10 Real Business Problems and How Product Engineering Solves Them

Summary: From fragmented systems to AI initiatives without ROI, the business challenges have become complex. But these challenges have a solution: software product engineering. In this article, we explain how enterprise product engineering can offer actionable solutions to these business challenges. Plus, we discuss how practical product engineering solutions simplify operations, reduce costs, and drive innovation.

In 2019, McKinsey reported that 70% of digital transformation and software product initiatives fail. That was more than half a decade ago. Pre-pandemic. Pre-AI boom. Before low-code platforms became mainstream.

Today, despite the explosive advancements in technology, software statistics suggest that businesses are still struggling to turn tech investments into real impact. The reason isn’t access to technology but the approach.

Too many organizations treat technology as a checkbox. They are just building tools for the sake of building. What they’re missing is: Enterprise Product Engineering.

Product engineering services are a strategic, end-to-end way to solve real business problems. It creates value for enterprises by offering a structured, outcome-driven approach that helps businesses not only adopt technology but also use it effectively to solve their most pressing problems.

But most businesses are not even aware of this. They don't know which problems software product engineering for digital transformation can solve.

In this article, we'll share insights from years of hands-on experience across industries.

We’ll outline ten of the most common business problems and illustrate how product engineering for enterprises solves business challenges.

How Product Engineering Solves The Most Pressing Enterprise Challenges?

Every business faces unique challenges, but some struggles remain common. In our experience of working with over a thousand clients, here are the most recurrent business problems we have heard, which can all be solved with planned product engineering for enterprises.

1. Our tech stack has outgrown our ability to manage it. Every single change feels like open-heart surgery.

Most enterprises have modernized their operations over the past decade. They’ve migrated workloads to advanced software tech stacks that include cloud platforms like AWS, Azure, and GCP. On paper, this modernization sounds like progress. But in reality, it results in a sprawling ecosystem. Hundreds of APIs, microservices, SaaS tools, CI/CD pipelines and analytics platforms, don’t simplify operations. Instead, they slow down development, increase the risk of errors, and drive costs sky-high.

Modern product engineering strategies for large enterprises help solve this problem. It takes a holistic approach, which includes

• Auditing the existing stack
• Identifying redundant components
• Implementing modular, scalable architecture

With microservices, API governance, and automated testing pipelines, teams can isolate changes without breaking the system. For one, this reduces technical debt. But what it also does is accelerate feature delivery and improve reliability.

In short, with advancements in technology, ecosystem sprawls are becoming common. Product engineering drives software product modernization, which transforms tangled, fragile ecosystems into manageable, high-performing engines that support your business growth.

2. We’re investing heavily in AI, but can’t operationalize it

With so much hype about AI taking over every aspect of human life, most organizations have started with AI pilots. This means everyone is pumping cash into ML models, predictive analytics, and gen AI tools. But a vast majority of them struggle to move beyond experimentation. The models sit in notebooks. Proofs-of-concept stall. Businesses never see real ROI. The challenge here isn’t the technology itself. Instead, it is more about integrating AI into existing systems, workflows, and decision-making processes.

AI-driven product engineering services bridge the gap between AI research and operational value. It helps:

• Design end-to-end pipelines
• Integrate AI models with core business applications
• Automating inference and monitoring teams

All this together ensures AI insights are actionable and reliable. Clear product-focused roadmaps prioritize high-impact use cases. Modular, scalable architectures make future iterations faster and safer. And instead of AI being a side project, product engineering for AI implementation makes it a living part of the business. The outcome? Tangible results from custom software development and enterprises get to capitalize fully on their AI investments.

In short, organizations often invest heavily in AI but fail to realize value because models remain isolated. AI-driven product engineering integrates, automates, and scales solutions to deliver tangible, actionable results.

3. We ship faster, but see no meaningful results

Do business outcomes feel slow even when you ship a dozen updates every quarter? Well, that's the productivity paradox, a challenge enterprises face with DevOps and Agile. You invest heavily in technology and processes, but business outcomes don't improve proportionally.

Well, that's because when Agile and DevOps weren't designed to be implemented in isolation. But when that happens, teams may ship features rapidly, but problems deter meaningful value. Problems like:

• Interdependencies
• Delayed analytics
• Fragmented workflows

Software product engineering for digital transformation resolves this by bringing software product discovery, design, development, QA, and analytics together. When tech strategies are aligned with teams and business objectives, measurable results are seen.

With this connection between velocity and value, software product development becomes a strategic move that transforms rapid delivery from a metric of activity into a driver of impact.

In short, shipping updates quickly often fail to improve business outcomes because fragmented workflows and misaligned processes limit value. Software product engineering aligns teams, technology, and objectives to turn speed into measurable impact.

4. We were promised efficiency, but we spend even more on infrastructure now

Most cloud environments, tech tools, and deployment platforms promise efficiency. They show you how much you could save with what they are offering. But more often than not, businesses that act on these latest software development trends with insufficient FinOps practices end juggling between the multi-cloud environments, have unmanaged deployments, and face tool sprawls.

This drives costs higher and affects margins, prompting CFOs to scrutinize engineering budgets.

Reducing cloud costs with product engineering addresses these challenges. Software product engineering strategies that facilitate this cost reduction include:

• Refactoring workloads
• Automating scaling
• Embedding continuous cost monitoring within systems.

By designing infrastructure with efficiency in mind, organizations gain visibility, control, and predictability over resource usage.

Enterprise product engineering also ensures that tech investments align with business objectives. It ensures performance maintenance and agility while avoiding unnecessary expenditure. The result is a system where cost efficiency and operational excellence go hand in hand.

In short, cloud tools often promise efficiency but increase costs when unmanaged. Product engineering refactors workloads, automates scaling, and embeds cost monitoring, aligning infrastructure with business goals for predictable, efficient operations.

5. Every product, region, or department built its own front-end and back-end

Customers today expect seamless, consistent digital experiences. But when an enterprise's internal systems are fragmented, that's hard to deliver. If different departments (or verticals!) in your organization also have their own frontend and backend, you'd know the struggle of:

• Fragmented user experiences
• Inconsistent APIs
• Disconnected workflows

This frustrates customers, undermines brand coherence, and creates operational inefficiencies that slow growth.

Product engineering solutions tackle these challenges by creating unified experience layers. Plus, the shared design systems align teams around a single vision.

Composable architectures give way to omnichannel platforms that are consistent, scalable, and adaptable. With software product engineering for digital transformation, different types of disconnected software systems are turned into well-integrated ecosystems. That's what drives user delight, stronger engagement, and better business positioning.

In short, fragmented systems across products or departments create inconsistent experiences and inefficiencies. Product engineering unifies front- and back-ends with composable architectures, delivering seamless, scalable, and engaging digital experiences.

6. We have analytics, but our decisions still rely on gut feelings

Many organizations have analytics, but they are unable to use it for actual decision making due to siloed data and disconnected teams. It slows insight-to-action, causing missed opportunities, lower efficiency, and slower innovation.

Product engineering solutions solve this by building real-time intelligence pipelines, integrating predictive analytics, and creating actionable dashboards within workflows. A clear software development guide ensures data flows and integrations are implemented consistently. By leveraging software product engineering for digital transformation, enterprises turn raw data into timely, actionable insights, enabling smarter decision-making, improving efficiency, and driving continuous innovation. Fragmented analytics become a strategic asset, powering growth and competitive advantage.

In short, siloed data delays decision-making, leaving teams reliant on gut instincts. Product engineering embeds real-time analytics and predictive insights into workflows, enabling faster, data-driven decisions and measurable business improvements.

7. We depend on five different vendors just to deliver a single release

Scaling enterprise operations often brings unexpected challenges. The most persistent one? Coordinating multiple vendors to deliver a single product or release. This usually happens due to fragmented responsibilities, overlapping work, and unclear accountability. The result? Slow delivery, increased costs, and operational friction.

Now it might sound counterintuitive to bring in another vendor for enterprise software product engineering services at this juncture. After all, why would you want to add more vendors to your already unmanageable list of vendors?

Well, that's because the new partner can be the one that consolidates all the vendors. With that, you can have a single point of responsibility across the entire lifecycle. Right from software product strategy consulting to design, development, deployment and ongoing support, a product engineering partner will also ensure outcomes are measured against meaningful business metrics, not just completed tasks.

When all that happens, your projects benefit from:

• Reduced dependency complexity,
• Streamlined collaboration,
• Internal teams concentrated on priorities, not vendor issues

Software product engineering can take you from a tangled vendor to a reliable engine. One that supports busts harmful product development myths, ensures faster delivery, better quality, and sustained operational efficiency.

In short, relying on multiple vendors slows delivery and increases complexity. A product engineering partner consolidates responsibilities, streamlines collaboration, and ensures faster, higher-quality releases with clear business outcomes.

8. We have tools and budget, not the right engineering muscle

A decade ago, technology budget was scarce. But today, most organizations have the budget (and tools!) to innovate with technology. What they lack now is the right engineering expertise. Shortages in AI/ML, full-stack development, and product-focused talent slows down teams. Local hiring is often slow (not to mention costly!) and offshoring takes time, effort, and expertise.

To tackle this business problem, organizations need specialized resources to drive scalable innovation. Software product engineering services address this gap. With the right partner, you can get flexible, integrated squads that complement existing teams. These squads bring a mix of AI, DevOps, and full-stack capabilities. For organizations, this means accelerated delivery without hiring/resourcing hassles.

By leveraging enterprise product engineering, companies can maintain development momentum. If and when needed, they can rapidly bring new products to the market. And they can reduce dependence on scarce in-house talent. This approach transforms talent constraints from a bottleneck into a strategic advantage and enables sustained innovation and growth.

In short, having tools and budget isn’t enough without the right engineering talent. Product engineering provides specialized, flexible teams that accelerate delivery, reduce talent bottlenecks, and enable sustained innovation.

9. We made digital platforms, but they’re getting all the results.

Digitizing existing workflows is no longer enough. Digital-native competitors are not just adopting technology, they are reimagining business models, reshaping customer experiences, and creating entirely new value propositions. Enterprises that focus only on modernization risk falling behind. After all, incremental improvements will never be able to match the pace of software product innovation in the market.

Modern product engineering strategies enable organizations to continuously evolve their digital offerings by:

• Embedding data-driven insights into product development
• Leveraging adaptive pricing models
• Updating products iteratively

With that, companies can keep pace with changing customer expectations. This approach ensures that digital investments translate into real competitive advantage. It further allows enterprises to not just participate, but actively shape the market, stay relevant, and gain leadership.

In short, simply digitizing workflows isn’t enough as competitors innovate rapidly. Product engineering embeds data-driven insights, iterative updates, and adaptive strategies to turn digital investments into real market advantage.

10. We’re constantly patching, monitoring, and updating, but it never feels secure enough

Keeping systems secure and compliant often feels like running on a treadmill. Threats evolve faster than teams can respond. Multiple apps, APIs, and cloud environments make regulatory compliance a constantly moving target. Whether GDPR, HIPAA, or SOC2, enterprises find themselves:

• Reacting to incidents
• Patching vulnerabilities
• Updating controls

Yet the sense of security remains elusive.

With enterprise software product engineering services, security and compliance become standard. It becomes integral to the software development process rather than afterthought. How? With automated vulnerability scans, continuous monitoring, and DevSecOps practices. This ensures risks are identified and mitigated proactively. By embedding security into design and delivery pipelines, organizations can also reduce exposure and lower security debt. The result is that developers can focus on innovation, not firefighting.

In short, constant patching and monitoring rarely deliver true security. Product engineering embeds security into development with automated scans, continuous monitoring, and DevSecOps, proactively reducing risks and freeing teams to innovate.

Getting Started with Product EngineeringTransitioning to enterprise product engineering isn’t just about new tools. It’s about turning complexity into strategic advantages. The outcomes depend on partnering with experts in software product engineering. You don't need a team that just brings tech to the table. You need a partner who brings deep technical expertise and hands-on experience too. A team that understands your business goals and the technology landscape.At Radixweb, our product engineering solutions consolidate systems, build composable architectures, embed AI, and ensure continuous security, integrating full-stack, AI/ML, and DevOps expertise seamlessly into client environments.With software product engineering for digital transformation, we've helped organizations achieve faster time-to-value, higher efficiency, and continuous innovation. With us, technology becomes a driver of growth, better experiences, and cost reduction. Schedule a no-sales strategy consultation with Radixweb to discover our approach to solving enterprise challenges and delivering sustainable business advantages.