Total Cost of Ownership for Custom Software Projects: What Businesses Need to Know

The software industry faces a critical challenge: high project failure rates. A recent BCG survey of global C-suite executives revealed that more than 30% of their technology development projects ran over budget and behind schedule. The root causes of these failures often stem from misalignment between business and technology teams, unrealistic timelines, and inadequate resource allocation.

Another reason for budget overruns lies in the inaccurate total cost of ownership (TCO) estimation for building custom software. As the study suggests, many companies focus only on the initial development costs and don’t take into account ongoing expenses such as infrastructure, licensing, third-party services, maintenance, scaling, security, and operational support. However, these overlooked costs can add up over time, significantly impacting the overall budget.

Understanding what TCO means and what it comprises will let you better align your project budget with goals, avoid hidden expenses, and ensure long-term software viability. In this article, we’ll explore the costs that shape TCO in custom software development and ways to estimate it.

But first, let’s start by discovering why TCO is an important factor in financial decision-making.

When investing in custom software development, businesses often focus on upfront development costs while underestimating long-term expenses. However, the real financial impact goes beyond initial coding and deployment. Without a clear understanding of the total cost of ownership, your company risks making short-sighted decisions that could drain resources and hinder growth.

That’s why understanding the total cost of ownership is essential for long-term planning.

TCO provides a comprehensive view of all costs associated with custom software development over its entire lifecycle, many of which can be overlooked in budgeting.

So, why does estimating TCO matter?

When calculated correctly, TCO allows you to assess your choices and whether they are economically viable and efficient in the long run. Take the example of the FBI’s Virtual Case File system. Initially budgeted at $170 million, it was intended to modernize the bureau’s case management. However, due to poor project management and escalating maintenance requirements, the TCO skyrocketed, and the project was eventually dumped after costing over $100 million more than planned.

When calculating the TCO for custom software, expenses fall into two main categories: direct and indirect costs. Understanding what these cost categories comprise is essential for accurately preparing initial budgets and long-term financial planning.

Direct costs are easily measurable and directly tied to software development, deployment, and maintenance. These expenses are typically documented in financial reports and project budgets, covering aspects such as developer salaries, infrastructure, licensing, and ongoing support.

Indirect costs, in turn, are harder to quantify, but they significantly impact the total cost of ownership over time. These costs are not typically included directly in project budgets but affect business operations and profitability.

Let’s start with direct custom software costs. These costs typically include the following expenses.

One of the most significant TCO components is the initial investment in building custom software. This includes the costs of planning, designing, coding, testing, and deploying the software. The total cost depends on many factors, including project complexity, team composition, and pricing models.

Below are some of the key aspects affecting development costs.

• Costs associated with software architecture, design, and prototyping. It covers everything from defining system components, database structures, architecture type, and cloud deployment strategies to creating wireframes, mockups, user flow, and prototypes. The cost of this phase depends on system complexity and the technologies used.
• Quality assurance (QA) costs. QA is a crucial part of software development, which, based on Leobit’s experience, typically constitutes 15-25% of the total project budget. QA includes manual testing and automated testing. The costs of manual testing depend on the number of test cases and their complexity. Automated testing uses scripts and tools (e.g., Selenium, Cypress, and JUnit) to test software functionality at scale. While the initial investment is higher since you need to pay a fee for using tools, automation reduces long-term testing costs by accelerating test execution, and minimizing human effort.

• Documentation. Well-structured documentation is crucial for long-term software maintainability. It should cover code structure, API specifications, deployment procedures, and troubleshooting guides. Lack of proper documentation can slow down onboarding, increase debugging time, and complicate future updates. Investing in clear, up-to-date documentation reduces dependency on specific team members and ensures continuity as the software evolves. This, in turn, helps you avoid unnecessary expenses in the future.
• Team composition. Certain software projects require highly specialized expertise (e.g., AI/ML engineers, data scientists, security and compliance experts) that can drive up costs. On top of that, the experience level of developers (e.g., junior, middle, or senior) can also significantly affect development costs and efficiency.
• Collaboration model. The choice between in-house development and outsourcing significantly affects TCO. In-house development costs include salaries, benefits, and overhead (e.g., office space, equipment, software licenses). Moreover, hiring skilled developers can take months and also increase costs. Outsourcing, in turn, offers access to a broader talent pool without the need for long-term hiring commitments. Depending on the outsourcing destination, the labor costs can also be lower.
• Custom software development pricing models. If you choose to outsource, a collaboration between a software development service provider and you can go through several main models: project-based contract, time & material (T&M), outstaffing ODC, BOT (Build-Operate-Transfer), and a dedicated team model.

Software often requires hosting, server space, and databases, all of which come with ongoing infrastructure costs. The choice of hosting affects both the upfront investment and long-term expenses but also impacts performance, security, and scalability.

Infrastructure and hosting costs will depend on the following factors.

• On-premises vs. cloud-based deployment. On-premises infrastructure requires a substantial upfront investment in servers, networking equipment, and data centers. Additionally, businesses need to hire experts to handle setup and ongoing maintenance, further increasing costs. Beyond that, you should also cover ongoing expenses for energy consumption and dedicated IT staff. Cloud-based deployments eliminate capital expenditures by offering a pay-as-you-go model. However, long-term costs can accumulate due to storage, bandwidth, and API request fees.

• Cloud service and deployment models. While cloud services offer flexibility and reduced upfront investment, their long-term costs vary based on usage, storage needs, and service model (IaaS, PaaS, and SaaS).
• Scalability considerations. Cloud environments offer on-demand scaling, which can minimize idle costs. However, improper scaling configurations can have quite the opposite effects and lead to unexpected cost surges. On-premises scaling, in contrast, requires buying additional hardware. The long-term financial impact of scalability depends on workload predictability, data transfer fees, and system architecture choices.

In a nutshell, to properly plan your project budget, consider the initial deployment and the total cost of ownership (TCO) over time.

Once deployed, custom software requires continuous maintenance and support to ensure stability, security, and performance. These costs accumulate over time and significantly contribute to the TCO. Neglecting maintenance can lead to technical debt, security vulnerabilities, and system glitches, which would only increase long-term expenses.

Below, we’ve gathered the main aspects affecting maintenance costs.

• Regular updates and performance optimization. Software maintenance can cost 60-80% of total lifecycle costs. This includes refactoring code, database optimizations, and adapting to updated APIs or third-party integrations. Without consistent upkeep, software can become obsolete over time and lag behind competitors.
• Software monitoring and security patching. Continuous system monitoring is crucial for identifying performance bottlenecks, security threats, and potential issues before they become major problems. Security patching is particularly critical, as unpatched vulnerabilities expose businesses to cyberattacks. Implementing automated monitoring tools and a proactive patch management strategy helps mitigate risks but requires dedicated resources and infrastructure investment, hence influencing TCO.
• Customer support and helpdesk expenses. Supporting end users through troubleshooting, training, and issue resolution adds another layer to TCO. The complexity of the software and its user base determines support costs. For instance, enterprise-grade applications with a global audience often require multilingual support teams, 24/7 availability, and service-level agreements (SLAs), which would, in turn, increase operational expenses.

Custom software rarely operates in isolation. It can integrate with existing systems, third-party services, and external data sources. The complexity of these integrations significantly impacts the total cost of ownership, as you should also account for their maintenance and potential compatibility issues.

• Costs of using third-party services. Many custom applications rely on third-party libraries, frameworks, and services to extend functionality. These could be a payment gateway, an authentication provider, or an analytics tool. While such solutions accelerate development, they introduce ongoing licensing costs, API usage fees, and potential vendor lock-in. Updates to third-party tools may require refactoring code, which may add to maintenance overhead.
• Proprietary vs. open-source software costs. Proprietary software, like commercial databases or enterprise frameworks, usually comes with licensing fees but offers support, security, and compliance guarantees from the vendor. In contrast, open-source software is free to use but may require additional investment in security audits, maintenance, and specialized developer expertise to ensure stability and meet business requirements. As a result, the choice between proprietary and open-source software impacts both short-term and long-term costs.
• Subscription fees. Cloud platforms and SaaS tools often operate on a subscription-based model, charging businesses based on usage, storage, or feature tiers. Infrastructure providers like AWS, Azure, or Google Cloud impose fees for computing power, data transfer, and storage, which can scale unpredictably as the business grows. Additionally, tools like CI/CD pipelines, database management platforms, and testing suites contribute to recurring operational costs.
• Collaboration platforms. Modern software development relies on collaboration tools like Confluence, Microsoft Teams, and Jira for documentation, communication, and project management. While these platforms enhance productivity and streamline workflows, they introduce additional licensing fees per user. For large development teams, these costs can become substantial, especially when integrating multiple tools across departments.

A well-planned approach to managing licensing, integration, and third-party service costs lies in carefully selecting software dependencies and monitoring their usage. When planned right, it ensures that costs remain predictable and aligned with business objectives.

The cost of securing software varies depending on industry requirements, geographic location, and the sensitivity of the data being processed. However, it is very likely you’ll have to include the following expenses in your TCO calculation.

• Regulatory compliance and certification expenses. If your business operates in regulated industries like fintech or healthcare, you must ensure your software adheres to standards such as GDPR, CCPA, HIPAA (Health Insurance Portability and Accountability Act), PCI DSS (Payment Card Industry Data Security Standard), or SOC 2 (Service Organization Control 2). Achieving compliance requires legal consultations, security audits, and periodic assessments, all of which add to long-term costs. Failure to comply can result in heavy fines or even lead to lawsuits.
• Data protection and cybersecurity measures. Ensuring your data is safe at rest and in transit requires investments in encryption, secure authentication mechanisms, and network security protocols. Features like multi-factor authentication, role-based access control, and intrusion detection systems enhance security but increase development and operational costs.

In a nutshell, compliance and security costs are unavoidable components of software ownership. However, integrating security measures from the early stages of development and continuously monitoring compliance requirements allows your company to minimize financial risks.

Now that we have discussed the direct software development expenses, let’s turn to indirect costs. These expenses aren’t directly related to software development but impact the overall TCO over time. They are often harder to quantify but significantly affect the total investment.

Deploying custom software often requires significant investment in training and change management to ensure successful adoption. Even the most well-designed solution can fail if end users are not adequately prepared or don’t understand how to use it.

Though it may be difficult to estimate them from the outset, the following costs contribute to TCO and should also be considered to understand the whole picture.

• User training and documentation. Developing comprehensive user manuals, FAQs, and interactive tutorials adds to initial costs but reduces the long-term burden on support teams. Training complexity depends on the software’s functionality, where more complex systems may require extensive onboarding while simpler applications may require minimal training.
• Resistance to change and productivity loss. If you develop an internal tool, chances are that your employees may initially resist new software due to unfamiliarity or disruption to established workflows. Investing in change management strategies, such as phased rollouts, pilot programs, and user feedback loops, helps mitigate resistance but requires additional planning and resources.

Training and change management costs are an essential but often underestimated part of software ownership. A well-structured training plan and proactive change management strategy can help you minimize productivity losses and ensure a smoother adoption for your users.

As your business grows, your software should scale accordingly and accommodate increased user demands and new features. Failing to plan for scalability can lead to performance bottlenecks, expensive rearchitecting efforts, and higher operational costs, all of which contribute to the total cost of ownership (TCO).

Here, we’ve gathered the most important aspects you should consider.

• Infrastructure scaling and performance optimization. Expanding a software system to support more users or handle higher data volumes often requires additional server resources and database optimizations. In cloud-based deployments, auto-scaling features help dynamically allocate resources based on demand. However, without careful monitoring and cost optimization strategies, expenses can quickly grow due to inefficient resource usage. On-premises scaling, on the other hand, demands hardware investments and increased maintenance efforts.

• Software upgrades and codebase maintenance. As technology advances, software frameworks, programming languages, and third-party integrations need regular updates or migration to newer versions to remain secure and compatible. Maintaining legacy code can become expensive over time and require refactoring or even a complete overhaul.

• Adding new features and expanding functionality. Your business needs to evolve, requiring software to adapt to new features and integrations. Developing these enhancements requires additional planning, coding, and testing, which would also affect TCO. Poor initial architecture can make feature additions complex and expensive. To reduce future enhancement costs, it’s important to ensure the software has a modular, well-documented architecture from the start.
• Long-term technical debt management. Rapid development cycles or shortcuts taken to meet deadlines can lead to technical debt (i.e., inefficient code, outdated dependencies, or workarounds that hinder future development). So the more technical debt your software has, the more time, cost, and effort it would take to get rid of it.
• End of support for the technology used. Software frameworks, databases, and third-party services can reach the end of their lifecycle. That is actually what happened to Xamarin recently. When such a situation occurs, your business should migrate to newer technologies. Delaying upgrades and staying with outdated technology can lead to security vulnerabilities, compliance risks, and compatibility issues. Planning for technology transitions will add to TCO, but it will also prevent costly emergency migrations.

Scaling and future enhancements are inevitable in a software’s lifecycle. Proactive planning, scalable architecture, and ongoing performance monitoring help minimize costs and ensure that the software remains efficient, adaptable, and aligned with business needs.

Since the costs of custom software extend far beyond initial development, you should use structured calculation methods to account for both direct and indirect expenses over the software’s life cycle. There are several approaches to estimating TCO for software development, each suited to different project scopes and financial planning needs.

Let’s take a closer look.

• Lifecycle cost analysis (LCA). This method evaluates costs across different phases of the software lifecycle (software architecture, design, development, deployment, maintenance, and eventual expansion). It ensures that you account for long-term expenses, including upgrades, compliance, and security.
• Cost breakdown structure (CBS). CBS categorizes expenses into distinct components, such as infrastructure, licensing, development, integration, and support. This granular breakdown helps identify hidden costs and allocate budgets efficiently.
• Incremental TCO estimation. In agile development, software evolves over multiple iterations, so a one-time TCO estimate will be insufficient. Instead, you should reassess costs at each development stage to account for new feature requirements, shifting priorities, and evolving market conditions. However, continuous monitoring is required to prevent cost overruns.
• Comparative TCO modeling. Businesses evaluating deployment models or technology stacks can use comparative modeling to assess costs. This would help them identify the most cost-effective option. For example, comparing on-premises and cloud-based solutions might start with calculating upfront capital expenses for on-premises hardware versus subscription-based cloud pricing. Additionally, businesses need to assess long-term operational costs and the expenses associated with compliance and security for each deployment model.

Yet, estimating TCO manually can be time-consuming and prone to errors, especially for complex software systems. The good thing is that the market offers ready-to-use tools to help automate and refine the process.

Here are some of them.

• Spreadsheets and custom models. Many businesses rely on Excel or Google Sheets to create detailed TCO models. Advanced features such as pivot tables, macros, and what-if analysis help simulate different cost scenarios, making it easier to assess long-term financial impact. The biggest drawback, however, is that they require manual updates and a solid understanding of cost modeling to ensure accuracy.
• Cloud TCO calculators. Leading cloud providers like AWS and Microsoft Azure offer built-in TCO calculators to estimate infrastructure expenses, including virtual machines, storage, data transfer, and managed services. For example, AWS’s calculator allows you to compare different instance types, reserved vs. on-demand pricing, and projected scaling costs over time. Azure’s tool provides insights into hybrid cloud strategies. While these calculators are valuable for infrastructure planning, they often overlook indirect costs such as compliance, integration efforts, and long-term software maintenance. So, to get a complete TCO picture, you should supplement these estimates with manual calculations.
• IT financial management software. Solutions like Apptio, ServiceNow, and Upland ITFM integrate real-time financial data, track IT spending across departments, and provide automated cost forecasting. They can also help you allocate budgets, identify cost-saving opportunities, and ensure that IT investments align with business objectives. Unlike spreadsheets, financial management software provides centralized visibility and reduces the risk of human error.

To ensure a more precise and well-rounded TCO estimation, you can use a combination of these tools.

Estimating the TCO for custom software is a complex process that requires a detailed analysis of both direct and indirect costs across the software’s lifecycle. However, several challenges often lead to inaccurate estimations.

Here are some of the most common ones and strategies to address them.

• Incomplete cost identification. One of the biggest pitfalls is when companies focus solely on development expenses while underestimating ongoing costs, such as cloud hosting, third-party integrations, security updates, etc. For example, a business may budget for initial development but fail to account for API request fees or increasing data storage costs as the software scales. To be on the safe side, we suggest including a comprehensive cost breakdown that covers the entire software lifecycle. By using cloud TCO calculators and financial modeling tools, you can forecast these costs more effectively.
• Hidden costs and technical debt. Rushed development and shortcuts can lead to technical debt, hard-to-diagnose bugs, and undocumented features that slow down future updates. To minimize this risk, we recommend you prioritize code quality, invest in regular refactoring, and enforce robust documentation practices.
• Inflation and cost adjustments. Many cost estimates fail to account for inflation, which, in the long run, may lead to unrealistic long-term budget planning. To be on the safe side, we suggest integrating inflation adjustments into your TCO models. To create a more accurate financial outlook, you should use historical data and economic projections.
• Hard-to-determine costs. Some expenses, such as security breaches, system downtime, and unexpected performance issues, are difficult to predict but can have significant financial consequences. To mitigate these risks, you can set aside contingency budgets that could cover potential events that are hard to predict in budgeting.
• Missing cost components. Large software projects often involve numerous cost factors, making it easy to overlook certain expenses, such as compliance costs, or license upgrades. To prevent underestimation, you can use standardized cost frameworks, conduct regular audits, and validate calculations against real-world software deployments.
• Absence of benefit analysis. TCO calculations should not focus solely on costs, but you should also evaluate your software’s return on investment (ROI). For example, the B2B purchasing and assortment management platform for jewelry enterprise retailers that we developed helped our customer achieve 26% revenue growth in just six months. Without quantifying these gains, businesses risk seeing software purely as a financial burden rather than an investment.

Addressing these challenges requires a structured and proactive approach to TCO estimation. To ensure a well-rounded analysis, companies should estimate key performance indicators (KPIs) such as time savings, error reduction, increased customer retention, or higher sales conversion rates.

Considering both immediate and long-term costs allows your company to develop a realistic budget and so minimize financial risks. Financial modeling tools can help you compare TCO against projected ROI, ensuring that cost decisions align with long-term business goals.

Many businesses fall into the trap of focusing only on initial development costs while underestimating ongoing expenses such as maintenance, cloud hosting, security, compliance, and scaling. To accurately plan a budget and ensure long-term growth after the initial development stage is over, you need to calculate a TCO before starting software development.

Additionally, a thorough TCO estimation requires considering both direct and indirect costs to ensure a well-structured budget. To do such estimation right, you can use structured methods like lifecycle cost analysis and comparative modeling, along with tools such as cloud TCO calculators, IT financial management software, and custom spreadsheet models.

With experience in delivering 150+ software projects, Leobit can help you accurately estimate the TCO for your custom solution. Contact us to ensure a cost-efficient and scalable software investment.