How Enterprise Architects can get more support for technology led innovation
Enterprise Architects are increasingly vital as guides for technology-led innovation, but they often struggle with obstacles like siloed teams, misaligned priorities, outdated governance, and unclear strategic value. The blog outlines six core challenges—stakeholder engagement, tool selection, IT-business integration, security compliance, operational balance, and sustaining innovation—and offers a proactive roadmap: embrace a “fail fast, learn fast” mindset; align product roadmaps with enterprise architecture; build shared, modular platforms; and adopt agile governance supported by orchestration tooling.
Agi Marx, June 18, 2025
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Fast-tracking data initiatives from prototype to production – Part 1
Summary This blog will go through four core solutions for scalable innovation. Most data and AI pilots end up in the “POC graveyard,” never scaling to production or delivering ROI. The problem isn’t the technology—it’s the lack of strategy, data readiness, ownership, and focus. Common pitfalls include unclear success metrics, poor-quality data, scattered pilots, and…
How Enterprise Architects can get more support for technology led innovation
Enterprise Architects are increasingly vital as guides for technology-led innovation, but they often struggle with obstacles like siloed teams, misaligned priorities, outdated governance, and unclear strategic value. The blog outlines six core challenges—stakeholder engagement, tool selection, IT-business integration, security compliance, operational balance, and sustaining innovation—and offers a proactive roadmap: embrace a “fail fast, learn fast” mindset; align product roadmaps with enterprise architecture; build shared, modular platforms; and adopt agile governance supported by orchestration tooling.
Securing stakeholder engagement and collaboration for your self-service platform
To succeed in today’s data-driven environment, organizations must prioritize ethical data use, seamless tech integration, and cross-functional collaboration. This blog recommends establishing clear data privacy and ethics policies, aligning AI initiatives with governance frameworks, and using a self-service platform to integrate legacy and modern systems.
Understanding the how of digital transformation: part 3 – scale and optimize
Digital transformation doesn’t stop at initial rollouts—it’s a continuous journey of scaling and refining successful initiatives. First, identify pilots that delivered real value and scale them across teams, regions, or systems using cloud-native, scalable platforms
Understanding the how of digital transformation: part 2 – execution and implementation
This blog outlines how to execute digital transformation successfully by using agile methods, collaborative implementation, and phased technology integration. Key actions include adopting iterative frameworks like Scrum, building MVPs with cross-functional teams, using low-code tools for speed, and integrating new systems with legacy infrastructure.
Understanding the how of digital transformation: part 1 – planning and assessment
This blog highlights that effective digital transformation starts with structured planning and assessment. Begin by auditing your current tech, processes, and talent to identify gaps, then define clear business-aligned goals and KPIs.
