers who provide a low estimate, looking for the best case to win the business rather than the most probable cost.
One of the panel members pointed out that some outsources bid “possiblistic” prices rather than probabilistic prices. Possibilistic estimates are possible, if everything goes right, but everything going right is not probable.
That is one of the reasons SEER provides a range in addition to likely costs & schedule.
We recommend planning for the probable, not just the possible.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Software Code Counter Review and Recommendations
Galorath’s Mike Churchman did a comprehensive evaluation of numerous code counting tools and provided recommendations.
While some people may wonder why anyone would want to count code (it can be useful when estimating the amount of work in reuse as well as gaining a benchmark for estimating new code when using lines as a size measure) Mike’s evaluation is very useful. I am including only the report on the top two tools.
Recommendations:
C/C++USC CodeCount
JavaUSC CodeCount
PerlUSC CodeCount (if you can get around the bug)
PHPCLOC.EXE, with adjustment factor
PythonCLOC.EXE, with adjustment factor
Test files:For Java, Perl, PHP, and Python, he used several files which I pulled from various SourceForge projects. For C++, he used our standard sample file from the manual and Dan’s book.
Manual count (Control)In the test files, he counted partial lines separately from SLOC, simply because he wasn’t sure about what to do with them, so my initial SLOC count simply doesn’t include partials at all.
The code counters which he tested were (for the most part) smart enough to tell the difference between blank lines, comments, and actual code. With very few exceptions, their blank-line and comment counts agreed, and matched my hand-counts.
There was, however, some significant variation in the SLOC numbers which they reported.
C/C++, Java, and Perl:The USC code counter generally gave the most conservative SLOC counts — ranging from the same as mine, to over 25% less. In many cases, the USC count was about 4% to 10% lower than his hand count.
Perl bug:He found one bug in the USC code counter for Perl: it appears that if the number of opening and closing quotes in a comment block don’t match, the counter stops counting SLOC, although it will continue to count comments and blank lines. Unfortunately, it also fails to recognize a quote character at the end of a comment line, unless it is followed by two spaces.
PHP and Python:The USC code counters don’t handle PHP and Python. The best of the ones that are available all give reasonably accurate counts of code (as opposed to comment or blank) lines, but they count partial lines as full lines. One promising-looking application, for example, counts (according to the online documentation) physical, rather than logical lines.
Suggestion:For PHP and Python (and for Perl, if you can’t find any practical way around the USC counter’s bug), you could use CLOC.EXE, which seems to give accurate total counts for SLOC + partial lines, then apply an adjustment factor to the output to get something reasonably close to an accurate SLOC count.
How do you come up with and adjustment factor? His first impulse would be to take some representative samples of code from various sources (the test files that I’ve been using might be sufficient, although we may want something larger), hand-count SLOC and partials, get an average SLOC-to-total (SLOC + partials) ratio for each language, and use that as a multiplier.
Other Code Counters:Universal Code Counter gives counts which generally match CLOC.EXE, sometimes, however, it seems to be rather far off the mark, and it reverses the counts for blanks and comments, which leaves me somewhat in doubt of its accuracy. Most of the other counters were less accurate, or at least less reliable.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Variances In Personnel Can Change Productivity By a Factor of 10
I got a question today from someone defining best practices on productivity based on personnel. They wanted to know what the differences might be based on their capabilities. It was easy to perform such a trade study in SEER-SEM for the overall productivity or just a partial.
Knowledge bases normally set these so no work is required unless there are known or anticipated specific circumstances. But this trade study took seconds. Here is part of the answer provided:
SEER people-specific parameters include:
Analyst Capabilities: Capabilities of the team to function (not just the individuals) and the impacts of management, motivation, etc. on that team
Analyst Application Experience: Average experience of the software team that will work on the project with the overall domain (such as finance or command & control)
Programmer Capabilities: Capabilities of the team to function (not just the individuals) and the impacts of management, motivation, etc. on that team
Programmers Language Experience: Average team experience with the programming language(s) that will be used in this implementation activity
Development System Experience: Average team experience with the computers, operating systems and other items that will be used to develop the software
Target System Experience: Average team experience with the target computers, operating systems and other items that will be used to execute the software in the end (target) environment
Practices & Methods Experience: Average team experience with the development processes, methods, standards and procedures used on this project
Knowledge bases set these in normal ranges so individual ratings are not required. And if you do know or want to do tradeoffs: One of the important things is to rate the team, not just the individuals, and how they will perform together. And of course the range allows the expressions of your uncertainty up-front.
Looking at the full range, from the worst of the worst to the best of the best, can provide a 10 to 1 variance in cost.
Also, here is a chart showing how those parameters increase costs when they are at the worst case.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Estimating the Cost & Schedule of Packaged Software Deployments
Packages (such as ERP systems, payroll systems, etc) can be great cost savings to organizations, offloading most of the development and maintenance. But they are not a panacea and many deployments fail. About two thirds of the cost of a large package deployment is not the software itself, but the IT infrastructure and other services. SEER for IT covers all those other two thirds of the cost along with SEER for Software (SEER-SEM) which handles all the software development and COTS cognition associated with such a program. Thus a complete package deployment can be estimated, planned and controlled.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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SEER-H Electro Optical Sensor Estimation Validation
If you estimate Electro Optical Sensors you will know what a challenge it can be. That is why SEER-H’s ElectroOptical Sensor model was developed. The following is feedback from a user: SEER-H EOS was within 6% of actuals and they thought they could have gotten even closer had they answered all the questions instead of just the first three. The report follows:
A confirmation of the SpyGlass EOS estimating tool and platform influence factors.
I received a recent Government Procurement announcement for one of the systems in the EO Sensor model database that provided the the unit’s cost and procurement history. The sensor is one of the projects in the CostIQ library. I loaded the the procurement info into the CostIQ SEER-H EOS project i.e. prior units, quantity buy and learning curve. SEER-H EOS projected a production cost of $487,722 and the actual Government procurement cost was $458,000, within 6% of the actual. Note: I had only reset the 3 parameters noted above.
I would expect if I were to do a detail analysis of the procurement/procurement history and tweaked SEER-H EOS the results would even more closely matched the actual procurement cost.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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Viable Software Estimation Modeling: A Key Component Of Software Risk Management
I spoke with someone recently who explained the reason they use SEER is for risk management. They pointed out that not only can they determine the risks of schedule, effort and reliability, but the whole of SEER allows them to do risk reduction. A process improvement: no problem, a quick trade off is performed by setting the appropriate SEER parameters for process improvement, process experience, development tools and practices and they can see exactly what to expect, both good and bad. Then when asked to justify the result he can state explicitly: this includes reduction of team experience with processes, the process improvement going on during this project, any tools being deployed in the process improvement effort and the anticipated cost / benefit.
And for projects that are not challenged with new and different challenges, knowledge bases do the job without needing to concentrate on parameters.
Thank you for reading “Dan on Estimating”, if you would like more information about Galorath’s estimation models, please visit our contact page or call us at +1 310 414-3222.
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