The Covid-19 pandemic hastened digital transformation for many businesses. In just over
a year, organizations learned to design, test, release and even retire software and
business services at a pace they had previously not imagined was possible.
According to McKinsey Global Surveys,
Companies have accelerated the digitization of their
customer and supply-chain interactions and of their
internal operations by three to four years. And the share of
digital or digitally enabled products in their portfolios has
accelerated by a shocking seven years.
Although the need for digital transformation grows, few manage it properly. As McKinsey notes elsewhere, about 70% of digital transformations fail, while only 30% succeed.
In the past, digital transformation was driven largely by the need to better serve customers. As a result, companies were often cautious about how quickly they introduced new technologies for fear that their customers wouldn’t be ready or able to adapt to change. At the beginning of 2020, 67% of U.S. CEOs expressed concerns about migrating all of their business to the cloud. The pandemic has largely quelled those fears by making digital innovation a requirement for survival.
As a result, the post-pandemic world is increasingly being defined by software. Organizations across industries are embedding software in their products — software-defined assets — and connecting those products to their operations and ecosystems, creating connected software-defined assets. These cyber-physical assets need continuous development, upgrading and retiring. The digital lifecycle management (DLCM) process requires platforms to operate them, pipelines to power the value stream and the core capability to evolve them. To succeed, all organizations will need to make software engineering a central activity of their business.
Software engineering capabilities ensure that organizations can compete and respond to change, whether in market conditions or highly regulated environments. In a software-defined business, product updates and enhancements are delivered daily, weekly or monthly to connected energy systems, health care technologies, civic infrastructure and more.
This new operating model will naturally segue into AI-driven predictive and preventative operations, allowing organizations to move away from responding to outages and fixing broken systems and move toward more resilient systems, reducing the costs of operational processes and innovation. A software-defined model also facilitates and supports a virtual workforce, providing organizations with access to a richer talent pool and the cost and labor flexibility that enables a business to scale seamlessly.