How to Build a Digital Transformation Roadmap for Your Organization

Particularly for established enterprises, the first step of a digital transformation journey is likely to focus on adopting new technologies and technical approaches, and possibly retiring existing technical debt. It often involves migrating workloads to the cloud and modernizing legacy technologies. While this is largely a technology-focused effort, it also requires changes to existing IT capabilities and operating models. Almost immediately organizations migrating to the cloud are likely to see returns on their efforts, including reduced cost of ownership, improved IT staff productivity, improved operational resilience, and greater technical agility. Recent studies of AWS customers revealed 50% lower cost of operations over five years, 47% more efficient IT infrastructure management, more than twice as many features delivered per year, a 69% reduction in unplanned downtime, and 45% fewer security incidents per year.

For instance, travel company Expedia Group, who shifted the majority of its mission critical applications and nearly 20 years of data from its on-premises data centers to the cloud, sped up vendor payments, saved millions of dollars, and was able to scale to handle hundreds of million website visitors each month. Global media company Discovery retired its on-premises data centers used for playout of content to broadcast, cable and satellite channels, moving those capabilities to the cloud to decrease costs, improve reliability, and accelerate their ability to deploy channels. And GE Aviation moved its development and production environments to the cloud, enabling new ways to share data across the two environments that wasn’t possible in their on-premise setup. In doing so GE accelerated innovation while being mindful of security and compliance, and shifted the IT teams focus from IT tactics to value creation.

With the right technical platform in place, attention shifts to optimizing the organization’s operating model in an effort to become more data-driven. Data helps organizations quickly validate strategic directions while minimizing risk, and accelerate time to market for their new innovations through better decision-making and the ability to predict business outcomes. Changes to operating models may include using new data and analytics platforms to derive actionable insights and improve customer experience, or using machine learning to automate business processes. This aspect of transformation is likely to be more complex than technological transformation as it involves enterprise-wide changes. However, the resulting benefits of improved operational efficiency, effectiveness, and agility will likely lead to outsized business outcomes. AWS customers have realized 35% more productive application development teams, and a 29% increase in time devoted to innovation.
 
As a dramatic illustration of how technological transformation in turn enabled operational changes, United Airlines realized that by collecting and analyzing organization data in real-time it could create the “intelligent airport,” using IoT sensors and machine learnings to improve the efficiency of its ground service operations including catering, fueling and gate readiness, bagging tracking and routing, and the end-to-end customer journey. The new operation models saved the company $120M, 1.3 million personnel hours, and reduced emissions by 7%. Volkswagen Group also made dramatic changes to its operating models in an effort to transform its automotive manufacturing and logistics processes, harness IoT capabilities and machine learning to connect systems across 120 factory sites, yielding a 30% increase in productivity and €1 billion in supply chain savings through greater efficiency.

The third aspect of digital transformation to consider is strategic transformation: reinventing business models. Business model reinvention involves reconsidering how organizations create customer value and capture the resulting profits. For those organizations whose current business models are threatened or have become unsustainable, this may include using digital technologies to enter new markets or industries. For those not threatened, business models can still be evolved to drive greater customer value, and to innovate new products and solutions that drive differentiation, competitive advantage, and long-term value while deepening customer engagement. These changes are likely to require new or improved business capabilities, which in turn drives the need for further operational and technological transformation.

Design, engineering, and entertainment software maker Autodesk realized entirely new lines of business from its technological and operational evolution. Moving to the cloud enabled Autodesk to deliver its software as a subscription-based service, with high availability and the ability to push out regular updates and new features. Over time Autodesk realized the power of the cloud to augment their customers’ work, and rolled out new capabilities using machine learning models including one that helps designers organize and sort through thousands of generative design options, and another that can help recognize models based on visual similarity. Financial services firm Goldman Sachs also took advantage of the cloud to create entirely new lines of business, including a consumer banking business with $110B in retail deposits, a cloud-native transaction banking platform, and Goldman Sachs Financial Cloud for Data, a new suite of cloud-based data and analytics solutions for financial institutions.