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Featured-Post-Software-EN Software Engineering (EN)

Software Development Agency Rates in Switzerland: What You Really Pay

Software Development Agency Rates in Switzerland: What You Really Pay

Auteur n°2 – Jonathan

In Switzerland, quotes for the same software requirement can vary threefold. This dispersion goes beyond hourly rate differences: it reflects choices in approach, expertise, technical scope and project governance. Decision-makers must therefore scrutinize a quote’s details to distinguish what’s included, what’s estimated and what might be billed as extras.

Components of the Quote: Understanding What Lies Behind the Price

A high hourly rate isn’t necessarily indicative of long-term extra costs. A low-cost quote may hide significant technical shortcomings.

Hourly Rate, Fixed Price or a Hybrid Model

In Switzerland, a developer’s hourly rate can range from 100 to 200 CHF depending on expertise and specialization. Agencies in Zurich, for example, often charge more than those in Geneva, citing higher living costs and payroll expenses.

However, an all-inclusive fixed price for a bespoke digital project can offer budget visibility—provided the scope is precisely defined. This is common for mobile app proposals or software quotes structured in phases (“discovery,” development, testing, deployment).

Hybrid models combine a daily rate with milestone-based fixed fees: they ensure both flexibility and budget control. Yet they require meticulous tracking of the software project scope and shared governance between the client and the Swiss development provider.

Licenses, Infrastructure and Maintenance

A quote may include software license costs (commercial component libraries, ERP, CMS, proprietary third-party APIs) or rely entirely on open-source solutions. The open-source approach naturally avoids vendor lock-in and minimizes recurring fees, thereby reducing the total cost of ownership (TCO) over time.

Sizing cloud infrastructure, provisioning servers, CI/CD pipelines and monitoring often represent 15–25 % of the overall budget. This line item—sometimes underestimated—ensures performance and scalability for a digital project.

Finally, corrective and evolutionary maintenance (SLA, support, security patches) should have its own line in the quote. A reliable Swiss-made provider will detail availability commitments and response times without artificially inflating the initial bill with poorly anticipated extras.

Surprises and Additional Costs

Unforeseen costs usually arise from out-of-scope change requests or unplanned technical adjustments. Billed hourly, these can drive the budget up at the end of a project. We’ve published advice on how to limit IT budget overruns.

Documentation, user training and digital project support are sometimes deemed optional, even though they determine a software’s sustainability and adoption. It’s wiser to include these services in the initial digital project estimate. Our article on the risks of missing technical documentation offers pointers to avoid this pitfall.

Lastly, a seemingly low quote may hide extensive subcontracting to low-cost developers without guarantees on code quality or responsiveness in case of critical bugs.

Factors Influencing Software Development Agency Rates in Swiss Romandy

Several local and strategic variables affect the cost of application development in Geneva and beyond. Understanding these factors lets you compare digital agency quotes knowledgeably.

Agency Location and Structure

Agencies based in Geneva or Zurich often maintain city-center offices with high fixed costs. These overheads are reflected in hourly rates but ensure proximity and responsiveness.

A small specialized firm may offer slightly lower rates, but there’s a risk of resource overload during peak periods, which can triple or quadruple your delivery times. Conversely, a larger agency provides absorption capacity and scaling—essential for large-scale bespoke digital projects. Your software’s security, performance and scalability also depend on the size of the provider.

Choosing between a local agency and an international group’s subsidiary also affects your level of strategic advice. A Swiss-made player with its core team in Switzerland often leverages deep knowledge of the local economic fabric and delivers project support aligned with Swiss regulatory requirements.

Expertise, Specialization and Project Maturity

Specialized skills (AI, cybersecurity, micro-services architecture) command higher rates but ensure robustness and scalability for business-critical software.

A mature project backed by strategic planning benefits from an exhaustive specification and a clear software project scope. This reduces uncertainties and, ultimately, the risk of costly project compromises.

In contrast, an exploratory project with frequent iterations demands more flexibility and short cycles. The budget must then include a margin for prototyping, user testing and adjustments, rather than imposing an overly rigid development budget.

Client Size and Corporate Culture

Large corporations or publicly traded companies typically require longer validation processes, security audits and frequent steering committees. These layers add significant time and cost.

An SME or scale-up can adopt leaner governance. The cost-quality-time triangle can be adjusted more swiftly, but the absence of formalities may lead to late scope reviews and additional expenses.

Industry sectors (finance, manufacturing, healthcare) often impose high compliance and security standards. These requirements must be anticipated in the quote to avoid hidden clauses related to audits or certifications.

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How to Balance Cost, Quality and Timelines

The lowest price isn’t always the best choice: it can mask technical and human deficiencies. A well-defined software project scope ensures alignment between business needs and your web application budget.

Apply the Quality-Cost-Time Triangle

The classic quality-cost-time triangle illustrates necessary trade-offs: accelerating a project raises costs, cutting price can extend timelines, and lowering quality entails long-term risks.

A small, simple project—like a custom API integration—can be done quickly and affordably. By contrast, an integrated platform with ERP, CRM, mobile modules and reporting systems requires significant investment and a more extended schedule.

When comparing digital agency quotes, request a clear breakdown across these three axes: which scope is covered, at what quality level and within what timeframe? Without this transparency, choosing a quality agency becomes impossible.

Prioritize Your Project’s Functional and Technical Scope

Precisely defining essential features (MVP) and those slated for phases 2 or 3 helps frame the initial budget. This approach controls Geneva application development costs without compromising business value.

A vague scope leads to endless back-and-forth and dozens of billed hours for minor tweaks. Conversely, an overly rigid scope may exclude needs that emerge during the project.

The right balance is to split the project into clear milestones and include a buffer for the natural uncertainties of bespoke development in Switzerland.

Assess Long-Term Value and Solution Maintenance

Poorly documented software without automated tests incurs disproportionate maintenance costs. Every update becomes a leap into the unknown, risking breaks in existing functionality.

By evaluating the five-year TCO rather than just the initial budget, a “bargain” quote often reveals its shortcomings: under-resourced QA, missing CI/CD pipelines, underestimated repeat deployments.

Investing slightly more upfront to ensure a modular architecture, leverage open-source and define a maintenance plan can sharply reduce recurring costs and secure your application’s longevity.

Pitfalls and False Low-Ball Offers: Avoid Unrealistically Low Quotes

An abnormally low rate seldom means genuine savings. Understanding low-cost methods and contractual traps helps you keep control of your budget.

Low-Cost Offers and Offshore Subcontracting

Some Swiss providers fully outsource development to offshore teams. Their rates seem attractive, but distance, time-zone differences and language barriers can delay deliveries.

Back-and-forth on anomaly management or specification comprehension becomes time-consuming and generates hidden costs, especially for coordination and quality assurance.

Combining outsourced development with a local Swiss management team offers a better balance: faster communication, adherence to Swiss standards and accountability from the primary provider.

Another issue with agencies subcontracting their own software and app development abroad is limited control over code quality and technical decisions. We often work with clients who were lured by low prices but ended up with software or a mobile app that couldn’t handle user load, had security vulnerabilities, numerous bugs or lacked evolvability. These combined issues can render the digital solution unusable. Engaging an agency whose core team is based in Switzerland ensures a flexible, secure software solution truly aligned with your strategic needs.

Insufficient Contractual Clauses and Guarantees

A quote may offer a fixed price without detailing liability limits, SLAs or intellectual property rights. In case of dispute, lacking these clauses exposes the client to extra costs for fixing defects.

Free bug-fix warranties are often limited to a few weeks. Beyond that, each ticket is billed at the standard (and usually higher) hourly rate once the inclusive maintenance window closes.

A reputable provider always states the warranty duration, delivery conditions and offers digital project support covering minor evolutions without surprises when issuing a mobile app or business software design quote.

Misleading Presentations and Hasty Estimates

A one-day estimate without proper scoping, software engineer input or risk analysis yields an unreliable quote. Error margins can exceed 30 %, with upward revisions during execution.

Agencies offering quick quotes sometimes aim to lock in clients before they explore competitors. This undermines transparency and can compromise trust throughout the project.

Comparing digital agency quotes therefore requires a rigorous selection process: scoping workshop, solution benchmarks and joint validation of assumptions and estimated effort.

Choosing a Sustainable, Controlled Investment to Succeed in Your Software Project

Understanding quote components, the factors driving rates in Swiss Romandy and the trade-off between cost, quality and timelines enables an informed choice. A fair rate relies on a clearly defined scope, a modular architecture and a realistic maintenance plan.

Whatever your industry or company size, at Edana our experts are ready to analyze your digital project estimate and help you structure a tailored budget. Their contextual approach—rooted in open-source and business performance—ensures uncompromising digital project support.

Discuss your challenges with an Edana expert

PUBLISHED BY

Jonathan Massa

As a specialist in digital consulting, strategy and execution, Jonathan advises organizations on strategic and operational issues related to value creation and digitalization programs focusing on innovation and organic growth. Furthermore, he advises our clients on software engineering and digital development issues to enable them to mobilize the right solutions for their goals.

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Digital Consultancy & Business (EN) Featured-Post-Software-EN

Total Cost of Ownership: Custom Software vs Pay-Per-User SaaS Licenses

Total Cost of Ownership: Custom Software vs Pay-Per-User SaaS Licenses

Auteur n°3 – Benjamin

Content:
Comparing the total cost of ownership (TCO) of custom software with that of pay-per-user SaaS licenses is crucial for any medium or large company in Switzerland as it directly impacts financial health, innovation capacity, and competitiveness.

Beyond the sticker price, you must factor in initial investments, recurring subscriptions, hidden update costs, and flexibility to adapt to evolving business needs. This analysis determines not only the short-term financial burden but also the impact on cash flow, scalability, and innovation.

This article outlines the key selection criteria, reveals the hidden costs of many SaaS solutions, and shows how Swiss companies can reduce vendor lock-in risks, control their technology roadmap, and gain a sustainable competitive advantage tailored to their specific challenges by favoring an open-source custom solution.

Breakdown of Initial and Recurring Costs

The structuring of CAPEX and OPEX differs significantly between custom software and SaaS licenses, affecting your budget from the earliest stages.

Initial Investments (CAPEX) vs Subscriptions (OPEX)

For custom software, CAPEX includes functional analysis, design, development, and architecture. These expenses are incurred upfront and create a tangible asset that you can amortize over multiple accounting periods.

In pay-per-user SaaS, OPEX begins at deployment: each additional license generates a monthly or annual cost. If your headcount grows or you add temporary users, operational expenses can skyrocket without ever creating proprietary intangible capital.

Our article CAPEX vs OPEX illustrates the fundamental difference between these two concepts and helps you better structure your digital projects to optimize their return on investment.

Recurring Costs and Pricing Scalability

SaaS subscriptions often include updates, support, and hosting, but pricing frequently evolves. Price tiers or additional fees for advanced modules can appear without warning.

Conversely, custom software can be hosted in your own cloud or with any open hosting provider you choose. Costs for future enhancements are controlled through a flexible maintenance contract aligned with your actual needs, without sudden price spikes.

Integration and Customization

Adapting a SaaS to your value chain requires connectors, APIs, and additional development work. These external services often come as fixed-price or hourly-rate projects.

For example, a mid-sized Swiss e-commerce company integrated a stock management module into its SaaS CRM. The initial integration cost reached 60,000 CHF, followed by 8,000 CHF per month for support and further developments—totaling 156,000 CHF over two years. It’s essential to account for these fees when considering a SaaS-based business tool.

Hidden Costs and Scalability Challenges

Beyond subscriptions and licensing fees, invisible costs emerge through vendor lock-in, forced updates, and technological dependency.

Vendor Lock-In and Supplier Dependency

With SaaS, your data, processes, and workflows reside on the provider’s platform. When you decide to migrate or integrate another tool, transition costs (export, formatting, testing) can exceed 25% of the project’s initial budget.

A large Swiss logistics company spent 250,000 CHF migrating to an open-source solution after five years on a SaaS platform that had become too rigid. These unbudgeted expenses extended the migration timeline by six months. Anticipating such scenarios early on helps avoid unwanted costs, delays, and operational standstills.

Upgrades and Compatibility Impact

Automatic SaaS updates can cause regressions or incompatibilities with custom-developed modules designed to tailor the solution to your business needs. You then depend on the provider’s support team to fix or work around these anomalies.

In contrast, custom software follows a release schedule driven by your internal governance. You decide when to introduce new features, testing compatibility with your other systems in advance. This independence often brings more peace of mind, freedom, and control.

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Mid- and Long-Term Financial Analysis

Over a three- to five-year horizon, comparing total cost of ownership reveals the strategic advantage of custom software.

Time Frame: ROI and Cash Flow

In SaaS, OPEX remains constant or rising, weighing on cash flow and limiting the ability to reallocate budget toward innovation. Short-term savings can become significant fixed charges.

Custom-built software amortized over three to five years generates a peak in initial CAPEX but then stabilizes expenses. You eliminate recurring license fees and free up cash for high-value projects in the mid to long term. This strategy makes all the difference when the time frame exceeds three years.

CAPEX vs OPEX Comparison: Predictability and Control

CAPEX is predictable and plannable: you budget the project, approve milestones, then amortize according to your accounting rules. Shifting to OPEX can complicate budget visibility, especially if the pricing model evolves.

For example, a mid-sized Swiss company that consulted us after a poor decision saw a transition to per-user SaaS cost them 420,000 CHF over five years, compared to 280,000 CHF in CAPEX for a custom development—placing the custom solution’s TCO 33% lower.

Added Value: Flexibility and Continuous Innovation

Investing in custom solutions builds an evolvable foundation. You implement MVPs, test, refine; each iteration increases your product’s value. This agility results in shorter time to market and better alignment with business needs.

In contrast, you rely entirely on the SaaS provider’s product roadmap: your improvement requests may wait several roadmap cycles, delaying your market responsiveness.

Example: Large Swiss Enterprise

A Swiss industrial group with 500 users across three subsidiaries opted for a custom solution to centralize its quality processes. The initial project cost 600,000 CHF in CAPEX, followed by 40,000 CHF annually for maintenance. By comparison, the SaaS alternative billed 120 CHF per user per month—totaling nearly 2,160,000 CHF over five years.

Beyond the financial gain (TCO reduced by 70%), the group integrated its own continuous analysis algorithms, boosting quality performance by 15% and anticipating failures through custom business indicators.

Key Principles to Optimize Your Custom Project

Agile governance, open source usage, and a modular architecture are essential to controlling TCO.

Modular Architecture and Microservices

Opt for functional segmentation: each microservice addresses a specific domain (authentication, reporting, business workflow). You deploy, scale, and update each component independently, reducing risks and costs associated with downtime.

This technical breakdown simplifies maintenance, enhances resilience, and allows you to integrate new technologies progressively without overhauling the entire system.

Open Source Usage and Hybrid Ecosystem

Favor proven open source frameworks (e.g., Symfony, Spring Boot, Node.js, Nest.js, Laravel) to secure your code and leverage an active community. You reduce licensing fees and avoid vendor lock-in.

Complement with modular cloud APIs and services for hosting, analytics, or alerting. This hybrid approach combines performance with autonomy while ensuring maximum flexibility.

Governance and Business-IT Alignment

Establish a steering committee comprising the CIO, business stakeholders, and architects. Periodically reassess the roadmap to adjust priorities, validate changes, and anticipate budgetary impacts.

This collaborative approach ensures a 360° vision, avoids redundant developments, and optimizes resource allocation.

Maintenance Processes and Scalability

Implement CI/CD pipelines to automate testing, deployments, and updates. Continuous reporting on test coverage and dependencies alerts you to potential vulnerabilities and regressions before production.

This proactive system guarantees quality, secures future releases, and reduces long-term operational workload.

Maximize the Value and Flexibility of Your Software Investments

Comparing TCO between custom software and SaaS licenses shows that while SaaS offers rapid deployment, custom solutions create an evolvable, controllable, and cost-effective asset in the mid to long term. By structuring investments through amortizable CAPEX, avoiding vendor lock-in, and adopting a modular open source architecture, you boost agility and optimize cash flow.

Regardless of your situation, our experts can help you define the solution that best addresses your challenges and implement a robust TCO management strategy.

Discuss Your Challenges with an Edana Expert

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Featured-Post-Software-EN Software Engineering (EN)

Refactoring Software Code: Benefits, Risks, and Winning Strategies

Refactoring Software Code: Benefits, Risks, and Winning Strategies

Auteur n°2 – Jonathan

Refactoring involves restructuring existing code without altering its functional behavior, in order to improve maintainability, robustness, and scalability. In contexts where IT teams inherit solutions developed hastily or without a long-term vision, the technical debt quickly becomes a barrier to innovation and a significant cost center. By investing in a solid refactoring approach, organizations can turn this liability into a sustainable competitive advantage. However, if poorly orchestrated, refactoring can lead to service interruptions, additional costs, delays, and regressions. This article breaks down the challenges of refactoring, its business benefits, the risks to anticipate, and winning strategies to optimize each phase.

Understanding Refactoring and Its Challenges

Refactoring cleans up and organizes code without changing its functionality, reducing technical debt and limiting regression risks. It creates a clearer, more modular foundation to support innovation but requires a thorough understanding of the existing codebase and its dependencies.

Definition and Objectives of Refactoring

Refactoring refers to all modifications made to the internal structure of software to improve code readability, modularity, and overall quality.
These changes must not alter the functional behavior: end users perceive no difference, while development teams gain agility in implementing new features and speed in fixing defects. This improves performance, facilitates maintenance, and results in more flexible, scalable software with fewer bugs and limitations.

When to Initiate a Refactoring Project

A refactoring project is justified when the codebase becomes difficult to maintain, delivery timelines worsen, and test coverage is no longer sufficient to ensure stability.
For example, a Swiss industrial company operating a critical business application found that every fix took on average three times longer than at project launch. After an audit, it undertook targeted refactoring of its data access layers, reducing ticket processing time by 40% and minimizing production incidents.

The Connection with Technical Debt

Technical debt represents the accumulation of quick fixes or compromises made to meet tight deadlines, at the expense of quality and documentation.
If left unaddressed, this debt increases maintenance costs and hampers agility. Refactoring acts as a partial or full repayment of this debt, restoring a healthy foundation for future developments.
Indeed, when technical debt grows too large and it becomes difficult to evolve the software—because every task requires too much effort or is unfeasible due to the current software’s rigid structure—it’s time to proceed with either refactoring or a complete software rebuild. The choice between rebuilding and refactoring depends on the business context and the size of the gap between the current software architecture and the desired one.

Business and Technical Benefits of Refactoring

Refactoring significantly improves code maintainability, reduces support costs, and accelerates development cycles. It strengthens robustness and promotes scalability, providing a stable foundation for innovation without compromising operational performance.

Reduced Maintenance Costs

Well-structured and well-documented code requires less effort for fixes and enhancements, resulting in a significant reduction in the support budget.
Internal or external teams spend less time understanding the logic, enabling resources to be refocused on high-value projects and accelerating time-to-market.

Improved Flexibility and Scalability

Breaking the code into coherent modules makes it easier to add new features or adapt to evolving business requirements without causing conflicts or regressions.
For instance, a Swiss financial services company refactored its internal calculation engine by isolating business rules within microservices. This new architecture enabled the rapid integration of new regulatory indicators and reduced compliance implementation time by 60%.

Enhanced Performance and Agility

By eliminating redundancies and optimizing algorithms, refactoring can improve application response times and scalability under heavy load.
Reducing bottlenecks and optimizing server resource consumption also contributes to a better user experience and a more cost-effective infrastructure.

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Risks and Pitfalls of Poorly Managed Refactoring

Poorly planned refactoring can lead to service interruptions, regressions, and budget overruns. It is essential to anticipate dependencies, define a precise scope, and secure each phase to avoid operational consequences.

Risks of Service Interruptions and Downtime

Deep code structure changes without proper procedures can cause service outages, impacting operational continuity and user satisfaction.
Without testing and progressive deployment processes, certain modifications may propagate to production before detection or generate unexpected behaviors during peak activity. It is therefore crucial to organize properly and involve QA experts, DevOps engineers, and software developers throughout the process. Planning is also critical to avoid any surprises.

Functional Regressions

Deleting or modifying code segments considered obsolete can impact hidden features, often not covered by automated tests.
These regressions are often detected late, triggering a domino effect across other modules and leading to costly rollbacks in both time and resources.

Scope Creep and Cost Overruns

Without clear objectives and rigorous scope management, a refactoring project can quickly expand, multiplying development hours and associated costs.
For example, a Swiss distribution company had planned targeted refactoring of a few components, but the lack of clear governance led to the integration of an additional set of features. The initial budget was exceeded by 70%, delaying delivery by six months.

Winning Strategies for Successful Refactoring

A structured, incremental approach based on automation ensures refactoring success and risk control. Combining a precise audit, robust testing, and phased deployment secures each step and maximizes ROI.

Audit and Preliminary Planning

Before any intervention, a comprehensive assessment of the code, its dependencies, and test coverage is essential to identify critical points.
This audit quantifies technical debt, sets priorities based on business impact, and defines a realistic schedule aligned with the IT roadmap and business needs.

Incremental and Controlled Approach

Breaking refactoring into functional, testable, and independently deliverable batches prevents tunnel effects and limits the risk of global incidents.
Each batch should be accompanied by clear acceptance criteria and review milestones, involving IT teams, business stakeholders, and quality experts to ensure buy-in and coherence.

Automation and Testing Culture

Integrating CI/CD tools and automated test suites (unit, integration, and end-to-end) secures every change and accelerates deployments.
Implementing coverage metrics and proactive alerts on code defects fosters continuous improvement and prevents the reintroduction of technical debt.

Transform Your Code into an Innovation Driver with Software Refactoring

When conducted rigorously, refactoring reduces technical debt, strengthens stability, and provides a healthy foundation for scalability and innovation. The benefits include reduced maintenance timeframes, increased agility, and improved application performance. Risks are minimized when the project is based on a thorough audit, an incremental approach, and extensive automation.

If your organization wants to turn its legacy code into a strategic asset, our experts are ready to support you from auditing to establishing a culture of lasting quality. Benefit from contextual partnerships based on scalable, secure, and modular open-source solutions without vendor lock-in to ensure the longevity of your digital ecosystem.

Discuss your challenges with an Edana expert

PUBLISHED BY

Jonathan Massa

As a specialist in digital consulting, strategy and execution, Jonathan advises organizations on strategic and operational issues related to value creation and digitalization programs focusing on innovation and organic growth. Furthermore, he advises our clients on software engineering and digital development issues to enable them to mobilize the right solutions for their goals.

Categories
Featured-Post-Software-EN Software Engineering (EN)

Regression Testing: Securing Your Software’s Evolution with Non-Regression Tests

Regression Testing: Securing Your Software’s Evolution with Non-Regression Tests

Auteur n°14 – Daniel

In an environment where software is constantly evolving to meet business requirements, ensuring stability and reliability has become a strategic imperative. Non-regression tests act as a real shield, detecting issues introduced with each update or new feature addition. However, if poorly designed, these tests can become a drain on resources and an obstacle to agility. How do you develop an effective regression testing strategy? Which tools and methods should you choose to cover your critical use cases without overburdening your processes? This article outlines key principles and best practices to safeguard your software’s evolution by combining effort optimization, intelligent automation, and a business-oriented focus.

Why Non-Regression Tests are a Shield Against Invisible Bugs

Non-regression tests identify anomalies introduced after code modifications or updates, avoiding the hidden-bug tunnel effect. They serve as an essential safety net to ensure that existing functionalities continue to operate, even in long lifecycle projects.

Increasing Complexity of Business Applications

Over development cycles, each new feature introduces cryptic dependencies. Interconnections between modules accumulate, making every change potentially risky.

Without systematic non-regression tests, a local fix can trigger a domino effect. The consequences aren’t always immediate and can surface in critical business processes.

A complex project, especially in industries like manufacturing or finance, can involve hundreds of interdependent components. Manual testing quickly becomes insufficient to adequately cover all scenarios.

Business Impacts of Invisible Regressions

An undetected regression in a billing or inventory management module can lead to calculation errors or service disruptions. The cost of an incident in a production environment often exceeds the initial testing budget.

Loss of user trust, the need for emergency fixes, and service restoration delays directly affect return on investment. Every minute of downtime carries a measurable financial impact.

Fixing a bug introduced by an uncovered update may involve multiple teams—development, operations, support, and business units—multiplying both costs and timelines.

Use Case: Business Application in an Industrial Environment

A Swiss SME specializing in industrial automation noticed that after integrating a new production scheduling algorithm into its business application, certain manufacturing orders were being rejected.

Through an automated non-regression test suite targeting key processes (scheduling, inventory tracking, report generation), the team identified a flaw in resource constraint management.

Early detection allowed them to fix the code before production deployment, avoiding a line stoppage at a critical site and preventing revenue losses exceeding CHF 200,000.

Different Approaches to Non-Regression Testing for Successful QA

There is no single method for regression testing, but rather a range of approaches to combine based on your needs. From targeted manual testing to end-to-end automation, each technique brings its strengths and limitations.

Targeted Manual Testing for Critical Scenarios

Manual tests remain relevant for validating highly specific and complex functionalities where automation would be costly to implement. They rely on business expertise to verify rare or sensitive use cases.

This type of QA (Quality Assurance) testing is particularly useful during the early project phases, when the codebase evolves rapidly and setting up an automated testing framework would be premature.

The drawback lies in the time required and the risk of human error. It is therefore essential to document each scenario and assess its criticality to decide whether it should be automated later.

End-to-End Automated Tests and Snapshot Testing

End-to-end tests simulate the complete user journey, from the front-end (Selenium, Cypress, Playwright, etc.) to the back-end (Postman, Swagger, JUnit, etc.). They verify end-to-end consistency after each build or deployment.

Snapshot tests, which compare screenshots, are effective at detecting unwanted visual changes. They compare the rendered output before and after code changes, thus contributing to the overall quality of the software.

Integration into a CI/CD pipeline ensures automatic execution on every commit and significantly reduces rollbacks. However, maintaining these tests requires rigorous discipline to manage false positives and test case obsolescence.

Visual Testing and Other Advanced Quality Assurance Techniques

Automated visual tests extend the concept of snapshot testing by detecting pixel variations and interface anomalies without requiring an overly strict baseline.

Log analysis–based tests and API contract validation ensure that inter-service integrations remain stable and compliant with specifications.

These techniques, often integrated into open source tools, help strengthen coverage without multiplying manual scripts and support a continuous quality improvement approach.

Use Case: Swiss E-Commerce Platform

An online retailer with multiple channels (website, mobile app, in-store kiosks) implemented end-to-end automated tests to simulate multi-step orders.

Any change to the catalogue, pricing grid, or checkout flow triggers a suite of tests validating the entire process and promotional consistency.

This reduced support tickets related to customer journey errors by 70% after deployment while accelerating time-to-market for marketing campaigns.

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How to Prioritize and Intelligently Automate Non-Regression Tests

The key to effective regression testing lies in rigorously selecting the scenarios to cover. Automating for the sake of testing is not the goal: you must target high-risk, high-value business areas.

Identifying Critical Scenarios

Start by mapping business processes and prioritizing features based on their impact on revenue, compliance, and user experience.

Each use case should be evaluated on two axes: the probability of failure and the severity of consequences. This risk matrix guides test prioritization.

High-criticality scenarios typically include payments, sensitive data management, and communication flows between essential services.

Defining a Test Prioritization Strategy

Once scenarios are identified, define a progressive coverage plan: start with high-impact tests, then gradually expand the scope.

Set minimum coverage thresholds for each test type (unit, integration, end-to-end), ensuring regular monitoring of progress and potential gaps.

This approach avoids a “test factory” effect and focuses efforts on what truly matters for service continuity and user satisfaction.

Progressive Implementation of Regression Testing Automation

Automate unit and integration tests first, as they are easier to maintain and faster to execute, before assembling more complex and resource-intensive scenarios.

Use modular, open source frameworks to avoid vendor lock-in and ensure test suite flexibility. Adopt a parallel testing architecture to reduce overall execution time.

Ensure clear governance: regular script reviews, test data updates, and team training to maintain the relevance of the test repository.

Use Case: Financial Portfolio Management System

A Swiss wealth management institution automated its integration tests to cover performance calculations and inter-account transaction flows.

Using a market data simulation library and parallel execution across multiple environments, the IT team reduced validation time from 48 hours to under 2 hours.

Early detection of a bug in portfolio consolidation prevented a calculation error that could have produced significant discrepancies in client reports.

The Right Time to Invest in a Regression Testing Strategy

Neither too early—when the codebase is still evolving too rapidly to justify a major investment—nor too late—at the risk of facing a backlog of fixes. Identifying your project’s maturity threshold allows you to determine the right timing.

Risks of Investing Too Early

Implementing an automation infrastructure before the architecture is stable can lead to excessive costs and high script obsolescence rates.

In early phases, favor structured manual tests and lay the foundation for unit tests.

Premature over-automation diverts resources from feature development and can demotivate teams if tools are not aligned with project realities.

Challenges of Acting Too Late

Delaying non-regression tests until the end of the development phase increases the risk of production regressions and emergency fix costs.

Technical debt resulting from the lack of tests grows with each iteration, impacting quality and your team’s ability to deliver on time.

Going back to manually cover forgotten scenarios can stall your teams for several full sprints.

Assessing Your Organization’s Maturity

Analyze deployment frequency, post-deployment defect rates, and incident resolution times to measure your automation needs.

If emergency fixes account for more than 20% of your development capacity, it’s time to strengthen your non-regression test coverage.

Adopt an iterative approach: validate the ROI of each automation milestone before moving to the next, adjusting your IT roadmap.

Optimize Your Software Evolution While Meeting Deadlines

Non-regression tests are essential for preventing hidden risks and ensuring the integrity of your business applications, but they require a targeted and progressive approach. By combining manual tests for critical cases, modular automation, and prioritization based on criticality, you can secure your deployments without overburdening your teams or blowing your budget.

Whether your project is at the start, in the industrialization phase, or in an advanced maintenance cycle, Edana’s software quality experts can support you in defining and implementing a tailor-made, modular, and scalable strategy, from planning to maintenance.

Discuss Your Challenges with an Edana Expert

PUBLISHED BY

Daniel Favre

Avatar de Daniel Favre

Daniel Favre is a Senior Software Engineer. He designs and builds bespoke business solutions (SaaS, mobile apps, websites) and full digital ecosystems. With deep expertise in architecture and performance, he turns your requirements into robust, scalable platforms that drive your digital transformation.

Categories
Featured-Post-Software-EN Software Engineering (EN)

Insourcing or Outsourcing a Software Project: A Structuring Decision with Lasting Impacts

Insourcing or Outsourcing a Software Project: A Structuring Decision with Lasting Impacts

Auteur n°3 – Benjamin

When undertaking a project to develop or integrate business software or a digital application, the question of execution goes beyond merely recruiting resources: it requires deciding between insourcing, outsourcing, or a hybrid model. This choice structures your costs, defines your level of control over your roadmap, impacts delivery speed, and underpins internal skill development. Adopting the right approach to run a digital project is not a trivial matter: it’s a strategic lever with lasting effects on your company’s performance and agility.

Why Choose Software Development Insourcing?

Insourcing a software project provides full control over the functional and technical scope. This option enhances business coherence and long-term skill development.

Mastery and Business Proximity

By insourcing your development, you ensure that your project team fully understands the business challenges. Technical decisions stem directly from the business vision, with no loss of information.

Communication flows more smoothly between developers and end users, reducing the risk of misunderstandings and speeding up decisions when the scope changes.

Example: A Geneva-based industrial company established an internal unit dedicated to its upcoming ERP to oversee parts traceability. This team, versed in production processes, designed workflows perfectly aligned with both quality and logistics requirements. While it took slightly longer than if they had engaged an external provider, the company ultimately gained a unit it could rely on for future projects—a worthwhile investment given its steady stream of digital initiatives and the expansion of its existing IT and development department.

Skill Development and Sustainability

A key benefit of insourcing is the direct transfer of know-how within your organization. Skills acquired during the project remain available for future updates.

At each phase, your teams deepen their technical expertise, bolstering autonomy and reducing long-term dependence on external vendors.

Thanks to this knowledge transfer, the company builds a lasting skills foundation tailored to its context, enabling continuous deployment of new features.

This approach makes sense if your company can invest in training staff and is focused on the very long term—especially when multiple digital projects are in the pipeline and technological innovation is a constant in your strategic roadmap.

HR Complexity and Total Cost

The main challenge of insourcing lies in talent management: recruiting, training, and retention require significant time and budget investment.

Salary costs, social charges, and associated IT infrastructure can quickly exceed those of an outsourced service—particularly for rare roles such as cloud architects or cybersecurity experts.

Moreover, managing an internal team demands rigorous project management processes and a structured skills-development plan to prevent stagnation and demotivation. This is why many in-house technology team initiatives fail.

The Advantages of Software Development Outsourcing

Outsourcing a software project allows you to quickly mobilize specialized expertise and meet tight deadlines. This approach provides economic and operational flexibility, enabling you to adjust resources on the fly.

Rapid Access to Specialized Skills

By engaging an external provider, you immediately gain teams experienced in specific technologies (AI, mobile, API integration, cybersecurity, etc.) without an internal ramp-up period.

This reduces time-to-market, especially when launching a new service or responding to competitive pressures.

One of our financial-sector clients, after several months weighing insourcing versus outsourcing, chose to outsource the overhaul of its mobile client platform to our team. Leveraging several React Native experts, we delivered the MVP in under three months.

Budget Flexibility and Scaling

Outsourcing simplifies project load management: you purchase a service rather than a permanent position, scaling headcount according to design, development, or maintenance phases.

In the event of a workload peak or scope change, you can easily ramp up from two to ten developers without a recruitment cycle.

This adaptability is invaluable for controlling costs and avoiding underutilization when needs fluctuate.

Dependency and Relationship Management

Entrusting a project to a provider carries a risk of technical and contractual dependency, especially if governance is not clearly defined.

Rigorous communication—including kick-off workshops, milestone reviews, and quality metrics—is essential to ensure transparency and keep the schedule on track.

Without structured oversight, you may face challenges during support or evolution phases, particularly if the provider shifts resources or priorities.

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The Hybrid Model: Balance and Flexibility

The hybrid model combines an internal team for governance with an external team for execution. It leverages the strengths of both approaches to balance control, expertise, and responsiveness.

Combining the Best of Both Worlds

In a hybrid setup, the company retains authority over overall architecture and strategic decisions, while the provider handles specific development tasks and industrialization phases.

This division preserves a clear business vision while benefiting from specialized expertise and readily available resources.

A notable case involved a major retail client: the internal team defined the roadmap and UX, while our teams handled back-end and front-end development and ensured scalability. In some instances, the client’s developers collaborated directly with our team—each scenario is co-built between the external provider and the company.

Mixed Governance and Management

The success of a hybrid model hinges on shared management: joint steering committees and agile rituals maintain coherence among stakeholders.

Roles are clearly defined: the internal team acts as product owner and validates deliverables, while the external team executes the work and provides technical recommendations.

This way of working fosters co-construction and allows rapid reaction to priority changes while preserving a long-term vision.

Typical Use Case

The hybrid model is well suited to high-criticality projects with roadmaps requiring strong responsiveness (staggered launches, frequent updates).

It’s also ideal when a company wants to build internal skills without covering the full cost of an in-house team from day one.

For example, a Basel-based manufacturer opted for a hybrid approach to develop an AI module for quality control while gradually integrating data scientists internally.

Choosing Based on Your Context and Priorities

The decision between insourcing, outsourcing, or a hybrid approach depends on project criticality and your strategic objectives. You need to assess IT maturity, available resources, and the project lifecycle phase to determine the optimal model.

Project Criticality and Time-to-Market

For a highly strategic project where any incident could affect business continuity, insourcing or a hybrid model may offer critical levels of control.

Conversely, if rapid market launch is the primary concern, outsourcing guarantees immediate scaling and proven expertise.

The challenge lies in calibrating governance to balance speed and robustness without sacrificing one for the other.

IT Maturity and Internal Capacity

A company with an experienced team in the targeted technologies may consider insourcing to optimize long-term costs.

If maturity is limited or skills are hard to recruit, outsourcing avoids the risk of underperformance.

The hybrid model then becomes a way to upskill the internal team in partnership with a provider.

Lifecycle Phase and Strategic Ambitions

During the proof-of-concept or prototype stage, outsourcing accelerates validation of business hypotheses.

In the industrialization phase, a hybrid model ensures product reliability scales up before an internal team gradually takes over maintenance.

For a long-term project with significant business evolution, insourcing the core ensures platform coherence and sustainable skills.

Align Your Strategy: Insourcing, Outsourcing, or Hybrid

Each organization must take time to define its priorities: desired level of control, deployment speed, available resources, and long-term ambitions.

By matching these criteria against your business context and IT maturity, you’ll identify the organizational model that maximizes ROI and ensures sustainable performance for your software or IT project.

Our experts are ready to discuss your challenges, share real-world experience, and co-create an approach tailored to your digital strategy.

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Featured-Post-Software-EN Software Engineering (EN)

UI Components: The Key to Designing and Developing Scalable, Consistent Digital Products

UI Components: The Key to Designing and Developing Scalable, Consistent Digital Products

Auteur n°4 – Mariami

Componentization goes beyond mere code reuse. It structures collaboration between design and development, ensures interface consistency, and reduces time to production. For platforms experiencing rapid functional evolution, adopting a component-based approach creates a clear framework that eases onboarding, maintenance, and scalability. Yet without rigorous orchestration, a component library can quickly become a chaotic stack, leading to complexity and UX inconsistencies. This article explains how to break down silos between design and code, maximize operational benefits, establish solid governance, and deploy a concrete case study tailored to your business needs.

Design Components vs. Code Components: Two Sides of the Same Logic

Code components encapsulate logic, styles, and tests, while design components capture user needs and interactive experience. Their convergence through a design system unifies naming, behavior, and documentation.

Modularity and Configuration in Code

In a front-end codebase, each code component is isolated with its own CSS scope or style module. This encapsulation guarantees that adding or modifying a style rule does not affect the entire application. Props enable customization of the same component without duplicating code.

Unit tests accompany each component to verify its rendering, interactions, and robustness. This granularity streamlines CI/CD, as each update is validated in isolation before merging into the global application.

Modern frameworks like Vue 3 or React optimize these practices. For example, slots in Vue 3 promote composition of nested components without bloating their internal code.

Interactive Components in Design

On the design side, each design component represents an autonomous interface element—button, input field, or information card. It’s defined with its states (default, hover, active, disabled) and responsive variants.

This granularity enables precise user-centric responses, as every component is documented with its use cases, accessibility constraints, and guidelines. Designers can then prototype and test complete user flows using interactive tools.

In a recent example, a Swiss logistics platform standardized its filters and tables within a shared Figma file. Each documented filter included its mobile variant, error behavior, and inactive state. The development framework then used these definitions to generate React components that were 100 % compliant.

The Design System as a Bridge

The design system plays a central role by establishing a common language. It sets a consistent level of granularity between mockups and code, with a catalogue of tokens (colors, typography, spacing) and a unique nomenclature.

Interactive documentation—often via Storybook—exposes each code component with its variants, code snippets, and design notes. On the design side, Figma or Zeroheight centralizes prototypes and guidelines.

This workflow drastically reduces back-and-forth between designers and developers and ensures traceability of decisions. It also simplifies onboarding, as each interface element is clearly referenced and tested.

The Operational Benefits of a Componentized Approach

A component-based architecture reduces technical debt and boosts team productivity while ensuring a coherent UX/UI and controlled scalability. These gains are evident in long-term projects and when onboarding new team members.

Reduced Technical Debt and Maintainability

When each component is isolated, a style or logic change often requires updating a single file. This limits side effects and accelerates urgent fixes. Unit test coverage per component also ensures greater stability over successive evolutions.

By decoupling software building blocks, you avoid monolithic front ends whose maintenance becomes a nightmare beyond a certain size. A Swiss industrial company reported a 60 % reduction in production incidents after migrating to a modular component library, as fixes involved only single-line diffs.

The code also becomes more readable for operational teams, who can more easily adopt the codebase and propose improvements without fear of breaking other parts.

Productivity Gains and Accelerated Onboarding

Documented components provide a central reference point to build upon instead of starting from scratch. Each new feature relies on proven building blocks, systematically reducing development time for similar features.

For newcomers, the component structure serves as a guide. They explore the catalogue, quickly understand usage patterns, and contribute to production without a lengthy learning curve.

On a large-scale digital project, this model enabled three new developers to contribute fully in their first week—compared to one month previously. Code and documentation consistency played a decisive role.

Consistent UX/UI and Controlled Scalability

Using a shared library ensures a continuous experience for the end user: the same visual and behavioral components are employed across all sections of the platform. This strengthens interface credibility and reduces support and training needs.

Regarding scalability, component breakdown simplifies adding new features. Existing patterns are extended rather than starting from a blank slate, thus shortening time-to-market.

The ability to incrementally add modules without rebuilding complex foundations ensures constant agility, essential for ever-evolving business environments.

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What Many Underestimate: Component Governance

Without clear rules and governance processes, a component library can proliferate chaotically and become unmanageable. Rigorous versioning and interactive documentation are indispensable to maintain order.

Naming Conventions and Cataloguing

A consistent naming system is the first line of defense against duplication. Each component should follow a hierarchical naming architecture, for example Atom/TextField or Molecule/ProductCard. This facilitates search and comprehension.

Cataloguing in a tool like Storybook or Zeroheight indexes each variant and associates it with a precise description. Teams immediately know where to look and how to reuse the right building block.

Without cataloguing, developers risk creating duplicates, fragmenting maintenance efforts, and losing track of previously implemented updates.

Versioning and Backward Compatibility

Implementing semantic versioning clarifies the impact of updates. Minor versions (1.2.x) introduce additions without breaking changes, while major versions (2.0.0) signal breaking changes.

Documentation must specify changes and offer migration guides for each major version. This prevents a component update from triggering a cascade of fixes across the platform.

Poor version management often leads to update freezes, as fear of regressions hampers adoption of improvements.

Interactive Documentation and Collaborative Tools

Using Storybook for code and Figma for design creates a shared source of truth. Every component change is visible in real time, accompanied by usage examples.

Automated changelogs generated via Git hooks inform teams of updates without manual effort. Pull request reviews systematically include documentation updates.

This fosters trust among designers, developers, and project managers while ensuring complete decision traceability.

Role of Tech Leads and Project Managers

Effective governance relies on library guardians. Tech leads validate new contributions, enforce guidelines, and plan priorities.

Project managers incorporate design system maintenance into the roadmap, allocate resources for refactoring, and secure a dedicated budget for continuous evolution.

Without a technical sponsor and business leadership, a design system can stagnate or fragment, undermining its anticipated benefits.

Concrete Example: From Mockup to Production Without Friction

Imagine a product filtering and table display use case, built without friction between design and development. Each step relies on a modular component library and a collaborative workflow.

Use Case Breakdown

The filter comprises three main components: the search field, the product row, and the overall table. The search field handles input and auto-suggestion from the first keystroke. The product row displays the image, title, status, and available actions.

Each component is specified in design with its states (error, loading, empty), then implemented in code with its props and callbacks. The global table orchestrates the API call and distributes data to the rows.

This breakdown isolates query logic, presentation, and interaction, facilitating unit tests and reuse in other contexts.

Technical Implementation

In Vue 3, the search field uses a watcher on the input prop and triggers a request via a debounced method to limit network calls. The product row is a stateless component relying solely on its props.

The table delegates state management (loading, error) to a wrapper, simplifying internal markup and avoiding code duplication. Styles are handled via CSS modules to limit impact on the rest of the page.

Each component is isolated in Storybook, where all scenarios are tested to ensure behavior remains consistent across releases.

Design-Dev Collaboration and Tools

The Figma prototype uses the same tokens as the code and is linked to Storybook via a plugin. Designers update colors or spacing directly in Figma, and these updates are automatically reflected in the front end.

Developers and designers meet in weekly reviews to validate component changes and plan future evolution. Feedback is recorded in a shared backlog, preventing misunderstandings.

This collaboration builds trust and accelerates delivery, as no separate QA phase is needed between prototype and code.

Measurable Benefits

In just two sprints, teams delivered the filter and table feature with near-zero production bugs. Development time was cut by 35 % compared to an ad hoc approach.

Subsequent enhancements—adding a category filter and customizing columns—required only two new variants of existing components, with no impact on existing code.

The ROI is measured in rapid updates and internal user satisfaction, benefiting from a stable, consistent interface.

Think Modular, Win Long-Term

Adopting a well-governed component architecture turns each building block into a reusable, maintainable asset. This approach structures design-dev collaboration, reduces technical debt, accelerates time to market, and ensures a consistent UX.

Regardless of your industry context, expertise in creating and governing design systems and component libraries allows you to industrialize your interfaces without sacrificing agility. Our modular, open-source, and platform-agnostic experts are at your disposal to help deploy this strategy and support your digital transformation.

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PUBLISHED BY

Mariami Minadze

Mariami is an expert in digital strategy and project management. She audits the digital presences of companies and organizations of all sizes and in all sectors, and orchestrates strategies and plans that generate value for our customers. Highlighting and piloting solutions tailored to your objectives for measurable results and maximum ROI is her specialty.

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Featured-Post-Software-EN Software Engineering (EN)

Understanding the Proof of Concept (PoC): Benefits, Limitations, and Method for Validating a Digital Idea

Understanding the Proof of Concept (PoC): Benefits, Limitations, and Method for Validating a Digital Idea

Auteur n°2 – Jonathan

In a context where technical uncertainty can slow down or even jeopardize the success of a digital project, the Proof of Concept (PoC) proves to be a crucial step. In a matter of weeks, it allows you to test the feasibility of an idea or feature before committing significant resources. Whether you’re validating the integration of a new API, testing a business algorithm, or confirming the compatibility of a solution (AI, e-commerce, CRM, etc.) with an existing system, the PoC delivers rapid feedback on technical risks. In this article, we clarify what a PoC is, its benefits and limitations, and outline the method for conducting it effectively.

Precise Definition of a Proof of Concept

A PoC is a targeted feasibility demonstration focused on a specific aspect of a digital project. It doesn’t aim to prototype the entire product but to validate a technical or functional hypothesis.

A Proof of Concept zeroes in on a narrow scope: testing the integration, performance, or compatibility of a specific component. Unlike a prototype or a Minimum Viable Product (MVP), it isn’t concerned with the overall user experience or end-user adoption. Its sole aim is to answer the question, “Can this be done in this environment?”

Typically executed in a few short iterations, each cycle tests a clearly defined scenario. Deliverables may take the form of scripts, video demonstrations, or a small executable software module. They aren’t intended for production use but to document feasibility and highlight main technical challenges.

At the end of the PoC, the team delivers a technical report detailing the results, any deviations, and recommendations. This summary enables decision-makers to greenlight the project’s next phase or adjust technology choices before full development.

What Is the Use of a Proof of Concept (PoC)?

The primary purpose of a PoC is to shed light on the unknowns of a project. It swiftly identifies technical roadblocks or incompatibilities between components. Thanks to its limited scope, the required effort remains modest, facilitating decision-making.

Unlike a prototype, which seeks to materialize part of the user experience, the PoC focuses on validating a hypothesis. For example, it might verify whether a machine-learning algorithm can run in real time on internal data volumes or whether a third-party API meets specific latency constraints.

A PoC is often the first milestone in an agile project. It offers a clear inventory of risks, allows for requirement adjustments, and provides more accurate cost and time estimates. It can also help persuade internal or external stakeholders by presenting tangible results rather than theoretical promises.

Differences with Prototype and MVP

A prototype centers on the interface and user experience, aiming to gather feedback on navigation, ergonomics, or design. It may include interactive mockups without underlying functional code.

The Minimum Viable Product, on the other hand, aims to deliver a version of the product with just enough features to attract early users. The MVP includes UX elements, business flows, and sufficient stability for production deployment.

The PoC, however, isolates a critical point of the project. It doesn’t address the entire scope or ensure code robustness but zeroes in on potential blockers for further development. Once the PoC is validated, the team can move on to a prototype to test UX or proceed to an MVP for market launch.

Concrete Example: Integrating AI into a Legacy System

A Swiss pharmaceutical company wanted to explore integrating an AI-based recommendation engine into its existing ERP. The challenge was to verify if the computational performance could support real-time processing of clinical data volumes.

The PoC focused on database connectivity, extracting a data sample, and running a scoring algorithm. Within three weeks, the team demonstrated technical feasibility and identified necessary network architecture adjustments to optimize latency.

Thanks to this PoC, the IT leadership obtained a precise infrastructure cost estimate and validated the algorithm choice before launching full-scale development.

When and Why to Use a PoC?

A PoC is most relevant when a project includes high-uncertainty areas: new technologies, complex integrations, or strict regulatory requirements. It helps manage risks before any major financial commitment.

Technological innovations—whether IoT, artificial intelligence, or microservices—often introduce fragility points. Without a PoC, choosing the wrong technology can lead to heavy cost overruns or project failure.

Similarly, integrating with a heterogeneous, customized existing information system requires validating API compatibility, network resilience, and data-exchange security. The PoC isolates these aspects for testing in a controlled environment.

Finally, in industries with strict regulations, a PoC can demonstrate data-processing compliance or encryption mechanisms before production deploy­ment, providing a technical dossier for auditors.

New Technologies and Uncertainty Zones

When introducing an emerging technology—such as a non-blocking JavaScript runtime framework or a decentralized storage service—it’s often hard to anticipate real-world performance. A PoC allows you to test under actual conditions and fine-tune parameters.

Initial architecture choices determine maintainability and scalability. Testing a serverless or edge-computing infrastructure prototype helps avoid migrating later to an inefficient, costly model.

With a PoC, companies can also compare multiple technological alternatives within the same limited scope, objectively measuring stability, security, and resource consumption.

Integration into an Existing Ecosystem

Large enterprises’ information systems often consist of numerous legacy applications and third-party solutions. A PoC then targets the connection between two blocks—for example, an ERP and a document management service or an e-commerce/e-service platform.

By identifying version mismatches, network latency constraints, or message-bus capacity limits, the PoC helps anticipate necessary adjustments—both functional and infrastructural.

Once blockers are identified, the team can propose a minimal refactoring or work-around plan, minimizing effort and costs before full development.

Concrete Example: Integration Prototype in a Financial Project

A Romandy-based financial institution planned to integrate a real-time credit scoring engine into its client request handling tool. The PoC focused on secure database connections, setting up a regulatory-compliant sandbox, and measuring latency under load.

In under four weeks, the PoC confirmed encryption-protocol compatibility, identified necessary timeout-parameter adjustments, and proposed a caching solution to meet business SLAs.

This rapid feedback enabled the IT department to secure the budget commitment and draft the development requirements while satisfying banking-sector compliance.

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How to Structure and Execute an Effective PoC

A successful PoC follows a rigorous approach: clear hypothesis definition, reduced scope, rapid build, and objective evaluation. Each step minimizes risks before the main investment.

Before starting, formalize the hypothesis to be tested: which component, technology, or business scenario needs validation? This step guides resource allocation and scheduling.

The technical scope should be limited to only the elements required to answer the question. Any ancillary development or scenario is excluded to ensure speed and focus.

The build phase relies on agile methods: short iterations, regular checkpoints, and real-time adjustments. Deliverables must suffice to document conclusions without chasing perfection.

Define the Hypothesis and Scope Clearly

Every PoC begins with a precise question such as: “Can algorithm X process these volumes in under 200 ms?”, “Is it possible to interface SAP S/4HANA with this open-source e-commerce platform while speeding up data sync and without using SAP Process Orchestrator?”, or “Does the third-party authentication service comply with our internal security policies?”

Translate this question into one or more measurable criteria: response time, number of product records synchronized within a time frame, error rate, CPU usage, or bandwidth consumption. These criteria will determine whether the hypothesis is validated.

The scope includes only the necessary resources: representative test data, an isolated development environment, and critical software components. Any non-essential element is excluded to avoid distraction.

Build Quickly and with Focus

The execution phase should involve a small, multidisciplinary team: an architect, a developer, and a business or security specialist as needed. The goal is to avoid organizational layers that slow progress.

Choose lightweight, adaptable tools: Docker containers, temporary cloud environments, automation scripts. The aim is to deliver a functional artifact rapidly, without aiming for final robustness or scalability.

Intermediate review points allow course corrections before wasting time. At the end of each iteration, compare results against the defined criteria to adjust the plan.

Evaluation Criteria and Decision Support

Upon PoC completion, measure each criterion and record the results in a detailed report. Quantitative outcomes facilitate comparison with initial objectives.

The report also includes lessons learned: areas of concern, residual risks, and adaptation efforts anticipated for the development phase.

Based on these findings, the technical leadership can decide to move to the next stage (prototype or development), abandon the project, or pivot, all without committing massive resources.

Concrete Example: Integration Test in Manufacturing

A Swiss industrial manufacturer wanted to verify the compatibility of an IoT communication protocol in its existing monitoring system. The PoC focused on sensor emulation, message reception, and data storage in a database.

In fifteen days, the team set up a Docker environment, an MQTT broker, and a minimal ingestion service. Performance and reliability metrics were collected on a simulated data stream.

The results confirmed feasibility and revealed the need to optimize peak-load handling. The report served as a foundation to size the production architecture and refine budget estimates.

Turning Your Digital Idea into a Strategic Advantage

The PoC offers a rapid, pragmatic response to the uncertainty zones of digital projects. By defining a clear hypothesis, limiting scope, and measuring objective criteria, it ensures informed decision-making before any major commitment. This approach reduces technical risks, optimizes cost estimates, and aligns stakeholders on the best path forward.

Whether the challenge is integrating an emerging technology, validating a critical business scenario, or ensuring regulatory compliance, Edana’s experts are ready to support you—whether at the exploratory stage or beyond—and turn your ideas into secure, validated projects.

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PUBLISHED BY

Jonathan Massa

As a specialist in digital consulting, strategy and execution, Jonathan advises organizations on strategic and operational issues related to value creation and digitalization programs focusing on innovation and organic growth. Furthermore, he advises our clients on software engineering and digital development issues to enable them to mobilize the right solutions for their goals.

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Featured-Post-Software-EN Software Engineering (EN)

Re-engineering of Existing Software: When and How to Modernize Intelligently

Re-engineering of Existing Software: When and How to Modernize Intelligently

Auteur n°16 – Martin

In many Swiss organizations, aging business applications eventually weigh down agility, performance, and security. Amid rising maintenance costs, the inability to introduce new features, and a drain of expertise, the need for a measured re-engineering becomes critical. Rather than opting for a lengthy, fully budgeted overhaul or a mere marginal refactoring, re-engineering offers a strategic compromise: preserving functional capital while modernizing the technical foundations and architecture. This article first outlines the warning signs you shouldn’t ignore, compares re-engineering and full rewrites, details the tangible benefits to expect, and proposes a roadmap of key steps to successfully execute this transition without compromising operational continuity.

Warning Signs Indicating the Need for Re-engineering

These indicators reveal that it’s time to act before the application becomes a bottleneck. Early diagnosis avoids hidden costs and critical outages.

Obsolete Technologies with No Support

In cases where a component vendor no longer provides updates or security patches, the software quickly becomes fragile. Known vulnerabilities remain unaddressed, exposing data and impacting regulatory compliance. Without official support, every intervention turns into a reverse-engineering project to find a workaround or patch.

This lack of maintenance triggers a snowball effect: outdated frameworks cause incompatibilities, frozen dependencies block the deployment of new modules, and teams spend more time stabilizing than innovating. This state of software obsolescence undermines the system’s resilience against attacks and evolving business requirements.

Over time, the pressure on the IT department intensifies, as it becomes difficult to support multiple technology generations without a clear, structured modernization plan.

Inability to Integrate New Modules and APIs into the Existing Software

A monolithic software or tightly coupled architecture prevents adding third-party features without a partial rewrite, limiting adaptability to business needs. Each extension attempt can trigger unforeseen side effects, requiring manual fixes and laborious testing.

This technical rigidity lengthens development cycles and increases time to production. Innovation initiatives are hindered, project teams must manage outdated, sometimes undocumented dependencies, and rebuild ill-suited bridges to make modern modules communicate with the legacy system.

Integration challenges limit collaboration with external partners or SaaS solutions, which can isolate the organization and slow down digital transformation.

Degraded Performance, Recurring Bugs, and Rising Costs

System slowness appears through longer response times, unexpected errors, and downtime spikes. These degradations affect user experience, team productivity, and can lead to critical service interruptions.

At the same time, the lack of complete documentation or automated testing turns every fix into a high-risk endeavor. Maintenance costs rise exponentially, and the skills needed to work on the obsolete stack are scarce in the Swiss market, further driving up recruitment expenses.

Example: A Swiss industrial manufacturing company was using an Access system with outdated macros. Monthly maintenance took up to five man-days, updates caused data inconsistencies, and developers skilled in this stack were nearly impossible to find, resulting in a 30% annual increase in support costs.

Re-engineering vs. Complete Software Rewrite

Re-engineering modernizes the technical building blocks while preserving proven business logic. Unlike a full rewrite, it reduces timelines and the risk of losing functionality.

Preserving Business Logic Without Starting from Scratch

Re-engineering focuses on rewriting or progressively updating the technical layers while leaving the user-validated functional architecture intact. This approach avoids recreating complex business rules that have been implemented and tested over the years.

Retaining the existing data model and workflows ensures continuity for operational teams. Users experience no major disruption in their daily routines, which eases adoption of new versions and minimizes productivity impacts.

Moreover, this strategy allows for the gradual documentation and overhaul of critical components, without bloated budgets from superfluous development.

Reducing Costs and Timelines

A targeted renovation often yields significant time savings compared to a full rewrite. By preserving the functional foundations, teams can plan transition sprints and quickly validate each modernized component.

This modular approach makes it easier to allocate resources in stages, allowing the budget to be spread over multiple fiscal years or project phases. It also ensures a gradual upskilling of internal teams on the adopted new technologies.

Example: A Swiss bank opted to re-engineer its Delphi-based credit management application. The team extracted and restructured the calculation modules while retaining the proven business logic. The technical migration took six months instead of two years, and users did not experience any disruption in case processing.

Operational Continuity and Risk Reduction

By dividing the project into successive phases, re-engineering makes cutovers reliable. Each transition is subject to dedicated tests, ensuring the stability of the overall system.

This incremental approach minimizes downtime and avoids the extended unsupported periods common in a full rewrite. Incidents are reduced since the functional base remains stable and any rollbacks are easier to manage.

Fallback plans, based on the coexistence of old and new versions, are easier to implement and do not disrupt business users’ production environments.

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Expected Benefits of Re-engineering

Well-executed re-engineering optimizes performance and security while reducing accumulated technical debt. It paves the way for adopting modern tools and a better user experience.

Enhanced Scalability and Security

A modernized architecture often relies on principles of modularity and independent services, making it easier to add capacity as needed. This scalability allows you to handle load spikes without overprovisioning the entire system.

Furthermore, updating to secure libraries and frameworks addresses historical vulnerabilities. Deploying automated tests and integrated security controls protects sensitive information and meets regulatory requirements.

A context-driven approach for each component ensures clear privilege governance and strengthens the organization’s cyber resilience.

Reducing Technical Debt and Improving Maintainability

By replacing ad-hoc overlays and removing superfluous modules, the software ecosystem becomes more transparent. New versions are lighter, well-documented, and natively support standard updates.

This reduction in complexity cuts support costs and speeds up incident response times. Unit and integration tests help validate every change, ensuring a healthier foundation for future development, free from technical debt.

Example: A Swiss logistics provider modernized its fleet tracking application. By migrating to a microservices architecture, it halved update times and eased the recruitment of JavaScript and .NET developers proficient in current standards.

Openness to Modern Tools (CI/CD, Cloud, Third-Party Integrations)

Clean, modular code naturally fits into DevOps pipelines. CI/CD processes automate builds, testing, and deployments, reducing manual errors and accelerating time-to-market.

Moving to the cloud, whether partially or fully, becomes a gradual process, allowing for experimentation with hybrid environments before a full cutover. Decoupled APIs simplify connections to external services, be they CRM, BI, or payment platforms.

Adopting these tools provides greater visibility into delivery lifecycles, enhances collaboration between IT departments and business units, and prepares the organization for emerging solutions like AI and IoT.

Typical Steps for a Successful Re-engineering

Rigorous preparation and an incremental approach are essential to transform existing software without risking business continuity. Each phase must be based on precise diagnostics and clear deliverables.

Technical and Functional Audit

The first step is to catalogue existing components, map dependencies, and assess current test coverage. This analysis reveals weak points and intervention priorities.

On the functional side, it’s equally essential to list the business processes supported by the application, verify discrepancies between documentation and actual use, and gauge user expectations.

A combined audit enables the creation of a quantified action plan, identification of quick wins, and the planning of migration phases to minimize the impact on daily operations.

Module Breakdown and Progressive Migration

After the assessment, the project is divided into logical modules or microservices, each targeting a specific functionality or business domain. This granularity facilitates the planning of isolated development and testing sprints.

Progressive migration involves deploying these modernized modules alongside the existing system. Gateways ensure communication between old and new segments, guaranteeing service continuity.

Testing, Documentation, and Training

Each revamped module must be accompanied by a suite of automated tests and detailed documentation, facilitating onboarding for support and development teams. Test scenarios cover critical paths and edge cases to ensure robustness.

At the same time, a training plan for users and IT teams is rolled out. Workshops, guides, and hands-on sessions ensure rapid adoption of new tools and methodologies.

Finally, post-deployment monitoring allows you to measure performance, leverage feedback, and adjust processes for subsequent phases, ensuring continuous improvement.

Turn Your Legacy into a Strategic Advantage

A reasoned re-engineering modernizes your application heritage without losing accumulated expertise, reduces technical debt, strengthens security, and improves operational agility. The audit, modular breakdown, and progressive testing phases ensure a controlled transition while paving the way for DevOps and cloud tools.

Performance, integration, and recruitment challenges need not hinder your digital strategy. At Edana, our experts, with a contextual and open-source approach, are ready to support all phases, from initial analysis to team training.

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PUBLISHED BY

Martin Moraz

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Martin is a senior enterprise architect. He designs robust and scalable technology architectures for your business software, SaaS products, mobile applications, websites, and digital ecosystems. With expertise in IT strategy and system integration, he ensures technical coherence aligned with your business goals.

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Featured-Post-Software-EN Software Engineering (EN)

What Is Domain-Driven Design (DDD) and Why Adopt It?

What Is Domain-Driven Design (DDD) and Why Adopt It?

Auteur n°14 – Daniel

Many software projects struggle to faithfully capture the complexity of business processes, resulting in scattered code that is hard to evolve and costly to maintain. Domain-Driven Design (DDD) offers a strategic framework to align technical architecture with the company’s operational realities. By structuring development around a shared business language and clearly defined functional contexts, DDD fosters the creation of modular, scalable software focused on business value. This article presents the fundamentals of DDD, its concrete benefits, the situations in which it proves particularly relevant, and Edana’s approach to integrating it at the heart of bespoke projects.

What Is Domain-Driven Design (DDD)?

DDD is a software design approach centered on the business domain and a shared language. It relies on key concepts to create a modular architecture that clearly expresses rules and processes.

Key Vocabulary and Concepts

DDD introduces a set of terms that enable technical and business teams to understand one another unambiguously. Among these notions, “entities,” “aggregates,” and “domain services” play a central role.

An entity represents a business object identifiable by a unique ID and evolving over time.

An aggregate encompasses a coherent cluster of entities and value objects, ensuring the integrity of internal rules upon each change.

Building a Ubiquitous Language

The Ubiquitous Language aims to standardize terminology between developers and business experts to avoid misalignments in the understanding of requirements.

It emerges during collaborative workshops where key terms, scenarios, and business rules are formalized.

Bounded Contexts: Foundations of Modularity

A Bounded Context defines an autonomous functional scope within which the language and models remain consistent.

It enables decoupling of subdomains, each evolving according to its own rules and versions.

This segmentation enhances system scalability by limiting the impact of changes to each specific context.

Why Adopt DDD?

DDD improves code quality and system maintainability by faithfully translating business logic into software architecture. It strengthens collaboration between technical and business teams to deliver sustainable value.

Strategic Alignment Between IT and Business

By involving business experts from the outset, DDD ensures that every software module genuinely reflects operational processes.

Specifications evolve in tandem with domain knowledge, minimizing discrepancies between initial requirements and deliverables.

Business representatives become co-authors of the model, guaranteeing strong ownership of the final outcome.

Technical Scalability and Flexibility

The structure of Bounded Contexts provides an ideal foundation for gradually transitioning from a monolith to targeted microservices architecture.

Each component can be deployed, scaled, or replaced independently, according to load and priorities.

This modularity reduces downtime and facilitates the integration of new technologies or additional channels.

Reduced Maintenance Costs

By isolating business rules into dedicated modules, teams spend less time deciphering complex code after multiple iterations.

Unit and integration tests become more meaningful, as they focus on aggregates with clearly defined responsibilities.

For example, a Swiss technology company we collaborate with observed a 25% reduction in support tickets after adopting DDD, thanks to better traceability of business rules.

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In Which Contexts Is DDD Relevant?

DDD proves indispensable when business complexity and process interdependencies become critical. It is particularly suited to custom projects with high functional variability.

ERP and Complex Integrated Systems

ERPs cover a wide range of processes (finance, procurement, manufacturing, logistics) with often intertwined rules.

DDD allows segmenting the ERP into Bounded Contexts corresponding to each functional area.

For instance, a pharmaceutical company distinctly modeled its batch and traceability flows, accelerating regulatory compliance.

Evolving Business Platforms

Business platforms frequently aggregate continuously added features as new needs arise.

DDD ensures that each extension remains consistent with the original domain without polluting the application core.

By isolating evolutions into new contexts, migrations become progressive and controlled.

Highly Customized CRM

Standard CRM solutions can quickly become rigid when over-customized to business specifics.

By rebuilding a CRM using DDD, each model (customer, opportunity, pipeline) is designed according to the organization’s unique rules.

A Swiss wholesale distributor thus deployed a tailor-made CRM that is flexible and aligned with its omnichannel strategy, without bloating its codebase thanks to DDD.

How Edana Integrates Domain-Driven Design

Adopting DDD begins with a thorough diagnosis of the domain and key service interactions. The goal is to establish a common language and steer the architecture toward sustainable modularity.

Collaborative Modeling Workshops

Sessions bring together architects, developers, and business experts to identify entities, aggregates, and domains.

These workshops foster the emergence of a shared Ubiquitous Language, preventing misunderstandings throughout the project.

The documentation produced then serves as a reference guide for all technical and functional teams.

Progressive Definition of Bounded Contexts

Each Bounded Context is formalized through a set of use cases and diagrams to precisely delineate its perimeter.

Isolation ensures that business evolutions do not affect other functional blocks.

The incremental approach allows adding or subdividing contexts as new requirements emerge.

Service-Oriented Modular Architecture

Identified contexts are implemented as modules or microservices, based on domain scale and criticality.

Each module exposes clear, versioned interfaces, facilitating integrations and independent evolution.

Open-source technologies are favored to avoid excessive vendor lock-in.

Align Your Software with Your Business for the Long Term

Domain-Driven Design provides a solid foundation for building systems aligned with operational realities and adaptable to business transformations.

By structuring projects around a shared business language, Bounded Contexts, and decoupled modules, DDD reduces maintenance costs, strengthens team collaboration, and ensures agile time-to-market.

If business complexity or operational maintenance challenges are hindering innovation in your company, our experts are ready to support you in adopting a DDD approach or any other software architecture tailored to your context.

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PUBLISHED BY

Daniel Favre

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Daniel Favre is a Senior Software Engineer. He designs and builds bespoke business solutions (SaaS, mobile apps, websites) and full digital ecosystems. With deep expertise in architecture and performance, he turns your requirements into robust, scalable platforms that drive your digital transformation.

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Featured-Post-Software-EN Software Engineering (EN)

How to Successfully Outsource Your Software Development?

How to Successfully Outsource Your Software Development?

Auteur n°3 – Benjamin

Outsourcing software development is no longer simply about cost reduction: it has become a catalyst for innovation and competitiveness for mid-sized to large enterprises. When it is guided by a clear product vision, structured through shared governance, and aligned with business strategy, it enables you to leverage new expertise without compromising on quality or security.

Outsourcing: a strategic lever if properly framed

Outsourcing must serve your strategic objectives, not just your operational budget. It requires a precise framework to avoid overruns and ensure efficiency.

Redefining software development outsourcing beyond cost

Thinking that outsourcing is merely a financial trade-off is reductive. It’s about co-building a product vision that combines internal expertise with external know-how to deliver features with high business value.

A strategic approach considers user impacts, regulatory constraints, and future evolutions from the outset. This framework protects against ad hoc solutions, promotes priority alignment, and limits the risk of cost overruns.

This approach transforms contractual relationships into long-term partnerships based on concrete, shared performance indicators rather than simple time-and-materials billing.

Embedding a product vision for results-driven development

Aligning outsourcing with a product approach requires defining a common “minimum viable product” with clear value-added objectives and a structured release plan.

For example, a Swiss medtech company chose to entrust medical imaging control modules to an external provider while maintaining an internal product team. Each sprint was validated by a joint committee, ensuring functional coherence and compliance with medical standards.

This collaborative management enabled them to deliver a stable prototype within three months and iterate quickly based on field feedback, all while controlling costs and quality.

Ensuring the quality of outsourced work with proven methods

To prevent quality drift, it’s essential to standardize best practices and technological standards from the provider selection stage. Automated testing, code reviews, and continuous integration must be part of the selection criteria.

Using open-source, modular frameworks maintained by a large community strengthens solution robustness and minimizes vendor lock-in. The chosen partner must share these requirements.

By structuring the project around agile ceremonies and transparent tracking tools, you gain fine traceability of deliverables and permanent quality control.

Strategic alignment and governance: the foundations of successful IT outsourcing

An outsourcing project cannot thrive without shared business objectives and rigorous oversight. Governance becomes the bedrock of success.

Aligning outsourcing with the company’s business roadmap

Each external work package must anchor in the company’s strategic priorities, whether it’s entering new markets, improving user experience, or reducing risks.

For instance, a major Swiss bank integrated external development teams into its digitalization roadmap. Instant payment modules were scheduled alongside internal compliance initiatives, with quarterly milestones validated by the executive committee.

This framework ensures that every software increment directly supports growth ambitions and complies with financial sector regulations.

Implementing agile, shared project governance

Governance combines steering committees, daily stand-ups, and key performance indicators (KPIs) defined from the start. It ensures fluid communication and rapid decision-making.

Involving business stakeholders in sprint reviews fosters end-user buy-in and anticipates feedback on value. This prevents siloed development and late-stage change requests.

Transparent reporting, accessible to all, strengthens the provider’s commitment and internal team alignment, reducing misunderstandings and delays.

Clearly defining roles and responsibilities in the software development project

A detailed project organigram distinguishes the roles of product owner, scrum master, architect, and lead developer. Each actor knows their decision-making scope and reporting obligations.

This clarity reduces confusion between project ownership and execution while limiting responsibility conflicts during testing and deployment phases.

Finally, a well-calibrated Service Level Agreement (SLA), supplemented by progressive penalties, incentivizes the provider to meet agreed deadlines and quality standards.

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Collaboration models adapted to outsourcing: hybrid, extended, or dedicated?

The choice of partnership model determines flexibility, skill development, and alignment with business challenges. Each option has its advantages.

Extended team for greater flexibility

The extended team model integrates external profiles directly into your teams under your management. It enables rapid up-skilling in specific competencies.

A Swiss retail brand temporarily added front-end and DevOps developers to its internal squads to accelerate the deployment of a new e-commerce site before the holiday season.

This extension absorbed a capacity peak without permanent cost increases while facilitating knowledge transfer and internal skill development.

Dedicated team to ensure commitment

An outsourced dedicated team operates under its own governance, with management aligned to your requirements. It brings deep expertise and contractual commitment to deliverables.

You select a provider responsible end to end, capable of handling architecture, development, and maintenance. This model is well-suited for foundational initiatives like overhauling an internal management system.

The partner’s responsibility includes availability, scalability, and long-term competency retention, while ensuring comprehensive documentation and specialized support.

Hybrid: combining internal expertise and external partners

The hybrid model combines the benefits of extended and dedicated teams. It allows retaining control over strategic modules in-house and outsourcing transversal components to a certified pool of external resources.

This approach facilitates risk management: the core business remains within the company, while less sensitive components are handled by specialized external resources.

The resulting synergy optimizes time to market while ensuring progressive skill-building of internal teams through mentoring and knowledge-transfer sessions.

Caution: how to avoid the pitfalls of poorly managed software outsourcing

Outsourcing carries risks if conditions are not met. The main pitfalls concern quality, dependency, and security.

Unframed offshoring and the promise of skills without methodology

Choosing a low-cost provider without verifying its internal processes can lead to unstable and poorly documented deliverables. The risk then is multiplying rework and project slowdowns.

Work rhythms and cultural barriers can complicate communication and limit agility. Without local oversight, coordination between teams becomes heavier and deadlines harder to meet.

To secure this model, it is imperative to enforce proven methodologies, standardized reporting formats, and interim quality control phases.

Technical dependency risk and invisible debt

Entrusting all maintenance to a single provider can create critical dependency. If engagement wanes or the partner shifts strategy, you risk losing access to essential skills.

This gradual loss of internal knowledge can generate “invisible debt”: absence of documentation, lack of unit tests, or inability to evolve solutions without the initial provider.

A balance of skill transfer, comprehensive documentation, and maintenance of an internal team minimizes these risks of technical debt and dangerous long-term dependency.

Data security and legal responsibility in outsourced development

Providers can be exposed to security breaches if they don’t adhere to encryption standards, best storage practices, or audit processes. Non-compliance can have serious regulatory consequences.

It is essential to verify the partner’s certifications (ISO 27001, GDPR) and formalize liability clauses in case of breach or data leak.

Regular access reviews, penetration testing, and code reviews ensure continuous vigilance and protect your digital assets against internal and external threats.

Make IT outsourcing a competitive advantage

Well-framed outsourcing becomes a true growth lever when based on a product vision, solid governance, and an agile partnership. Hybrid or dedicated collaboration models offer flexibility and expertise, while rigorous management prevents cost, quality, or security pitfalls.

By relying on open-source principles, modularity, and skill transfer, you minimize technological dependency and invisible debt, while gaining responsiveness and control over business challenges.

At Edana, our experts are available to help you define a tailored outsourcing strategy aligned with your performance and security objectives. Together, let’s make outsourcing a driver of innovation and resilience for your company.

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