How to Hire Developers in Ukraine: A 2026 Guide

Hiring developers in Ukraine gives you access to 300,000+ IT professionals with strong STEM education, English fluency, and rates 50-70% lower than the US or Western Europe. The country’s tech sector exported $6.66 billion in services in 2025, and its talent pipeline adds roughly 25,000 new graduates every year. This guide covers what you actually need to know to hire well: costs, hiring models, legal setup, vetting, and how to make the engagement work long-term.

Ukraine has been a go-to destination for software outsourcing for over a decade. What changed in recent years is the scale of the ecosystem and its proven resilience. Despite the ongoing war, 96% of client contracts have been maintained, and the industry continues to grow. If you are evaluating Ukraine as a hiring destination, the question is no longer “is it viable?” but rather “what is the smartest way to do it for my specific situation?”

Let us walk through that decision step by step.

Why Companies Hire Developers in Ukraine

A Deep Talent Pool with Strong Technical Foundations

Ukraine produces between 23,000 and 31,500 IT graduates annually, according to the IT Ukraine Association. Around 97% of working software engineers hold bachelor’s or master’s degrees in STEM fields, per research from N-iX and Grid Dynamics. The total IT workforce now stands at over 300,000 professionals, making Ukraine the largest tech talent pool in Eastern Europe after Poland.

The strength goes beyond numbers. Ukrainian universities have historically emphasized mathematics, algorithms, and computer science theory. This translates into developers who are strong problem-solvers, not just framework operators. The country consistently ranks among the top performers in international programming competitions, and its engineers are well-represented at companies like Google, Amazon, and Microsoft.

The most in-demand specializations include JavaScript/TypeScript (React, Angular, Node.js), Python, Java, C#/.NET, PHP, and a fast-growing AI/ML segment. According to Alcor’s 2026 market report, AI and machine learning vacancies in Ukraine jumped 115% in 2025, reflecting a global trend that is especially pronounced in the Ukrainian market.

Cost Efficiency Without Compromising Quality

The cost advantage of hiring in Ukraine is significant, but it is not just about cheap labor. It is about getting senior-level talent at a fraction of Western rates.

Here is how the numbers compare:

SeniorityUkraine (Annual)United States (Annual)Western Europe (Annual)
Junior$15,000 – $25,000$70,000 – $90,000$40,000 – $55,000
Mid-level$25,000 – $45,000$90,000 – $140,000$55,000 – $80,000
Senior$45,000 – $70,000$140,000 – $195,000$80,000 – $120,000

Sources: PayScale, Arc.dev, Glassdoor

For hourly engagements, Ukrainian developers typically charge between $25 and $80 per hour depending on seniority, technology stack, and the complexity of the project, according to Mobilunity. Compare that to $100-$200+ per hour for equivalent talent in the US.

The total cost of engagement extends beyond the developer’s salary, of course. If you work through an agency or a dedicated development team provider, you should factor in management overhead, infrastructure costs, and the partner’s margin. Even so, the all-in cost is typically 40-60% less than building the same team in the US or UK.

Timezone Alignment with Europe and Workday Overlap with the US

Ukraine operates in Eastern European Time (EET, UTC+2), which means:

  • Full overlap with most of Europe (1-2 hours offset from CET)
  • 5-7 hours ahead of US East Coast, giving you 3-4 hours of real-time collaboration during a standard workday
  • Comfortable overlap with UK business hours (2 hours ahead of GMT)

This makes Ukraine particularly well-suited for European companies that need real-time collaboration, and workable for US-based teams that can shift standups to the morning or adopt an async-first workflow.

Ukraine’s IT Market by the Numbers

A quick snapshot of the Ukrainian tech sector in 2025-2026:

  • $6.66 billion in IT services exports in 2025, up 3.3% from 2024 (IT Ukraine Association)
  • 300,000+ IT professionals in the workforce (Alcor)
  • 23,000-31,500 new IT graduates entering the market annually (IT Ukraine Association)
  • 97% of developers hold STEM bachelor’s or master’s degrees (N-iX)
  • 89% of IT specialists speak English at a professional level (Codebridge)
  • IT services now represent 43% of Ukraine’s total exports, making it the country’s single largest export category (Digital State Ukraine)

The three largest IT hubs are Kyiv (71,000+ developers), Lviv (20,000+), and Kharkiv, with growing clusters in Dnipro, Odesa, and Vinnytsia. Lviv, in western Ukraine, has become especially popular with international clients due to its proximity to the EU border, strong IT community, and relative stability.

What Ukrainian Developers Typically Cost

Average Salaries by Seniority

Salary expectations vary by technology stack, city, and whether the developer works as a full-time employee or a B2B contractor (the latter is more common in Ukraine’s IT market).

For the most common stacks (JavaScript, Python, Java, .NET, PHP):

  • Junior developers (0-2 years): $1,200 – $2,000/month
  • Mid-level developers (2-5 years): $2,000 – $3,500/month
  • Senior developers (5+ years): $3,500 – $5,500/month
  • Tech leads and architects: $5,500 – $8,000+/month

Specialized roles command premiums. DevOps engineers start at around $2,000/month for juniors and reach $4,400+/month at the senior level. AI/ML specialists, blockchain developers, and cybersecurity engineers sit at the top of the pay scale, often exceeding $6,000/month for senior talent. (Sources: Mobilunity, Qubit Labs)

Hourly Rates vs. Full-Time Costs

If you engage developers on an hourly basis through an agency, expect rates of:

  • Junior: $25 – $35/hour
  • Mid-level: $35 – $50/hour
  • Senior: $50 – $80/hour

These rates typically include the agency’s overhead and margin. For direct B2B contracts with individual developers, rates are lower, but you take on more management responsibility.

Total Cost of Engagement: Beyond the Salary

When budgeting, account for these additional costs:

  • Recruitment fees (if using a headhunter): typically 1-2 monthly salaries
  • Equipment and tools: $1,500 – $3,000 for initial setup (laptop, licenses)
  • Management overhead: if you hire directly, plan for 10-15% of your internal manager’s time
  • Partner margin: if working through a managed team provider, this is baked into the rate

The bottom line: even at the high end, a senior Ukrainian developer costs roughly what a mid-level developer costs in the US, with comparable or better technical output.

Three Hiring Models: Which One Fits Your Situation?

There is no single “right way” to hire in Ukraine. The best model depends on your team size, management capacity, timeline, and how much operational complexity you want to handle.

Direct B2B Contracts

How it works: You find and contract developers directly. They work as independent contractors (FOP, the Ukrainian equivalent of a sole proprietorship) and invoice you monthly.

Best for: Companies that already have technical leadership in-house, need 1-3 developers, and want maximum cost efficiency.

Advantages: Lowest cost per developer. Direct relationship. Full control over selection.

Challenges: You handle recruitment, onboarding, and day-to-day management. No local HR support. IP protection requires a well-drafted contract. If a developer leaves, you start from scratch.

Dedicated Development Teams

How it works: A local partner recruits and employs developers on your behalf. The team works exclusively on your project, but the partner handles HR, payroll, office space, equipment, and retention.

Best for: Companies scaling to 3-15+ developers who need a stable, long-term team without opening a legal entity in Ukraine.

Advantages: You control the work; the partner handles the operations. Easier to scale up or down. Built-in retention support. The team feels like yours because they work only on your product.

Challenges: Higher per-developer cost than direct B2B (the partner’s margin). You still need your own technical management.

This model is one of the most popular for mid-market companies and startups that need to build a development arm quickly. If this is the direction you are considering, a dedicated software development team setup through an experienced local partner can save months of trial and error.

Managed Teams Through a Technology Partner

How it works: A technology partner takes ownership of delivery, not just staffing. They provide the team, the technical leadership (often a tech lead or project manager), and accountability for outcomes.

Best for: Companies that need development capacity but lack internal technical leadership, or that want to outsource a specific project or product module entirely.

Advantages: Reduced management burden. The partner is accountable for delivery quality, not just headcount. Often includes QA, DevOps, and design as part of the package.

Challenges: Less direct control over individual team members. Success depends heavily on choosing the right partner.

If you do not have a CTO or VP of Engineering in-house, a managed team model with a technology consulting partner makes more sense than trying to manage remote developers yourself.

How to Choose

A simple decision framework:

FactorDirect B2BDedicated TeamManaged Team
Your team size need1-3 devs3-15+ devs3-10+ devs
In-house tech leadershipRequiredRequiredOptional
Time to first hire2-6 weeks2-4 weeks1-3 weeks
Operational burden on youHighMediumLow
Cost per developerLowestMediumHighest
ScalabilityLimitedHighMedium

Where to Find Ukrainian Developers

Platforms and Marketplaces

  • Clutch.co – The standard directory for vetted software development companies. Filter by technology, project size, and client reviews.
  • Arc.dev – Curated marketplace for pre-vetted remote developers, including a strong Ukrainian contingent.
  • LinkedIn – Direct sourcing works well. Ukrainian developers are active on LinkedIn, and many are open to outreach, especially for interesting technical challenges.
  • Upwork and Toptal – Useful for short-term or freelance engagements, though rates tend to be higher than direct sourcing.
  • DOU.ua – Ukraine’s largest tech community and job board. It is in Ukrainian, but it is where the local talent actually hangs out.

Local IT Communities and Clusters

Ukraine has strong regional IT clusters, particularly in Lviv, Kyiv, Kharkiv, and Dnipro. These clusters organize events, run job boards, and serve as community hubs. The Lviv IT Cluster alone represents over 30,000 specialists.

Engaging with these communities, whether through events, partnerships, or local hiring partners, gives you access to passive candidates who are not actively job-hunting on global platforms.

Working with a Local Partner

For most international companies, the fastest and lowest-risk path is partnering with a local technology company that already has recruitment infrastructure, employer branding, and a network in the Ukrainian market. This is especially true if you need to hire more than two or three people.

How to Evaluate and Vet Ukrainian Developers

Technical Assessment Best Practices

Standard technical interviews work the same way regardless of the candidate’s location. What matters more is calibrating your expectations:

  • Live coding sessions over Zoom or Google Meet work well. Ukrainian developers are accustomed to remote interviews.
  • Take-home assignments (2-4 hours max) are effective for evaluating real-world problem-solving ability.
  • System design interviews are essential for senior hires. Expect strong performance here; Ukrainian engineers are trained in computer science fundamentals.
  • Code review exercises reveal how a developer thinks about maintainability, testing, and collaboration.

Avoid relying solely on algorithmic puzzle interviews. They test a narrow skill set and tend to disadvantage strong practical engineers.

Communication and Cultural Fit

Communication quality is rarely a problem at the senior level. About 89% of Ukrainian IT professionals speak English at a professional level, and the percentage is even higher among senior developers who have worked with international clients.

That said, communication style can differ:

  • Ukrainian developers tend to be direct and factual in their communication. Do not mistake brevity for disengagement.
  • They generally will not push back loudly on a bad technical decision unless you explicitly create a culture where that is expected. Set the expectation early that you want honest feedback.
  • Written communication (Slack, email) is often stronger than verbal for developers who are fluent but not native English speakers. Build your workflow around async-first communication.

Red Flags to Watch For

  • A developer or agency that cannot provide references from international clients
  • Rates that seem too low (below $20/hour for senior work), which often signal misrepresented seniority
  • Reluctance to do a paid trial period or technical assessment
  • Vague answers about team composition (some agencies rotate developers across multiple clients)
  • No clear IP assignment clause in the contract

Legal and Compliance Considerations

Contract Structures

The most common arrangement for hiring Ukrainian developers is a B2B contract (contractor agreement). Under Ukraine’s simplified tax system, individual IT professionals register as FOPs (sole proprietors) and pay a flat 5% income tax. This is the standard structure for the industry and is fully legal.

For companies that need formal employment relationships (for compliance, IP, or policy reasons), two options exist:

  • Employer of Record (EOR): A third-party provider like Remote, Deel, or a local EOR becomes the legal employer in Ukraine, handling payroll, taxes, and benefits. You manage the work; they handle the paperwork. This is the fastest way to hire compliantly without opening a Ukrainian entity.
  • Own legal entity: Registering a representative office or LLC in Ukraine. This makes sense only if you plan to hire 20+ people and want full operational control.

IP Protection and NDAs

Intellectual property assignment must be explicitly documented in your contract. Under Ukrainian law, the creator of a work holds the copyright unless there is a written agreement transferring those rights. A properly drafted contractor agreement should include:

  • Full assignment of all IP created during the engagement
  • Work-for-hire provisions
  • Non-disclosure obligations
  • Non-compete clauses (enforceable to a reasonable extent)

If you are working through an agency or team extension partner, they should handle IP assignment as part of their standard contract. Always verify this.

GDPR and Data Compliance

If your business processes EU citizen data, GDPR compliance applies regardless of where your developers are located. Key considerations:

  • Sign a Data Processing Agreement (DPA) with any Ukrainian contractor or partner who will access personal data
  • Ensure adequate security measures (encrypted communications, access controls, VPN)
  • Ukraine is not currently on the EU’s adequacy list, so you will need Standard Contractual Clauses (SCCs) for data transfers

Most established Ukrainian IT companies are already GDPR-aware and can demonstrate compliance infrastructure. Ask about their data protection policies during due diligence.

Tax Implications

For US and UK companies, payments to Ukrainian B2B contractors are generally straightforward. Ukraine has double taxation treaties with most major economies. Key points:

  • No withholding tax on payments for services rendered by Ukrainian FOPs (in most cases)
  • VAT does not apply to software development services exported from Ukraine
  • Consult a tax advisor familiar with international contractor arrangements to confirm your specific obligations

Working with Ukrainian Developers During Wartime

This is the question every prospective client asks: “Is it safe to rely on a Ukrainian development team right now?”

The data says yes, with appropriate planning.

Infrastructure Resilience

The Ukrainian IT industry has invested heavily in business continuity since 2022. According to Digital State Ukraine, 96% of client contracts have been maintained throughout the conflict.

How? Multiple layers of redundancy:

  • Starlink satellite internet is now standard in most IT offices and many developer homes, providing backup connectivity when grid-based internet fails. By late 2023, Ukraine had over 47,000 active Starlink terminals, according to CircleID.
  • Backup power (generators, battery systems, Powerwalls) is standard for IT companies and increasingly common for individual developers
  • Distributed team structures with team members spread across multiple cities and some working from EU countries (Poland, Portugal, and others)
  • Kyivstar’s Starlink Direct-to-Cell service, launched in 2025, ensures mobile connectivity even during infrastructure attacks (United24 Media)

What This Means for You

In practice, most international clients report minimal disruption. Teams have adapted their workflows:

  • Flexible schedules that shift around air raid alerts
  • Async-first communication to accommodate unpredictable interruptions
  • Cross-trained team members who can cover for each other
  • Regular backup of all work to cloud repositories

The wartime period has, paradoxically, made Ukrainian IT teams more resilient and better at remote work than many of their global peers. The teams that survived and thrived through 2022-2025 are battle-tested in a very literal sense.

That said, risk mitigation is still wise. If you are building a team in Ukraine, consider:

  • Distributing critical knowledge across multiple team members
  • Having at least one team member outside Ukraine as a continuity measure
  • Building generous buffer time into project timelines for the first few months
  • Choosing a partner with a documented BCP (Business Continuity Plan)

How to Set Your Ukrainian Development Team Up for Success

Hiring is only half the equation. The difference between a great outcome and a mediocre one comes down to how you integrate and manage the team.

Onboarding with Intention

Treat Ukrainian developers exactly like you would treat any remote team member:

  • Provide thorough documentation of your codebase, architecture, and coding standards
  • Schedule dedicated onboarding time (at least one week of structured ramp-up)
  • Assign a buddy or mentor from your existing team
  • Set clear expectations about communication norms, meeting cadence, and escalation paths

Do not skip this step just because you are paying an hourly rate. Underinvesting in onboarding is the number one reason remote engagements underperform.

Communication Cadence

A reliable communication rhythm matters more than constant availability:

  • Daily standups (15 minutes, async or sync) to stay aligned
  • Weekly demos to maintain visibility into progress
  • Bi-weekly retrospectives to surface issues before they compound
  • Shared Slack/Teams channels for real-time questions throughout the day

Tools that work well: Slack, Jira, Confluence, GitHub/GitLab, Loom (for async video updates). Ukrainian developers are proficient with all major collaboration tools.

Retention Strategies

Developer turnover in Ukraine’s IT market runs around 15-20% annually, which is comparable to global averages. To retain your best people:

  • Pay at or above market rates (check DOU.ua salary surveys annually)
  • Offer professional development opportunities (conferences, courses, certifications)
  • Give developers ownership of meaningful technical decisions
  • Treat them as team members, not interchangeable resources
  • If working through a partner, ensure they have solid retention programs (career growth paths, team events, performance reviews)

Frequently Asked Questions

Is it safe to outsource software development to Ukraine in 2026?

Yes. Ukraine’s IT sector has maintained 96% of its client contracts throughout the full-scale war. Companies have invested in Starlink connectivity, backup power, distributed teams, and formal business continuity plans. The industry exported $6.66 billion in services in 2025, demonstrating continued reliability. Risk mitigation through team distribution and documented BCPs is recommended.

How much does it cost to hire a senior developer in Ukraine?

A senior developer in Ukraine typically earns $3,500 to $5,500 per month as a B2B contractor, or $45,000 to $70,000 annually. Through an agency, hourly rates for senior talent range from $50 to $80. This is approximately 50-65% less than equivalent talent in the US, where senior developers earn $140,000 to $195,000 annually.

What is the best way to hire developers in Ukraine?

It depends on your scale and management capacity. For 1-3 developers with strong in-house tech leadership, direct B2B contracts offer the best cost efficiency. For 3-15+ developers, a dedicated team model through a local partner handles recruitment, HR, and retention while you maintain technical control. For companies without internal technical leadership, a managed team model provides both talent and delivery oversight.

Do Ukrainian developers speak English well enough for daily collaboration?

Yes. Approximately 89% of Ukrainian IT professionals speak English at a professional level, and the rate is higher among senior developers with international experience. Written English is typically strong. For daily collaboration via Slack, code reviews, and documentation, communication is rarely an issue. Video calls and presentations may require more patience with developers who are fluent readers and writers but less practiced speakers.

What timezone do Ukrainian developers work in?

Ukraine uses Eastern European Time (EET, UTC+2; UTC+3 during summer). This provides full overlap with European business hours (1-2 hours offset from Central European Time) and 3-4 hours of overlap with US East Coast working hours. Many Ukrainian developers are flexible with schedules and willing to adjust for key meetings or standups.

Key Takeaways

Ukraine remains one of the strongest destinations for hiring remote development talent in 2026. The combination of 300,000+ skilled professionals, strong STEM education, competitive rates, and proven wartime resilience makes it a compelling choice for companies of all sizes.

The key to success is not just finding good developers. It is choosing the right hiring model for your situation, investing in proper onboarding, and treating your Ukrainian team as genuine collaborators rather than a cost-saving measure.

If you are exploring the option of building a development team in Ukraine, we are happy to share what we have learned from operating in this market. Reach out to discuss your specific needs.

Sources

Is AI Replacing Outsourcing? No, But It’s Raising the Bar

AI is not replacing software outsourcing. It is fundamentally changing what good outsourcing looks like. Companies that still treat outsourcing as a way to get cheaper code are about to discover that the real value has shifted: the best outsourcing partners now deliver leaner, AI-augmented teams that ship faster, catch bugs earlier, and operate with a level of technical fluency that raw headcount never could.

This shift is already measurable. The global software development outsourcing market is projected to reach $618 billion in 2026 and nearly $977 billion by 2031, according to Accelerance’s 2026 Global Software Development Rates report. But the nature of that spending is changing. What companies are buying is no longer labor arbitrage. It is outcomes, speed, and AI-native capability.

Here is what this shift means for decision-makers evaluating outsourcing partners right now.

From Cost Arbitrage to AI-Augmented Delivery

For two decades, the outsourcing pitch was simple: your developers cost $150 an hour, ours cost $40. That math still works, but it is no longer the main reason companies outsource.

According to PwC’s 2025 AI Agent Survey, 79% of organizations now report some level of agentic AI adoption, and 66% of those say AI agents are already delivering measurable productivity value. When a four-person team augmented by AI can produce what a ten-person team did two years ago, the conversation shifts from “how many developers do I need?” to “how effectively does this team use AI?”

McKinsey’s research on AI in software engineering puts the productivity impact at 20 to 45 percent of current annual spending on development functions. Organizations with near-universal developer AI adoption report gains exceeding 100%, according to McKinsey and Jellyfish’s joint research. The gap between AI-native teams and traditional teams is growing every quarter.

This does not mean outsourcing is shrinking. It means the evaluation criteria have changed. Companies building custom software need partners who understand this shift.

The Numbers Behind the Shift

The data tells a clear story. Gartner predicts that 40% of enterprise applications will include task-specific AI agents by the end of 2026, up from less than 5% in 2025. That is an eightfold jump in a single year. The agentic AI market itself is projected to grow from $5.25 billion in 2024 to $199 billion by 2034, a compound annual growth rate of roughly 44%, according to market analysis by Landbase.

For companies choosing outsourcing partners, this means asking a new set of questions. Not “do you use AI tools?” but “how deeply is AI embedded in your delivery workflow, and what measurable impact has it had?”

How Is Agentic AI Changing Outsourced Teams?

The biggest shift in 2026 is not that developers use AI copilots. That was 2024. The real change is the rise of agentic AI: autonomous systems that can reason, plan, and execute multi-step workflows across the entire software development lifecycle.

Unlike basic code completion tools, agentic AI systems can autonomously handle documentation generation, unit test creation, initial code refactoring, and even root-cause analysis during debugging. A 2025 pilot by Meta AI showed that pairing engineers with agentic debugging assistants led to a 4x acceleration in identifying and resolving bugs.

What Agentic AI Actually Looks Like in Practice

In a modern outsourced team, agentic AI changes daily workflows in concrete ways:

Project managers use AI-driven tools that track productivity metrics in real time, flag scope creep before it becomes a problem, and auto-generate status reports from commit history and ticket data.

Developers still write architecture decisions and complex business logic by hand. But boilerplate code, repetitive patterns, and standard CRUD operations are increasingly generated and reviewed by AI agents. The developer’s role shifts toward orchestration, code review, and system design.

QA engineers deploy automated agents that simulate thousands of concurrent users, generate edge-case test scenarios, and run regression suites continuously. Manual QA cycles that used to take weeks now happen in hours.

The result is not fewer people. It is different people doing different work. According to PwC, 67% of executives say AI agents will drastically transform existing roles within the next 12 months, and 48% say they will likely increase headcount because of the change AI agents bring.

What Should You Demand from an Outsourcing Partner in 2026?

If AI is the new baseline, what should you look for when evaluating an outsourcing partner in 2026? The criteria have shifted, and many companies have not caught up.

AI Fluency Over AI Buzzwords

Every outsourcing company now claims to “use AI.” The real question is whether AI is embedded in how they actually deliver, or whether it is a marketing checkbox.

Ask specific questions: What percentage of your developers actively use AI tools daily? How has your average delivery velocity changed in the past 12 months? What AI governance practices do you follow? Can you show before-and-after metrics from AI adoption on actual projects?

Partners worth hiring can answer these questions with data, not slogans.

Leaner Teams, Higher Output

The old outsourcing model sold headcount. The new model sells outcomes. With AI augmentation, a well-structured team of five can outperform a traditional team of twelve on many project types.

This means outsourcing partners should be transparent about team composition. How many people are on the team, what does each person do, and how does AI fit into the workflow? If a partner is pitching a team of fifteen for a project that could be delivered by seven with AI tooling, that is a signal worth examining.

According to the U.S. Bureau of Labor Statistics, demand for software developers is projected to grow 15% from 2024 to 2034. The talent shortage is real. But the answer is not just hiring more people. It is hiring the right people and equipping them with the right AI tools.

Security and Governance Built In

AI introduces new risk vectors. Code generated by AI can contain subtle vulnerabilities. Data pipelines that feed AI models may process sensitive information. Automated agents can make decisions that trigger compliance issues if they are not properly governed.

According to PwC, 60% of businesses do not fully trust AI agents to perform tasks autonomously, and 28% rank lack of trust as a top-three challenge. Your outsourcing partner should have clear policies on AI governance: what gets reviewed by humans, what data AI tools can access, how generated code is validated for security, and how AI-related decisions are documented.

This is not optional. It is table stakes.

What New Roles and Skills Does AI Create in Outsourcing?

AI is creating roles that did not exist two years ago. Prompt engineers, LLM integration specialists, AI governance leads, and autonomous system auditors are becoming standard positions in forward-thinking outsourcing teams.

Gartner’s five-stage model of enterprise AI evolution, outlined in their August 2025 analysis, projects that by 2029, at least half of knowledge workers will be expected to create, govern, and deploy AI agents on demand. The shift from “using AI tools” to “orchestrating AI systems” is happening faster than most organizations anticipated.

For outsourcing buyers, this means evaluating not just current capabilities but learning velocity. Is the partner investing in AI training? Are they creating new roles to match the new reality? Do they have a clear roadmap for how their delivery model will evolve over the next 18 months? A fractional CTO or AI advisor can help you evaluate these signals objectively.

The partners that cannot answer these questions are the ones whose value proposition is eroding.

Frequently Asked Questions

Is AI replacing software outsourcing?

No. AI is changing what outsourcing delivers and how teams operate, but the core need for external technology partnerships remains strong. The global outsourcing market continues to grow. What is changing is the nature of the work: companies now outsource for AI-native capability and speed, not just labor cost savings.

How does agentic AI change outsourced development?

Agentic AI introduces autonomous systems that handle multi-step development tasks like documentation, testing, refactoring, and debugging. This shifts developers toward higher-value work like architecture decisions, system design, and AI orchestration. Teams become leaner but more productive, with Gartner predicting 40% of enterprise apps will integrate task-specific AI agents by end of 2026.

What should I look for in an AI-ready outsourcing partner?

Look for partners who can demonstrate measurable AI adoption metrics, not just marketing claims. Key indicators include: daily AI tool usage rates among developers, before-and-after delivery velocity data, clear AI governance policies, and investment in new AI-specific roles. The ability to articulate how AI changes their actual delivery workflow is the strongest signal.

Will outsourcing costs go down because of AI?

It depends. Per-hour rates may not drop significantly, but cost-per-outcome should improve. AI-augmented teams deliver more value per person, which means smaller teams can tackle larger projects. The real savings come from faster delivery, fewer defects, and avoiding costly rework. McKinsey estimates AI can reduce software engineering spending by 20 to 45 percent through productivity gains.

How do I assess if an outsourcing partner is genuinely AI-capable versus just using buzzwords?

Ask for specifics. Request metrics on how AI tools have changed their delivery timeline on recent projects. Ask what AI governance framework they use. Ask what happens when AI-generated code fails security review. Genuine AI maturity shows in processes and data, not in pitch decks.

The Bottom Line

AI is not the end of software outsourcing. It is the beginning of a much more demanding version of it. The bar for what constitutes a good outsourcing partner has risen, and it will keep rising as agentic AI matures and becomes the default way software gets built.

The companies that will get the most from outsourcing in 2026 and beyond are those that stop buying headcount and start buying capability. That means partners who are not just aware of AI but are building their delivery models around it.

If you are evaluating outsourcing partners or rethinking your current setup, we can help you assess what an AI-augmented team should look like for your specific needs. Explore our AI consulting services or learn how our dedicated development teams integrate AI into every phase of delivery.

  1. Accelerance – 2026 Global Software Development Rates & Trends
  2. PwC – AI Agent Survey 2025
  3. McKinsey – The Economic Potential of Generative AI
  4. McKinsey – Measuring AI in Software Development (Jellyfish)
  5. Gartner – 40% of Enterprise Apps Will Feature AI Agents by 2026
  6. Landbase – Agentic AI Statistics 2026
  7. U.S. Bureau of Labor Statistics – Software Developers Outlook

Managed Delivery vs Team Extension

Most teams still argue “outsourcing vs outstaffing.” In 2026, that framing is… not very useful.

The real decision is your operating model:

  • Managed Delivery: you delegate outcomes, your partner owns execution.
  • Team Extension: you extend your team with embedded specialists, you own delivery.
  • Hybrid: the default choice for teams protecting core IP while scaling capacity.

This guide summarizes what current research implies about each model, what the real risks look like in 2026 (especially with AI-assisted development), and how to pick a model without accidentally losing control.

  • Pick Managed Delivery when you want a partner to own a defined outcome and you can enforce transparency.
  • Pick Team Extension when you want embedded engineers and you can lead delivery well.
  • Pick Hybrid when your core product needs long-term ownership, but you still need speed on contained initiatives.

If you cannot clearly answer “who owns delivery?”, you’re not choosing a model. You’re improvising.

Why the labels matter less than ownership

“Outsourcing” and “outstaffing” are loaded terms. They often imply price-first decisions and low ownership standards, even when the work is high-quality.

If you’re scaling a product organization, the board-level concern is not the label. It’s:

  • Who owns delivery outcomes?
  • How do we measure performance?
  • How do we prevent knowledge loss and dependency?
  • How do we keep speed from turning into invisible debt?

The most mature teams define their model through ownership and governance, not staffing vocabulary.

The reality in 2026: distributed work is normal, and hiring is still hard

Remote and hybrid work are not exceptions anymore. Stack Overflow’s 2024 Developer Survey reports 42% hybrid and 20% in-person (with the remainder remote).

At the same time, hiring remains constrained. ManpowerGroup’s 2024 Talent Shortage results show roughly three out of four employers reporting difficulty filling roles (commonly reported around 74–75% depending on regional summaries).

So the decision is not “should we work with external teams?” Most companies already do. The decision is which model protects product ownership while increasing delivery capacity.

Model 1: Managed Delivery (delegate outcomes)

Definition: You assign a product area or project outcome to a partner. The partner provides the cross-functional team and delivery leadership (planning, execution, reporting). You define the goal, constraints, and success metrics.

When it works best

Managed Delivery is a strong fit when:

  • you need speed with clear accountability for a defined scope
  • your internal leaders are bandwidth-constrained
  • you want a partner to own execution end-to-end (including delivery management)

The 2026 risk: opacity (and expensive surprises)

In Managed Delivery, risk rises when delivery happens inside a “black box” and you cannot answer basic questions later:

  • Why was this architectural decision made?
  • What AI tools were used, and under what controls?
  • Can we maintain and extend this without the original team?
  • If we switch partners (or bring it in-house), how painful is it?

This is why Managed Delivery should be treated like an operating model, not a purchasing decision.

What “good” looks like (non-negotiables)

If you choose Managed Delivery, require:

  • a shared backlog with clear acceptance criteria
  • decision records for architecture and tradeoffs (short and consistent)
  • measurable delivery outcomes (not “hours burned”)
  • an explicit AI usage policy and mandatory human review
  • a clean handover plan from day one (docs, runbooks, ownership map)

Model 2: Team Extension (embedded capability)

Definition: Engineers join your team and work inside your processes. Your engineering leadership owns delivery. The partner supports hiring, onboarding, continuity, and retention.

When it works best

Team Extension is a strong fit when:

  • the work is core IP or tightly coupled to your product roadmap
  • you expect frequent reprioritization
  • you already have (or are willing to build) a stable delivery operating system

The 2026 risk: management overhead (and “more people, same velocity”)

Team Extension amplifies your internal reality.

If planning, decision-making, and documentation are weak, adding engineers increases coordination cost and delivery noise. If your delivery system is solid, Team Extension is one of the cleanest ways to scale without losing ownership.

What “good” looks like

  • a real onboarding path (environment, domain, conventions, first-week tasks)
  • clear ownership boundaries (services, modules, decision rights)
  • effective technical leadership (reviews, architecture direction, coaching)
  • disciplined rituals (planning, release practices, retros that lead to change)

What high-performing teams measure (because headcount is not a strategy)

High-performing engineering organizations use outcome metrics, not activity metrics.

DORA popularized four measures of software delivery performance:

  • deployment frequency
  • lead time for changes
  • change failure rate
  • time to restore service

These metrics matter because they shift the conversation from “how many people” to “how well does the system deliver.”

Implication for operating models:

  • If you choose Managed Delivery, require reporting aligned to these outcomes (or equivalent) per product area.
  • If you choose Team Extension, ensure your internal delivery system can produce and improve them.

AI changes the risk profile (and the opportunity)

AI-assisted development is mainstream, and it genuinely improves throughput in many contexts. Microsoft Research reported a controlled experiment where developers with GitHub Copilot completed a coding task 55.8% faster than the control group.

But: productivity is not the same as maintainability, reliability, or quality.

In 2026, mature teams treat AI as part of the engineering system:

  • what tools are allowed
  • what data is prohibited
  • what requires human review
  • what needs traceability (especially for sensitive changes)

Implication for operating models:

  • In Managed Delivery, AI governance must be explicit, otherwise you risk inheriting untraceable decisions and hidden debt.
  • In Team Extension, internal standards matter, otherwise speed becomes chaos in nicer packaging.

Security (keep it simple): ask for ISO 27001 or similar, and check the scope

You don’t need a frameworks lecture. You do need basic due diligence.

A practical starting point: ask whether the partner is certified to ISO/IEC 27001 (or an equivalent assurance report like SOC 2 Type II) and what the certification or report scope covers. ISO/IEC 27001 is a widely used standard for an information security management system (ISMS) and promotes a holistic approach across people, policies, and technology. 

Then confirm a few basics in plain language:

  • where your code and data live (and who can access them)
  • how secrets are handled
  • incident response expectations
  • rules for AI tool usage with client code and data

This is not about bureaucracy. It’s about avoiding preventable surprises.

Strategic comparison: who owns what?

AreaManaged Delivery (Outcome Ownership)Team Extension (Embedded Capability)
Delivery OwnershipPartnerYour Engineering Leadership
Planning & ExecutionPartnerYou
Quality SystemPartner-led (must be specified)You-led (must exist internally)
TransparencyMedium (requires governance)High (if processes are mature)
Best ForDefined scope, speed, accountable executionCore product work, frequent pivots
Typical Failure Mode“Black box” dependencyInternal chaos amplified

The 2026 pattern: hybrid is the default for mature orgs

The strongest organizations rarely pick one model everywhere. They use hybrid intentionally:

  1. Team Extension for the core
  • architecture and platform foundations
  • core product logic and long-term maintainability
  • areas where knowledge compounding matters
  1. Managed Delivery for contained outcomes
  • time-bound initiatives
  • integrations, migrations, internal tools
  • defined product modules with clear acceptance criteria and governance

Hybrid reduces risk and increases focus. It also makes the org resilient when priorities change mid-quarter (because they always do).

Choosing the right model: 6 questions that cut through noise

  1. Is this work part of our competitive advantage? If yes, prefer Team Extension or hybrid where your team owns the core.
  2. How often will we pivot? Frequent pivots favor Team Extension. Managed Delivery works best when outcomes are stable.
  3. Do we have delivery leadership bandwidth? If your leads are saturated, Team Extension may slow you down. Managed Delivery can protect focus if governance is strong.
  4. What level of transparency do we need? If this touches core architecture, regulated data, or enterprise buyers, define transparency requirements upfront.
  5. How will we measure success? Agree on outcome metrics (defect escape rate, incident rate, customer impact).
  6. How will we reduce long-term dependency? Require documentation ownership, decision logs, clean handover, and continuity planning from day one.

Bottom line

In 2026, do not ask “Outsourcing or Outstaffing?”

Ask: Do we want to delegate outcomes, or do we want to extend our own delivery system?

Choose the model that matches your internal maturity, your appetite for delivery ownership, and the risk profile of what you’re building.

unicrew Earns a Spot on TechReviewer’s Top 20 Software Developers List for 2025

unicrew is a technology consulting and custom software development company that has proved its worth by delivering top-notch solutions to clients and providing them with flexibility and support.

Extensive experience in delivering full-cycle software development services, along with deep technology expertise, enabled the company to be listed among the leading web and mobile companies according to prominent online directories and research agencies.

Now there is another accomplishment: unicrew has been featured by a trustworthy analytics company, TechReviewer.co, as a leading Software Development Company in 2025.

We are honored to be recognized as one of the best software development companies worldwide. We will continue to justify the confidence placed in us by TechReviewer, our clients, and partners.

We believe we will reach new heights, expand our technology expertise, and gain more winning awards in custom software development, mobile, and web app development.

AI for Businesses: Common Biases and Their Refutations

Artificial Intelligence (AI) has emerged not just as a buzzword but as a pivotal force reshaping how companies operate, compete, and innovate. AI is increasingly at the forefront of business strategies, driving efficiencies and enabling new capabilities across industries. From small startups to global conglomerates, AI technologies are integral to solving complex problems, enhancing decision-making, and creating personalized customer experiences.

The transformative impact of AI on business is evident in the numbers. According to a report by PwC, AI could contribute up to $15.7 trillion to the global economy by 2030, with $6.6 trillion likely coming from increased productivity and $9.1 trillion from consumption-side effects. This staggering potential makes AI an optional tool and a fundamental asset in the modern business toolkit.

Read our blog on how AI is reshaping industries and how your business can harness its full potential responsibly and effectively.

Debunking Common Business Biases about AI (with Facts and Examples)

Let’s delve deeper into the common biases surrounding AI in business, exploring real-world examples and statistics to provide a clearer understanding of the reality of AI implementation.

Bias 1: AI Can Completely Replace Human Decision-Making

“Well, AI is on the edge, but I’m not sure it is worth implementing in my company. I prefer to leave the decision-making process on the human side,” said the CEO of The Best World Company. Artificial intelligence (AI) is rapidly transforming our world, and its impact on decision-making is undeniable. But will AI leave us entirely out of the loop and make all our choices?

The answer is a resounding no

While AI excels in data processing and pattern recognition, it lacks the human-like consciousness or emotional intelligence necessary for many decision-making processes. For instance, IBM Watson has assisted in crafting cancer treatment plans by analyzing vast medical data. Yet, the final decisions always involve human doctors’ assessments to consider ethical nuances beyond AI’s current grasp. This example underscores that AI is intended to augment, not replace, human decision-making.

Here’s why AI is more of a teammate than a takeover artist:

  • Data Deluge, Common Sense Drought: AI excels at crunching massive datasets but falls short on common sense reasoning. Imagine an AI tasked with traffic flow optimization. While it can analyze historical patterns and road closures, it might not understand the intuitive idea of letting an ambulance pass through a red light.
  • Ethical Echo Chambers: AI algorithms are only as good as the data they’re trained on. Biased data leads to biased decisions. A study by ProPublica found that an AI tool used in criminal justice risk assessment systematically misjudged Black defendants, perpetuating real-world inequalities.
  • Creativity Can’t Be Cracked (Yet): Human ingenuity reigns supreme when generating new ideas and approaches. AI can sift through mountains of data to find patterns that inform creative solutions but can’t replace that spark of originality.
  • The Buck Stops With Us: Ultimately, humans should be responsible for decisions, especially those with significant consequences. AI can be a powerful tool for providing insights and recommendations, but the final call should remain with people who can consider ethical implications and the broader context.

The future belongs to a powerful collaboration between humans and artificial intelligence. AI can augment our decision-making by:

  • Identifying hidden patterns in complex data sets
  • Automating repetitive tasks, freeing up human time for analysis and innovation
  • Providing real-time insights and recommendations

Bias 2: AI Implementation Is Always Costly and Complex

“What, AI? Oh no, we’re already over our annual budget! It’s damn expensive!” – a common concern of the average CFO. Artificial intelligence (AI) has become synonymous with tech giants and million-dollar budgets. But what if we told you that AI solutions are becoming increasingly accessible and affordable, even for small and medium-sized enterprises (SMEs)?

The High Cost of Complexity… Debunked!

Traditionally, AI implementation has been a complex undertaking requiring specialized teams and hefty upfront costs. Here’s why that perception is outdated:

  • Pre-built Solutions for Common Needs: Gone are the days of custom-building everything from scratch. Today, there’s a thriving marketplace of pre-built AI solutions designed for specific tasks like customer service chatbots, data analysis, and even marketing automation. These solutions are tailored for SMEs, often with pay-as-you-go pricing models, making them highly cost-effective.
  • Cloud-Based Deployment: Forget the need for expensive on-premise servers. Cloud-based AI platforms offer ready-to-use infrastructure with the processing power needed to run AI models. It eliminates the upfront costs of hardware and IT maintenance, making AI accessible to businesses of all sizes.
  • The Democratization of Data: Data is the fuel for AI, but collecting and managing it was a significant hurdle. Now, cloud storage solutions offer secure and scalable data storage at competitive rates. Many AI platforms offer built-in data tools, simplifying business processes without a dedicated data science team.

Real-World Examples: Big Results, Small Price Tags

Here are some practical examples of how SMEs are leveraging AI to compete with the big boys:

  • E-commerce giant Shopify utilizes AI to personalize product recommendations for millions of online store owners. This AI solution doesn’t require coding knowledge and integrates seamlessly with their existing platform, proving that AI can be simple and user-friendly.
  • Small marketing agencies use AI-powered social media management tools to automate tasks like scheduling posts and analyzing audience engagement. It frees up valuable time and resources for developing creative strategies.

The Takeaway: AI is Your Ally

AI is no longer a luxury reserved for corporate giants. With the availability of pre-built solutions, cloud-based deployment, and increasingly accessible data storage, AI is becoming a powerful tool for SMEs to boost efficiency, gain valuable insights, and compete globally.

So, ditch the misconception that AI is out of reach. Explore the possibilities and see how AI can transform your business.

Bias 3: AI Is Only for Tech Companies

“We’re too old-schooled for AI and don’t even use those vaunted new technologies. Leave it for IT companies,” brushed off the founder of crafted cheese manufacturing. The idea that AI is just for tech companies is about as outdated as a rotary phone (and let’s face it, even rotary phones are getting smart with AI-powered spam filters!). AI is revolutionizing industries far beyond the realm of computers and software, with real-world impacts we can see every day. Here’s a glimpse:

  • E-commerce Chatbots: Faster Cheese Discovery: A study by Drift found that businesses using chatbots see a 70% improvement in customer satisfaction through faster response times and 24/7 availability. Imagine a cheese lover in a hurry; an AI chatbot can recommend cheeses based on their taste preferences in minutes, leading to a more enjoyable shopping experience.
  • AI on the Auto Service Fast Track: According to a McKinsey report, AI-powered appointment scheduling can increase efficiency in service industries by up to 20%. It translates to less time spent on hold and quicker car maintenance. AI can analyze attendee data to suggest optimal conference scheduling in the event industry, leading to smoother event experiences.
  • Precision Farming with a Digital Touch: A Forbes article highlights that AI-powered solutions in agriculture can increase crop yields by 5-10% while reducing water usage by 15%. These solutions benefit cheesemakers by providing a consistent supply of high-quality milk and promoting sustainable farming practices that are good for the environment.

The next time someone dismisses AI as a tech fad, remind them that AI is transforming the world around them, from cheese manufacturing to how we get our cars serviced. AI is here to stay, improving our lives in surprising and impactful ways.

Bias 4: AI Compromises Security and Increases Risk of Data Leaks

“Do you really want the ChatGPT to grab our data and train new models with it? Or share it with our competitors?” asks the security director sternly. To alleviate concerns about AI posing a threat to security and increasing the probability of data breaches, it is crucial to consider the data and strategies presented by PwC. They showcase how AI can improve, rather than weaken, security protocols.

  1. Increased Data Breaches and Investment in Cybersecurity: The PwC 2024 Global Digital Trust Insights survey indicates that the number of businesses experiencing data breaches over US$1M has risen from 27% to 36% year over year. This surge has spurred an increase in investments in cybersecurity, particularly among companies utilizing Generative AI. These companies report fewer instances of costly cyber breaches when they show greater maturity in their cybersecurity initiatives​​.
  2. Generative AI and Cyber Threats: There is a notable concern among business and tech leaders about the potential for Generative AI to facilitate cyber attacks. Approximately 52% of surveyed leaders anticipate that Generative AI could lead to catastrophic cyber attacks within the next 12 months. However, the same leaders also acknowledge the potential of Generative AI to enhance organizational productivity and develop new business lines within three years​​.
  3. Implementation of Leading Cyber Practices: PwC identifies organizations that consistently implement leading cyber practices—”Stewards of Digital Trust”—and finds that these organizations are more likely to have experienced less costly cyber breaches. Only 29% of these stewards experienced a $1M+ breach compared to 36% of organizations. Moreover, these organizations are more likely to report that the most damaging cyber breach cost them less than $100K​​.
  4. Responsible AI: To mitigate risks associated with AI, PwC advocates for adopting “Responsible AI” frameworks that guide the trusted and ethical use of AI. This approach emphasizes human supervision and intervention and requires organizations to consider additional areas such as data risks, model and bias risks, prompt or input risks, and user risks​.
  5. AI in Risk Management: AI and data analytics significantly enhance risk management by providing deep insights and improving compliance across business networks. This capability is a game-changer in navigating a rapidly changing risk and regulatory landscape, thereby increasing effectiveness, reducing costs, and building trust​​.

These insights from PwC illustrate AI’s security and data protection challenges and the significant opportunities for enhancing these areas through strategic implementation and responsible management of AI technologies.

Bias 5: AI Implementation Requires Strong Technical In-House Expertise

“AI is cool; I like it. But who will be in charge of implementing it, given that we are a small business and have no budget for hiring expensive AI professionals?” – Reasons the HR manager of a small local company.

Let’s face it: AI can sound intimidating. Especially for small businesses, the fear of needing a team of expensive specialists to implement it can be a significant roadblock. But what if I told you that’s not the case? Here’s a reality check with some numbers to back it up:

  • 63% of small and medium businesses (SMBs) report already using AI (Source: SMB Group).
  • AI adoption is rising, with a projected market value exceeding $1.5 trillion by 2030 (Source: Gartner).

It means that small businesses are increasingly recognizing the power of AI, and the good news is that they are succeeding without needing a team of tech wizards.

Why the Fear?

The perception of needing a massive in-house technical team for AI implementation is a common bias. However, the truth is the AI landscape has evolved significantly:

  • Scalable Solutions: Today, many ready-to-use AI solutions are built specifically for various business needs. These solutions require minimal technical expertise and often have user-friendly interfaces and pre-built workflows. Imagine using drag-and-drop features to set up an AI chatbot for your customer service or having an AI assistant automatically categorize your invoices – no coding required!
  • Training and Support: Gone are the days of needing an in-house AI guru. Many vendors offer comprehensive training programs and ongoing support to ensure businesses can leverage their AI solutions effectively. Think of it like learning a new software program – you don’t need a computer science degree, just a willingness to learn, and the vendor is there to guide you.

Real-World Applications and Success Stories

Businesses across industries leverage AI to improve decision-making, optimize operations, and enhance customer experiences. Let’s explore some success stories.

Snaplore: Transforming Knowledge Management with AI Power

Snaplore is a cutting-edge knowledge management solution enhanced by AI. It goes beyond typical speech-to-text features to provide a comprehensive array of intelligent functionalities that transform how users interact with digital content. The platform utilizes AI-driven note-taking to analyze video recordings, automatically organizing speech into relevant topics and paragraphs without manual effort. This integration of Whisper AI and ChatGPT allows for a more efficient and enriched content repository that is well-structured and easy to navigate.

Moreover, Snaplore features a bespoke AI assistant, Snaplore Bot, designed to participate in meetings actively. It records discussions and breaks them into easily understandable topics and summaries, simplifying knowledge management.

In essence, Snaplore represents a significant shift in knowledge management paradigms. It envisions a future where sharing knowledge is as effortless and efficient as having a conversation, powered by advanced AI technology.

Aetna Streamlines Medical Claims Processing with AI

Aetna, a major health insurance company, faced significant issues with manual claims processing, characterized by inefficiencies, delays, and errors. To overcome these challenges, Aetna turned to artificial intelligence, implementing an AI-powered system with machine learning algorithms. This advanced system is designed to automate several critical tasks, including data extraction, eligibility verification, and medical coding.

Introducing this AI system has led to substantial improvements in operational efficiency. Specifically, it has achieved a 20% reduction in claims processing time, enhancing overall productivity. Moreover, the automation has not only increased accuracy but also allowed Aetna’s human staff to redirect their focus toward handling more complex claims and improving customer service interactions.

A crucial aspect of Aetna’s implementation was its collaboration with an AI service provider, which helped ensure that the automated system adhered to strict standards for secure data handling and compliance with relevant regulations. This partnership underscores the importance of maintaining high security and regulatory standards in deploying AI technologies in sensitive sectors like health insurance.

Walmart & A new in-store AI  

Walmart’s internally developed AI technology enables employees to scan items such as bananas to assess their ripeness. The system then uses generative AI to provide recommendations through a digital dashboard on handling the product, thus removing the necessity for human judgment when informed advice is lacking.

According to RTS, the U.S. discards approximately 60 million tons of food annually, constituting around 40% of the nation’s food supply. This waste is the predominant contributor to U.S. landfills, making up about 22% of municipal solid waste.  “Utilizing our AI-powered waste management system helps reduce our environmental impact, conserves societal resources, and simultaneously lowers our operating costs,” said Sravana Karnati, senior vice president and chief technology officer for Walmart International Technology, Walmart Global Tech.

These examples showcase how AI is transforming businesses. By leveraging AI solutions from external providers, companies of all sizes, even those with limited technical expertise, can benefit from AI’s capabilities to make smarter decisions, streamline operations, and gain a competitive edge.

Bonus: Strategic Implementation of AI in Business (with Tips and Advice)

The strategic implementation of AI in business involves aligning AI technologies with organizational goals to drive efficiency and innovation. It is crucial to start with a clear understanding of the specific business challenges AI addresses and ensure a robust framework for measuring success. 

Evaluating AI Solutions

“When evaluating AI tools and services, businesses should focus on matching their specific needs with the offerings that are both cost-effective and integrate smoothly into their existing systems,” – said Oleksandr Trofimov, Chief Technology Officer at Unicrew. A comprehensive guide to assessing these solutions includes:

  1. Needs Assessment: Clearly define the problems the business aims to solve with AI and the expected outcomes.
  2. Vendor Evaluation: Analyze different AI vendors based on reliability, support, scalability, and compliance with industry standards.
  3. Cost-Benefit Analysis: Consider not only the initial cost but also the total cost of ownership, which includes maintenance, upgrades, and necessary training.
  4. Ease of Integration: Assess how well the AI solution can be integrated with current systems. Solutions that offer APIs and modular designs typically ensure easier integration.
  5. Trial and Pilot Testing: Conduct pilot tests with the AI solutions to evaluate performance and impact before full-scale deployment.

Integration Strategies

“Integrating AI into existing processes requires strategic planning to minimize disruption and avoid extensive initial investments in expert staffing,” – said Ihor Prudyvus, Engineering Director at Unicrew. Key strategies include:

  1. Incremental Integration: Deploy AI solutions in non-critical areas to assess their impact and refine processes before broader implementation.
  2. Use Cloud-Based AI Services: Leverage cloud platforms to utilize AI capabilities without making a heavy upfront investment in infrastructure.
  3. Cross-Functional Teams: Create cross-functional teams that include AI experts and domain specialists to ensure the technology is applied effectively and meets business goals.
  4. Staff Training: Equip existing staff with the necessary skills to work alongside AI through workshops and ongoing training sessions.

Continuous Learning and Adaptation

“For a business to remain competitive using AI, it must emphasize continuous learning and adaptation in its strategy,” – said Ihor Prudyvus, Engineering Director at Unicrew. Important aspects include:

  1. Staying Updated on AI Trends: The team’s knowledge base should be regularly updated on the latest AI developments and technologies.
  2. Security Practices: Constantly improve security measures around AI deployments to protect data and systems from new vulnerabilities.
  3. Feedback Loops: Implement feedback mechanisms to learn from AI outcomes and refine solutions accordingly.
  4. Partnerships with AI Academia and Industry Leaders: Partner with universities and industry leaders to gain insights into cutting-edge AI research and applications.

Following these guidelines, businesses can strategically implement AI to enhance efficiency, innovate, and maintain a competitive edge in their respective markets.

Final Thoughts

It is crucial to adopt artificial intelligence with a balanced and thoughtful perspective. AI offers immense potential to enhance business operations, drive innovation, and streamline decision-making processes. However, its integration should be approached carefully, considering ethical implications, workforce impact, and long-term sustainability. Leaders who embrace AI thoughtfully can unlock significant benefits for their organizations, fostering an environment where technology and human expertise work together to achieve greater efficiency and success. Embracing AI is not just about leveraging new technology—it’s about leading with foresight and responsibility in the digital age.

If your business needs assistance in AI implementation, our AI team is ready to support you.

It is crucial to adopt artificial intelligence with a balanced and thoughtful perspective. AI offers immense potential to enhance business operations, drive innovation, and streamline decision-making processes. However, its integration should be approached carefully, considering ethical implications, workforce impact, and long-term sustainability. Leaders who embrace AI thoughtfully can unlock significant benefits for their organizations, fostering an environment where technology and human expertise work together to achieve greater efficiency and success. Embracing AI is not just about leveraging new technology—it’s about leading with foresight and responsibility in the digital age.

Why Transformation Efforts Fail: 11 Reasons and How to Finally Triumph

In an era marked by rapid technological advancements and shifting market dynamics, transformation is not just a strategic initiative but a survival imperative. Yet, McKinsey’s 2024 report indicates that only about 35% of transformation initiatives achieve their targeted goals. This staggering number underscores the need to dissect and understand the complexities of organizational change.

Understanding Transformation in 2024

Why is transformation, not just a strategic option but a necessity in 2024? The answer lies in the compelling evidence provided by recent studies and reports.

Revenue Growth and Competitive Edge

According to a 2024 report by Forbes, companies actively engaged in transformational strategies are expected to see a significant increase in their revenue growth – up to 30% more compared to their less agile counterparts. This projection highlights the direct correlation between effective transformation and financial performance, indicating that businesses that embrace change are more likely to achieve a competitive edge in their respective industries.

Employee Engagement and Customer Satisfaction

A 2024 study by Harvard Business Review presents another critical dimension of transformation – its impact on human resources and customer relations. The study suggests that 70% of businesses leading in adaptability and transformation also exhibit higher employee engagement and customer satisfaction levels. This trend underscores the holistic benefits of transformation that go beyond financial gains. By fostering a culture that values innovation, adaptability, and continuous learning, organizations not only enhance their operational efficiencies but also create a more motivated workforce and a loyal customer base.

Leading Change Why Transformation Efforts Fail: 11 Reasons

We will delve into 11 Reasons Transformation Efforts Fail to deepen our understanding further. This exploration will cover a range of factors, from technological advancements to organizational resilience.

why transformation efforts fail

The Challenge of Change (Reasons 1-3)

Change is an inevitable yet often daunting aspect of organizational growth. But why does it frequently encounter resistance despite being aimed at improvement? This resistance is not merely a defiance of new workflows but a deeper reluctance to alter ingrained mindsets and habits. Could this be stemming from an inherent fear of the unknown among employees? “Effective change management, therefore, must transcend beyond the mere communication of the ‘what’ and the ‘how’ of change; it must compellingly articulate the ‘why,'” – adds Tural Mamedov, Chief Executive Officer at Unicrew.

1. Resistance to Change

A revealing survey by KPMG identifies that 33% of transformation failures are due to employee resistance. Recall Microsoft in 2018, grappling with the shift to a cloud-first approach, met with resistance from its traditionally inclined teams. How did they eventually succeed? It was through a combination of persistent leadership and a strategic realignment of their corporate culture.

Solution:

“Implement a robust change management strategy that includes transparent communication, employee involvement, and leadership that models the desired change. Recognizing and addressing concerns early can reduce resistance,” – said Tural.

2. Lack of Clear Vision

Consider this: a study by Harvard Business Review found that a mere 22% of employees feel their managers provide a clear direction for the future. Despite having the required technology, Kodak’s missed opportunity in digital photography exemplifies the consequences of a vision disconnect. Isn’t this a telling reminder of the necessity for a clear and compelling vision?

Advice:

Leaders should communicate a clear, compelling vision that is easily understandable and resonates with employees. Align this vision with the organization’s overall goals and ensure it’s consistently reinforced at all levels.

3. Inadequate Leadership Commitment

Did you know that transformation efforts are 5.3 times more likely to succeed with active senior leader involvement? Reflect on HP’s failed digitization attempt in the early 2000s, a clear case of leadership inconsistency. This underscores the non-negotiable need for steadfast leadership commitment in driving transformation.

Solution:

As Ihor Prudyvus, Engineering Director at Unicrew, aptly stated, “Cultivate strong leadership commitment by involving leaders in the planning and execution stages. Encourage them to lead by example, showing their dedication to the transformation through their actions and decisions”.

Technological and Process Hurdles (Reasons 4-5)

The realm of software engineering is synonymous with continual evolution. But what are the implications when integrating new technologies leads to a tangle of technical challenges and compatibility issues? It’s evident that while legacy processes might offer comfort, they can also limit progress. How do we then navigate adopting new technologies to ensure they complement rather than disrupt our existing operations? The solution lies in a meticulously strategized approach to technology integration and process management.

4. Obsolete Technology and Processes

Gartner highlights a critical challenge: 45% of businesses are hindered by outdated technologies. Nokia’s reluctance to embrace new operating systems during the smartphone revolution is a cautionary tale. How can organizations stay technologically agile in such a dynamic landscape?

Advice:

“Regularly audit and update technological tools and processes. Encourage a culture of continuous improvement and innovation, where staying ahead of technological trends is a priority,” – adds Ihor.

5. Ineffective Communication

Towers Watson’s study reveals that companies with highly effective communication are 3.5 times more likely to outperform their competitors. Consider the downfall of Enron, exacerbated by internal communication failures. Isn’t effective communication a cornerstone of successful transformation?

Solution:

Develop a comprehensive communication strategy that includes regular updates, feedback loops, and clear channels for employees to voice concerns. Tailor communication methods to suit different groups within the organization.

Cultural and Human Factors (Reasons 6-8)

“Did you know that the culture of an organization can significantly impact its ability to adapt to change? Cultures prioritizing learning, agility, and innovation typically navigate transformation more successfully,” – said Oleksandr Trofimov, Chief Technology Officer at Unicrew. But what about organizations with rigid, hierarchical cultures? These environments often struggle with change, as they are entrenched in traditional working methods. The 2024 Deloitte Human Capital Trends report emphasizes the importance of nurturing a culture that embraces change, fosters innovation, and prioritizes continuous learning. Organizations increasingly focus on upskilling their workforce and aligning their human resource strategies with their transformation goals.

6. Organizational Culture

Bain & Company reports that while over 80% of companies view their culture as a competitive edge, only 10% successfully cultivate a culture that truly drives success. Google’s success in transformation is largely attributed to its culture of innovation and openness. How can other organizations replicate this kind of cultural transformation?

Advice:

Leaders should actively work to cultivate a positive and adaptive culture. This can be achieved through regular team-building activities, open forums for discussion, and recognition of those who embrace and drive change.

7. Employee Engagement and Support

Gallup highlights that companies with engaged employees are 21% more profitable. Conversely, GE’s struggle with digital transformation in the 2010s, partly due to inadequate employee buy-in, showcases the critical need for engagement. How can organizations foster a more engaged and supportive workforce?

Solution:

“Increase engagement by involving employees in decision-making processes, providing opportunities for growth, and recognizing their contributions. Engaged employees are more likely to support and contribute to transformation efforts,” – adds Oleksandr.

8. Lack of Training and Development

LinkedIn’s 2020 Workplace Learning Report emphasizes that 51% of companies consider upskilling a priority. In contrast, Blockbuster’s failure to adapt to the streaming trend, partly due to a lack of skill development, illustrates the perils of neglecting employee training. How crucial is continuous learning and development in ensuring successful transformation?

Solution:

Invest in continuous learning and development programs. Tailor training to meet the organization’s and its employees’ evolving needs, ensuring that everyone has the skills and knowledge needed for the transformation.

Strategic and Tactical Missteps (Reasons 9-11)

“Why do well-intended visions often fall short in execution? This discrepancy usually arises when a realistic plan and sufficient resources do not underpin ambitious goals. What are the repercussions when tactical plans don’t align with strategic objectives? Such misalignments can lead to a series of operational failures, ranging from poor planning to an underestimation of complexities. How can organizations bridge the gap between visionary thinking and practical execution?” – adds Ihor Prudyvus, Engineering Director at Unicrew.

9. Misalignment of Strategy and Execution

The Project Management Institute found that 1 in 6 IT projects experience a cost overrun of 200%. The flawed rollout of Healthcare.gov is a stark example of this misalignment. What strategies can organizations adopt to align their vision with execution capabilities better?

Advice:

Ensure that strategy formulation includes input from those responsible for execution. This alignment creates a cohesive approach and facilitates smoother implementation of plans.

10. Underestimating the Complexity of Change

IBM’s insights reveal that companies underestimating the complexity of change are 50% less likely to succeed. Sears’ struggle to compete with e-commerce giants is a classic case of underestimating change complexity. How can organizations more accurately gauge and prepare for the complexities of transformation?

Solution:

Conduct thorough planning and involve experts to assess the complexity of proposed changes accurately. Regularly reassess and adapt plans as the transformation progresses.

11. Inconsistent Follow-Through

Forbes reports a startling statistic: only 8% of organizations consistently see their strategies through to completion. Xerox’s wavering focus between core business and diversification exemplifies inconsistent strategic follow-through. What steps can be taken to ensure consistent execution and follow-through in transformation initiatives?

Solution:

“Establish a system of accountability and regular progress reviews. Keep the team focused on long-term goals and ensure consistent efforts in executing the strategy” – said Ihor.

Bonus: Top-5 Books You Should Read About Transformations

You already know why transformation efforts fail for various reasons, ranging from inadequate planning and communication to resistance from employees or stakeholders. Several books from Unicrew delve into the topic of why transformation efforts fail and provide insights on how to make them successful. 

“Leading Change” by John P. Kotter

In this classic book, Kotter outlines eight common reasons why transformation efforts fail and offers a framework for successful change management.

“Our Iceberg Is Melting: Changing and Succeeding Under Any Conditions” by John Kotter and Holger Rathgeber

This fable-style book presents a story about penguins facing a melting iceberg. It illustrates the challenges and dynamics of organizational change and offers practical lessons on overcoming obstacles.

“Switch: How to Change Things When Change Is Hard” by Chip Heath and Dan Heath

This book explores change’s psychological and behavioral aspects, explaining why people resist transformation and providing strategies for overcoming resistance.

“The Innovator’s Dilemma: When New Technologies Cause Great Firms to Fail” by Clayton Christensen

While primarily focused on disruptive innovation, this book also discusses why established organizations can struggle with transformation and offers insights on how to navigate disruptive change successfully.

“The Lean Startup: How Today’s Entrepreneurs Use Continuous Innovation to Create Radically Successful Businesses” by Eric Ries

Although primarily aimed at startups, this book provides valuable insights into applying lean principles and experimentation to transformation efforts in larger organizations.

Conclusion

The path to successful transformation, especially in the dynamic field of software engineering, is filled with potential pitfalls. The key to navigating these challenges lies in understanding the multifaceted nature of change – from leadership commitment and cultural adaptation to strategic alignment and technological agility. By learning from the successes and failures of others, organizations can better position themselves to survive and thrive in the face of change.

Time and Materials vs. Fixed Fee

Selecting the appropriate contract model (Time and Materials vs. Fixed Fee) for software development projects is crucial for success. It becomes imperative to grasp the advantages and disadvantages of each to make a well-informed decision. But finding the appropriate contract type becomes vital in attaining project success and optimizing value. In this blog, we will delve into the characteristics of these contract models and provide examples to illustrate scenarios where one may be more suitable than the other.

What is a Time and Materials Contract?

Under a T&M contract, clients are billed according to the actual time spent by the engineers on the project. The developers’ hourly rate determines payments and is typically made at regular intervals, such as monthly or as predetermined by the agreement.

“Simultaneously, clients can adjust the project’s scope and requirements throughout development. This flexibility allows for modifications in response to factors such as obsolete features, altered stakeholder preferences, or shifting company priorities”, – said Ihor Prudyvus, Engineering Director at Unicrew.

Advantages of Time and Material (T&M) Contract

  • Enhanced Flexibility: Unlike fixed-price contracts, the T&M model allows for quickly incorporating new ideas and changes during the project. Features can be added or removed, and unforeseen challenges can be addressed promptly. This flexibility is a crucial factor that makes businesses prefer the T&M pricing model over fixed-price contracts.
  • Tailored Solution: As project requirements are continuously adjusted to adapt to changing conditions; clients receive a highly relevant product custom-tailored to their current business needs.
  • Elimination of Estimation Risks: Clients only pay for the development hours the developers expended by opting for a time and materials approach. This eliminates the risks associated with incorrect estimation, whether overestimating or underestimating the project scope. The developers can dedicate as much time as necessary to deliver a high-quality solution without the constraints of predefined budgets.
  • Quick Project Initiation: With a time and materials contract, developers can begin coding without needing detailed written specifications. This allows for an immediate start to the project, enabling developers to begin working on the implementation immediately. This agile approach promotes efficiency and reduces delays associated with extensive pre-planning.

Disadvantages of Time and Material (T&M) Contracts

  • Uncertain Budget: One of the drawbacks of opting for a time and materials contract is the absence of a fixed budget. Since the project cost is determined based on the actual time and resources utilized, deciding on the final fee in advance becomes challenging. This lack of budget predictability can make financial planning more difficult for clients.
  • Uncertain Deadlines: With the scope of work being subject to change in a T&M contract, accurately predicting the exact release date becomes highly challenging. The flexibility and adaptability offered by T&M contracts can result in uncertainties regarding project timelines, making it difficult to set firm deadlines.
  • Proactive Client Involvement: T&M contracts require active and continuous involvement from the client throughout the development process. As important decisions must be made during various stages of development, the client must be engaged and available to provide feedback, make choices, and address evolving requirements. This level of client involvement may require additional time and commitment.

Time and Materials vs. Fixed Fee: When T&M Contracts Are Preferred?

“The Time and Materials pricing model is suitable for projects that involve changing requirements based on business needs, projects influenced by market conditions, and projects lacking a well-defined detailed specification, among others. If someone analyzes Time and Materials vs. Fixed Fee models pros & cons, it is worth noticing that the T&M model offers a certain degree of flexibility.”, – explained Oleksandr Trofimov, Chief Technology Officer at Unicrew.

Let’s explore some situations highlighting when a preference for Time and Materials Contracts emerges.

  • Startup Projects. Startups often operate in dynamic environments and may need to pivot their product strategy based on market feedback. A T&M contract allows for adaptability and supports the agile nature of startups. For example, a startup is developing a new software application. They opt for a T&M contract because they expect the project requirements to evolve rapidly based on user feedback and market trends. The contract allows them to adapt and make changes as needed.
  • Full Cycle Development. Projects that involve building a product from scratch benefit from T&M contracts. For instance, a company developing a new mobile app may require exploration, prototyping, and experimentation in the initial stages. T&M contracts accommodate these iterative processes.
  • Software Modernization. When a business aims to enhance or modernize an existing system incrementally, T&M contracts are suitable. For example, a company updating its e-commerce platform may prioritize improvements in modules or features over time, which can be managed effectively with T&M contracts.
  • Research and Development (R&D) Projects. R&D initiatives often involve exploration, experimentation, and innovation, where the scope and requirements may evolve as discoveries are made. T&M contracts provide the flexibility to accommodate the unpredictable nature of R&D projects.
  • Projects with Uncertain Requirements. In cases where the project requirements still need to be fully defined or are subject to frequent changes, T&M contracts are preferable. This could be due to evolving market conditions, user needs, or technological advancements.
  • Team Augmentation. When businesses require additional resources to augment their existing teams, T&M contracts offer flexibility and transparency. For example, a company working on a complex project may need to bring in specialized developers or designers for a specific duration to enhance the team’s capabilities.

What is a Fixed Fee Contract?

To better decide in the battle of Time and Materials vs. Fixed Fee, we need to analyze the Fixed Fee mode deeper. The fixed-fee contract is a pricing model where predetermined costs, project scope, and deadlines are agreed upon in advance by the service provider and client. Once signed, these parameters cannot be changed. It requires engineers to have a clear vision of the final product. If the client wants to add features, all terms, including price, workload, and timeline, must be renegotiated separately.

Interesting fact! A study by Deloitte found that fixed-fee pricing can incentivize service providers to focus on delivering results efficiently and effectively, as they are motivated to complete the project within the agreed-upon budget.

Advantages of Fixed Fee Contract

  • Budget Certainty: Fixed Fee contracts provide clients with a clear understanding of the total cost from the beginning. This predictability is crucial for planning and resource allocation for small and medium-sized businesses (SMBs) with limited budgets. Probably, it is the most attractive perk in betting in Time and Materials vs. Fixed Fee competition.
  • Defined Scope: Fixed Fee contracts establish a well-defined scope of work before the project commences. This minimizes the risk of scope creep and ensures alignment between the client and the development team.
  • Risk Allocation: Fixed Fee contracts shift the risk of project delays or additional work to the development team. Clients are protected from unforeseen circumstances, and the development team takes responsibility for delivering the project as agreed upon.

Disadvantages of Fixed Fee Contract

  • Lack of Flexibility: Fixed-price contracts are challenging to adjust to new requirements or market conditions. Usually, any changes require a separate agreement to be signed.
  • Lengthy Planning Process: In the fixed-price model, the service provider must thoroughly understand all requirements in advance, leading to detailed discussions and a more prolonged planning phase.
  • Risk of underestimation: There is a risk that the service provider may need to pay more attention to the effort, resources, or costs involved in completing the project. If the fixed fee is set too low, it can lead to financial losses for the provider, as they have to bear any additional expenses or unexpected challenges that arise during the project.

Scenarios Where Fixed Fee Contracts Are Preferred

“The fixed-fee pricing model is effective only for brief projects and certain MVPs, such as those where all requirements can be clearly defined and accurately estimated upfront,” – said Oleksandr Trofimov, Chief Technology Officer at Unicrew. What about examples? Consider the following scenarios where a preference for fixed-fee contracts arises:

  • SMB Projects. SMBs often have tighter budget constraints and need to control costs efficiently. Fixed Fee contracts provide budget predictability and enable businesses to allocate resources more effectively. Imagine a profitable small business determined to conquer the digital world despite limited resources. They partner with a seasoned IT consulting firm to optimize their tech capabilities within budget constraints. They gain access to exceptional IT services through a fixed-fee contract while managing their financial resources effectively.
  • Well-Defined Projects. Projects with clearly outlined requirements, objectives, and a fixed scope suit Fixed Fee contracts. For instance, a software company seeks to create a fitness-tracking mobile app. They provide a development team with detailed specifications, including wireframes and functionality. The company and the development team ensure clear objectives and a precisely defined scope by establishing a fixed-fee contract.
  • Projects with Fixed Timelines. When a project has a strict deadline or must be completed within a specific timeframe, a fixed fee contract guarantees the development team’s accountability for timely delivery. Consider a financial institution requiring an upgrade to its core banking system to comply with new regulations by a deadline. They enlist the services of an IT solutions provider to handle the upgrade promptly. A fixed fee contract ensures that the provider is responsible for completing the project on time, ensuring regulatory compliance.
  • Projects with Minimal Scope Changes. In projects where significant changes in requirements during development are unlikely, opting for a fixed-fee contract offers clarity and reduces the risk of scope creep. Let’s say a healthcare organization plans to implement an electronic medical records (EMR) system based on its existing processes and needs. They hire an IT integration company to customize and deploy the EMR system. Both parties agree on a fixed fee contract because the organization’s requirements are expected to remain relatively stable throughout the implementation, minimizing the risk of scope creep.

To Sum Up

In response to the question, “Which pricing model is superior: Time and Materials (T&M) Contract or Fixed Price Contract?” we would state, “The T&M contract holds a slight advantage over the fixed price system due to its inherent flexibility.” However, both models have their merits. The fixed-price pricing structure is well-suited for smaller-scale projects, urgent deadlines, or developing a minimum viable product (MVP). Conversely, if your project is substantial and intricate and requires greater flexibility in determining features and other aspects, opting for the time and material model would be more advantageous.

By comprehending each contract type’s unique features and advantages and carefully evaluating the specific circumstances, businesses can make a knowledgeable choice and establish a solid foundation for a successful software development project.



Hey, engineer, do you understand my business?

Over the past few years, startupers have been eager to learn “the Uber Way” – how to exploit proper IT solutions for creating a product that could offer users an intuitive interface and shake up their respective markets. This fascination soon led to the popularization of “uberization” — becoming so sought-after it practically became its own buzzword!

Ingredients of product success

But Uber, likewise many other successful products, has something that stands them out from the range of products that failed.  Uber’s success is powered by more than just a great market fit – its engineers have also crafted cutting-edge technology that perfectly reflects the original business plan. Beyond impressive technical savvy, Uber showed an outstanding understanding of what customers really wanted and needed to create a winning product!

A product journey is a way that consists of different stages and combines a lot of people. The total scope strongly depends on what you plan to develop – the corporate IT solutions require another approach than developing MVP for startups.

But there always is something at the beginning. Behind all great products lies a dream that turned into an idea.  Understanding it in its original form and turning it into a product is one of the biggest challenges the IT world faces, whether the idea is small or huge. Today we want to discuss what needs to be done for the initial idea to be translated into an appropriate tech solution.

Why do misunderstandings occur?

During our work, we faced a lot of different clients that had proficient knowledge of their business; however, when it came to the technical part of the implementation, they needed some guidance (that’s why they hired us). Although IT solutions for business can significantly streamline complex processes and boost revenue, the final success depends on effective collaboration between all stakeholders and eliminating all bottlenecks.

Someone can say: “Okay, there are people that have an idea on the one side and engineers that can implement the necessary solution on the other side, so what else do you need to make it happen?”

In the real world, that is more complex. And the most popular reason why the products failed is the discrepancy in translating business needs into a product roadmap understandable to all stakeholders. The gaps can occur at any stage, but in the initial stage, when the product idea has to be decomposed into a software architecture and development plan, the mistakes are very painful. During the work process, a lot of misunderstandings appear, which can be caused by different reasons:

  • The unfamiliarity of the new domain
  • Stakeholders use their internal slang
  • Product Complexity (the high-level vision of the product isn’t decomposed into more simple modules)
  • Stakeholder requirements must be clearer, have ambiguity, edge cases, etc.

 Who is a Business Analyst, and why do we need one?

To ensure the client’s requirements are captured correctly and then transferred to the tech team, we need someone in the middle who can serve as a bridge that will unite the business shore with the tech one. 

Of course, we’re talking about the Business Analyst role here. 

So again, who is a Business Analyst, and why do we need one?

It is someone with project domain knowledge and can communicate with the client in an understandable language. At the same time, it has appropriate tech skills that allow translating the client’s business needs into technical requirements that are understandable for the development team. Such an approach is highly important in outsourced IT solutions, as the outsourcing engineering team must not only properly catch the idea of the product but be able to select the most appropriate tech stack.

To ensure that our BA approach is as effective as possible, we created the Expectation Management System (EMS) that allows us to align with the List of Deliverables that will guarantee the successful execution of the project.

Below are a few things we do to provide high-quality expertise supported by our Expectation Management System.

Now tell User Story

Considering there are a lot of different domains, there is no way you can be an expert in each one. That’s why we’ve implemented a proactive approach for our business analysts: we conduct a pre-discovery phase during which our specialists get familiar with the domain of our customers in includes: 

  • Searching & familiarisation with the available content (articles, reports, case studies)
  • Watching the domain-related videos
  • Conducting a Market analysis (qualitative and quantitative)
  • Viewing open jobs and their description

This is the minimum required from our specialists to understand our clients better. The mentioned phase is crucial for preparing the most relevant questions, which, in turn, allows us to save a lot of time and be on the same page with our clients. We use the individual approach to each case as the pre-discovery phase for developing IT solutions for manufacturing could differ from the software development for e-commerce.

After the pre-discovery phase is done, we are better prepared for the discovery phase. We can:

  • Ask better questions
  • Set up the correct priorities
  • Avoid assumptions
  • See a strategic goal of the client and align it with the development team.

All the requirements gathered during the discovery phase are outlined in the form of User Stories that are understandable for both: the client and the development team. Each User Story is followed by a List of Acceptance Criteria that includes specific information on how it should be implemented.

Example of User Story

We understand that some of our clients prefer visualization over textual representation. To ensure that we understand them right and not overwhelm them with tons of text, we create business process modes that are represented in the form of a diagram with a list of actions, transitions, and events combined into processes.

This allows us to:

  1. Demonstrate how the solution (or its separate process) will work
  2. Cover potential edge cases that were not determined during the requirements-gathering sessions
  3. Build a better internal solution structure 
  4. Make sure everyone is aligned on how the solution will work.

Sometimes, we experience cases where the only way to ensure we understand the client is to demonstrate the solution. But how can we do it when the development phase hasn’t even started yet?

For cases like these, we create prototypes of the solution. This way, our client will be able to recreate real-life use cases that will take place within the solution that will be implemented.

To share our experience with the team, we create case studies of the applied approaches, the circumstances where they were applied, and the conclusion of whether they succeeded or not. This allows us to use our experience to build new approaches or utilize ones that work best for our clients and us.

How to be on the same page? Tips from Business Analyst

I want to share some tips for the Product Team that could be useful for more effective collaboration with the engineering team:

  1. Think and communicate like your application’s end user. Try not to use complex professional terminology, even if you develop a narrow solution. 
  2. Prioritize the user’s benefits. As it is very hard to satisfy all possible users’ expectations, choose one or a few of the most important, without which your application can’t stand out from the competitors.
  3. Share with Business Analyst and development team the reasons why the existing solutions can’t satisfy the customers. So they can capture the best ideas on how to develop better solutions. 
  4. Be open to new ideas, and evaluate every question, even if it seems very stupid.
  5. Be friendly with numbers and facts. If you request a solution that overcomes the competitors, provide relevant numbers you would like to achieve. For example, if you detected that your competitors failed due to traffic overload, share it with the engineering team. They can develop systems that support the necessary amount of user requests.

TOP 20 Supply Chain metrics for tracking

The supply chain is an essential component of your company’s success. The system is responsible for the efficient and seamless delivery of products or services you provide directly to your customers. And if any issue occurs due to poor supply chain management, it harms your entire business. Look closely at supply chain metrics and why they matter for your business.

You will discover why you need to add supply chain management software development to your business processes and what to pay special attention to.

20 Supply Chain Metrics to Keep an Eye on

Supply chain metrics measurement is the process of identifying the particular parameters that describe supply chain performance. By collecting and analyzing key metrics, you get valuable opportunities:

  • Detecting all the inefficiencies and learning how to avoid them;
  • Defining your strengths and highlighting them for your customers;
  • Creating a business development plan based on those facts;
  • Setting clear goals and achieving them.

And what is crucial, no investments are required. You choose, measure, and employ the needed metrics to boost your business. Most supply chain specialists say analytics is crucial to decrease costs. Here are some things you may consider for improving your supply chain efficiency:

Remember: You must always have data. This data aggregation service gives you unexplored access to data, improving your marketing potential. We will examine the top 20 Supply Chain metrics and their application.

Supply chain costs vs. sales

We’re also adding cost analysis related to sales to our supplier chain list. The indicator calculates your sales costs as a percentage of your sales and measures how much you spend compared to ‘everything.’ Using these Supply Chain metrics, your company can conduct an accurate spending analysis and create systems to help you achieve savings. Optimizing the supply chain means lowering costs as much as possible. Still, in this case, as I said earlier, it is vital to cut costs wherever this is practical rather than reduce the number.

Pick & pack cycle time

Using the supply-chain performance measurement, you can assess how efficiently the supply chain is divided and grouped by specific lines. Each metric within this metric aims to quantify how long it takes to take a product from its shelf until it gets packed. You will know the delays once you have set your targets and monitored your production process. You can therefore use targeted actions to fix the issue and decrease the time to market throughout the process.

Days sales outstanding (DSO)

Days Sales outstanding KPI measures the speed at which your organization collects and generates revenue. A low DSO number means the business has fewer days to pay the invoice. A higher DSO level demonstrates that a company is offering its goods to customers using a credit or taking longer to collect revenue in a tangible sense, which may affect cash flows and reduce profits. By often calculating this amount, you can increase the efficiency of the revenue and thus improve the bottom line.

Inventory to sales ratio

Inventory-to-sales ratio is an essential measurement for your manufacturing process. The metric measures inventory compared to real quantities for selling and is expressed in ratios. Such a metric can be helpful for companies that want to increase their profit margin and help you know what is going on in an unexpected situation when you need to adjust stock. To achieve healthy ratios, you must find ways to achieve them properly. If you want your ratio to be less than 10%, you must reduce the ratio.

Delivery time

The list of the supply chain metrics could hardly be full without the Delivery time metric. Delivery time is a KPI of the supplier chain that measures the time required to complete the delivery process at the customer. Orders must be correctly prepared, and the destination must arrive within an agreed period. And customer experience will affect the overall customer experience: nobody loves waiting for shipments for a month. It’s logical for suppliers to reduce the supply chain management KPI to ensure better information for the customer about the delivery of the goods or the product.

Warehousing costs

Our inventory cost lists are updated. The time and space allocated to your inventory are vital for maintaining healthy supply chains. While these costs differ from stockyard to stockyard, it’s crucial to measure this indicator periodically and evaluate it to identify potential and reduce unnecessary costs. Its operation consists of several expenses, including labor, warehouse lease, utility, equipment, material handling systems, supply orders, and storage costs.

Gross Margin Return on Investment (GMROI)

Regardless of service, product, and industry, every industry focuses on obtaining maximum return to investors (ROI) on all commercial activities. A consistent, solid ROI is essential for an effective eCommerce business strategy. The GMROI accurately represents a percentage gain for a single AED or an average dollar investment for each of your products. The calculated value is divided between the average profit and gross profits.

Supply chain costs

The cost indicator is an important indicator of supply chain performance which indicates relevant costs on supply chain management. Costs can be a plan or a team management plan and show how efficient the company is. Increasing profits for businesses is one of many effective strategies. It can determine the potential for improvement and minimize sales. Obviously, this must be evaluated before the cost cuts are implemented in a supply chain.

Reasons: Supply chains measure the factors that cause a return customer to return their orders – information that will ensure an effective eCommerce operation in the long run. Featuring a digestible pie diagram with a key showcasing the primary motivation of return – a measurable measure – your supply chain process can help identify your weaknesses and critical areas for improving performance — the quality and efficiency of your product.

Cash-to-Cash Cycle

One of the most valuable Supply Chain metrics is Cash-to-Cash Cycle which helps to determine how long it takes to convert resources into real cash flows. Working on three core ratios – day of inventory (DOI), day of payable (DOP), and day of receivable – the cash-to-cash time cycle KPI shows the duration needed between these times. This valuable supply chain measurement helps you take the correct steps to keep your business running at a lower cost of operation.

Cash-to-Cash Cycle

This valuable Supply Chainmetric helps to determine how long it takes to convert resources into real cash flows. Working on three core ratios – day of inventory (DOI), day of payable (DOP), and day of receivable – the cash-to-cash time cycle KPI shows the duration needed between these times. This valuable supply chain measurement helps you take the correct steps to keep your business running at a lower cost of operation.

Freight Bill Accuracy

Shipping and freighting your goods from supplier to warehouse to the consumers is essential for your entire business, and a failure can result in wasted time and money. Billing accuracy is crucial to profit and customer satisfaction; tracking this metric can help spot negative trends, improve shipment accuracy, and ultimately increase business growth. How can freight bills be accurately calculated?

Inventory Days of Supply

Though not the most comprehensive or panoramic of Supply chain metrics, Inventory Days of Supply is handy since it gives you a reasonably accurate estimate of the time needed for your stock to run out without replenishment. Daily, you can monitor stream data, analyze stock-based issues and prevent stock-based problems, which helps save your reputation and generate profits.

Fill rate

Next on this list is the fill rate. This key metric can indicate the percentage of your customers’ orders fulfilled for the first time. The fill rate in the supply chain is an essential indicator of product quality and customer satisfaction. Line or online orders or individual item deliveries determine your supply-to-demand rate.

Perfect Order Rate

It is a key supply chain KPI for businesses across many industries. Perfect Order Rates measure your success in providing timely and incidentless order fulfillment and help you resolve problems affecting your order. As a result, the more perfection you get, the more you will have to improve your customer retention and retention rates.

Inventory velocity (IV)

The Inventory velocity or IV is a crucial supply chain graphical measure providing an overview of how much inventory will be used over the next quarter or year. This KPI will help you optimize your inventory to meet customer demand.

On-time shipping

The on-time shipping is significant to the delivery timeline for a product or service; it is an excellent indicator of when to send an order to a client or partner to determine the best delivery time for your product.

Nevertheless, each logistic business is unique and may require establishing the specific supply chain metrics for their software. We offer the best solution and an experienced development team if you need to customize your supply chain platforms.

What is CTO as a Service?

In today’s business climate, technology is more important than ever. Companies must have a robust online presence to compete, and they need to be able to adapt quickly to changes in the market. For many businesses, the Chief Technical Officer (CTO) is the key decision-maker regarding planning the technology upgrade. However, not all businesses have the resources to hire a full-time CTO. That is why the popularity of CTO as a Service is constantly increasing.

Let’s discover the following topics:

What is a CTO as a Service, and what do they do for a business?

According to IBM research “The CTO revelation“, since 2019, more CTOs are reporting increased capability maturity, including 600% more who are experiencing advanced digital process automation capabilities, 530% seeing advanced hybrid cloud operations, 353% realizing advanced cloud-native development, plus surges in those reporting the maturity of other key technologies.

CTO as a service

A Chief Technology Officer as a Service (CTOaaS) is an outsourced professional who provides strategic and technical guidance to businesses in information technology, product development, and data security. CTOaaS providers work with businesses to assess their needs and develop customized solutions that address these needs. In addition, CTOaaS providers also provide ongoing support and advice to businesses to ensure that their systems remain up-to-date and effective.

CTO as Service provider offers a variety of benefits to businesses, including access to expertise, flexibility, and cost savings. By working with a CTOaaS provider, businesses can focus on their core competencies and leave the management of their IT infrastructure to the experts.

The benefits of having an outsourced CTO on your team

An outsourced CTO can bring a wealth of experience and knowledge to your team. They can help you develop and implement strategies to improve your online presence and better compete in the market. In addition, an outsourced CTO can provide invaluable support during times of change or crisis. An experienced professional on your team can help you navigate challenges and make the best possible decisions for your business.

There are many cases when CTO as a Service can favor a business. Perhaps the most obvious case is when a business does not have the resources to hire a full-time CTO. By outsourcing this role, businesses can gain access to the expertise and knowledge of an experienced professional. In addition, outsourced CTOs can be more flexible than in-house CTOs and can often provide services at a fraction of the cost.

CTO consulting can also be helpful during times of change or crisis. When a business is going through a transition or experiencing difficulty, having an experienced CTO on board can help to navigate these challenges and make the best possible decisions for the company. Overall, CTO as a Service can be an excellent solution for businesses that need help with their information technology and product development strategies.

When a company plans to make a digital leap or needs to estimate the potential benefits of new technologies implementation precisely, a CTO is a proper expert who plays a crucial role.

CTO as a service
Oleksandr Trofimov, CTO at Unicrew:

“Most technology consulting cases are about assessing the feasibility of new technologies and developing a plan for their implementation. Many companies, especially SMEs, are looking for pre-estimation of the scope and budget of future digital transformation. That is a very common point, as businesses need to allocate resources and estimate the potential benefits that these new technologies could bring to the company. Experienced CTO can do it more precisely, given their solid background of delivered projects. By working with a CTO, businesses can make sure that they are making the best possible decisions when it comes to technology”.

When it comes to the digital future of a business, the solution that a CTO makes can literally make or break the company. To ensure that your business makes the best possible technology decisions, it is essential to work with an experienced CTO who can help you assess the feasibility of new technologies and develop a plan for their implementation. By doing so, you can be sure your business is on the right track to success in the digital age.

Differences between technology consulting and CTO as a Service

As the world increasingly relies on technology, businesses are turning to technology consultants for help with everything from developing new products to streamlining their operations. However, there is a big difference between technology consulting and CTO as a Service.

Technology consulting is typically focused on providing advice and guidance on specific projects, while CTO as a Service is responsible for the overall strategic vision of the company’s technology needs. This means that CTO as a Service is more involved in long-term planning and decision-making, while technology consultants focus on day-to-day implementation. Although both roles are important, they require different skills and approaches.

Tips for working with an outsourced CTO

When working with an outsourced CTO, clear communication is key. Explain your company’s goals and needs so the CTO can provide the best possible advice and support. It is also important to keep the lines of communication open; regular check-ins will help to ensure that both parties are on the same page.

To get the most out of an outsourced CTO, it is also important to give them the freedom to experiment and innovate. Encourage them to think outside the box and develop new ideas that could benefit your business. By taking these steps, you can maximize the value of working with an outsourced CTO.

The CTO should understand your clients’ profiles and their needs so you can be sure that they will be able to provide the best possible service. In addition, by understanding your clients’ journey map, the CTO can help ensure the technology implementation process is as smooth as possible.

When working with outsourced CTO Services, it is vital to establish clear metrics and deliverables. This will help ensure that both parties are on the same page and that the CTO delivers value to your business. Sometimes, founders or the company’s board are tempted to establish the CTO’s KPIs related to daily tasks, like a response time for the company’s website or other performance indicators of the company’s digital platforms. But it is a very shortsighted stance.

If you have decided to outsource an experienced CTO, don’t overload them with tasks that can complete middle-level managers or engineers. Rather, exploit their skills and knowledge to make your company more resilient and long-lasting. What could be the deliverables you can expect from the outsourced CTO?

  1. IT infrastructure audit (including your legacy systems).
  2. Defining what technologies (and how) can improve your customers’ experience.
  3. Building and managing the engineering team (in-house or outsourced) given the company’s strategy and goals.
  4. Digital Transformation Road Map with the budgeting and milestones.
  5. Augmenting the company strategy with the vision of technology implementation.
  6. Assessment and contracting of IT vendors within the approved budget.
  7. Representation of the company at industry events, meetings, and negotiations (if it is related to the technologies).
  8. Developing company policies in cybersecurity and data protection.
  9. Taking managerial control over all activities related to company digital assets.
  10. Assuring high-quality documentation and knowledge transfer.
  11. Mentorship and supervising their subordinates.

The mentioned checkpoints don’t cover the entire responsibility of the CTO; in every case, it could be specific metrics, but the general idea is that expectations and KPIs should be discussed on the shore, not at the ship.

How to estimate and plan the CTO work?

There is no one-size-fits-all answer to this question, as the best model for working with an outsourced CTO will vary depending on a company’s specific needs and circumstances. However, here are a few tips on how to estimate the work involved in working with an outsourced CTO:

  1. Per-hour model. Estimate the time needed for regular check-ins and communication, both for planning and decision-making.
  2. Project-based model. You can negotiate the fixed fee for the implementation of the project, including consultation and management.
  3. Subscription-based model. You pay a fixed price (monthly or annually) for a defined amount of hours per week (or month) within which an outsourced CTO is available for your company’s projects.
  4. Full-time outsourcing. A full-time outsourced CTO doesn’t differ from an in-house expert, but the employer can avoid the hassle of onboarding. In fact, the CTO works on the company’s projects, but all administrative routine lies on the vendor side.

The future of the outsourced CTO role

As businesses increasingly rely on technology, the Chief Technical Officer (CTO) role is evolving. In the past, the CTO was responsible for ensuring that a company’s IT infrastructure was up to date and fit for purpose. However, the CTO is expected to do much more in today’s digital world. They must be proactive in identifying new technologies that can give their business a competitive edge, and they must also be able to translate complex technical concepts into plain English for non-technical staff.

As a result, many companies are now outsourcing this role to specialist firms. This allows them to tap into a pool of experienced CTOs who can provide expert advice and guidance on all aspects of technology. It is clear that the outsourced CTO role is here to stay, and it is set to become even more important in the years ahead.

How to know that the company needs an outsourced CTO?

Even though CTO as a service for startups is the most popular model, not only startups need the outsourced CTO role. Many companies, especially SMEs, experience the need for digital growth intensively but are getting stuck for the lack of technology leadership within the team. They are good at their business but become confused about managing digital transformation. However, here are a few tips on how to know if a company needs an outsourced CTO Service:

  1. Are you struggling to find the right person for the role of CTO?
  2. Does your CTO have too much on their plate and is struggling to keep up with demand?
  3. Do you need someone with specialist expertise in a particular area (e.g., cybersecurity, digital transformation, etc.) that your in-house team doesn’t have?
  4. Would you like someone to mentor and supervise your team of engineers?
  5. Is your IT infrastructure outdated or inadequate for your needs?
  6. Are you seeking someone to help you plan and execute your company’s digital strategy?

If you answered “yes” to any of these questions, then it may be time to consider outsourcing the role of CTO to a specialist firm.

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Frequently Asked Questions

 What is CTO as a Service?

CTO as a Service is a model where a company contracts with an outsourced CTO provider to help them manage their technology and digital needs. This can include anything from advice on new technologies to full-time management of the company’s IT infrastructure.

What are the benefits of using CTO as a Service?

There are many benefits to using CTO as a Service, including access to expertise, flexibility, and cost savings.

  • Access to Expertise. One of the main benefits of working with an outsourced CTO is access to expertise. This includes specialized knowledge in information technology, product development, and data security.
  • Flexibility. Another advantage of outsourcing the role of CTO is that businesses can be more flexible with their needs. If requirements change or the company experiences rapid growth, the CTOaaS provider can easily adapt.
  • Cost Savings. Finally, using a CTOaaS provider can be more cost-effective than hiring a full-time CTO. This is because the provider will only charge for the used services, which can save businesses money in the long run.

How does CTO as a Service work?

Outsourced CTO Service providers offer various services which can be tailored to fit the needs of each business. Typically, CTOaaS providers will offer technology advice, strategy planning, and full-time management of a company’s IT infrastructure. In some cases, they may also offer mentorship and training for in-house engineers. There are a few main models of CTO outsourcing, such as per-hour fee, project-based contract, subscription model, and full-time outsourced CTO.

How can I sign up for CTO as a Service?

If you would like to sign up for CTO as a Service, please get in touch with the Unicrew team. The residents of our development house are savvy technology gurus with a huge experience in delivering complex projects in digital transformation. We would happily offer you a free estimation and discuss your needs.

How much does CTO as a Service cost?

The cost of CTO as a Service can vary depending on the provider and the used services. Typically, CTOaaS cost includes working hours ranging from $40 to $200 per hour. In the resource estimation, you should consider the maturity of the CTO candidate, your project scope, and duration. Besides, many CTOaaS providers grant bonuses and discounts given the project scope and CTO engagement. The best way to figure out it is to discuss it with Unicrew’s experts.