IT transformation seems, at first glance, like a software upgrade. But it’s about rewiring how the business runs—so teams can ship faster, operate more reliably, and adapt without breaking everything else.
Today’s enterprise IT leaders face intense pressure to modernize amid legacy systems that can’t scale, fragmented tech stacks that drive up costs, and digital-native competitors seizing market share. But many feel stuck between two bad options: stay put and keep falling behind, or replatform and risk a migration that takes too long and still doesn’t solve the underlying constraints.
Transformation feels risky because many IT leaders have lived through failed migrations and expensive “fixes” that created more work, not less. But the equation has flipped: the risk of standing still now outweighs the risk of moving forward. As Elina Vilk, David’s Bridal’s president and CBO, said: “It’s possible that the risk of not taking a digital transformation was even greater.”
This guide bridges IT transformation theory with commerce-specific execution. We’ll cover what IT transformation really means, why it’s more critical than ever in 2026, and how leading brands are modernizing their platforms, teams, and architectures—without 18-month disruptions—to unlock faster execution, lower costs, and quicker time to value.
IT transformation is the strategic overhaul of an organization’s technology infrastructure, systems, and processes to achieve business objectives and prepare the enterprise for what’s next.
Unlike a more narrow “IT modernization” (which might focus on updating one system or moving to the cloud), IT transformation reimagines how IT can drive efficiency, agility, and innovation across the company. It touches infrastructure, applications, data, security, and even the operating model and culture that drive the organization forward.
This breadth distinguishes it from digital transformation, which typically refers to reinventing business models or customer experiences (for example, launching new digital channels). IT transformation, in contrast, provides the technological foundation that enables such initiatives. In practice, they overlap, but IT transformation is what makes digital transformation scalable and repeatable.
But IT transformation goes beyond technology to include the people and processes that operate, maintain, and use technology, too. Upgrading software without changing workflows, skills, and culture will fall flat. Think of the difference between installing a multi-factor authentication tool and actually training and requiring users to use it.
In practice, this means retraining teams, breaking down organizational silos, and modernizing how the business operates—not just the tools it runs on.
As Jeff Lawson, CEO of Twilio, wrote in his book Ask Your Developer: “For a long time, most companies considered IT something that supported the business—software and servers that ran the back office, or the PC on every desk.” Now, he writes, “Software has moved from being a cost center to a profit center.”
But for many organizations, this remains potential, not reality. If you only transform the technology, you end up with a more efficient cost center—not a profit-driver.
The payoff to this work is IT that’s faster, more flexible, and aligned to business outcomes—driving value rather than just supporting it. Done right, IT transformation delivers speed without sacrifice: rapid execution on a stable, cost-efficient foundation.
For example, after undergoing IT transformation with a modern commerce platform, brands often report significantly faster execution with lower costs. Independent research found that Shopify implementations average 20% faster than competitors, with enterprise brands 66% more likely to launch on time.
In other words, transformation does not have to mean 18-month disruptions. With the right approach, it can actually speed time to value and increase the revenue once transformation is achieved. The same study also found Shopify projects were 3x more likely to stay on budget, evidence that with proper planning and platform choice, transformation can be both fast and predictable.
Ultimately, IT transformation is how organizations move faster—without trading away stability, security, or control.
In both everyday life and enterprise decision-making, opportunity cost is easy to underestimate—especially when the downside of standing still feels safer than the risk of change.
In today’s market, that tradeoff no longer holds. Standing still on legacy systems has become a risky strategy, as competitors accelerate and the costs of inaction keep compounding.
Legacy systems create a cycle of technical debt and inefficiency. Because they were not designed for today’s needs, patches and integrations pile up, making the environment fragile.
Over time, technical debt compounds: Each workaround or bolt-on fix introduces complexity that makes the next change harder and bigger transformations harder still. Organizations end up in maintenance mode, with IT teams spending most of their time keeping the lights on instead of innovating. This has a direct business impact: slow time to market, inability to adapt to new channels, and rising costs.
Legacy platforms also often have known security vulnerabilities that can’t be easily fixed without major upgrades, creating business risk. They also make it harder to hire and retain talent. Skilled engineers don’t want to work on COBOL or antiquated enterprise resource planning (ERP) systems, so you might struggle to hire or retain the expertise to maintain them.
This is the inaction tax in practice: The longer you stay stuck, the more the gap widens—and the harder it becomes to catch up. This is why IT transformation usually begins with confronting hard questions about which systems to replace or rearchitect entirely.
One of the biggest technology trends enabling IT transformation is the shift to composable architecture. Composability refers to designing your IT stack as a set of interchangeable building blocks rather than one giant suite.
In a composable commerce approach, a company might use a headless commerce platform for core transactions, a separate content management system (CMS) for content, a best-of-breed search service, and more—all connected via APIs.
The primary advantages are flexibility and speed: You can upgrade or swap components without replatforming everything, and you can adopt new services by plugging them into your ecosystem. Modular, API-first infrastructure also reduces vendor lock-in and allows faster innovation cycles because teams can work on different services independently.
This is a stark contrast to the old world of commerce suites, where changing one thing might require a full regression test of the entire system. As market velocity increases and consumer expectations change faster than traditional IT can respond, composable architecture has risen as one strategy to address legacy rigidity.
It’s worth noting that composable doesn’t mean composing systems from scratch. Shopify, for example, provides a broad commerce platform with extensive APIs and more than 8,000 integrations that allow enterprises to treat it as a foundation to support a larger ecosystem.
Shopify invested $1.4 billion into the future of commerce in 2024, a long-standing commitment to continuous innovation that delivers hundreds of new enterprise features annually—capabilities that would require years and millions of dollars in custom development on legacy platforms.
Transforming enterprise IT is a complex, context- and business-specific endeavor, but successful initiatives tend to focus on a few core pillars. These pillars provide a framework for covering strategy and architecture as well as people and process. Together, these five pillars show how organizations move fast without introducing new risk—and turn transformation into compounding value rather than disruption.
Every IT transformation must start with a clear strategic vision that aligns with business goals. This isn’t about upgrading tech for tech’s sake. It’s about enabling specific business outcomes. Define what success looks like in business terms, such as:
These objectives will guide technical decisions and help secure executive sponsorship. Executive buy-in is crucial: without C-level and cross-functional support, transformation projects can stall due to organizational inertia or competing priorities. This usually means building a return on investment (ROI) model projecting revenue gains, cost savings, and agility improvements.
A strategy should also quantify the cost of delay—the inaction tax—alongside the upside of faster time to value and more predictable delivery.
Identify key metrics up front, such as customer satisfaction scores, page load times, fulfillment speed, or percentage of revenue from new channels, to measure impact over time.
Strategic alignment also means embedding the transformation in the company’s overall strategy. IT leaders should work closely with business unit leaders to ensure tech initiatives directly support marketing, sales, and operations.
Establish a steering committee with stakeholders from IT and other departments to steer the transformation and maintain alignment. For example, at David’s Bridal, the leadership framed their nine-month overhaul as “Aisle to Algorithm”—a company-wide transformation of how they run the business, not an IT-only project.
Modernizing your architecture is at the heart of IT transformation. This pillar captures the technical blueprint: How you design your systems for flexibility, scalability, and integration. Key tenets include:
The goal isn’t complexity—it’s reducing operational burden. When your platform handles foundational capabilities reliably, teams spend less time maintaining brittle integrations and more time shipping what differentiates the business.
To see architectural decision-making in action, look at the luxury apparel brand Belstaff, which underwent a complete IT transformation called “Mission Phoenix,” implementing Shopify for unified commerce, a new ERP system, and middleware in a big-bang go-live.
Navid Jilow, director of technology, said “IT transformation starts with data centralization. We found the proposition where you can combine your point of sale and ecommerce platform under a single platform very appealing.”
In many legacy environments, data is siloed. Customer information is in one system, inventory is in another, and online and in-store data are isolated. This fragmentation prevents companies from getting a true 360-degree view of the business or the customer.
As a result, a core goal of transformation is often to create a single source of truth for key data domains. Done well, centralization enables speed and reduces risk. When teams trust the data, they spend less time reconciling systems—and fewer things break when you launch new channels or workflows.
Unified data unlocks powerful capabilities: personalized marketing across channels, real-time inventory visibility, consistent pricing and promotions, and comprehensive analytics to drive decision-making. Key aspects of this pillar include:
Together, these elements enable real-time operations and unified commerce. When online and offline systems share a single source of truth, brands can move faster without sacrificing consistency.
Technology change alone doesn’t guarantee success. The organization and culture must transform in parallel. The fourth pillar is about people: preparing and empowering your teams, restructuring processes, and cultivating a culture that embraces continuous improvement.
A major IT overhaul often introduces new technologies (cloud platforms, new programming languages, modern DevOps tools, etc.). You need to invest in training your existing teams so they can succeed in the new environment. Upskilling can take many forms, including:
The goal is to ensure IT staff (and even end-users, if their tools change) are comfortable and proficient with the new systems.
But transformation efforts can stall if departments operate in isolation or cling to “the way we’ve always done it.”
Navid Jilow, from Belstaff, explains: “A big hurdle for corporations is the fact that even though the system is broken, it’s a system that we know. Learning a new one seems really time-consuming and also requires a big financial investment.”
The right platform choice can help smooth this over. Navid continues, A lot of the tasks you can do in Shopify are quite intuitive, so the user interface sticks out. It’s great when one of the applications is quite easy to use because that breaks down the barriers of change and makes the project delivery process much easier.” When tools are intuitive, adoption happens faster—which shortens time to value and reduces prolonged transformations.
Throughout, embrace agile methodologies (such as scrum and Kanban) and build a DevOps culture. These practices encourage iterative development and quick wins, helping teams deliver value incrementally while adapting to change.
DevOps breaks down silos between development and operations, implementing CI/CD pipelines for faster, more reliable releases. By adopting these practices, IT teams stay aligned with the pace of business change.
While speed and agility are often the headline goals, security and compliance must remain firm priorities throughout IT transformation. In fact, periods of transition can increase risk if not managed carefully (for example, during data migration or when running old and new systems in parallel). The goal is to modernize IT without opening the door to breaches or compliance violations. Key considerations in this pillar include:
Selecting a platform that prioritizes security can make this pillar easier. Shopify, for instance, provides enterprise-grade security out of the box, including PCI compliance, SOC 2 audits, GDPR-compliant features, DDoS protection, and a robust infrastructure that is monitored 24/7. In other words, security doesn’t have to slow transformation down—it can improve when foundational controls are handled at the platform level.
Transforming IT is a journey, but you can map it into clear phases that make it more practical. This roadmap breaks transformation into seven phases with clear outcomes—so you can reduce risk, measure progress, and keep momentum.
Objective: Establish a clear baseline of your current IT landscape and identify pain points and opportunities.
In this initial phase, conduct a thorough audit of existing systems, architecture, and processes. Document all the technologies in use (including versions, customizations, and integrations), and map out data flows. Identify areas of technical debt, and engage stakeholders across departments to record frustrations and wishlist items.
Actionable steps might include:
By the end of this phase, you should have a clear understanding of where you are and the top problems to solve. These findings set the stage for the transformation—and help you quantify the inaction tax: what it costs to keep operating this way for another 6, 12, or 18 months.
Objective: Define the target state and secure organizational commitment to the transformation roadmap.
In this phase, use the findings from Phase 1 to craft a compelling vision of the future IT environment and how it will support business strategy. Answer two questions: Where are we going, and why now? Key activities include:
By the end of Phase 2, you should have approval and funding to execute the transformation. If Phase 2 goes to plan, you’ve replaced “Should we?” with “How fast can we?”
Objective: Design the target architecture and select the technology stack and partners to realize it.
Phase 3 turns strategy into a build plan. Key steps include:
At the end of Phase 3, you should have a detailed technical game plan and the teams (internal and external) ready to execute. Think of it as having the blueprints and contractors lined up for a house build.
Objective: Prepare the organization—both IT and business users—for the upcoming changes through training, communication, and change-management planning.
Phase 4 can run in parallel with some of the technical build, but it focuses on the human side of transformation. Key steps include:
By the end of Phase 4, the organization should feel informed and prepared, and the teams should be equipped with the knowledge to execute and adopt the changes. This de-risks deployment because your users won’t be blindsided, and your IT staff won’t be grappling with unknown tech while on a tight timeline.
Objective: Test the new systems and processes in a controlled environment, validate that everything works end to end, and incorporate feedback before full rollout.
By Phase 5, a significant portion of the new platform should be built or configured. Here’s what happens in this phase:
The pilot phase gives you a chance to fail small, learn fast, and fix early—rather than face big failures on day one. It builds stakeholder trust as well: seeing it work in a pilot can get any remaining skeptics on board.
Objective: Roll out the transformed systems and processes across the entire enterprise, whether in phases or via a big-bang deployment, and stabilize the new environment with intensive support.
Depending on your strategy, Phase 6 could be a one-time big switch or a series of rollouts. Key steps in Phase 6:
The accomplishment of Phase 6 warrants some celebration, but the journey isn’t over: Phase 7 focuses on continuous improvement, which truly never ends in a transformation mindset. This is also where the “speed without sacrifice” payoff becomes visible: teams spend less time putting out fires and more time improving.
Objective: Continuously monitor the transformed environment, optimize performance and processes, and institutionalize a culture of ongoing innovation and improvement.
The final phase is less a time-bound period and more the new modus operandi after go-live: optimizing what’s been delivered and building on it for the future. Key activities and principles here include:
Transformation doesn’t end—it compounds. By Phase 7, your enterprise should have the tools, processes, and mindset to keep evolving. The IT organization becomes a driver of innovation, and the compounding advantages of moving fast start to manifest. Each improvement builds on the last, creating an ever-wider gap between you and competitors who are stuck on legacy platforms.
In the course of an IT transformation, you will encounter several architectural paradigms and patterns. These patterns help guide technical decisions during execution. Think of them as tactical choices within a broader transformation strategy—not mutually exclusive “either/or” camps. The right mix depends on your goals, constraints, and speed requirements.
One prevalent pattern is moving from a monolithic application to a microservices architecture. In a legacy monolith, all features are tightly integrated in one application. This often leads to scalability and flexibility issues. Changes require redeploying the whole system, and scaling applies to everything at once.
Breaking down the monolith involves identifying functional domains and carving them into separate services. This pattern greatly improves agility: teams can work on different services simultaneously without stepping on each other, and you can use the right tool for each job.
It’s worth noting that going full-microservices is complex. Not every transformation needs dozens of microservices. Some opt for a middle ground that balances those trade-offs. Shopify, for example, provides unified core commerce services such as checkout, while offering extensibility via APIs and an app ecosystem—so you can modernize where it matters without rebuilding everything yourself.
Headless commerce means the front end (the presentation layer customers see) is separated from the backend commerce logic (product info, cart, checkout, often provided via APIs).
In a headless setup, the front end is typically a custom application that uses APIs from a commerce platform. Headless architecture provides flexibility for custom user experience (UX). Brands can design whatever experience they want without being constrained by the templates or technology of a monolithic platform.
Many enterprises use Shopify Plus headlessly: they keep Shopify for major systems like product, cart, and checkout, but build a custom front end that uses Shopify’s APIs. Belstaff, for example, used Shopify as the core but built a completely custom front end in collaboration with their agency. The result is a unique digital flagship experience that doesn’t look cookie-cutter, while still benefiting from Shopify’s robust commerce engine behind the scenes.
Composable commerce is related to headless but broader: It’s the approach of using best-of-breed components for each function of your commerce stack, and assembling them together, often via headless integration. Instead of one platform that does everything, you pick and choose the optimal services for things like search, CMS, and personalization, and assemble them together.
The MACH architecture concept is relevant here: it stands for Microservices, API-first, Cloud-native, and Headless. A composable architecture adheres to those principles. It claims greater flexibility and avoidance of vendor lock-in. If your search service isn’t cutting it, you can swap it out for another without replatforming the whole site.
The trade-off is orchestration: more vendors can mean more integrations to maintain, more contracts to manage, and more surfaces for things to break.
Underpinning many of these patterns is the move to cloud-native infrastructure. This goes beyond lifting and shifting servers to the cloud; organizations need to truly use cloud capabilities, including auto-scaling, managed services, and infrastructure as code.
Cloud-native implies your systems are designed to exploit elastic scaling (scale out on demand and scale back in to save cost), to be resilient (spread across available zones/regions), and manageable (with automation). It also often means using containerization (Docker, Kubernetes) or serverless architectures to deploy applications in a portable, efficient way.
No major transformation comes without bumps in the road. The key is to anticipate the failure modes and design the program to reduce risk up front.
Problem: People naturally resist change, especially after years on familiar systems—even when those systems are inefficient. Resistance can show up as passive drag (slow adoption, work-arounds) or active pushback (complaints, refusal to use new tools).
Solution: The antidote is robust change management focused on demonstrating value to the users and making the new system as easy as possible to adopt. Some strategies include:
Make adoption easy, make benefits visible, and support teams through the transition—so change happens faster and with less friction.
Problem: Migrating data from old systems to new ones is often one of the toughest technical challenges. Data might be spread across multiple databases, formats, and silos. Legacy data could be inconsistent or full of errors. And during migration, there’s a risk of data loss or prolonged downtime if not handled carefully.
Solution: A robust data governance and phased migration strategy is key. Here’s how to manage it:
Also consider running reports on both old and new systems in parallel for one cycle to catch any discrepancies early.
Problem: In legacy setups, companies often bolt on numerous subsystems over time—each with custom scripts or ETLs connecting them. The result is a complex web, and when one system changes, half a dozen integrations might break. During transformation, there’s a risk of perpetuating or even exacerbating integration complexity if legacy patterns are carried forward.
Solution: The key is to pursue a unified and API-first integration strategy and consolidate systems where possible. Strategies include:
Belstaff, for example, centralized data through a unified POS and ecommerce platform.
“IT transformation is really about data centralisation and gaining a one-platform view. Whether we have a customer shopping in-store or purchasing online, we now have that single view,” Navid says.
Problem: IT transformation projects have a reputation for going over budget and taking too long. Scope creep, unforeseen technical hurdles, and business distractions can all lead to overruns. This undermines confidence and ROI, and can even threaten project cancellation.
Solution: To keep on time and within budget, a combination of tight scope management, agile execution, and choosing platforms that inherently reduce complexity is critical. Key tactics include:
Research from an independent consulting firm shows, for example, that Shopify implementations are 20% faster on average, with brands 66% more likely to launch on time and 3x more likely to stay on budget. Use these benchmarks as planning guardrails and pair them with a disciplined scope and clear decision-making.
Problem: During a major IT overhaul, the organization can become more vulnerable to security incidents or compliance lapses.
Solution: Maintain a security-first mindset throughout the project, and plan for a zero-downtime, secure transition. Strategies include:
With platforms like Shopify, some of these challenges can be erased entirely. Shopify maintains enterprise-grade security (including PCI DSS, SOC 2, and ISO 27001), helping teams maintain strong security and compliance during and after migration.
One of the most important aspects of any transformation initiative is demonstrating its value. After all, significant investments of time, money, and effort need to translate into tangible returns for the business. Measuring the ROI of IT transformation requires tracking a mix of technical performance metrics and business outcomes, and tying each to business priorities that the organization cares about. The goal isn’t to collect KPIs for their own sake—it’s to show how improvements in speed, cost, and reliability compound into value over time.
These metrics gauge how the transformation improved the IT organization’s and business’s agility and operational efficiency:
Speed metrics matter because they reduce cycle time. Over time, shorter cycles mean more experiments, faster fixes, and more opportunities captured. Shopify stores, for example, render 1.8x faster on average than stores on other platforms, making Shopify a compelling option to IT and business leaders alike.
These metrics capture the financial impact, the “cost” side of ROI:
Sometimes, much of this calculation is done ahead of time, giving you a glimpse of ROI before you even start. Research from an independent consulting firm shows, for example, that Shopify delivers 33% better total cost of ownership on average compared to competitors.
These metrics translate IT improvements into business outcomes:
According to EY Research, brands replatforming to Shopify see 15% incremental revenue from the direct benefits of transformation.
Finally, consider metrics related to the organization’s capacity to innovate and adapt:
The key is to treat metrics as connected levers, not isolated scorecards. When speed improves, teams ship more. When reliability improves, they spend less time on maintenance. When costs drop, you reinvest. That compounding effect is what turns IT transformation into a surplus of value.
A modern IT leader needs to execute transformation programs and keep an eye on emerging trends to future-proof their strategy. In 2026 and beyond, several trends are shaping how enterprises approach IT and commerce.
AIOps refers to the use of artificial intelligence and machine learning to enhance IT operations, including automating routine tasks, performing predictive analysis for issues, and intelligently monitoring systems.
As IT environments become more complex with hybrid cloud, microservices, and the Internet of Things (IoT), traditional human monitoring struggles to keep up. AIOps platforms ingest large volumes of log and performance data to detect anomalies, correlate events across systems, and trigger automated remediation. The ROI is practical: fewer incidents and faster recovery.
While AIOps focuses on AI in operations, generative AI (GenAI) is a broader trend affecting many facets of business. In software development and IT, GenAI can assist in code generation, automated testing, and documentation. Tools like GitHub Copilot already help developers code faster by suggesting code snippets or generating boilerplate based on comments.
These tools are increasingly used to reduce development time for repetitive or boilerplate work. For enterprise use, generative AI can help create configuration scripts, test cases, or infrastructure templates from natural language requirements.
AI can also support knowledge-base articles or help with customer support chatbots. Teams should integrate these tools to speed up development and reduce errors.
Edge computing involves processing data closer to where it’s generated or needed (e.g., on IoT devices or local edge servers) rather than relying solely on central cloud data centers. This reduces latency, which is vital for certain use cases, such as real-time analytics, IoT sensor processing, and AR/VR experiences. For global businesses, edge also helps with data sovereignty and performance across regions.
For example, retailers might use edge computing to deliver faster, localized experiences beyond traditional content delivery networks (CDNs). Or in stores, edge computing can allow real-time processing of data from smart shelves or cameras to adjust pricing or detect inventory needs instantly without round-tripping to and from the cloud.
Real-time data-processing trends also tie in. Customers now expect live updates (inventory counts in real time, dynamic pricing, etc.). A unified platform plus edge can make these instantaneous.
Quantum computing remains an emerging technology, but forward-looking IT leaders are already tracking its implications. While general-purpose quantum computing is not yet practical for enterprise IT, it’s on the horizon, potentially within 5–10 years for select use cases.
That said, preparing for the quantum era is a trend, especially being aware of potential impacts and starting to adapt in critical areas like encryption. One big aspect is quantum-resistant cryptography. Quantum computers could break current encryption algorithms like RSA and ECC relatively quickly. Forward-thinking IT teams are looking at post-quantum-cryptography algorithms to implement.
Some companies are already experimenting with quantum simulators or partnering with quantum cloud providers like IBM Q or AWS Braket for R&D tasks like complex optimization or modeling. It might not affect commerce operations directly yet, but possibly things like supply chain optimization or personalization algorithms could see quantum boosts eventually.
Sustainability is a rising priority globally, and IT is a significant energy consumer. According to International Energy Agency research, data centers and data transmission networks are responsible for 1% of energy-related greenhouse gas emissions.
Green IT includes things like:
In commerce specifically, sustainability can extend to showing customers carbon footprints of products, using AI to optimize delivery routes for minimal emissions, and more. Many companies now report on IT energy usage and carbon footprint as part of ESG reporting. For a transformed IT department, aligning with sustainability might mean choosing vendors with green credentials—like Shopify, which has initiatives like the Shopify Sustainability Fund.
Transformation is at its clearest in action, so let’s examine two concrete case studies of enterprises that have undergone IT transformation in the commerce realm, highlighting their challenges, approaches, and outcomes. Each example ties back to the core payoff: faster execution, more predictable delivery, and compounding surplus value over time.
Challenge: Belstaff, a British luxury apparel brand founded in 1924, faced a situation common to many legacy retailers. They had fragmented, outdated systems, including a separate ecommerce platform, isolated POS in stores, and a monolithic ERP, all stitched together in a costly and inflexible way. Technical debt was high; their IT was largely outsourced at great expense, yet the architecture was a “black box” that the internal team found hard to adapt. As Belstaff’s director of IT Navid Jilow put it, “Even though the system was broken, it was the system we know.” But not changing meant falling further behind.
Approach: Belstaff launched “Mission Phoenix,” a code name symbolizing rebirth from the ashes. They decided on a big-bang transformation: replacing their entire commerce stack in one coordinated effort. The centerpiece was moving to Shopify Plus for a unified commerce platform. Alongside, they implemented a new cloud-based ERP (NetSuite) and middleware to connect everything. They partnered with a Shopify Plus agency for the headless front-end development and used Shopify’s APIs to integrate with their ERP and other tools.
Results: The transformation was a resounding success. Belstaff was able to eliminate a lot of legacy costs and moved away from expensive outsourced IT contracts and decommissioned servers/software licenses, saving significantly on those costs. They achieved the goal of unified commerce: now stores and online operate on one platform, giving them a full view of customers. Now, over 30% of customers are acquired through email marketing, which is powered by unified data.
Even more valuable, Belstaff set themselves up for the future and are now positioned for 20–30 years of innovation. With a simpler, unified foundation, teams can launch new capabilities faster—without rebuilding brittle integrations each time.
“We really have been able to turn around the position that we were in before and get rid of some of the really expensive costs we had, but also be more agile at the same time,” Navid says. “The website is very compelling, it’s got an excellent customer experience journey, our technology stack that supports that is great and easy to use.”
Belstaff’s “big bang” cutover is a useful reminder: with the right platform and governance, transformation can be fast and predictable—unlocking long-term surplus value.
Challenge: Kooks is a 60-year-old family business manufacturing high-performance exhaust systems for cars and racing. They had been selling wholesale to speed shops and dealers as well as DTC, but their previous digital setup was limited—a custom website with poor search and no online B2B ordering, plus disconnected systems for inventory and orders. The site was slow and hard to use. Internally, they lacked real-time inventory visibility, and online orders weren’t syncing properly with manufacturing inventory, causing issues.
Approach: Kooks decided to unify and modernize their commerce on Shopify Plus, with a focus on both DTC and B2B channels. They partnered with an agency that specializes in manufacturing commerce to implement a solution. On the DTC side, they built a new Shopify online store with a custom theme and robust search/filtering.
Over on the B2B side, they used Shopify’s native B2B features to create a wholesale portal integrated with the same back end. That means dealers can log in, see their specific pricing, and order online with ease. They integrated Shopify with their ERP to sync inventory and orders in real time.
The new site loads faster and is mobile-responsive, which is crucial given that many car enthusiasts use mobile at track events or garages. With Shopify, they replaced a piecemeal system with a unified commerce platform for both retail and wholesale.
Results: Kooks achieved impressive outcomes, including a 22% increase in conversion rate on their DTC site and a 38% reduction in TCO.
“Before switching to Shopify, our old website held us back—we lacked analytics, marketing tools, B2B capabilities, had no live inventory or search functionality, and were stuck with a platform that was restrictive and hard to scale,” says Georgia Kryssing, sales and marketing director at Kooks.
Those gains map directly to the transformation payoff: faster execution (teams can launch and iterate), lower total cost, and better outcomes for customers and dealers.
Your platform choice can determine whether transformation compounds into value, or creates disruption. In IT transformation, you actually want both speed and endurance, which means picking a technology partner that accelerates your journey and continuously innovates with you. Here are the key criteria and considerations when selecting that partner.
Look for a platform that is proven at enterprise scale and can keep pace with change without adding complexity. Platform maturity means it’s stable, secure, and feature-rich out of the box. For example, Shopify Plus is a mature platform used by millions of brands, so it’s battle-tested.
At the same time, gauge the vendor’s R&D investment and roadmap. How frequently do they release new features? Are they leaders in adopting new tech? You want a partner that keeps you ahead of the curve, not one you outgrow in two years. Shopify is known for a high cadence of innovation: Shopify invested $1.4 billion in R&D in 2024.
When choosing a platform, analyze the full cost implications, not just licensing. Some questions: Is pricing transparent and scalable? Do costs stay the same as you scale? Shopify, for example, has a straightforward pricing model and often ends up cheaper because so much is included (hosting, security, CDN, etc.).
Also consider hidden costs: Will this platform require a lot of custom development or maintenance to keep the business moving? With Shopify, many features are built in or available as reasonably priced apps, reducing custom dev costs. An independent study showed Shopify offers 33% better TCO on average.
Examine the partner’s track record in implementations, especially for on-time, on-budget delivery at enterprise scale. Do they have a methodology or program? What’s their average implementation timeline for similar clients? Ask for proof of speed and predictability: average timeline, on-time delivery, and on-budget performance for comparable scope.
With Shopify’s approach, for example, brands were 66% more likely to launch on time and 3x more likely to stay on budget. This is the anxiety reducer for CTOs: transformation doesn’t have to mean 18-month disruption.
No platform exists in isolation. Evaluate how well it plays with others and extends. Key here is API quality: Is there comprehensive, well-documented API access to all needed functions? Shopify is API-first with GraphQL and REST endpoints for almost everything, plus webhooks, which means you can integrate anything from ERPs to custom front ends if needed.
Also, check for prebuilt integrations: Does the platform have connectors for popular systems you use? The Shopify App Store has many integrations ready. A strong ecosystem reduces integration sprawl by letting teams adopt proven connectors instead of building (and maintaining) one-off custom work.
Consider the level of support and customer success services the partner provides for enterprises. Will you have a dedicated account team or solutions architect to assist? Check if they offer migration assistance or programs, too—many have onboarding specialists or even incentives. Additionally, look at their service-level agreements (SLAs) for uptime and support response for enterprise contracts. You need assurance they’ll be there if something goes wrong at 2 a.m. on Black Friday.
Support is part of predictability: clear escalation paths, migration guidance, and enterprise-grade responsiveness reduce overall downtime risk.
Finally, evaluate how the partner’s platform performs in metrics that matter for revenue, such as site speed, conversion rates, and checkout optimization. For example, checkout is mission-critical. Shopify’s checkout is known to convert extremely well. Research from a Big Three management consulting company found that Shopify’s checkout converts 15% better on average than other platforms, with top brands seeing up to 36% higher conversion.
When you evaluate partners through the lens of speed, predictability, and total cost, the goal becomes clear. Choose a platform that reduces maintenance, shortens time to value, and keeps teams shipping—without trading agility for risk.
IT transformation isn’t optional—it’s a continuous business imperative. For enterprise teams, the goal is to build an operating model that can absorb disruption and keep shipping. To recap a few key takeaways:
Enterprise IT transformation is the foundation for competing in modern commerce. Organizations that move quickly gain compounding advantages: faster innovation cycles, lower operational costs, and the agility to capitalize on market opportunities in real time.
While many enterprises feel stuck between legacy systems and risky migrations, that tradeoff is no longer relevant. Shopify gives teams a faster, more predictable path to IT transformation, so they can modernize without disruption, respond to change with confidence, and move from “Should we?” to “How fast can we?”—with clear time to value.
IT transformation modernizes core infrastructure, systems, architecture, and operating models to improve performance, scalability, and cost. Digital transformation builds on that foundation to change business models and customer experiences. IT transformation enables digital transformation, but they are not the same thing.
IT transformation timelines vary by scope. Targeted initiatives (cloud migration, platform re-architecture) can take 3–9 months, while enterprise-wide transformations often take 12–36 months. Shopify can accelerate these timelines—research shows Shopify implementations average 20% faster than competitors, with enterprise brands 66% more likely to launch on time.
The biggest IT transformation challenges are resistance to change, complex data migration from legacy systems, budget overruns from underestimating scope, and integration complexity across ERP, CRM, and custom applications. Successful transformations rely on strong governance, phased delivery, and executive alignment.
IT transformation costs should be evaluated using a total cost of ownership (TCO) framework that accounts for the full lifecycle: acquisition, implementation, integration, training, ongoing operations, and eventual upgrades or decommissioning—not just up-front spend. Independent research shows Shopify delivers 33% better TCO on average compared to competitors.
IT transformation success is measured through a KPI framework covering speed (time to launch, deployment frequency), cost (TCO reduction, infrastructure efficiency), revenue (conversion, new digital revenue), and innovation (feature velocity, experimentation rate, integration flexibility).
