Over the last few weeks, I’ve blogged about digital transformation and Analytics’ prominent role in that effort. When everything is digital, understanding and acting on what data tells you becomes paramount.
In last week’s installment, I covered the final step of that transformation, including reviewing the whole journey:
Part of this transformation also is bringing about changing roles and expanded skill sets, as well as developing buy-in for change – especially when some in your organization might resist any adjustments to the status quo.
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There are some well-defined roles in the analytics and BI realm. They include (but aren’t limited to) business analyst, data scientist, data engineer, business user, CDO, and citizen data scientist / engineer.
As many outside observers have already noted, the data science, analytics and BI, and data worlds are converging on each other. Some might even say they are “colliding”—a term that Gartner analyst Carlie Idoine writes and speaks about. A key premise of this convergence is a change in roles, with hybrids developing that cross over traditional boundaries. For example, data engineers are expanding to include more business analysis and/or data science skills. Data scientists have always had strong data skills. Business users are now doing their own analysis, not just consuming content others have created.
All these point to a need to expand skill sets to improve effectiveness in the organization and adapt to changes that are brought about by any transformation—whether brought about by internal change or accelerated by external events.
The concept of T-Shaped Skills has been around for a while. It’s an idea popularized in the 1990s by Ideo CEO Tim Brown. The T shape is a metaphor for the depth and breadth that an individual has in their skills. The vertical stem of the ‘T’ represents the depth of skills and expertise in a specific field, while the horizontal bar represents a thinner but broader layer of skills, knowledge and collaboration across other disciplines and skill areas. Increasingly, analytics professionals will require broad knowledge of the overall architecture (the top of the “T”) and deep knowledge in one or more specific areas (the leg of the “T”) — emphasizing both breadth and depth.
Gaining broader knowledge now required doesn’t just involve fostering a wider range of technical abilities to meet the challenges of digital transformation; it also means developing the business effectiveness skills that make the person a good communicator, a data storyteller, a better listener, and an advocate for change across the whole organization, not just within business or IT.
There are many resources out there for you to tap into. My best suggestion is to search the web using the term “T-shaped skills development” and browse through some of the great resources out there. I recommend you take this information in hand and put together some programs and processes to enable skills development for yourself and your team.
It’s important to keep in mind that you may need to take matters into your own hands and develop some skills on your own. In times of change and disruption, you need to “take the bull by the horns” and plan for your own future, following your interests along the way. Roles will continue to evolve and it’s best to keep your finger on the pulse of your company (and the market as a whole) to figure out where your individual skills development plan will take you.