We all know that the tech world is constantly moving and changing, and you probably realize that the skills within your career need to keep up with the changes. That means not only updating your skills as the technologies you work with evolve, but also coming up to speed on new, relevant technologies that affect your career.
I try hard to think of my skills in terms of my career, not just my current job. That is, while my employer obviously requires certain skills that I need to keep fresh or up to date, my career may require a different, and often larger, set of skills to remain relevant in the marketplace.
One of my first tech jobs was as a systems operator for a company’s IBM AS/400 midrange computer (now known as the IBM iSeries). I had certain job skills that I needed to continually develop and keep fresh: the OS/400 Command Language, the various ongoing changes IBM would make to the computer’s operating system, and the occasional changes to the hardware itself. My employer was responsible for helping me keep those skills fresh by sending me to classes and buying me books.
In the broader realm of people who operate computers for a living, however, AS/400 was a dead end. The field wasn’t growing; people weren’t buying new AS/400s. In fact, their almost-total reliance on the AS/400 would eventually prove to be a competitive disadvantage for the company, as new competitors came in with newer technologies that let them be more competitive for a lot less money. I probably could have eked out a 40-year career at my employer, doing nothing but operating that old AS/400, but I would have been entirely dependent on that company for my income, because there are relatively few job opportunities in the AS/400 space. In reality, my employer was eventually bought by one of its competitors, and the AS/400 was eventually decommissioned. That would have been terrible for me! With only that one skill, which had little relevance in the marketplace, I would have been hard-pressed to quickly learn new, more-relevant skills so I could have gotten a new job.
So the first axis of career skills is keeping your existing, employer-required skills fresh. The second axis is making sure to keep your career skill set relevant. Your career skill set will often need to be larger than the skill set your employer requires and may require a significant personal investment of time and money to maintain. Although your employer is welcome to stick with a given set of technologies, even if it hurts the company’s competitive edge at some point, you need to make sure that your career can stay relevant in a competitive, ever-changing technology market.
You can express this idea as a chart (figure 5.1), which can be a great way to help you decide where to focus your learning efforts.
I’ll categorize my skills in these four zones:
Job-safe skills are ones that are fresh, meaning that I can hold down my current job, but they may not be fully relevant in the rest of the industry. These are skills I might have on maintenance mode, meaning that I keep up enough to maintain my job but don’t otherwise invest in them.
Career-safe skills are ones that are super-relevant in the industry, but I might not be fresh enough in them to hold down a job, and they’re perhaps not needed by my current job. These are skills I won’t actively focus on, although I try to make sure I know how to come up to speed quickly should I need to.
Danger-zone skills are neither fresh enough to maintain my job nor relevant in the industry. I need to work on these skills, but probably only as much as my job needs. I don’t need to be any more proficient than my job requires.
Awesome-zone skills are relevant in the industry, and they’re ones where my knowledge is fresh and up to date. These skills are the ideal ones to have because I can use them in my current job and in other jobs if needed.
Here’s how I might fill in that chart (figure 5.2).
Here’s what that means to my learning plans:
I’m great at VBScript, but it’s not relevant anymore, so I’m not going to spend much time on it learningwise.
iSeries CL isn’t relevant anymore either, and I’m not nearly as up to speed on it. If my current job requires me to learn more, I will; otherwise, I won’t focus on it.
Java 11 is a highly relevant skill that I know little about. That might be okay. Maybe Javas 11 is a direction I don’t truly want to pursue, but it’s might enhance my career. I need to make some thoughtful decisions.
Keeping my employer-mandated skills fresh has always felt straightforward. A variety of training media exists in the world (and I’ll get into some of them later in this chapter), and I can use whichever ones my employer and I agree will get the job done. Typically, my employer will pay to keep those skills fresh, making the process easy.
I’ve had a harder time keeping my career skills relevant. It can be tough to decide what relevant means! That’s what I want to touch on next.
What skills are required to keep your career—to keep you—relevant in the broader global marketplace? Because you own your career, and because your career is intended only to take you to your success, only you can decide what relevant means. The process begins by understanding what problem you solve for employers. Do you maintain networks? Write proprietary desktop applications? Create web applications? Keep servers up and running? Whatever your broad solution area is, that’s where you need to focus. Few of us can be true jacks of all trades these days, so you’ll want to keep yourself centered on the broad problem space you solve for.
You can absolutely switch broad spaces I don’t mean to imply that, for example, a network engineer can’t ever become a software developer. You absolutely can! But you’re changing fields at that point and in many ways changing your career. It’s a bigger undertaking and not a process I’ll touch on in this chapter.
When you identify the broad space you’re in, you need to start looking at the market trends in that space. What technologies are employers hiring for?
One way to answer this question is to rely on your professional network. Chatting with colleagues in other companies can certainly help give you a broader view of what’s going on in the industry.
Instead of the new and shiny, I look for technologies that appear again and again in job listings. If lots of people are hiring for skill in a technology, by definition, that technology is relevant in the current market. I’ll be honest: my approach can result in my being a smidge behind the curve, in that I’m waiting for employers to adopt a technology rather than predicting what I think they’ll adopt. But my approach is the only way I’m able to limit all the things I have to learn to some reasonable set that is likely to enhance my career.
I think it’s important to recognize that you do not need to become an expert in every skill employers in your field are hiring for. First, it’s entirely valid to choose a reasonable subset of those skills. Second, you need only basic familiarity with the skills you choose, along with a strong set of learning muscles.
I like to visualize each of my tech skills on a breadth versus depth continuum to determine what I know and what I need to know. This approach aligns with the knowledge pyramid created by Mark Richards and Neal Ford, which you can see at http:// mng.bz/eMBJ. Their pyramid, now familiar to many in the tech field, looks something like figure 5.3.
The idea is that in any given technology, there will be all the stuff you know how to do—the skills you have. That’s your technical depth for the subject. For some subjects, technical depth will represent a large chunk of the pyramid; for others, the chunk may be more like a sliver. In addition, there’s generally a bigger chunk of stuff about technology that you know exists but that you’re not confident doing; that stuff represents your technical breadth, or the areas where you could become proficient, given a little time. Then there is the chunk of things that you don’t even know you don’t know—the stuff about the technology that’s beyond your reckoning. For technologies in which you’re a strong practitioner, this chunk might be fairly small. My goal here is to
Identify the skills in which I need strong technical depth to get or retain a job.
Identify the portions of the skill that I need to know to get or retain a job.
Learn the skills and skill components that I identified in steps 1 and 2. As I learn them, I’ll pick up a lot of the second-layer “stuff I know I don’t know” knowledge and skills, and I can make those targets for future learning to make myself even more proficient.
Another way to look at proficiency is to examine your level of knowledge in the “stuff I know” chunk of the pyramid. All of us have skills in which we’re strong and ones in which we’re so-so. This way of assessing our proficiency is sometimes called a T-shaped skill set, which you can see in figure 5.4.
The T-shaped chart is just another way of looking at the pyramid, except that you assess several skills instead of one. The skills for which the list of “stuff I know” is big are where my skills are deep (as in Windows), and they appear as taller bars on the T-chart. Considering all the skills about which I know at least a little, you’ve got my breadth, represented by all the bars on the chart. I can increase the depth of any of my shallow skills (Linux and iSeries, for example) if I need to. That’s where the scatter graph and its four quadrants come in handy: I want to focus my learning efforts on the skills on which I’m currently shallow and those that are highly relevant in the marketplace.
When you’ve thought about the skills in which you’re deep and the ones in which you’re not, and you’ve looked at which skills are relevant in the marketplace or needed by your job, you’ve got the beginnings of where to focus your learning time.
You can also focus some or all of your learning time on topics that are of general relevance in the industry, depending on your job role. For that approach, start by choosing a reasonable subset of skills in which you want to stay relevant. That can be tough, because any field of technology has a set of competing choices. Here are some examples from a variety of fields:
Systems administrator—Operating systems include Windows, Linux, UNIX, and older mainframe and midrange operating systems.
Database administrator—Choices include Microsoft SQL Server, Oracle, MySQL, PostgreSQL, and dozens more.
All these technologies are important and popular, and you’ll find many employers hiring for any of them. So how do you choose? Do you have to become an expert in all of them?
To identify my reasonable subset of skills, I start by looking at market share to find out the popularity of a language, system, or tool. This task is often as simple as searching online for something like “networking vendor market share” or “cisco market share” and then focusing my research on one or two of the top competitors in the market. That approach serves two purposes:
If I have strong familiarity with the top competitors, the lower-lever ones won’t be hard to learn if I need to.
When I’ve identified my target technologies, I remind myself that I don’t need to become a world expert in them. I just need basic, core familiarity and confidence in my learning muscles’ ability to help me learn more quickly.
For me, basic familiarity usually means whatever I could get from 40 to 80 hours of instruction in the technology. That might not be enough to get a job, but it’s enough that I could direct my future learning in the right direction and quickly gain more knowledge so that I could get a job. Presuming that I scheduled two or three hours a night for three nights a week, I could get in 60 hours of learning in a couple of months. To me, that is a reasonable investment of time for a reasonable return of skills and knowledge.
There’s an upside to aiming only for basic familiarity: the basics of any technology tend to change most slowly. That means my learning investment in getting to that point will last longer, making it easier for me to keep that basic familiarity fresh, and giving me time to explore other topics to the same level of knowledge. My reliance on getting only to basic familiarity depends, as I’ve indicated, on my confidence in my learning muscles.
Everyone is familiar with the basic process of building muscle: you have to work those muscles every day, all the time. People sometimes talk about being lifelong learners, but I prefer to think of myself as a daily learner. Your brain’s ability to learn, and to learn quickly, is something you can train and develop, and the way to do that is the same way you build a stronger heart: moderate, daily exercise.
I schedule time every day to learn, often during my lunch hour, because I enjoy reading and that hour is a great time for me to read—and a great time to take a break from work and think about something else. But sometimes, that learning time is in the car on a long drive, when I can listen to a podcast or the audio track of a training video. I rarely schedule my learning time at night, because I know that I don’t retain information well past dinnertime.
What do I learn? Surprisingly, not always technology! Sometimes I read a news article and go down a rabbit hole. I enjoy reading about US Supreme Court cases, for example. I’m not a lawyer, and the articles often reference legal principles and cases that I’m not familiar with, so I learn about them. I’ll Google legal principles and run across briefings and other short documents. I’ll Google earlier cases as well and read articles about them. Before long, I’ve learned something and spent only an hour or so doing it.
If you’re trying to build a stronger heart muscle, the muscle itself doesn’t care if you’re running, walking, hitting a punching bag, swimming, or engaging in some other activity; it knows only that it’s being exercised, and it responds by slowly becoming stronger. It’s the same with learning: your brain doesn’t necessarily care what you’re learning, only that you’re exercising the mechanisms that it uses to learn. So I don’t always try to focus on a new technology skill. I do that all day at work, and some variety is nice now and then! But I’m learning something every single day.
My strong learning muscle means that I’m confident with having only basic familiarity with the key, market-leading technologies in my field, because I know I can learn more, and do so quickly, when I need to.
We’re all familiar with the “classic” learning media in the world of technology: instructor-led classes, self-paced videos, and books. These media are effective, and you should definitely use them when they’re appropriate. But I don’t want you to discount all the other fantastic ways to learn, especially when you’re learning to keep up versus building a new skill from scratch.
Vendor documentation is the first on my list of alternative learning resources. I know the quality varies drastically across the industry, but being able to learn from vendor docs is an incredibly important skill in our industry. If you can go to that source material, digest it, and construct new knowledge for yourself from it, you’ll be unstoppable.
I also use the internet, often for broad introductions to new technologies, features, or approaches. When I’m trying to develop a basic understanding of what something does and how it does it, I’ll start in a search engine. I’ll open tons of blog articles, Wikipedia articles, YouTube videos, and other bits of content. I’ll skim those articles rather than reading them closely, with the goal of finding ones that explain the topic at the level that works for me and what I already know, as well as how deeply I want to understand it.
Social media can be a learning resource too. One reason to build a strong audience on Twitter or other platforms is that you’ve got lots of people to ask for advice. If I’m trying to become familiar with a technology and can’t find any reading material that’s giving me what I need, I’ll ask my friends on Twitter what they recommend. I’ll have a dozen great recommendations within a day 99% of the time, which lets me focus my learning for the next few weeks.
My point is this: all learning is useful. You don’t need to rely exclusively on the formal modes of education that we’re all used to. If your learning goal is to keep up with a technology rather than master it, you can often invest less time, while still achieving the level of familiarity you want, by using more informal ways of learning.
I’ll offer another tip: there’s a pervasive belief that people tend to learn best from a particular set of learning media. In other words, you might feel that you learn best from reading, or from watching videos, or from attending an in-person class. That belief is a myth.1 Human brains don’t have any kind of built-in tendency that makes one medium more effective than another. Any brain can learn effectively from any medium, which is great news. You may need to exercise your learning muscle a little more to accommodate it to a particular medium, just as you might have to work up to running a marathon if you’ve never been an avid runner.
One difficulty in keeping your skills fresh is knowing when you’re doing enough to keep your skills fresh enough or relevant enough. Keep in mind that you don’t need to be a world-class expert in every possible topic to be relevant.
I like to divide my skills into three broad categories, and I think this exercise is useful for making sure you’re not attempting to overinvest in your skills:
Skills I need for my job—These skills are the ones I need to invest in most heavily, and I would expect my employer to co-invest with me, because these skills are enhancing the business. But—and this is a critical point—my employer needs to invest only to the level that the business requires. My employer and I might need to work together to determine when I have sufficient skill freshness, which might involve certification exams, internal or external skill assessments, and other tools. The exact tools you rely on together will differ greatly across technology disciplines, and you’ll need to do some research to discover what’s considered industry-standard in your part of the tech world.
Skills everyone else needs for their job—These tech skills are the ones that the industry in general is using but that I’m not using in my own job. Because my employer doesn’t need these skills, I don’t expect the company to help me out here (although it’s great if it’s willing and able to do so). For me, these skills are the most critical ones on which to focus my resources, because these areas are where I risk falling behind. That is, if everyone else is using these skills, and I’m not, the industry is probably moving in a direction that my current employer isn’t. I risk losing my market relevance by ignoring industry directions. That said, I don’t necessarily have to master these skills. I simply need to get myself to the point of familiarity where I have some confidence that if I have to, I can rapidly reach basic proficiency, such as if I suddenly find myself in need of a new job. That’s a personal and subjective assessment, because you typically don’t need the level of proficiency that a certification would test for.
Skills that reflect general industry trends—I look outside my own specific area of tech to see what everyone else is talking about—not necessarily what everyone else is doing, but what’s on everyone’s minds. As I write this volume, tech like quantum computing might fall into that area. For these skills, I try to achieve elevator conversancy. That is, if I can talk knowledgeably about the technology at a high level for about five minutes, I consider myself good enough. These are areas I tag to keep up on, usually by adding them to a reading list of topics that I revisit once a quarter.
I’ve developed a few habits over the years that have helped me tremendously in keeping up with my career. I share them here, in the hope that at least a few of them will work for you as well:
Learning is a daily effort. The way the human brain works means that you want to have it learning new things every day. That’s how you keep the learning muscle strong, so that when you need to learn something, it’ll come more easily to you.
Learning is not just tech. I don’t always focus my daily learning on tech. Sometimes, I just need a break from the computer stuff! So I might grab a random Wikipedia article, or go down a rabbit hole on something I read in the news. I’ll find an interesting US Supreme Court ruling, for example, and read up on the legalities surrounding it. It interests me, and it expands my knowledge. You might follow another area of casual interest, reading up on real estate, art history, microbiology, or whatever sparks your imagination.
Schedule it. If you don’t make time for learning, it’s easy for it to not happen. Identify the value that learning adds to your career, and commit to spending the time on that learning that it takes to achieve that value. Keep in mind that all your learning time won’t happen at work: if it’s benefiting your career, you’re going to have to invest your free time.
Drag others into it. If you have colleagues or co-workers who are in a similar place, form a small study group. Meet once a week, and teach each other something; spend the days leading up to that session learning what you’ll be teaching. I’ve done this with small groups of four or five folks, and it’s really effective. We’ll divide a topic, and each person commits to a 10-minute teaching session. This approach lets each of us focus on a small area and adds structure to our learning efforts. Additionally, teaching our subtopics does wonders for reinforcing what we’ve learned in our own research.
Don’t be afraid of random. Although you should learn to do enough market analysis to decide what you should be learning, don’t be afraid to roll the dice. I’ll log in to Pluralsight and watch a random newly released course sometimes. It may not be in my field at all, but it’s learning, and that’s what’s important on a daily basis.
For this chapter, I’d like you to start developing a personal framework for staying relevant. I hope you can start engaging in these activities now and make them part of your daily routine:
Establish a daily learning schedule for yourself. Set aside time—an hour or two a day is sufficient—for learning. This time is an investment, and it may require you to give up something else, but this investment is worthwhile.
Spend a few weeks’ worth of your learning time analyzing your technology field, and come up with a list of the important, market-leading technologies you see employers hiring for on various job boards. This list becomes your learning list. Don’t let it be more than a half-dozen items at first: if it’s longer, trim it by focusing on the most market-leading technologies you’ve found.
Start spending your learning time achieving basic familiarity with the technologies on your learning list. Devote about 60 hours to each one. That’s 360 hours for a six-item list, which will take you about six months at two hours a day. Don’t focus on those technologies every day, however; give your learning muscles some variety by learning random topics as well. (The Random Article link on Wikipedia is a great way to find short new topics to explore.)
1 “Belief in Learning Styles Myth May Be Detrimental,” http://mng.bz/pJZP