Article originally published on CIO.com.
Digital transformation visions crumble from a lack expertise. Don’t let yours be one of them.
Digital health is the convergence of the Digital and Genomic Revolutions specifically health, healthcare, living and society. Personal empowerment is the heartbeat of digital health making our lives better by managing, tracking and improving wellness for a healthier tomorrow. The realization of this healthier and seamlessly connected future will require orchestration between the physical and digital world. This orchestration will be conducted by digital experts.
What does it take to be an industry expert? Is it pure raw intelligence or is there a subtler side to expertise? In some instances, experts that are required to transform organizations and tap into top-line innovation growth, may be the same experts preventing adoption of your organization’s digital capabilities. There is a lack of expertise when it comes to digital transformations and applying digital technology to dramatically improve performance of an enterprise in all aspects of human society.
There is something sacred about the word “expert.” This role can’t be given; it can’t be won; and it isn’t issued with a promotion – it’s earned.
Two types of expertise
There are fundamentally two types of expertise: Routine and adaptive. Routine experts often assume that their current knowledge and their problem definitions are correct. Adaptive experts have the ability to apply knowledge to novel problems or atypical business challenges and reshape problem definitions.
Digital transformation visions crumble because of a lack of experts or the wrong kind.
Giyoo Hatano of Dokkyo University and Kayoko Inagaki of Chiba University” studied aspects of cognitive development in the 1980’s. The updated translation is that digital transformation is impossible when companies are made up of only routine experts.
Routine experts are unable to think beyond their models built on procedural knowledge. Routine experts rely on similar experiences from their past when building a solution framework. When problems arise that are atypical and do not fit historical problems, they get stuck. For example, the problem may require a new model such as introducing digital disruption.
Digital disruption occurs when new technology affects existing business models and how products and services create value. Those regarded as routine experts would apply the same models they have used for the last twenty years and find they do not work. This illustrates the real problem preventing digital disruption, attempting to solve new problems with procedural expertise.
That’s not to say routine experts are not effective. Procedural skills are used to efficiently solve everyday problems in stable environments. Unfortunately, stable does not describe the digital environment that influences business today.
Another type of expert is the adaptive (or conceptual) expert. These experts not only retain procedural skills, the base of routine expertise, but they also understand the reasoning behind the skills they demonstrate. They internalize the need for invention and they have the desire to understand the meaning behind these procedural skills. Routine expertise has a pattern that is prevalent in every industry. The test is to be able to describe ‘why’ something works, not ‘how.’ The combination of the past knowledge and the reason why it works enables adaptive experts to grasp the full domain of information surrounding the skill. Taking this past knowledge, adaptive experts will then identify even more efficient methods of performing the skill.
Bottom of Form
In 1983 Gentner and Stevens introduced the concept of mental models, in their book of the same name. Mental Models help us visualize the theory with a series of short studies. They explain that individuals can run mental simulations and make predictions on conceptual outcomes. We can logically infer that conceptual experts step beyond the cultural limits procedural experts experience and are able to explore problems more deeply than with simple trial-and-error. The desire to learn unlocks new thinking, removes conventional mental barriers, exposing raw talent.
Consider the following exercise:
“Two men played five games of checkers. Each won three games. How is this possible?”
Clearly, if the two men are playing against each other this problem is impossible to solve. Adaptive experts will already assume information is missing, constraints are flawed, and their problem is larger than what is being suggested.
After a few minutes most routine experts will realize the two men were not playing against each other and that the problem was indeed solvable. This example of restricted problem spaces, demonstrates how individuals build restricted definitions of problems. When you look at companies that are digitally innovative and companies that are not, the primary differentiating factor is the talent; each company defined the problem differently.
Growing digital innovation initiatives requires adaptive expertise to create a highly metacognitive organizational environment that promotes content knowledge, domain knowledge, and experimentation. Adaptive expertise is defined in the mind and fueled by the attitude that drives it.
The next time a team is assembled to deliver the next dermable (a type wearable that goes on your skin and can stand out like a tattoo, or blend into the color of your skin), swallowable, or nanobot, rethink who’s an expert.
Divergent thinking is essential for digital health creativity.