Software Cost Estimation: Guide to SCE

Estimating costs properly is essential for your business. Learn how to perform this process in this article!

Financial planning is a central element for many developers. The inability to plan your expenses is the surest way to encounter long-term organizational problems. The modern world is becoming increasingly reliant on the information technology tools. Most firms need to know how much their diverging products would cost to understand expenses. In this respect, software cost estimation is essential to proper planning and the consequent market success. In this article, we’ll review the definition of this term and outline the key procedures and tools necessary for this task.

Getting Started with Software Cost Estimation

Software cost estimation is the process of predicting the financial investment required for developing a software product. It involves assessing various factors:

• project scope;
• complexity;
• resources;
• time constraints.

This crucial step helps IT firms and businesses plan budgets and set realistic project timelines. Accurate cost estimation minimizes financial risks and ensures successful project delivery. It’s a vital aspect of project management, aiding decision-making and client communication. Effective estimation relies on historical data, expert judgment, and specialized tools to provide reliable cost projections.

Exploring the Mechanics of Software Cost Estimation

Software cost estimation deconstructs a project into its key parts. First, you should assess the project’s scope. It includes aspects such as features and functionalities. Secondly, consider factors like technology stack and required skill sets of the developers. A big aspect of making good predictions also involves development time. Even a company with a low hourly price can be extremely expensive if one engages in a long-term project. Historical data and expert judgment play vital roles in this process.

Once you have these details, apply estimation techniques like Function Point Analysis or COCOMO models. These methods use mathematical algorithms to calculate the effort and resources needed. The final step involves factoring in any potential risks or uncertainties. A good idea here is to hire management experts and actuaries to calculate both the technological and purely financial risk. What should be the result of dedicating time to full-scale software cost estimation? The result is a comprehensive projection of the project’s cost. 

Software Cost Estimation Models

Multiple models exist to assist businesses with the key task of software cost estimation. Here are some of the most popular models on the market:

1. COCOMO (Constructive Cost Model) 

COCOMO is a widely used model categorizing software projects into three modes: Basic, Intermediate, and Advanced. In its basic model, it estimates costs based on lines of code. However, more complex analysis is also possible with the help of this platform. It can adjust for multiple factors, such as product reliability and hardware attributes.

Every factor assigns diverging multipliers to a project depending on its rating (from very low to very high). For example, the knowledge of the developers offers a subzero multiplier (0.75, for instance), which lowers the costs. An urgent deadline can give a multiplier of 1.10, expanding the product costs. Based on these factors, one can later calculate the project price according to the number of hours or expert judgment. For a more academic discussion of COCOMO, we recommend an article by Chetan Nagar and Anurag Dixit.

2. Function Point Analysis (FPA) 

FPA splits all aspects of a computer program into several elements. They include measures such as inputs, outputs, inquiries, interfaces, and files. Showing some numbers after a simple calculation is easy. FPA assigns a low score for this task. In turn, delivering high-quality upscaling for the user images is a complex process that deserves higher points. It’ll get a higher score in FPA. After the software cost estimation specialists have finished calculating the points, they’re converted into effort estimates (usually based on hours). Using the hour-based method, you can analyze how much a product costs.

3. PERT (Program Evaluation and Review Technique) 

PERT or Program Evaluation and Review Technique is a probabilistic model considering optimistic, pessimistic, and most likely estimates for various project parameters. How does it function? It features four main steps:

1) Splitting the key task (for instance, creating a video app) into several small subtasks.

2) Estimating the most optimistic (everything goes perfectly), probable (the most likely issues occur), and pessimistic (everything that can go wrong goes wrong) scenarios for a task. 

3) Establishing the critical path: you should highlight the processes that, if delayed, can delay the completion of other tasks. The delay in setting up a server makes testing the app code hard.

4) Creating a timeline for development: with all this data in mind, you can create a full-scale timeline for developing your product. Knowing the approximate time the development will take, a firm gets an opportunity to do a full-scale software cost estimation.

4. Use Case Points (UCP)

In the UCP model, the managers split all product elements into use cases. For example, if we imagine a messaging app, use cases involve an encryption protocol, text coding, UI/UX, and various social functions such as friend lists. Once you’ve established the relevant use cases, it’s time to highlight their complexity and the number of assigned workers. Using this information, you can define how long every task takes and deduce costs from hourly payment.

5. Wideband Delphi

The key problem of all the preceding methods is their reliance on subjectivity. While they offer complex formulas, many of their elements, in reality, are opinion-based. The Delphi method is subjective by default, making it more reliable than other frameworks due to admitting weaknesses. Such an approach makes the attempts at software cost estimation potentially more accurate. How does this framework function? The model relies on expert judgment. Experts provide individual estimates, and then a facilitator summarizes and shares these estimates with a group. Rounds of estimation continue until a consensus is reached. The focus is on the top experts. In this way, subjectivity is countered by a high level of expertise. The method is so reliable that even healthcare organizations use it to help with diseases such as COPD, according to Sara Souto-Miranda (University of Aveiro, Portugal) and her colleagues. 

6. Parametric Estimation

Parametric models use historical data and statistical analysis to estimate costs. They consider project characteristics and apply regression analysis to derive cost estimates. If translated into more simple language, this information means that parametric estimation is about using past experience to give an approximate estimate of future projects. Many companies have developed multiple projects. This means they can make educated guesses.

7. Monte Carlo Simulation 

Monte Carlo simulations use random sampling and statistical techniques to estimate project costs. It’s a powerful technique for modeling complex situations and predicting outcomes in the face of uncertainty. It involves running thousands or even millions of simulations using random inputs to understand the range of possible results. This method is the most interesting because it doesn’t rely on subjective assessments. Instead, you need to use statistical data to do a Monte Carlo Simulation. The problem with the method is that sometimes, there are no statistics to make educated guesses.

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Main Factors That Affect Software Costing Estimation The Most

Multiple factors are crucial when considering any software costing estimation:

Scope and Clarity of Requirements

If you want to make a good software costing estimation, knowing what you want to develop is essential. The clarity and completeness of project requirements substantially impact cost estimation. Vague or frequently changing requirements can lead to cost overruns. This isn’t necessarily bad: sometimes, novel ideas need significant evolution to become of value to the customers. Creating a definite project scope may be difficult and even close to impossible if you’re in an innovative field. Still, the more information you offer, the better.

Complexity

The complexity of the software solution, including its architecture, integration with other systems, and technical challenges, greatly influences costs. More complex projects require more resources and time. Another vital problem with complex projects is that there’s always a risk of underestimating the key costs. Humans tend to confirm bias. More importantly, complex projects require complex technologies, which produce many unexpected bugs. In this situation, project complexity is likely to make all the estimations approximate.

Team Expertise 

The skills and experience of the development team matter. Skilled professionals can work more efficiently, potentially reducing costs, while less-experienced teams may take longer and incur more expenses. Here comes another problem in understanding if software costing estimation is reasonable. In this respect, the key problem is defining if a team is good. Extreme cases are easy to detect. However, not every cohesive team will bring major benefits to you. Why? The reason is simple. They may specialize in different tasks. 

Project Size and Duration

Larger projects spanning over a longer time tend to be more costly. Extended development periods may lead to increased labor and maintenance expenses. Simultaneously, if you have several small-scale projects, unified development time can benefit them. Economies of scale allow one to produce more due to having a cohesive team and many people working on the same task.

Technology Stack

Some technologies are more costly due to licensing fees or the scarcity of skilled professionals, while open-source options may reduce expenses. For example, governmental organizations must spend exorbitant sums on maintaining the professionals who know how to work with legacy programming languages. COBOL programmers can expect major income due to such systems being of value to government-related unemployment registers, according to Stack Overflow.

Overview of Estimation Types and Their Significance

Software cost estimating can take multiple forms. Some of them touch upon the aspects that may initially seem distant from the general cost estimation. Let’s review the key types of estimation existing in the modern market.

1. Time Estimation

Time estimation is crucial for project scheduling and planning. It helps determine when a project can be completed and ensures realistic deadlines. How does it assist the traditional cost estimation? In IT, many firms ask for remuneration based on payment per hour. This means, in essence, that knowing the overall amount of time you’ll need to develop a project is sufficient to estimate the costs. We at Keenethics, for example, offer specialist remuneration between 25 and 50 dollars per hour. Knowing how much every specialist gets, you can make good estimates of the overall costs to expect. Besides, when you know how much time development would take, it’s easier to orient one’s strategy to win a vital niche in the key markets.

2. Cost Estimation Per Se

Some companies can estimate cost based on diverging models. Most of them, as we’ve outlined above, use experience or the knowledge of the experts to make educated guesses about the overall project costs. For instance, a company developing dozens of websites yearly will likely know how much diverging products would cost. Such a direct cost estimation is useful but appears subjective and dependent on the immediate experience of the involved analysts. What’s the problem with such an approach? If met with novel technologies and new tasks, these specialists would not produce high-quality estimates. Cost estimation based solely on experience rather than other factors is limited only to well-known projects regarding their inputs and outputs.

3. Resource Estimation

Resource estimation means figuring out how many people and things are needed for a project. It ensures that the right resources are available when needed. When you know how much different projects require in terms of resources, predicting the future ones is easier. However, resource estimation for projects involving innovations (for instance, artificial intelligence) or new programming languages is less accurate. In this light, you can only be sure about the elements already developed in the past within them. Remember: novel projects are difficult to predict. If you have major innovations in mind, prepare to pay significant sums for promoting them.

4. Risk Estimation

Risk estimation assesses potential uncertainties and their impact on a project. It allows for risk mitigation planning and helps in avoiding unexpected setbacks. We’ve already discussed that most cost estimation methods involve uncertainty due to their subjectivity. In this light, risk estimation is the best addition to software cost estimation techniques. It allows one to look at the experience of varying risks as reflected in diverging formulas. A mainstream project such as a news website will likely face little risks. An AI-based platform for writing news articles, in turn, will be much riskier due to the known problems of the technology. Risk estimation is so valuable to most businesses today that actuaries have higher incomes in the U.S. than software developers. Some sources even name this profession as one of the most promising outside the medical field.

5. Quality Estimation

Quality estimation focuses on the expected quality of the project’s deliverables. It ensures that the project meets the required quality standards and customer expectations. This aspect is also an addition that can be, more or less, objective. Code of higher quality requires a bigger expenditure of time. As a result, good code will inevitably cost more than something average. 

More importantly, it’s easy to control the quality of code. Outside specialists know how to judge it and can perform independent stress tests to understand if a site or an app works well. Different projects need different quality. An MVP doesn’t require perfect code. A full product release needs to be as impeccable as possible. Based on this, you can make proper estimates about the overall price of your project.

6. Scope Estimation

Scope estimation defines the boundaries and deliverables of a project. As many people in IT know, development ends when developers and clients say it ends. In short, it’s possible to make extremely complex apps as long as you have unlimited time constraints. The problem with this approach is that you can easily lose the market to faster competitors in such conditions. This means defining the boundaries of a project, the key criterion of success, is essential if you want to have a realistic chance at success. Scope estimation is crucial because it helps avoid scope creep and ensures your project stays on track. 

7. Effort Estimation

Effort estimation calculates the work required from a project team. This aspect, once again, has a major subjective part and depends on the personal qualities of the involved individuals. It’s important for cost estimation due to reflecting the potential risks regarding the established price. If the workers define a project as difficult, this factor will inevitably be reflected in the cost review or, more importantly, the relevant risk analysis.

8. Accuracy Estimation

Accuracy estimation assesses the reliability of other estimations. It helps understand the level of uncertainty associated with project estimates. Usually, accuracy estimation comes in four forms:

1. Analysis based on experience;
2. Post-project analysis aimed at assessing the correctness of diverging measures;
3. Expert assessments (for instance, via the Delphi method);
4. Statistical probability risk analysis (via Monte Carlo framework, for instance).

Performing it is especially vital in projects with high risks and many unknowns. By considering past risky projects and all the potential pitfalls the specialists estimate, the experts can make realistic predictions about the long-term accuracy of the key estimations.

The Spectrum of Estimating Techniques

Multiple ways of estimating software costs exist in the modern market. Here are the key frameworks to consider:

Classification According to Data Quality

Deterministic Techniques

Primarily, you can try the deterministic techniques to assess potential project costs. They involve using experience in one form or another to judge certain projects. These estimates are accurate, but their key problem is the reliance on experience. If you have no past data, such estimates are unlikely to be valuable: 

1. Expert Judgment: Relying on the knowledge and experience of subject-matter experts to make estimates. Usually, experts have extensive knowledge of past experiences and can make serious judgments about the success of different techniques.
2. Analogous Estimating: Using historical data from similar past projects to estimate the current project. A common framework is to review several case analyses to then make a full-scale judgment about the long-term viability of a project, or even predict a cost based on past experiences.

Probabilistic Techniques

Probabilistic techniques also use a lot of past data, but they base themselves on the larger corpus of human activity. As a result, such frameworks may offer less accurate predictions than the ones using probabilistic analysis with good data. Still, they’re perfect for situations with many uncertainties. We’ve already discussed such probabilistic techniques in software cost estimation examples. You can read more about the Monte Carlo Simulation or PERT in other sections.

Classification according to hierarchy

Bottom-Up Techniques

Bottom-up estimation is a detailed and granular approach to estimating project parameters. It involves breaking down a project into smaller, more manageable tasks or parts. Each task is then estimated individually, and the estimates are aggregated to create a total estimate for the project. Key types of estimates:

1. Detailed Estimating: Breaking down a project into smaller tasks and estimating each task individually, then summing them up for a total estimate.
2. 3-Point Estimating: Combining three estimates for each task, optimistic, pessimistic, and most likely, to create a weighted average.

Top-Down Techniques

Top-down estimation techniques are a project management approach where you start with high-level or broad estimates and progressively break them down into more detailed estimates as the project planning and execution proceed. Here are two approaches that are the most common representations of this method:

1. Expert Opinion or Delphi Method: Gathering expert input anonymously and iteratively to reach a consensus estimate.
2. Functional Point Analysis: Assessing the functionality of an app to estimate the effort required.

Classification by the time of estimation

Historical Techniques

The first way to do an estimation based on the time of it being done is to assess before the project is complete. This approach benefits from the so-called historical techniques. The idea is to use the past data from different projects to make predictions:

1. Historical Data Analysis: Analyzing past project data to identify trends and patterns that inform current estimates.
2. Benchmarking: Comparing project estimates and outcomes against industry benchmarks or similar projects.

Step-by-Step Techniques

Not all projects can benefit from past predictions. Some requirements may be too unique to plan them accordingly. A project can also be too big to make definite assessments. In this light, the following techniques become essential for the long-term success of planning:

1. Rolling Wave Planning: you estimate high-level project parts at first and refine estimates as the project progresses. In short, the idea is simple. We offer a general estimate and then make it more accurate with the progress of the other components.
2. Progressive Elaboration: this approach is similar to rolling wave planning. The only key difference is that the managers and analysts continuously update and refine estimates as more information becomes available. In the rolling wave scenario, everything is done in iterations: earlier project parts receive more analysis than the later ones.

Software Project Cost Estimation Examples

Here are some hypothetical examples of software project cost estimation and the key techniques one may use to maximize the impact of these practices:

Mobile App Development

• Project Description: Suppose a startup plans to develop a mobile app for ride-sharing services. The app will have user registration, driver matching, real-time tracking, and payment processing features.
• Estimation Steps: The estimation begins by identifying key functionalities and user stories. Each user story is assigned a complexity rating, and development efforts are estimated in story points. For instance, user registration might be estimated at five story points and driver matching at eight story points. The development team’s velocity, or the number of story points they can complete in a sprint, is then determined. You can estimate the sprints required by dividing the total story points by the team’s velocity. The cost is then calculated based on the team’s hourly rates and the number of sprints.

Software Upgrade Project

• Project Description: Consider a scenario where a company wants to upgrade its existing customer relationship management (CRM) software to a newer version. The upgrade involves migrating data, testing, and ensuring compatibility with existing workflows.
• Estimation Steps: The estimation process starts with a detailed assessment of the current CRM system. The project is divided into phases, such as data migration and training. Each phase is estimated separately based on the hours required. For instance, data migration might take 100 hours, software upgrade 300 hours, and testing 150 hours. The estimated costs for each phase are added together to determine the total project cost.

These practical examples demonstrate how software project cost estimation involves breaking down a project into manageable components, which are then analyzed based on the required effort for each aspect. The estimates are then used to calculate the overall project cost.

Main Cost Estimation Tools

Several prominent tools for software project cost estimation exist on the market. Here are the key projects available to the customers.

Microsoft Project

Microsoft Project (a part of Microsoft 365) is a versatile project management app with robust cost estimation capabilities. It enables users to create detailed project plans and estimate costs based on various factors such as labor, materials, and overhead. With its user-friendly interface, it’s suitable for businesses of all sizes and industries, offering powerful project tracking and reporting features. Using this platform, one can easily recreate PERT and other estimation methods. Microsoft openly describes how to outline such charts via the in-built frameworks on its home site. 

Oracle Primavera

Oracle Primavera is an enterprise-level project management and cost estimation tool for complex and large-scale projects. It provides advanced features for budgeting and risk analysis. Primavera is particularly popular in industries like construction, engineering, and energy, where precise cost estimation and project control are critical. This project should be of interest to the users for two reasons. Firstly, it offers many options for project control and even has diverging versions that enable different controls (past Primavera frameworks were keyboard-based; this factor may interest many people even today). Secondly, the platform gives access to the whole Oracle ecosystem. This company is notable for its Java products and a dedicated operating system for cloud storage, Oracle Solaris. Still, the popularity of Primavera also leads to negative outcomes: you should be aware of the ransomware apps targeting this product. Thorough attention to updates is essential in this situation.

Estimatica: Diverging apps + expertise

While this discussion focuses on complex estimate apps, a good option is to use several non-specialized apps and combine this knowledge with vital field-related experience. Estimatica is a specialized construction cost-estimating site trusted by professionals in the construction industry. The company behind it provides access to an extensive database of material and labor costs, streamlining the process of creating accurate estimates. Estimatica doesn’t have a unique app for calculating the costs. Instead, it combines Planswift, Groundplan, Smartsheet, and Excel apps for different calculations. Its core team members have more than a decade of experience in the relevant field. As a result, they can make extremely accurate estimates without resorting to complex apps. All this makes it a comprehensive solution for construction projects. Remember: a good cost estimate is about processes rather than the calculation apps.

CostOS 

CostOS is a comprehensive cost estimating and management solution used in industries like construction, infrastructure, and energy. It provides features such as 2D and 3D takeoff, cost modeling, and what-if analysis to help users generate precise estimates. CostOS also offers advanced reporting and integration capabilities, making it a valuable tool for complex projects requiring accurate cost assessments. One can easily import their Excel cost estimation tables into this app to facilitate a simple transition. All this makes CostOS a perfect tool for estimating projects in the construction field.

QuickBooks 

QuickBooks, primarily an accounting software, also includes basic cost estimation features. It’s well-suited for small businesses and entrepreneurs who must create estimates, track expenses, and manage budgets. While not as robust as specialized project management tools, QuickBooks delivers a user-friendly interface and essential financial instruments to help businesses monitor and control costs across various industries. Since this app is so popular among many companies, it makes sense to use its internal tools for cost estimation. In our opinion, this framework is great for almost all fields as long as projects are small. QuickBooks accounting features will likely be sufficient if you intend to create a website.

Exploring the Purpose of Software Cost Estimation

The purpose of estimating software costs isn’t difficult. The key reason to consider it is two-fold. Firstly, it allows one to plan the expenditures for a certain project. This aspect is an essential element of success for a startup with limited funds. Secondly, software cost estimation is a positive practice because it allows the prediction of risks within a project. By performing a proper cost estimate, one can assess if their project will likely fail due to risks and if it deserves investment. In short, software cost estimation becomes a perfect method for safeguarding funds.

Estimating the Cost of Software Development with Keenethics

All in all, modern software cost estimation approaches are incredibly diverse. They offer a wide range of possibilities for the involved firms. You can predict both definite and indefinite situations. If you need help with software cost estimation, a good idea is to address professionals with multiple years of experience developing diverging projects. Experience can help determine costs or, at least, tell you that a project is risky due to many unclear elements. We at Keenethics give project cost estimates, which you can find on our website.

FAQs

What does software cost estimation stand for?

Software cost estimation is about calculating expenses in developing or maintaining software projects, aiding budget planning.

How to do software cost estimation?

To estimate software costs effectively, use expert insights, historical data, parametric models, and meticulously consider project scope, complexity, and resources.

What’s the best way to calculate risks?

Calculating risks effectively involves:

• Analyzing potential threats.
• Assessing their impact and likelihood.
• Using quantitative and qualitative methods like risk matrices and Monte Carlo simulations.