August 3, 2017
Those of us working in the IT space really love buckets, being able to classify things and assigning them to Bucket X and not Bucket Y. We have bucket systems for technologies, projects, and people.
Maybe it's a case of IT being based on order. Programmers work within the structure of a chosen language. Sysadmins know when and how backups must be done and server maintenance scheduled. For decades (even into the DevOps age) we have carefully delineated between developer and admin; "tech" and "user"; application and middleware.
True, this need for structure mirrored the organization. The finance group is fixated on structure with its rows and columns. For HR, a nightmare is not knowing where to plug someone into the org chart. In every department it's a capital crime to forget that someone is the Executive VP rather than a VP. In my own field of journalism I've worked with new college grads who couldn't understand why they didn't get the title of Senior Writer. But structure is forced on IT at a time when the IT group is supposed to be innovative, flexible, and adventurous.
Structure and adventure don't always play well together.
That may be why an innocuous comment on a fun little item got me thinking about structure in today's world.
We asked people in our InformationWeek Flash Poll which career specialty they would recommend to a young person. (If you haven't voted, I hope you will do so now). Someone who took the poll questioned why artificial intelligence wasn't listed.
Being the person who set up the poll answers -- the buckets -- I had drawn on my focus on analytics over the past few years and mentally dropped AI into the data science bucket. But, wait, AI is useless if it isn't built out as part of an application. Plus it's pretty well hamstrung without having data in the cloud. Where does it fit? Here, there and everywhere.
Even with revolutionary concepts we are once again worrying about structure, particularly what things are called. People debate where AI ends and machine learning starts. They argue about whether to call the field cybersecurity or infosecurity. Cloud companies spend hundreds of thousands of dollars trying to prove whether private clouds, public clouds or hybrid clouds are the best or most popular. Hey, it's all cloud, a new way of computing!
People who build and sell technology products and services, those who buy and implement those technologies, and those of us who write about technology are still hung up on what to call stuff and how to classify it.
Yet, what really matters is delivering results. Does the technology make the company more efficient or bring in new revenue? Does a tech project lead to better customer relationships? Does an emerging tech help employees work better and safer?
We have to free ourselves from our bucket mentality, be ready to step outside the comfort zones that structure imposes on us. With football season approaching, I'll draw on the wisdom of New England Patriots coach Bill Belichick (fans in Indianapolis, Oakland, New York, and Baltimore feel free to boo). His game is complex but his overriding message to players is simple: "Do your job."
On the surface, that means players work hard, learn, hustle, do what the coaches tell them. But Belichick also changes a player's job as needed and as the player's skills allow, putting offensive players in the defensive backfield, having defensive players catch passes, and making sure nobody takes things for granted. Their job is simply doing what needs to be done. Players who don't do their jobs end up selling insurance or shoes. Something must be working because he and his players have hands loaded with Super Bowl rings.
Back to IT.
Any young person who sets out to do one of the jobs listed in our poll can be absolutely sure that job as they know it today will have changed or been eliminated by the time they reach mid-career. Just ask anyone who based their career on mainframes or even PC architectures. Yet, you can thrive even if your specialty moves on, or you move on from it.
A field such as AI bridges many of today's buckets: data science, applications, security, robotics, and more. It isn't a career choice so much as a specialty, and even as a specialty it might involve only a temporary assignment. Maybe your experience is with cloud architecture, and you are pulled into a machine learning project for two years. After two years you move on to something new.
We have to break out of our bucket fixation, not only as individuals but in the big picture. It means rethinking the corporate structure, our approaches to education and training, and how we are compensated. We need to think: "How can I help the company?" "What can I do to serve the customer?" "How can I make a difference?" Maybe we will really shift from "not my job" to a "do your job" mindset in the real world.
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