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— Brian Marick, New Models for Test Development | Source

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IT outsourcing allows companies to focus on core activities while benefiting from the expertise of outside experts. The article discusses how to strategically approach outsourcing, especially in selecting the right consultants, as well as managing risks and monitoring the effects of cooperation. Learn how to plan and implement IT outsourcing to support your company’s long-term growth.

EU or non-EU consultants?

Nowadays, many companies, for compliance reasons, require suppliers to have their employees come from the EU zone and log in from an IP located in the EU. One may wonder why, but this is followed by a huge corporate machine and the area of compliance, which is crucial in security topics. Choosing between EU consultants and non-EU specialists requires a comprehensive analysis of both the advantages and limitations of each option.

Legal issues are the first critical aspect of this choice. The European Union has introduced a number of regulations, including RODO (GDPR), NIS2 and the Digital Operational Resilience Act (DORA), which precisely define data security and operational continuity standards. Consultants in the EU area are trained and adapted to these requirements, minimizing the risk of legal violations. Implementing GDPR-compliant processes can reduce legal risks by up to 30-40% compared to working with unprepared non-EU teams. It is worth noting that the most common GDPR violations relate to improper data processing (42%), insufficient technical and organizational measures (21%) and unauthorized data sharing (19%), highlighting the importance of working with teams aware of European legal requirements.

At the same time, working with highly skilled teams from outside the EU can offer significant advantages. Follow-the-sun models with teams from different time zones enable continuous work on projects 24 hours a day. In addition, some regions have developed specialized competence centers in areas such as AI or cyber security. The key is to implement appropriate legal and technical safeguards, such as SCC (Standard Contractual Clauses) agreements or VPNs with two-way authentication. It’s worth noting that SCC agreements, when updated in 2021, include much more stringent requirements, including mandatory privacy impact assessments of data transfers and the use of additional security measures.

Regardless of the team’s location, infrastructure security remains a key consideration. Working with EU consultants simplifies security management through uniform standards and regulations. A rational approach is to use EU teams for critical infrastructure projects, and for R&D projects it is possible to work with non-EU specialists using isolated development environments. Consider implementing a “Separation of Concerns” model, where non-EU teams do not have access to production data or critical infrastructure, and their work is always reviewed by internal teams before deployment.

The financial aspect often seems to tip the balance in favor of non-EU teams, but the total cost of collaboration (TCO) can be similar once the additional costs of risk management, compliance, communication and potential security incidents are factored in. According to market analyses, the difference in total cost can reduce by as much as 60-70% compared to the initial difference in hourly rates, especially for projects with high security requirements and integration complexity.

From the perspective of different roles in the organization, the issue looks different. The CTO tends to focus on regulatory compliance and overall risk; project managers focus on effective communication in the same time zones; and technical leaders primarily assess the competence of the team, regardless of location. It is important that the decision to select consultants be made multidimensionally, taking into account all of these perspectives and the specifics of the project.

**Balanced approach to consultant selection **

  • For projects with sensitive or regulated data: priority for EU teams

  • For projects requiring niche competencies: consider global talent

  • For projects with short deadlines: use the follow-the-sun model

  • Always: detailed confidentiality agreements and technical safeguards

  • Hybrid: EU management team + global specialists with limited access

How to choose the right IT service provider?

Choosing an IT service provider is a strategic decision that can determine the success or failure of an organization’s technology projects. Modern enterprises need more than just a subcontractor - they are looking for a partner that understands their business and can deliver value beyond a standard implementation. So how do you approach this complex decision-making process?

The first step is a comprehensive analysis of the potential supplier’s experience and portfolio. Instead of settling for general information from sales presentations, it’s a good idea to invite the supplier’s technical team to a workshop where they will present specific details from similar implementations. A good practice is to organize workshop sessions with finalists, during which technical teams solve real problems in the area related to the project. This method reveals not only actual competence, but also work styles and approaches to problem solving. An analysis of the structure of reference projects in terms of their scale, complexity and technological similarity to the planned project is also an important part of the evaluation. It is worth creating an evaluation matrix that includes such criteria as technological compatibility (0-10), scale of completed projects (0-10), length of cooperation with reference clients (0-10), and innovation of applied solutions (0-10).

The second key aspect is the evaluation of work processes and methodologies. A modern vendor should present specific artifacts from its manufacturing process - examples of documentation, test cases, a risk management plan or code quality metrics. It is good practice to introduce a short, two-week pilot phase with potential vendors to verify their actual work processes, so that significant differences in quality approach, not visible at the bid presentation stage, can be detected. During such a pilot, it is worth assessing not only the final results, but also the day-to-day aspects of cooperation: the quality of communication, the speed of response to changes, the transparency of reporting progress and problems. You can define a series of mini-tasks that should be implemented as part of the pilot, from simple fixes to complex functionalities, to test various aspects of cooperation.

Financial stability and human resources are the third pillar of evaluation. It is worth going beyond standard financial metrics and also looking at staffing structure, employee turnover, and recruitment and onboarding models. A recommended practice is to meet with key members of a potential project team before signing a contract, which significantly reduces the risk of discrepancies between the team’s declared and actual competencies. It can be helpful to analyze the age and seniority structure of the team - too much dominance of juniors may suggest problems with maintaining quality, while a lack of younger specialists may indicate difficulties with innovation and adaptation to new technologies. It is also important to assess the supplier’s training policy - whether it invests in the development of its employees, whether it has certification programs and how it ensures that the team’s technical knowledge remains up to date.

A fourth element, often underestimated, is cultural and value congruence between organizations. This aspect goes beyond formal metrics, but is fundamental to the long-term success of the collaboration. It’s worth holding informal meetings between teams to assess whether values, communication styles and approaches to problem solving are compatible. Cultural differences can lead to misunderstandings, delays and frustration, even if formal processes are well defined. A good practice is to hold an integration workshop before the actual project begins, where teams work together to develop rules for collaboration, communication protocols and mechanisms for escalating problems. It is also worth paying attention to the supplier’s transparency in the area of its own limitations and challenges - a partner that openly admits its weaknesses is usually more credible than one that presents itself as perfect in all aspects.

The fifth pillar in evaluating a potential vendor is its approach to security and quality. In an era of growing cyber threats and high user expectations, these aspects caot be treated as optional. It is worth conducting a detailed audit of a vendor’s security processes, including access management, source code protection, vulnerability management and incident response. Equally important is an analysis of quality assurance processes - whether the vendor uses automated testing, how it measures code quality, what coding standards it uses and how it manages technical debt. It can be helpful to request access to quality monitoring tools used by the vendor (e.g., SonarQube, CodeClimate) and analyze historical trends in the projects it manages.

From the perspective of different audiences, the priorities in choosing an IT vendor look different:

  • For the CTO, the long-term stability of the partner, technological compatibility with the IT strategy, and innovation potential are crucial.

  • Project managers focus on work methodologies, reporting tools and the ability to respond flexibly to change.

  • Technical leaders prioritize the team’s technical competence, quality assurance approach and compliance with coding standards.

A practical process for selecting an IT vendor

  • Step 1: Initial selection based on portfolio and references (2-3 weeks)

  • Step 2: Technical workshop with solution of real problem (1-2 days)

  • Step 3: Pilot mini-project with finalists (2-4 weeks)

  • Step 4: Meet with key team members and verify competencies

  • Step 5: Detailed contract analysis with emphasis on SLAs and escalation models

Is it worth investing in test automation?

Test automation is an area that raises a lot of debate among IT decision-makers, especially in terms of upfront costs and time required for implementation. However, concrete market data shows significant benefits from this investment - the average return on investment (ROI) for test automation can be more than 170% over 3 years, with a typical break-even point 6-9 months after implementation.

The most cost-effective applications of test automation include projects with long lifecycles, applications with frequent releases and business-critical systems. Typical results include a significant reduction in regression testing time - even from several days to a few hours after automating most test cases. At the same time, test automation is not a one-size-fits-all solution - for short-term projects, prototypes or interfaces subject to frequent visual changes, the costs of implementing automation can outweigh the benefits.

Typical test automation challenges include:

  • Maintenance costs for test scripts (15-20% of initial development cost per year)

  • Difficulties in automating complex test cases (e.g., multi-system integrations)

  • Need to continuously improve team skills in the face of evolving tools

An effective automation strategy should be based on prioritizing test cases by frequency of execution and stability of interfaces. Organizations often adopt an approach in which they automate the majority (80-90%) of regression tests and about 40-50% of functional tests, leaving the more complex and infrequently executed tests in the manual domain.

From the perspective of different roles, test automation offers different benefits:

  • For the CTO, it means reducing long-term costs and minimizing business risks

  • Project managers gain predictability of release cycle and shorter release windows

  • Testers and developers can focus on creative tasks instead of repetitive testing

Modern trends in test automation include the use of AI to generate test cases, behavior-based testing (BDD) and shift-left testing, where tests are integrated early in software development. The use of automated testing using user behavior modeling with the help of machine learning can increase the detection of defects in the user interface by up to 20-25%.

**A practical guide to investing in test automation **

  • Small projects (up to 5 developers): Unit test automation + business critical paths (ROI after ~12 months)

  • Medium-sized projects (5-15 developers): Complex regression automation + CI/CD (ROI after ~9 months).

  • Large projects (15+ developers): Full automation strategy with performance testing (ROI after ~6 months)

  • Legacy projects: incremental automation during refactoring (modular approach)

  • Key success factor: Involving developers in the testing process (shift-left)

How to effectively manage an external development team?

Managing an external development team requires specific tools, processes and communication methods that differ significantly from standard internal team management. Practical experience shows that a particularly effective approach combines a clearly defined framework for collaboration with precise tools for tracking progress.

To effectively manage an external team, the right tools are essential:

  • Project management platforms: JIRA, Azure DevOps or ClickUp with clearly defined workflow steps

  • Communication tools: Slack or MS Teams with dedicated subject channels

  • Documentation: Confluence or SharePoint with clear structure and access levels

  • Code sources: GitLab or GitHub with code review and CI/CD processes in place

  • Performance monitoring: team dashboards showing velocity, burn-down charts and code quality metrics

Best practices include implementing daily 15-minute stand-ups, weekly functionality demos and bi-weekly retrospective sessions. This approach can increase design transparency by up to 60% and reduce response times to problems by 30-40%.

Effective management requires defining precise “Definition of Ready” and “Definition of Done” for each task and introducing the practice of joint programming (pair programming) linking internal and external developers for critical system components. This approach can lead to a 30-40% reduction in defect rates and speed up the onboarding of new team members by up to half.

From the perspective of different roles, managing an external team requires a different approach:

  • CTO should focus on strategic alignment and knowledge transfer by scheduling regular strategy sessions

  • Project managers need precise metrics and KPIs, such as turnaround time, code quality (as measured by Sonar/CodeClimate), on-time delivery

  • Technical leaders should introduce coding standards, automated code reviews and periodic technology sessions

It is particularly important to manage risks specific to external teams, such as:

  • Loss of design knowledge - solution: code documentation, recording technical sessions, knowledge rotatio

  • Cultural barriers - solution: integration workshops, clear communication procedures, “project dictionary”

  • Staff turnover - solution: “shadow resource” for key roles, documentation standards, onboarding packs

A practical framework for managing an external team

  • Daily: 15-minute stand-up + monitoring of activity in the version control system

  • Weekly: Functionality demo + review of metrics (velocity, code quality, tests)

  • Every sprint: Retrospective with a concrete improvement plan + knowledge rotatio

  • Monthly: Strategic review + verification of compliance with business objectives

  • Quarterly: Security and code quality audit + integration workshop

What collaboration models work best?

Choosing the optimal collaboration model is fundamental to the success of an IT project. According to project sector research, more than 60% of IT projects go over budget or over schedule due to an inappropriately chosen collaboration model. Analyses of the European market show that hybrid cooperation models are gaining popularity - they now account for about half of all outsourcing contracts, compared to about a quarter a few years ago.

The Time & Materials model, based on billing for actual hours worked, works best for projects where the scope of work may evolve. This model allows for flexibility in responding to changes in the market and user preferences. Typical pitfalls of this model include:

  • Lack of control over the total budget - the solution: monthly hourly caps (limits)

  • The risk of inefficiency - the solution: clear KPIs and performance monitoring

  • Difficulties in long-term planning - solution: framework contracts with guaranteed availability

Team Leasing is effective for organizations with strong management competencies. This model allows the internal team to be supplemented with specialists in specific areas, such as microservices, UX or DevOps. Typical challenges include:

  • Differences in work culture - the solution: joint workshops and clear standards

  • Insufficient knowledge transfer - solution: pair programming and documentatio

  • Long onboarding time - solution: structured onboarding program (1-2 weeks)

Collaboration under the Fixed Price model is often chosen for well-defined projects. This model provides predictability of costs and deadlines, which is important for projects with fixed budgets. The main pitfalls are:

  • Low flexibility to changes - solution: include a buffer for changes (15-20%)

  • Risk of cutting quality under budget pressure - solution: clear acceptance criteria

  • Conflicts in scope changes - the solution: a clear change management procedure

The Success Fee model, where compensation is tied to the achievement of KPIs, is gaining popularity. In this model, partial remuneration can be tied to specific business results, such as increased adoption of self-service features in applications.

I

innovative hybrid collaboration models combine the advantages of different approaches:

  • Core & Flex: fixed core team + flexibly scaled resources

  • Milestone-Based T&M: hourly billing with milestone bonuses

  • Capacity-as-a-Service: guaranteed pool of hours with flexible assignment to projects

From the perspective of different decision-making roles:

  • CTO priorities: budget predictability, strategic flexibility, ROI

  • Project managers: on-time delivery, process transparency, change management

  • Technical leaders: code quality, team stability, technical standards

Guide to selecting a collaboration model

  • Projects with evolving requirements: Time & Materials with monthly limits

  • Long-term strategic projects: Core & Flex (permanent team + flexible resources)

  • Clearly defined, closed projects: Fixed Price with change management procedure

  • Optimization Projects: Success Fee tied to measurable KPIs.

  • Maintenance and Development: Capacity-as-a-Service with task prioritizatio

How are new technologies changing the IT vendor collaboration model?

The dynamic development of new technologies is fundamentally changing the rules of cooperation with external IT suppliers. DevSecOps, AI/ML in development processes, microservices architecture or low-code/no-code are not just technology trends, but factors transforming entire ecosystems of cooperation with technology partners.

DevSecOps as an approach that integrates security into the entire software development cycle requires a new model of collaboration. Successful implementation requires defining security standards at every stage of the process - from automated code scans to vulnerability management to penetration testing. The process often requires rebuilding vendor contracts, adding security metrics to KPIs and periodic security awareness workshops. In practice, this means changing the traditional model, where security was checked at the end of the manufacturing process, to one where it is an integral part of every stage. It also requires a redefinition of responsibility - external developers must take an active role in identifying and mitigating security risks, not just implementing functionality. Key practices include:

  • Security as Code: security infrastructure and policies as code in a repository

  • Automatic security scans as a condition for code acceptance (security gates)

  • Joint incident response teams (cross-vendor security teams)

  • Regular attack simulations and red team exercises with outside teams

  • Integrated vulnerability management with clear responsibilities

Artificial intelligence and machine learning are revolutionizing collaboration with IT vendors on many levels. Modern organizations are using AI to automatically analyze the quality of code delivered by third-party developers, which can lead to a reduction in code review time by up to 40%. ML systems find application in predicting delays in functionality deliveries, identifying patterns that lead to missed deadlines. Intelligent systems can analyze historical project data, identify patterns leading to delays or defects, and even predict potential problems before they occur. This makes it possible to proactively manage risks and take corrective action in advance. Examples of AI/ML applications in supplier management:

  • Intelligent task allocation based on historical performance and availability

  • Automatic classification and prioritization of defects with prediction of repair effort

  • Predictive risk analysis of delays and budget overruns

  • Monitor code quality and automatically detect potential problems

  • Team communication analysis to identify early signals of communication problems

The most advanced organizations are already implementing Intelligent Contract Management systems that use natural language processing to analyze supplier contracts, identify potential legal and financial risks, and monitor compliance of cooperation parameters with contractual provisions.

Microservices architecture enables modularization of IT vendor collaboration. Organizations can reorganize collaboration with multiple vendors, assigning them responsibility for specific microservices with clearly defined interfaces and contracts. Instead of a monolithic application developed by a single team, it becomes possible for different teams, often belonging to different vendors, to develop individual components in parallel and independently. The key to success is the precise definition of interfaces (API contracts) and the implementation of automated integration tests that verify the correctness of communication between microservices. In practice, this approach also requires the implementation of advanced DevOps practices, such as Continuous Integration, Continuous Delivery, and Infrastructure as Code. This approach allows for:

  • Parallel operation of multiple suppliers without interlocking with each other

  • Easier to measure the performance of individual teams

  • Faster vendor replacement for a specific component without affecting the overall system

  • Scale individual services independently of each other

  • Improved fault isolation and increased resilience of the system as a whole

Low-code/no-code platforms open up new opportunities for collaboration with IT suppliers. Using these platforms to rapidly prototype solutions with suppliers can shorten the conceptual phase by up to 60%. These tools democratize the software development process, allowing business representatives to actively participate in the design and implementation of solutions. In the context of cooperation with external suppliers, this leads to a fundamental change in the model - instead of communicating detailed requirements for implementation, the customer can independently create a functional prototype that accurately reflects its needs. The role of the supplier then evolves to optimize, scale and professionalize the solution. Key aspects of low-code collaboration:

  • Faster iteration and validation cycles for business ideas

  • Easier knowledge transfer between business and IT

  • Hybrid teams combining developers and domain experts

  • Reduce the risk of misunderstandings and misinterpretation of requirements

  • Shorter time-to-market for new functionality

Blockchain and distributed ledger technologies (DLT) are bringing a new dimension to IT vendor relationships through the ability to create “smart contracts” - self-enforceable contracts encoded in the blockchain. These contracts can automatically monitor delivery compliance, verify code quality through integration with CI/CD tools, and even automatically process payments when defined conditions are met. The technology offers an unprecedented level of transparency and automation in supplier relationship management, while minimizing the need for manual checks and verifications.

From the perspective of different roles in the organization:

  • CTO sees new technologies as an opportunity to transform the IT operating model and build more flexible, scalable collaboration structures

  • Project managers adapt agile methodologies to new technology paradigms, using AI/ML tools to better plan and manage risks

  • Technical leaders focus on ensuring architectural consistency in a distributed environment, defining standards for integration and communication between components from different vendors

Technological transformers of cooperation with suppliers

  • DevSecOps: Integrated security requires new contracts and metrics

  • AI/ML: Intelligent analytics for team performance and risk predictio

  • Microservices: Modularization of responsibility and increased autonomy for teams

  • Low-code: Accelerate iteration and integrate the business into the manufacturing process

  • API-first: Standardization of interfaces to facilitate multi-vendor integratio

What affects the quality of the software produced?

Software quality is a complex and multidimensional topic that goes significantly beyond the issue of not having bugs in the code. A modern approach to software quality must take into account both technical and organizational aspects, which together create an ecosystem that fosters the creation of valuable solutions.

The competency and experience of the development team is a fundamental quality factor. Introducing the practice of regular internal hackathons and technology workshops can translate into a significant decrease in the number of defects in code, up to 25%. Practical steps to build a quality team include:

  • Mentoring program connecting seniors with juniors (e.g., pair programming 2h/week)

  • Education budget for courses and certifications (min. 40h per year per developer)

  • Internal hackathons to test new technologies (quarterly)

  • Rotation of tasks to prevent knowledge silos (every 2-3 months)

Maturity of manufacturing processes is critical to quality. A comprehensive quality assurance framework should include:

  • Feature Toggles for frequent deployments without risk (100+ deployments per week)

  • Code Review based on security and performance checklists

  • Automatic monitoring of technical debt with acceptance limits (max 5% of new debt/sprint)

  • A/B testing for new functionality with automatic rollback when conversions drop

The approach to system architecture determines its long-term quality. A Domain-Driven Design (DDD) strategy with clear bounded contexts allows multiple teams to work in parallel without integration conflicts. Practical principles of architecture to support quality:

  • Modularity with clearly defined boundaries (max 7±2 dependencies per module)

  • Standardization of communication interfaces (REST API, gRPC, Event-Driven)

  • Design for testing (Dependency Injection, mockups/subs)

  • Code ownership with responsibility for the entire life cycle

In the context of working with external suppliers, practical quality assurance mechanisms are particularly important:

  • Automatic quality gates to block merging of substandard code

  • Definition of Done considering safety and performance criteria

  • Contractual linking of remuneration to quality metrics (defect leakage, debt ratio)

  • Joint quality teams (QA Guild) combining customer and supplier testers

A modern approach to quality also takes into account security aspects. Standards for high quality in outsourcing projects should include:

  • Automatic security scans as part of CI/CD pipeline

  • Regular application security audits by the red-team

  • Secure Coding workshops for all developers (mandatory every 6 months)

  • Vulnerability management with defined SLA for remediation (critical: 48h, high: 7 days)

From the perspective of different roles in the organization, software quality means:

  • For CTOs: reduced maintenance costs, risk mitigation and regulatory compliance

  • For project managers: predictability of delivery and reduction of unplanned work

  • For technical leaders: clean, testable code and a sustainable pace of development

A practical software quality framework

  • People: Regular code reviews, mentoring, communities of practice

  • Process: CI/CD with automated testing, definable Definition of Done

  • Technology: coding standards, technical debt monitoring, automation

  • Security: Secure SDLC, regular audits, vulnerability management

  • Measurability: specific quality KPIs (coverage, complexity, MTTR, defect density)

How to measure the effectiveness of cooperation with an external supplier?

Evaluating the effectiveness of partnerships with third-party IT service providers requires precise, measurable metrics to objectively assess the value of the partnership. Instead of relying on subjective perceptions, modern organizations are implementing comprehensive performance measurement systems that cover both technical and business aspects.

Key operational performance indicators (KPIs) should be clearly defined and regularly monitored. A balanced set of metrics for effective collaboration evaluation should include:

  • Team Velocity (story points/sprint) with trend + forecast

  • Defect Leakage Rate (% of defects detected after deployment)

  • Scope stability indicator (% of backlog/sprint changes)

  • MTTR (Mean Time To Repair) for production incidents

  • Code quality measured by automated tools (SonarQube)

These metrics should be available in real time through dashboards (e.g., Grafana, Power BI) for all stakeholders. It is a good practice to introduce weekly “review KPIs” with suppliers, so that trends can be quickly identified and corrective actions can be taken.

Specific performance measurement tools include:

  • JIRA + eazyBI for workflow analysis and forecasting

  • SonarQube/CodeClimate to monitor code quality

  • Dynatrace/New Relic to monitor application performance

  • Jenkins/GitLab CI to track the stability of the deployment process

  • Coupling with Service Desk system for incident analysis

Equally important is assessing the impact of the collaboration on business goals. In practice, it makes sense to link business goals to specific supplier metrics:

  • Reduction in request handling time (target: -30%) → provider measured by optimization implementation time

  • Increase system availability (target: 99.99%) → vendor accountable for SLA metrics

  • Reduction in maintenance costs (target: -20%) → incident reduction bonus

  • Increase user satisfaction (target: +15pts NPS) → joint usability studies

The challenge remains to objectively measure the quality of communication and relationship management. A structured process for evaluating collaboration should include:

  • Monthly satisfaction survey for key stakeholders (scale of 1-10)

  • Track response times to requests and inquiries

  • Measuring the number and quality of proactive improvements proposed by the supplier

  • Evaluate the transparency of communication about problems and risks

An advanced approach is to benchmark the performance of various vendors. The PZU Group has created an internal benchmark of IT vendors, which has made it possible to:

  • Unit cost comparison (e.g., cost/story point)

  • Summary of delivery times for similar functionality

  • Benchmarking the quality of solutions provided

  • Standardization of expectations for all partners

From the perspective of different roles in the organization, performance measurement requires consideration of different priorities:

  • CTO focuses on strategic and long-term metrics (TCO, time-to-market)

  • Project managers monitor operational metrics (timeliness, scope stability)

  • Technical leaders focus on quality indicators (technical debt, defect density)

**Framework for measuring the effectiveness of cooperation **

  • Daily: Activity in repositories, task progress, blockers

  • Weekly: Velocity, burn-down, defect rate, code quality metrics

  • Monthly: SLA compliance, customer satisfaction, process improvements

  • Quarterly: Business KPI impact, cost efficiency, innovation metrics

  • Yearly: TCO analysis, strategic alignment, vendor benchmarking