Although monumental resources and investment have been applied to digital transformation, the effort has not equaled success. Data is still hard to access, organize, and use. Leaders struggle to understand how to connect strategy to execution. Workforce and organizational culture barriers remain. Return on investment is difficult to demonstrate, leading to an endless cycle of vendor testing. Where investments are made, use cases often don’t scale as anticipated. These issues are compounded by the realization that what works for one use case often doesn’t translate to others that seem similar on the surface. As demonstrated in the visual above, digital transformation presents many possibilities and starting points – plant floor, supply chain, engineering, smart services and products, etc. The opportunities often require a range of disruption to traditional ways of operating, from the potential for massive revamping of business and work processes to completely new models for customer engagement.
Making sense of these myriad opportunities requires some means to filter decision making on which path(s) to take, why, and in what order. As organizations contemplate the breadth of these opportunities, a natural line of thinking arises: a technology or set of technologies (e.g., platform) can be identified and purchased to drive all or most aspects of change.
As a result, conversations become technology centric. Digital transformation turns into the pursuit of the silver-bullet solution or a proof-of-concept of the latest-and-greatest technology. Striving to get a potentially high-risk decision right, organizations look to compare solution techniques, tools, and technology architectures in “apples-to-apples” ways, even when that’s not possible.
