Being a digital product leader in an enterprise organisation comes with its own set of challenges. While there are shared struggles across all organisations—start-ups, SMEs, and enterprises alike—the scale, complexity, and constraints of an enterprise environment make these challenges fundamentally different.
At a start-up, digital product leaders often grapple with limited resources, rapid pivots, and the pressure to find product-market fit. In small to medium-sized businesses, the focus is often on scaling operations, optimising existing products, and balancing agility with stability. However, in an enterprise, digital product leadership is less about moving fast and breaking things, and more about navigating intricate structures, aligning multiple stakeholders, and driving digital transformation within established legacy systems and processes.
This is not just a matter of scale—it’s a fundamentally different playing field. In an enterprise, a digital product is rarely an isolated entity; it exists within a vast ecosystem of interconnected platforms, compliance requirements, business functions, and customer touchpoints. The complexity is not just technical but also organisational, requiring leaders to manage competing priorities, long decision-making cycles, and entrenched ways of working.
In this article, we’ll explore the unique challenges faced by enterprise digital product managers and draw on case studies to show how some enterprise brands address them.
1. Overcoming inertia
In large enterprises, deeply embedded processes, legacy systems, and historical decision-making create a strong path dependency that resists change. This structural inertia can stifle innovation and complicate the adoption of modern technologies or methodologies. Digital product leaders must navigate constraints imposed by entrenched infrastructures, risk-averse governance, and organisational resistance—factors that make driving meaningful transformation a complex and strategic challenge.
Case study: ANZ’s digital overhaul
ANZ Bank, facing outdated legacy systems and organisational resistance, embarked on a $2.5 billion digital transformation to modernise its banking infrastructure. The initiative includes ANZ Plus, a new customer platform set to replace legacy systems by 2027, improving scalability, automation, and customer experience. Challenges included cultural inertia, regulatory complexity, and integrating 1.2 million Suncorp Bank customers. By prioritising platform modernisation, operational efficiency, and regulatory alignment, ANZ is positioning itself competitively in the digital banking space, demonstrating the importance of strategic investment and phased transformation.
2. Balancing a healthy budget with strategic spending
Enterprise digital product teams operate with significantly larger budgets than start-ups or SMEs, enabling substantial investments in talent, technology, and innovation. However, this financial advantage can also lead to inefficiencies—such as over-engineered solutions, redundant tooling, or misaligned spending that fails to generate meaningful value. Striking the right balance requires recognising that not all expenditures yield immediate returns.
While cost optimisation is crucial, not all expenditure yield immediate returns. Strategic investments in infrastructure, R&D, and scalable capabilities are essential for long-term competitiveness. Effective budget management demands disciplined leadership, rigorous prioritisation, and a clear understanding of when to streamline costs versus when to invest proactively for sustainable growth.
Case study: Amazon’s investment in AI and logistics
Amazon continues to focus on long-term strategic spending to maintain its market dominance. In 2023, it invested $4 billion in AI startup Anthropic to enhance its generative AI capabilities, improving everything from customer recommendations to cloud services. This investment reflects Amazon’s push to incorporate AI into its operations, such as inventory management and supply chain optimisation. Alongside this, Amazon expanded automation in its fulfilment centres by integrating robotics, drones, and AI-driven systems. These innovations improve efficiency, reduce human error, and speed up delivery times, enhancing the overall customer experience. Despite concerns over high costs, these investments help Amazon maintain its competitive edge, ensuring scalability, operational efficiency, and continued market leadership in e-commerce and logistics.
3. Designing for an ecosystem-oriented experience
As digital products become more integrated with a wide range of services, platforms, and devices, ensuring seamless functionality within these ecosystems is crucial for adoption and ongoing engagement. For enterprise digital product managers, this involves designing solutions that work effectively on their own while also complementing and enhancing other tools in the ecosystem. Achieving this requires a combination of strategic planning, strong integration capabilities, and a deep understanding of user needs across various touchpoints. A successful ecosystem-oriented design approach focuses on creating interoperable experiences that deliver value both individually and within the larger digital environment.
Case study: Schneider Electric’s open IoT platform for better integration
Schneider Electric aimed to enhance interoperability and openness within its Internet of Things (IoT) platform to integrate more effectively with diverse services, platforms, and devices. Through a strategic partnership with THIS, Schneider developed an open business platform that connects global technology partners, enabling collaborative innovation. This initiative not only bolstered the standalone functionality of Schneider's solutions but also ensured seamless integration within the broader digital ecosystem. By enhancing connectivity and fostering ecosystem-wide collaboration, Schneider Electric improved customer-centric solutions, driving greater adoption and long-term engagement.
4. Ensuring scalable experience management
Scaling digital products introduces the challenge of maintaining consistent, high-quality user experiences across diverse audiences, geographies, and use cases. Enterprise product managers must not only provide seamless and personalised experiences but also navigate increasing operational complexity. This requires a strategic approach to experience management, where scalability, flexibility, and efficient resource allocation are key to maintaining user satisfaction while meeting expanding demands. Successful management hinges on designing adaptable solutions that can evolve with user needs and operational requirements across multiple environments.
Case study: Qualtrics' cross-lingual multi-task models
In 2022, Qualtrics, a leader in experience management, addressed the challenge of scaling text analysis across 12 languages to serve a global audience. To optimise operations and maintain high-quality results, they adopted cross-lingual and multi-task modelling techniques, consolidating multiple models into a single, unified deployment. Through model compression and distillation, they reduced latency and hardware costs, striking a balance between performance and efficiency. This innovative approach enabled Qualtrics to scale their capabilities seamlessly, delivering consistent, high-quality experiences across a wide range of linguistic and cultural contexts, while enhancing operational efficiency and ensuring a personalised experience for users worldwide.
5. Managing technical debt
Technical debt—resulting from rapid solutions, legacy architecture, or suboptimal code—can significantly impede product development and introduce security vulnerabilities. Proactively managing technical debt is critical to sustaining agility, enhancing security, and ensuring a seamless user experience. Effectively addressing this debt requires a strategic approach to refactoring, regular technical audits, and prioritisation of long-term maintainability over short-term expediency. By managing technical debt, organisations can optimise their development processes, mitigate risk, and support scalable growth.
Case study: Credit Suisse's digital nudging strategy
In 2022, Credit Suisse implemented a digital nudging strategy to address technical debt within its software development processes. By integrating digital prompts into the development environment, the initiative encouraged developers to proactively identify and resolve instances of technical debt, such as outdated code and inefficient architecture. This approach not only enhanced code quality but also promoted a culture of continuous improvement and responsibility. By embedding these nudges into the daily workflow, Credit Suisse fostered greater accountability, enabling developers to tackle technical debt in real-time. The strategy ultimately strengthened the organisation’s agility and ability to deliver secure, scalable software solutions.
6. Transforming data governance
With increasing regulatory pressure and the growing complexity of data, modernising data governance has become essential for ensuring compliance, security, and effective data utilisation. Establishing robust data governance frameworks is critical to maintaining data integrity, protecting user privacy, and enabling informed strategic decision-making. This requires a comprehensive approach that includes clear data stewardship, transparent policies, and advanced technologies to monitor and enforce governance. By transforming data governance, organisations can mitigate risks, enhance operational efficiency, and unlock the full potential of their data assets.
Case study: Microsoft’s Azure data governance update
Microsoft rolled out an enhanced data governance framework for Azure, designed to address growing demands for compliance, security, and data quality while supporting advanced AI and analytics capabilities. The framework integrates comprehensive governance tools and processes that enable customers to efficiently manage data access, track data lineage, and monitor compliance across Azure workloads. By increasing transparency and control, this update not only strengthened regulatory adherence but also empowered businesses to leverage data-driven technologies like AI with greater confidence. The result was a more efficient, secure, and scalable approach to data governance, enabling organisations to fully harness the power of their data while mitigating risks.
7. Fostering cross-departmental collaboration
Siloed operations can significantly hinder innovation and operational efficiency, particularly in large organisations. Fostering cross-departmental collaboration is essential to driving enterprise-wide success. Effective collaboration between teams—such as product development, marketing, design, and IT—ensures a unified approach to creating cohesive, user-centric experiences. By facilitating open communication and shared goals, cross-functional teamwork enables the integration of diverse expertise, resulting in innovative solutions and more streamlined execution across the organisation.
Case study: Google’s Project Synergy
In 2023, Google launched Project Synergy to eliminate silos between its AI and Cloud divisions, aiming to accelerate the development of integrated AI-driven cloud solutions. By aligning these key teams, Google streamlined product development processes, reducing inefficiencies and fostering deeper collaboration. The initiative not only enhanced operational efficiency but also drove innovation, enabling the creation of more powerful and seamless solutions. Project Synergy significantly strengthened Google’s competitive position in both the AI and cloud markets, unlocking new opportunities for integrated offerings and reinforcing its leadership in the technology space.
8. Integrating cutting-edge technologies
To maintain a competitive edge, digital product managers must proactively adopt and integrate emerging technologies that enhance user experience and address evolving market needs. Whether overseeing digital products, staying ahead of technological trends is crucial for meeting dynamic user expectations. This involves not only incorporating new tools and capabilities but also ensuring their seamless integration into existing systems, optimising performance, and driving innovation. Strategic adoption of cutting-edge technologies allows organisations to deliver enhanced functionality, improve user satisfaction, and maintain agility in a rapidly changing digital landscape.
Case study: Adobe’s AI-powered Creative Cloud
In 2023, Adobe enhanced its Creative Cloud suite by integrating generative AI tools, fundamentally transforming digital creativity and improving operational efficiency. Features like automatic image generation and content customisation have drastically reduced the time spent on creative tasks, allowing users to focus more on innovation and high-level design. By leveraging machine learning and AI, Adobe has empowered creative professionals, streamlined workflows, and solidified its position as a leader in the competitive creative software market. This shift underscores the vital role of cutting-edge technology integration in an AI-driven landscape, enabling Adobe to meet the evolving demands of its user base while setting new standards for creativity and productivity.
With two decades of experience working with enterprise brands, we’ve seen these challenges firsthand and understand how complex they can be.
If you’re interested in discussing options to solve your current or foreseen future challenges, feel free to reach out to our team.
You can also explore our work or download our latest whitepaper: The Ultimate Guide to Creating a Successful Digital Product Strategy in 2025.
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