At a world-class research institute like the Broad Institute of MIT and Harvard, talent is explicitly our core strength. Talent, and its near cousin intellectual property, are not only our greatest assets but essentially our only assets. “Broadies”, working together with our collaborators, create, sustain and widely disseminate compelling scientific research, open source software and data to accelerate the understanding and treatment of disease.
"The drive for detail and increasingly fine grained understanding pulled us into our niches"
This desire to “create, sustain and enhance compelling research” extends to all functions, including IT where we are relentlessly focused on helping to “enable science”, our version of focusing on the business. To execute on this goal, we have to be thoughtful in the talent we recruit. This article focuses on how we think about talent and how the definition is changing in response to changes in technology.
It should be no surprise that in this highly technical environment, filled with ground breaking research, innovation at every level, and highly demanding, specialized, unpredictable needs there is one constant: the demand for truly top-notch talent. The catch is that the definition of top-notch is changing. An example is how the combination of mature cloud models and the machine learning revolution are shaping the definition of what is needed to succeed.
The Long View
One view of the history of technical careers is that over time the emphasis has moved from the “renaissance thinkers” who were famous for the breadth of their interests, to the development of very highly focused specialists in ever narrower disciplines. While this specialization allowed for amazing progress, it is often painted as generating a myopic view of the world, and an inability to talk across disciplines. The criticism is that individuals become so deeply entrenched in their chosen discipline that they lose the ability to see their work in context or to learn from other specialists.
Today, among all the concern we hear about artificial intelligence driven job obsolescence, we may be missing a perhaps more subtle opportunity. The revolution in machine learning, deep learning, data science and the related skills represents an opportunity for experts in many fields to pick their heads back up and look around again. The drive for detail and increasingly fine grained understanding pulled us into our niches. The advent of a capability that can learn from detail even better than we can opens the possibility for a new cross disciplinary renaissance.
Rather than removing people from the equation, I believe this revolution allows us to take learnings from one discipline, and without spending years mastering the details, ask correlative questions of our native specialty. This brings us back to the definition of “top-notch” talent. What is changing about that definition is best seen in the concept of the “T-shaped” professional.
Fit to a “T”
The observation is that individuals are most effective when they build on a deep understanding of a given topic (the vertical bar of the T) and then leverage some breadth of understanding across other disciplines to enrich their thinking (the horizontal bar.)
Our view is that having spent generations with increasing emphasis on the vertical strengths, the horizontal skill is re-emerging as the differentiator between average and top-notch talent. This shift in emphasis away from specialization doesn’t negate the need for deep understanding of your chosen discipline (or business challenge) but it does acknowledge that the ability to connect across disciplines can be more impactful than making the next incremental improvement in one particular discipline.
This has added resonance in that it fits with our experience of the world. Connectors are often the ones who make the intellectual leaps that create new markets or make breakthrough observations. They are the ones who see a solution in one business and apply it to a new industry. They are the catalysts who ask “why?” because they don’t know “why not”.
We believe recruiting and developing these connectors is at the heart of what it takes to build a truly exceptional IT function.
Collectively, the IT profession has spent years focused on learning our trade. We have focused relentlessly on “understanding the business”. We have learned to map business processes, navigate finances, and run projects. So now when we can apply a machine learning algorithm to optimize the configuration of the computing cluster, manage data center power consumption, or leverage SaaS and Cloud technologies to do in months the ERP project that used to take years, there is a renewed opportunity for top-notch IT professionals to have a broader impact on our organizations.
The competition for talent is already fierce across our industry. This changing emphasis isn’t going to make it any easier. But maybe, just maybe, understanding which skills are truly differentiating skills will allow us to focus our efforts on both finding and developing the top notch talent we will need for whatever comes next.