Author: Adam Boettiger

1099 Contractor Opening for Digital Nomad

Part-Time Contractor Performing Dev Ops duties as Webmaster



We are seeking a contractor for an ongoing part-time role starting at 5-10 hours per week. Reports directly to Chief Marketing Officer.

The four areas that we need help in are Maintenance & Security, Site Performance (speed/mobile usability), SEO and Adding Content.

We have specific things that need to be done now. Others can wait, hours permitting. This is a long-term, scalable role for the right person.


  • Prior experience providing website maintenance / webmaster duties
  • Reliable internet connection
  • Experience locking down (securing) WordPress from exploits
  • Experience performing weekly & monthly maintenance on a WordPress site, updating plugins etc.
  • Experience with GTM Google Tag Manager
  • Experience using a browser plugin to determine that tags are firing properly
  • Experience setting up recurring site backups using something like Updraft
  • Experience optimizing a WordPress website for page speed and page experience
  • Knowledge of site-side SEO (image optimization/reduction, xml site maps, indexing, title, alt tag updates)
  • Experience with Contact Form 7 and/or Gravity Forms
  • cPanel & hosting experience (WPEngine)
  • Be responsive (within reason) by Slack channel, email & occasional video calls
  • Experience with CloudFlare CDN, other CDN, image cacheing
  • SSH/FTP etc.
  • DNS registry experience
  • Be organized and proactive (identify problems & recommend solutions)
  • Operate relatively autonomously, with minimal management
  • Be a freelancer and not an agency
  • Be the person doing the work (no subcontracting)
  • Be available for a video interview


  • Experience with WordFence or Securi plugins
  • Experience with landing page development, either via WP or an external service like Unbounce
  • Experience working with Canna Theme
  • Experience with Google Analytics, GA4, goals setup, reporting, alerts
  • Experience with Zapier
  • Experience working agile sprints

If this is you, please provide a cover letter of introduction and anything else you’d like us to review for consideration, along with your hourly rate.

Adam Boettiger [email protected]

Thank you!


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BHP: Galorath Estimation Framework Identified the Cost to Build a Smart Mine

The Challenge

BHP Group Limited is the world’s largest mining company by market capitalization and is based in Melbourne, Australia. In 2015 BHP began development of the world’s largest potash mine near the town of Jansen, near Saskatoon Canada. When complete, the Jansen mine is expected to produce eight million tons of marketable potash at full capacity.

To better understand the cost of this multi-billion-dollar project, BHP requested Galorath Incorporated to help generate an estimate for the Jansen Mine data infrastructure.  However, this is far from a typical data center.  Covering over 9600 square kilometers in size, the Jansen Mine will be an innovative and integrated smart city – underground.

Our Solution

With the boring machines beginning the first of two vertical shafts, Galorath assembled a team of experts that worked alongside the BHP project engineers to capture all the smart city requirements.  The team identified what Internet of Things components would make the journey 1000 meters below the surface as a fully connected environment.  According to Loren Budd, a Principal Business Analyst in Technology at BHP Billiton, the company was looking for an estimation capability that would provide a steadfast estimate and carry its project forward.

“We were looking for something we could use to build a comparable model for our mine and stand behind the numbers we got out of the model. We also needed to use it on a regular basis for day-to-day work once we’re in construction, as we revise it, as we finish projects, as we change our assumptions, and feed into our next project,” Budd said. “I’m really looking at this as a total solution to provide process and tooling to create that defendable budget, but also to use long term.”

The Result

Galorath estimation framework allowed BHP engineers to understand the complexity and cost of the thousands of interconnected computers, sensors, safety monitors, and intricate mining pathways. At the end of 2019, BHP CEO Andrew Mackenzie announced the project as 50% complete, with all major items on schedule and budget.  This includes the successful delivery of a 975-meter production mine at and service shaft 1,005 meters deep.

BHP is now completing the construction stages of the mine and will create an entire city to house the 2500 operations staff.  When complete, the Jansen mine will result in BHP producing fifteen percent of the world’s much-needed potash resources.

Galorath is proud to have been a part of the BHP Jansen Mine success story. Our vast range of experience in large complex projects and IoT technologies positions Galorath to be an invaluable partner for all technology and project types.

The future is now.  Let Galorath be your guide as you move onward from the ordinary and begin embracing this new dawn of innovation and smart cities of the future.

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Lines of Code Versus Function Points Versus Use Cases For Sizing

I, along with many others, have written about the virtues of one size metric versus another.  Some attempt to make their measure look better by bashing the others (a curious approach used by too many, in my opinion)

Lines of Code: Can Work I hear some people say “Lines of code don’t work because people don’t know how to count them.”  I certainly agree that if the definition of a line is not consistent sizing will suffer.  But some of these same people say “function points do work because they are not language specific and they are better defined that is sometimes true.

So many issues with Lines of code counting..  My personal favorite definition of lines of code involves using logical lines meaning that the number of physical lines it takes to write a statement is irrelevant.  That it is the logical statement that is important.  Even there some people call my definition of logical lines physical lines.  Go figure.  Of course SEER for Software will work with any definition, as well as the many function point definitions.

Function Points Can Work: There is some sound logic to the argument that function points work because they have a common definition.  Only problem is…

So many organizations make up their own definition… I recall reviewing a project estimate on a major program.  One of my standard questions “what is a function point” got an odd stare.  They said they would have to get back to me on that.  When they finally did I found that they had their own, company specific definition, nearly 10 times bigger than traditional.   Now that is not all bad.. if a consistent definition is used it is likely OK for estimating.  Only problem is they didn’t normally advertise that their definition was different.  So, when showing productivity they were much more productive.  But models showed over estimation (in SEER for Software they could have defined their new function point method and resolved this but they didn’t… they just put their not a function point count in as normal function points.  This is not a one time occurrence.  I have seen this on numerous occasions.

Oh.. and go tell senior management a system is 4000 function points.  More likely than not you will receive a blank stare.  A function point is a pretty esoteric concept to the uninitiated.

SEER-FBS in the table refers to SEER’s function based sizing.  Function based sizing can be used to approximate function points from simple characteristics with end user oriented language.  And it shows independent functionality.  For example, what is the effort to add 1 report.  Function based sizing was developed during a multi year study of how to make function point analysis quicker and consumable by laymen.

Use Cases Can Work:Then there are those who want to use use cases as their size measure.  I like use cases and we have written papers on this topic and even have an automated use case extraction  adapter to SEER-SEM.  Unfortunately, however, use cases cannot, by their very nature, provide as much fidelity in the estimate as more granular measures.  So… use cases are great for early estimates or high level portfolio planning.  But if a project manager wants a detailed estimate and plan, use cases provide too much variance in the estimate.  This is due to their nature.  They are wonderful since they are natural artifacts of the development process.  But they are much higher level abstractions of the problem.  My recommendation, use use cases early, then a more detailed size measure when producing a detailed project plan. Use case points, derived from use cases can help a bit if you are willing to refine the use case point estimates.  But now you may sink back into the function point issues.

Bottom line: all three measures, lines, function points and use cases can be used for estimation.  Definition is important.  And the closer to the natural artifacts of development the approach is the more likely it is to be used.  But just using use cases will have more variance.

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What Is Parametric Modeling?

Unlike most project management tools which focus on automating features or workflow, parametric, predictive modeling tools help organizations model and optimize project feasibility and ensure that projects meet established delivery guidelines. Parametric modeling takes its name from the project parameters or variables that are modified during the project simulation process.

Parametric models are built from a set of mathematical equations. These may be standard equations found in reference books, proprietary equations developed by consultants or vendors, or some combination of the two. In order for parametric models to have any validity they must be based on or proven using actual project data. It is the sophistication of the data analysis methods and the extensiveness of the underlying project data which determines the effectiveness of a modeling solution.

Parametric methods are very useful for subjecting uncertain situations to the rigors of a pre-defined and proven mathematical model. They can usefully embody a great deal of prior experience and are less biased than human thought processes alone.

Commercial parametric modeling solutions typically offer extensive graphical feedback, thus making them easier to use. Commercial models also offer other benefits, including support for risk-based inputs, sizing “wizards” and numerous assessment mechanisms to improve the accuracy of estimates.

Want to know more about parametrics? Software Sizing, Estimation, and Risk Management, a 541-page hardcopy reference book by Daniel Galorath and Michael Evans is available at

Galorath Incorporated has worked for over two decades to help organizations better plan for and control project risks, costs, duration and quality. In developing the SEER line of project management tools, they have leveraged modeling technology and project-applicable knowledge bases to replicate actual project outcomes.

Contact us to learn more.

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Price to Win: What It Is and When Estimation Gets Involved

I am continually amazed at the wide variety of opinions about what Price-To-Win is and who plays what role in Price-To-Win.

I have spoken to some customers that are offended by the term Price-To-Win.  They hear it as “trick the customer to win.”  Of course that is not what price-to-win is all about.  Price-to-Win is about choosing the most affordable alternative that fulfills the customer need and that also will be successful against competition.


Price-to-Win identifies the correct balance of capability that can be delivered to the customer at the value the customer wants. Price-to-Win provides management insight for:

  • Competitive positioning
  • Strategic partnering
  • Risk tolerance
  • Customer relations
  • Optimal bid strategy

This information is derived by:

  • Market inputs
  • Engineering identification of viable alternatives
  • Engineering architectural design of each alternative
  • Cost and risk analysis of alternatives and risk alternatives
  • Price analysis (cost and price are two different issues)


  • Step 1: Gather market intelligence: Marketing personnel identify competitors possible strategies and
  • Step 2: Determine requirements & features
  • Step 3: Sketch out Architecture Design
  • Step 5. Determine viable alternatives
  • Step 6: Cost Analysis & Estimation of Alternatives
  • Step 7: Select best alternative
  • Step 8: Establish price


Galorath and SEER primarily support the estimation and analysis of alternatives, taking inputs from engineering, marketing and others.  The result of this includes cost and cost risk.  Once that cost is determined, price analysis will determine the actual price to bid. This price may vary significantly from the cost based on business decisions.

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What Is IT Infrastructure: A Definition and a Taxonomy

There are probably as many definitions of IT Infrastructure as there are IT organizations.  I believe the following definitions are representative and appropriate:

IT Infrastructure: “IT infrastructure consists of the equipment, systems, software, and services used in common across an organization, regardless of mission/program/project.  IT Infrastructure also serves as the foundation upon which mission/program/project-specific systems and capabilities are built.” from

ITIL defines infrastructure more like: All of the components (Configuration Items) that are needed to deliver IT Services to customers. The IT Infrastructure consists of more than just hardware and software.

Additionally, for project planning purposes I believe IT Infrastructure should be subdivided into several components:

  1. Software Development
  2. Software Maintenance (corrective perfective, adaptive, block changes)
  3. Purchased Software (e.g. ERP system)
  4. IT Infrastructure hardware (e.g. servers, switches)
  5. IT Services (e.g software setup, help desk, computer administration)

Further, there are two major divisions of labor: the project and ongoing operations:

  • Project: The project is the portion of the system life cycle where the system is developmental, that is where it is not yet in operation.
  • Ongoing Operations: The ongoing operations is the portion of the system life cycle where the system is deployed to users

Of course, these major activities need to be further subdivided for detailed analysis and planning purposes.

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Should Cost Model – Should Cost Analysis For Projects

The advantages of outsourcing a project can be substantial – allowing your organization to free up internal resources, gain access to world-class capabilities, and increase revenue potential. Of course, there can also be significant cost savings.

However, to utilize these advantages, you must have a clear understanding of what you should be paying for an outsourced project. Without knowing the “should cost”, there is a strong likelihood that you will either be paying too much or requiring more hands-on attention than you originally anticipated.

A should cost analysis provides a solution that can give you the knowledge, data, and framework to empower you with the information you need to determine fair market pricing when negotiating with outsourced vendors. With the SEER project management tools from Galorath, you can create an accurate should cost model that enables you to effectively negotiate with suppliers while maximizing profitability through the optimization of a variety of critical parameters.

SEER’s “should cost” models provide the credible and defendable estimates necessary to effectively negotiate and give the insight to compare outsourcing options with in-house capabilities.

For nearly three decades, Galorath Incorporated has been dedicated to the mathematical science of parametrics in the application of cost estimation technology, developing solutions that assist project estimation, planning and management. SEER by Galorath solutions combine an intuitive interface, extensive project-applicable knowledge bases, sophisticated should-cost and project-modeling technologies and rich reporting features to accurately forecast real-world outcomes by combining advanced modeling technology with a database of industry and user-defined metrics.

SEER for Software provides a systematic approach for estimating the resources and scheduling that software development and maintenance projects require. Along with an unparalleled capability for trade-off and risk analysis, SEER contributes to the generation of realistic project plans, thus increasing the probability of a project’s success.

SEER for Hardware, Electronics and Systems provides total cost of ownership for the development of components, systems and integrated product assemblies from concept through design, test, production, operations and support.

SEER for IT enables organizations to develop an early, accurate assessment of costs, schedules and risks for IT projects and their operations, helping to maximize productivity and output with fixed or declining budgets.
SEER for Manufacturing estimates part and assembly manufacturing costs. All state-of-practice and state-of-the art manufacturing processes are supported and are routinely updated.
The SEER for Electro-Optical Sensors plug-in expands the capabilities of SEER for Hardware, Electronics & Systems, allowing you to perform a full lifecycle cost for space, manned aircraft, unmanned aircraft and missile based EO sensors.

The SEER-IC Integrated Circuit Estimation Model provides the automated tools you need to estimate the costs, schedules, and risks associated with developing and producing Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) and Radio Frequency Integrated Circuits (RFICs).

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Parametric Cost Estimating


An estimate is the most knowledgeable statement one can make at a particular point in time. A complete estimate includes:

  • Effort/Cost
  • Schedule
  • Risk
  • Reliability

A viable estimate should also be produced with consistent definitions and a repeatable estimating process, not just based on whims or guesses.

Parametric Cost Estimating couples a structured estimating process with statistically based parametric/predictive modeling methods to provide a basis for high confidence estimates. Parametric modeling takes its name from the parameters (or variables) that are modified during the project simulation process. Parametric models are built from a set of mathematical equations. These may be standard equations found in reference books, proprietary equations developed by consultants or vendors, or some combination of the two.

Parametric cost estimating is a method for estimating future proceedings based on analysis of past events and trends. “Parameters” (conditions) that appear to have driven what happened in the past are identified, and connected to past experience through mathematical relationships.

In order for parametric models to have any validity, they must be based on or proven using actual project data. It is largely the sophistication of the data analysis methods and the extensiveness of the underlying project data which determines the effectiveness of a modeling solution. With an extensive data base of project performance characteristics from a wide range of projects derived from both commercial and aerospace applications, Galorath’s SEER parametric modeling software provides users with proven and easy to use parametric cost modeling capabilities. Parametrics are what drive Galorath’s SEER models. They are also what the insurance industry and others use in estimating costs of future risks.

To facilitate the effective use of parametric cost estimation, Galorath provides the SEER suite of parametric cost estimation models software that has been demonstrated to provide excellent projections for cost, schedule, and risk across a wide range of applications including commercial, embedded, and defense oriented domains. As parametric modeling software, the SEER applications will support any estimation problem for:

For over two decades, Galorath Incorporated has helped organizations better plan and control project aspects such as duration, costs, risks and quality. The SEER line of project management tools powerfully combine project-applicable knowledge bases and modeling technology to predict project outcomes. To learn more about how we can help you better estimate, plan and control projects, call 301-414-3222 or contact us.

With a common user interface and integration across the SEER suite of models, the ability to use multiple parametric models is simplified and provides consistent capabilities for all projects. For example, in an IT system, software development, package implementation, IT infrastructure and IT services are all estimated along with total ownership costs.

An important part of parametric cost estimating is the ability to perform tradeoffs (what-if analysis) to find the most viable plan for a mix of possibilities. This critical ability is inherent in all of the Galorath applications.

SEER’s parametric modeling software provides:

Interface: An intuitive interface for defining and describing the problem and analyzing the solution. A series of pop-up windows and annotations help guide users through the process of defining project scope, complexity, and technologies. Users can generate a new project from an existing project “template” or by adding and defining individual work elements.

Simulation/modeling engine: Sophisticated, sector-specific mathematical models derived from extensive project histories, behavioral models, and metrics.

Knowledge bases: A virtual “in-house expert,” providing default project definitions, values, ranges, and calibrations based on the domain and histories. These enables users to develop first-look estimates when very little information is known, and to refine those estimates as details become available.

Output: Numerous charts, graphs, reports and dashboards for quickly summarizing and presenting project outcomes and alternatives, as well as work-in-progress.

Risk Analysis: A full risk analysis is included, allowing uncertainty to be evaluated and the best decisions to be made.

Additionally, Galorath has an experienced staff of consultants available to help with unique situations and to support our parametric modeling software during deployment, calibration, and estimate processes as well as overall estimating the parametric cost models to best fit your particular situation.

To see examples of how effective using the SEER parametric cost models can be, a number of SEER customers have graciously allowed some of their successes to be published on the Case Study portion of the Galorath web site.

Contact us to learn more about how SEER’s parametric cost estimating and modeling can help your organization take the guess work out of estimating, planning and controlling projects.

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Moving From a Rough Order of Magnitude (ROM) Estimate to a Detailed Project Plan


Project managers—whether they work for a software development company, a manufacturing company, or an engineering design firm—are faced with the common challenge of estimating project scope in terms of cost, effort, schedule, and risk. But before a project begins, your company must decide whether the project is even feasible based on your company’s budget. Or perhaps you want to gain some new business and you need to submit a proposal to develop some new widget.

Almost always, the project manager begins by determining a rough order of magnitude (ROM) estimate, which is just what the name sounds like. This estimate gives a “ballpark,” or order of magnitude, for the project. In other words, this high level estimate lets you know whether the project is going to take $50,000 or $5,000,000. Whether it will take six weeks, six months, or six years.

According to A Guide to the Project Management Body of Knowledge (PMBOK® Guide), a ROM estimate typically varies from −25% to +75%. For technology projects during business case analysis ROM estimates often -50 to + 50% of actual costs: generally on the low side. Depending on how the ROM was developed, the ballpark number may be enough to decide that the project is feasible and to proceed with that bid proposal – or not! A ROM estimate with an associated probability can provide sufficient information. Then, to gain a better understanding of the project costs, schedule, effort, and risk a more detailed estimate should be prepared. For example:

  • How much will the project cost per phase, per month, overall? What are the material costs?
  • What components/modules/parts/tasks are the key cost and schedule drivers?
  • What are the cost and schedule impacts of design alternatives or changes in overall scope?
  • What level of effort and how many personnel resources and of what type(s) will be needed?
  • How long will the project take? Can it be finished soon enough for the market?
  • What is the probability that the project will be completed on time and within budget?

SEER Tools Help with ROM and Detailed Estimates

SEER is an interoperable suite of products that lets you capture and input anything you know about a project and simulates what you do not yet know—giving you the range of probable outcomes, including a most likely estimate.

Regardless of whether you have a software project to develop a new mobile app with just 50 functions, a design project to develop and test a new avionics system for the latest jet, or a manufacturing project to determine the most cost-efficient way to manufacture that new widget, there is a SEER solution that helps you understand everything you need to know before committing:

  • SEER for Software — Provides a systematic approach for estimating the cost, schedule, effort, defects, and risk of software development and maintenance projects.
  • SEER for Information Technology — Provides total cost of ownership for IT projects, including infrastructure, services, operations, and on-going support.
  • SEER for Hardware — Provides total cost of ownership for the development of hardware and electronic components, systems, and integrated product assemblies from concept through design, test, production, operations, support, and retirement.
  • SEER for Manufacturing — Estimates detailed manufacturing and assembly costs for a wide variety of manufacturing processes. Identifies the cost drivers, risks, and ranges for production.

SEER provides the most comprehensive coverage of project domains. Furthermore, SEER solutions are interoperable, so users may combine the results from one solution into another solution to perform the best analysis possible.

Because the SEER models are parametric-based with a large number of knowledge bases, you can use the built-in intelligence to derive initial parameter settings based on industry experience, even if many of the parameters are not defined yet for the project. The following figure shows the knowledge base categories and example selections for SEER for Software.




SEER lets you build ROM estimates with as little or as much detailed information as you have available—again, capturing the information you know about a project’s parameters and simulating what you do not know. But in every case, the estimate is created in a repeatable, credible, traceable, defensible manner. When upper management or your customer asks how you derived the estimate, you have the traceability to show how and why the estimate came about.


Specifically, let’s say you’ve got a project to develop a sales toolkit and you are using the SEER for Software model to estimate the project.

Note: While this example is specific to a software project and shows the SEER for Software model, the same concepts apply across the suite of SEER models and any of the project domains that SEER covers, from manufacturing to IT.

Initially, you might only know that this should be a toolkit for sales staff, and the toolkit should contain a client database, a central repository, and some sort of product demonstration package.

Flexible Work Breakdown Structure

SEER supports a flexible functional work breakdown structure that lets you move from a first-order ROM estimate to a detailed budget estimate.

Suppose that in addition to the initial information (in which you only knew the three basic requirements of needing a database, repository, and a product demonstration package), you now have more specific requirements:

  • Client database must contain a contact manager, custom reporting capabilities, and a client interface.
  • Central repository must contain two types of databases, the ability to be replicated, and location set up.
  • Product demonstration package must contain a multimedia viewer, a browser, and a product index.

Given those requirements, you can add elements to the work breakdown structure to give more clarity and gain a more detailed estimate.

With the SEER for Software solution, each element can have:

  • Different parameter settings
  • Different sizing
  • Different development method
  • Different quality standards
  • Unique staff loading/profile

Furthermore, you can record and retain alternative solutions in the work breakdown structure, allowing you to make tradeoff analyses.


SEER tools use probabilistic models with built-in risk and uncertainty analysis. This means that given the likely risk and uncertainty of the project, you input parameter values and SEER will return a probability estimate of how likely you are to achieve your project goals.

Parameters are entered as input values of:

  • Least
  • Likely
  • Most

For example, how experienced will the programmers be for this project? If this is really unknown, you might say the worst case is going to be a programmer with a minimum amount of experience; the likely scenario is a mixed level of experience; and best case, the “A” team with 10 years of experience.

Or, what will the size be for one of the software modules? SEER for Software lets you express software size in a number of ways, for example:

  • Number and type of functions
  • Number of lines of code
  • Function points
  • Use cases
  • Story points

You might estimate that a single component might a least value (best-case scenario) of 2500 lines of code, a likelyscenario as big as 5000 lines, or a most value (worst-case scenario) is 15,000 lines of code.

The SEER tool, for example, SEER for Software in this case, will use the input values and return the probabilistic outcome, taking into account the uncertainties that you’ve entered. For example, you only have a 20% chance of doing the work you’ve described in 4 months and an 80% probability that it will actually take 9 months.

This probabilistic analysis lets you do tradeoffs in the model with parameters for which you actually have influence or a good understanding. What if the project was shifted to the “jelled” development team, what if some of the work is outsourced, what if functionality is reduced and postponed to a future release… and so on. SEER lets you change the what-if scenarios to give you the confidence level you need that the project can be completed under budget and on schedule.


After you have generated an estimate in SEER, whether that is a ROM estimate or a detailed estimate, you can transform the estimate into a detailed, task-oriented project plan in Microsoft Project or P6. This lets you:

  • Create custom life cycle templates that build best practices directly into your project plans
  • Customize labor categories to reflect the way that your organization assigns tasks (for example, to departments or labor categories) to accurately plan staff allocation for a project


Project managers need repeatable, reliable tools to help develop ROM estimates. SEER provides the ideal software to create such estimates because of the breadth of knowledge that the tools incorporate with the parametric analysis and probabilistic analysis of outcomes. Furthermore, SEER provides the ideal way to transition from a simple ROM estimate, to a detailed estimate, to a project plan that lets you manage the project from start to finish.

Contact us to learn more about how one of the SEER tools can help your organization take the guess work out of estimating, planning, and controlling projects.

Visit us at: or contact us at: [email protected]; +1-310-414-3222.

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Software Maintenance Cost

The need to monitor maintenance costs

most common mistake young tech entrepreneurs make is to drastically underestimate the amount of money spent on software. It is a common notion that software costs are a one-time expense that is incurred when the software is being developed/purchased. On the contrary, industry experts estimate that over 90% of all costs related to a relatively modern piece of software are the regular maintenance costs that most companies don’t account for. This ends up upsetting the budget and, in some cases, even throwing the entire project off track.

Modern software solutions are often highly intricate pieces of technology that require regular updates and maintenance. This maintenance work can often be tedious and time-consuming and needs to be planned for well in advance. State of the art, bespoke (custom made) software is even costlier to maintain as it requires a dedicated support team that is available at all times. Furthermore, effective software maintenance requires proper documentation so that the developers can be spared the trouble of going through thousands of lines of codes in multiple modules to locate and troubleshoot the problems.

Basic cost breakdown

The entire process of software maintenance involves many moving parts with varying degrees of complexity and resource requirements and hence different costs. Depending on the company’s software needs and existing market conditions, a varying number of services can be included in a standard maintenance package. Broadly, these services can be classified into three types.

  • Corrective
  • Adaptive
  • Enhancing

Corrective software maintenance procedures involve all the work done to troubleshoot problems that the program/ software might experience. These can be the problems that show up during the initial testing phase (in which case they are to be solved right away) or once it is out to the consumers (in which case the troubleshooter programs need to be issued in update packets sent to the users). These usually make up for 20% of all software maintenance costs.

Adaptive maintenance procedures involve all the updates/changes made to the program to match up to current industry standards. No matter how cutting edge, a piece of technology needs regular updating to keep up with the latest developments in its field. Consumers usually opt for the most convenient, comprehensive options, which make adaptive maintenance a vital part of the technological upkeep. It makes up about 25% of all software maintenance costs.

Enhancing maintenance can be clubbed with adaptive maintenance procedures depending on the   company’s   needs. They are usually procedures done to include/remove any program functions as per the board and consumers’ suggestions. These are usually segregated from adaptive measures as they are solely based on the company’s discretion. Regular system enhancement can ensure maximum user satisfaction. These make up over 35% of all software maintenance costs.

It is essential to understand that these procedures do not entirely account for the Total Cost of Ownership (TCO) of a piece of software. The TCO usually includes various other factors such as deployment costs, licenses, legal fees, copyright costs, app store/ search engine commissions, etc. Other indirect expenses like marketing the new software to potential clients, training existing employees to operate the software/ hiring specialists, etc. can also be counted under the TCO. The TCO is an essential tool that helps a company plan for any expenses incurred during the maintenance and deployment of a particular software.

Factors that affect software maintenance costs

A lot of real-world factors can lead to a fluctuation in software maintenance costs. An extremely dynamic market can require more modification than a particular software can handle. Such software pieces (called ‘inflexible programs’) need to be rebuilt from time to time to keep up with the industry standard. This leads to inflated software maintenance costs.   These can be managed by scheduling the process of modification as per the ROI that the program offers.

A software’s dependence on external servers (cloud or physical) is also a significant factor in deciding maintenance costs. Server space is relatively expensive and hence programs that require large servers can prove to be expensive.   A clear idea of the amount of data your program is expected to hold for a particular time helps in accurately estimating these costs. A lack of server space would leave your program essentially debilitated, while a surplus of it would be a waste of money.

Apart from these, there are numerous other real-world factors that can upset your software maintenance budget. These can be accounted for by having a ‘buffer sum’ that would be used in the case of any such emergencies. This can be about 15-20% of the total estimated maintenance cost.

Ways to cut down software maintenance costs

DevOps is a highly effective programming method that helps in minimizing maintenance costs. The practice involves techniques that can make software development ‘continuous’ where the existing modules are still functional and can be used by the company while the modified ones are being worked on. Once the changes are made, DevOps ensures seamless transition, helping the users achieve a smoother transition.

Automatic site monitoring tools can save the hassle and time required to inspect the site for bugs regularly. Uptime Robot, Site 24 x 7, Tornimo, etc. are services that can be availed to ensure better documentation and detection of errors in the software program. This makes the entire process smoother and hence saves the company a lot of time and resources.

Software maintenance is a tricky yet integral part of the operations for any company. By considering all factors and plotting down an accurate plan of action, companies can save themselves the trouble of having to face unexpected expenses/time delays. A well-documented, well looked after software is often the difference between a mediocre and a successful organization.

While the above methods give you a general idea about software maintenance costs, Galorath’s SEER Project Management Application can give you a more accurate figure for your company’s software costs.


Imagine your business is implementing a software solution and is performing a cost/benefit and ROI analysis. How do you estimate the total costs of the solution which go far beyond the initial deployment? Specifically, how do you estimate the software maintenance cost? How will you be able to factor in software maturity into the overall decision? Without reliable software maintenance cost estimation, your business will be unable to accurately assess the Total Cost of Ownership (TCO), and how well can you rely on the projected ROI.

Businesses frequently mistake software maintenance for “bug” fixing, however the bulk of cost issues are caused by enhancements in functionality, as the software solution evolves over time. Software evolution is extremely difficult to factor into costing estimates.

How do you control these future costs (and benefits) which will follow successful implementation of a software solution?


Software maintenance cost is derived from the changes made to software after it has been delivered to the end user. Software does not “wear out” but it will become less useful as it gets older, plus there WILL always be issues within the software itself.

Software maintenance costs will typically form 75% of TCO.

Software maintenance costs include:

  • Corrective maintenance – costs due to modifying software to correct issues discovered after initial deployment (generally 20% of software maintenance costs)
  • Adaptive maintenance – costs due to modifying a software solution to allow it to remain effective in a changing business environment (25% of software maintenance costs)
  • Perfective maintenance – costs due to improving or enhancing a software solution to improve overall performance (generally 5% of software maintenance costs)
  • Enhancements – costs due to continuing innovations (generally 50% or more of software maintenance costs)


Of course the percentage of each maintenance activity is variable based on the specific system and the above allocation rules of thumb are only rough general ideas.

Galorath’s SEER project management applications provide for an accurate and intuitive tool set for estimating software maintenance costs, development costs, upgrade costs and total ownership costs. SEER’s software maintenance cost model allows companies to identify the key drivers in post-deployment software costs and combines accurate estimation with a broad knowledge base.


Galorath’s SEER cost, schedule, risk and reliability estimating, planning and monitoring solution is used by thousands of projects worldwide: everything from IT systems to embedded systems.

For over 25 years, SEER has been providing cutting edge analysis and includes:

  • Project Cost Management Software – allows you to easily identify critical cost components and establish possible outcomes by changing parameters so you can test design/functionality/cost tradeoffs much earlier in the development cycle
  • Project Planning Software – helps you understand project scope and complexity, and allows a detailed, yet “intuitive” feel for project planning and assisting with the entire software development lifecycle
  • Project Tracking Software – provides superlative project monitoring and control to enable you to keep your software development on track

SEER for Software includes the following features:

  • Easy to Use Interface – a quick and easy, intuitive GUI for defining your software project. New projects may be added by using pre-existing project entries and defining new or modifying existing work elements. Powered by a pop-up wizard which guides users through the process of defining project scope and complexity and identifying what resources are required.
  • Simulation and Modeling Engine – leading, state-of-the-art modeling tools derived from a very wide ranging database of project histories, key metrics and behavorial models.
  • Knowledge Base – provides good “first look” estimations when information is scarce, effectively provides a virtual, in-house expert for providing project parameters and estimates based on prior project histories.
  • Output – a full suite of project management and executive reporting tools is provided including report writing templates, executive summaries, charts and sensitivity analysis for use at any time in the project’s development and deployment.
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