The article was originally published in May-June 2022 issue of the Harvard Business Review.
Keystone co-founder and Chairman, Marco Iansiti and Microsoft CEO, Satya Nadella, recently published an article in Harvard Business Review that summarizes three “pillars” of digital transformation (technology, architecture, and capability) and establishes a maturity model for the “stages” of digital transformation. Their insight is derived from years of research, examining why some companies struggle to reap the benefits of investments in digital transformation while others see successful results.
The authors break down digital maturity into five stages, based on their research examining hundreds of companies in manufacturing, health care, consumer products, financial services, aerospace, and pharma/biotech. In the traditional stage, while firms may benefit from pockets of innovation, they are typically organizationally and digitally siloed in a way that limits their ability to collaborate and innovate with data. As they mature, companies typically de-silo and change their ways of working to leverage real-time data to drive collaboration and experimentation. Companies in the highest levels of maturity (platform and digital native stages) leverage a comprehensive software and data foundation to support business units in developing innovative, AI and ML-enabled technologies. Ultimately, a successful digital transformation requires that all employees work together to rethink how every aspect of the business should operate.
Along with the article, the authors also published a survey that allows readers to understand the digital maturity of their organization, and highlights areas to focus on for continued transformation.
Summary: Many companies struggle to reap the benefits of investments in digital transformation, while others see enormous gains. What do successful firms do differently? This article describes the five stages of digital transformation, from the traditional stage, where digital and technology are the province of the IT department, through to the platform stage, where a comprehensive software foundation enables the rapid deployment of AI applications. The ideal is the native stage, whose hallmarks are an operating architecture designed to deploy AI at scale across a huge, distributed spectrum of applications; a core of experts; broadly accessible, easy-to-use tools; and investment in training and capability-building across the enterprise.