As I've learned in my 30 years in analytics, you can define the scope of your career around expertise in three knowledge areas: subject matter, product lines, and platforms.
Subject matter expertise addresses the degree of intimacy you have with the business rules and substantive meaning represented by the data you're processing. Visually, a text file of records may appear to just be lines of ASCII characters. However, knowing whether those records represent healthcare episodes, employment history, clinical trial phases, or financial transactions facilitates the ability to read the file contents correctly.
Knowing the story represented by the data helps you better assess whether observations, and the file as a whole, are consistent with the underlying business logic.
However, being a subject matter expert (SME) can have some disadvantages. A good reputation based on depth of knowledge in processing industry-specific data might get you to the top of the list when the organization needs an SME, but with it comes the risk of being pigeonholed. If you're known only as the person who can process specific classes of data, you may find your opportunities for assignments outside of your knowledge domain limited.
Product-line expertise addresses the breadth of analytics products you typically use to produce deliverables. Often, the type of environment -- tool rich or talent rich -- determines product line breadth.
A tool-rich environment is one in which the sponsors have chosen to invest in analytics products that will produce the desired results with a minimal amount of programming intervention. Organizations make this choice when the human capital pool is scarce or deemed too expensive to hire or train.
A talent-rich environment, on the other hand, is one in which the sponsors have chosen to invest in analytics professionals to produce the desired results, typically within a limited analytics product suite. Organizations make this choice when hiring or training programmers because it's more cost efficient than licensing additional products. It also happens when the desired deliverables are so complex or business-rule driven that customized programming is preferred over making a commercial product function beyond its intended purpose.
Platform expertise addresses the breadth of hardware architectures you use to do your work. The typical platforms are the mainframe, (also known as the Big Iron), midrange servers (such as Unix), and microcomputers.
While analytics software (such as is available from SAS, this site's sponsor) is consistent across platforms, each platform has components you have to consider to ensure that your applications function as expected.
Mainframes have a lot of processing power, but they tend to be expensive, so mainframe applications should be designed for maximum efficiency when execution time is a cost driver. Midrange servers are popular right now because they're less cost intensive than mainframes; they're also robust and fairly stable and reliable. The drawback is that using midrange servers also includes administrative and network security overhead; the native storage capacity is often less than with the mainframes as well.
Microcomputers have the least amount of processing power among the three, but they are physically portable and make data from personal and office productivity products analytics accessible.
The core issue concerning platform expertise is that you will have to develop some mastery of application tuning. Analytic products may execute on all three platforms, but the nuances and idiosyncrasies of each platform may impact outcomes such as execution speed, precision of default decimal values, processor utilization, and so on.
In effect, being an analytics professional means you have to decide whether to become a specialist or a generalist by subject matter, product line, or platform.
What choices have you made? What choices have been imposed upon you? Please share.
I can imagine bad leaders in siloed departments being threatened, Beth. It is a nice point you have implied, the link between siloed departments and defensive leadership. And it's a reminder of what analytics practitioners must practice anyway - how to be a stewart within a professional community.
So it's in the manner of delivery. I would think, too, that good leaders would encourage staff to do this sort of reachout and knowledge sharing. Bad leaders, on the other hand, might feel threatened by it.
Your point is well taken. I would suggest that any tips or tricks sent out by email to your colleagues should be in the context of supporting their tasks, objectives and goals. What I find works best is to identify a pain point of someone in your group or external to your group but in the organization, and offer a solution in text, diagram or code. I find that when you indirectly expand your skill profile by giving away ideas to help others, it is not seen as chest thumping. People tend to keep their secrets like Jedi protect their light sabers. When you offer solutions outside of how people perceive your core capabilities, you not only help them, but project yourself as a team player, and possibly get picked to be a part of compnay-wide project teams. For example, 10 years ago, I was part of a contractor team that resdigned a government system. I shared tips with the customer that made the customer's knowledge base stronger. And best of all, our support helped the customer get promoted. That led to other opportunities and to me eventually becoming a fed.
So yes, there are political consequences if your goal is to promote yourself directly. But if you demonstrate your breadth of skills, knowledge and experience by sharing information that helps others, then the risk of politcal consequences are reduced. But yes, one should never fall asleep on politics - people are fickled. Figuratively speaking, they will hail you on Palm Sunday and then nail you on Good Friday.
So I like this advice to send out tips and tricks and sort of assert yourself as a go-to authority. But couldn't this sort of activity get "politically" complicated if you're part of a department or team?
Ideally the area in which you become known as a SME is also an area that you enjoy and not perform by default (it is said that in the land of the visually impaired, the person who can see clearly with one eye becomes the ruler). What happens sometimes is that if you are the first persons to figure out (even accidently) what no one else can, then you become the go-to person. That can create some job-security, but can leave you pigeon-holed. In this situation, I suggest sending out technical tips and tricks via email on other problem areas. In other words, people will bring to you problems in which they see you as the SME. But it is up to you to publicize examples of other areas in which you can add value. Your good fortune or real strengths may attract certain projects toward you. But if you want to be considered for tasks beyond this one domain, then you have to provide evidence of the breadth of your knowledge.Try to market your self as a jack of several trades and a master of at least one.
Hi Bryan, regarding subject matter expertise, it sounds like you're saying analysts have to find the right balance between being an SME and being an analyst in general capable of tackling a variety of projects. Any recommendations on how to achieve that balance?
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