The Fish and The Fishing Rod: Core Skills for the Data Visualization Worker

Give a man a fish and he will eat for a day.
Fishing RodTeach a man to fish and he will eat for a lifetime.

 

Here is a good example of give-a-fish versus teach-to-fish: if you search for “excel dashboard” you’ll get at the top of the search results my own Excel dashboard tutorial and Charley Kyd’s Excel dashboard reports. These are two completely different approaches on how to help people making dashboards in Excel. While Charley’s gives you a nice fish, mine teaches you to fish. Which is better? Judging from that old saying, teaching people is always the right choice, but old sayings are often wrong. The right answer? It depends. (I already wrote about Kyd’s Excel dashboard reports.)

Example #2: imagine for a moment that you can buy some kind of dashboard-making device. How should it be designed? Dan Saffer is a designer and he writes about the difficulty of finding the right balance when adding controls to a device [fusion_builder_container hundred_percent=”yes” overflow=”visible”][fusion_builder_row][fusion_builder_column type=”1_1″ background_position=”left top” background_color=”” border_size=”” border_color=”” border_style=”solid” spacing=”yes” background_image=”” background_repeat=”no-repeat” padding=”” margin_top=”0px” margin_bottom=”0px” class=”” id=”” animation_type=”” animation_speed=”0.3″ animation_direction=”left” hide_on_mobile=”no” center_content=”no” min_height=”none”][link no longer available]:

“(…) by reducing controls (and thus reducing complexity for the user), you also reduce, well, control over the device. Users can do far less with it, and have little to no options for customization. Again, sometimes this is desirable. But sometimes, it is a disaster. Reducing complexity means reducing control, and some users, particularly those whose skill goes beyond that of amateur/beginner, don’t just want control, they need it to perform their tasks effectively. Thus, it becomes a balancing act, with simplicity and automation on one side, and complexity and control on the other.”

Again, you may want the fish (simplicity and automation) or the fishing rod (complexity and control). Actually, you want neither: you just want to get things done using the tools that best match your current or future skills (if you are willing to learn).

It’s tempting to pursue many interests at the same time, spreading yourself too thin. More often than not, that’s not the wisest thing to do. However, you can extend yourself by buying the fish (delegating, outsourcing, automating or finding the right templates). And the more specialized we become, the larger the fish market.

On the other hand, you must be good at something, right? For example, if you want to have a deeper understanding of how data visualization works, how it can help you and your business and how this can be applied to Excel charts and dashboards, you must learn. The more you know, the easier is for you to recognize or to create new connections between things and ideas. Outsourcing everything is not the answer.

What Are the Core Skills for the Data Visualization Worker?

This post sets the stage for a series on core skills for the data visualization worker, but it’s not easy to come up with a good answer. That’s why I’m asking you: what do you know / should know? What kind of skills should be promoted or de-emphasized/delegated? Share your thoughts in the comments below.

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7 thoughts on “The Fish and The Fishing Rod: Core Skills for the Data Visualization Worker

  1. A data visualization worker needs to understand task, technique, and tool.

    The task is the business need. Don’t stop with the specifications that your manager gave you or past practice. Dig deeper and find out how the chart will be (or might be) used.

    To this task, apply the appropriate technique. Here, there is no substitute for some academic training in statistics. Anyone can plot a time series, but what is the best way to extrapolate a particular trend? When should you use a scatterplot, and what kind of trendline should you have? Might a quantile function be a good way to present a risk analysis? Some old-school background would come in handy on these questions.

    Finally, understand the tool–in this case, Excel. All the theory in the world won’t matter if you can’t put it on the page.

  2. I think you’re minimizing the extent of Excel User’s dashboard offerings.

    Actually, Excel User started with an ebook showing how to build robust updatable dashboards. This expanded with some example workbooks to show how to implement the techniques in the book. When customers began clamoring for workbooks that were more extensive than the examples and faster to implement, Excel User listened to the customers and came out with their ready-made dashboards.

    So in addition to the fish, Excel User provides the know-how to fish, for those so inclined.

  3. Doug: Yes, that’s what I believe in too. But how do you prioritize those skills? Do you have to know everything? Can you delegate the understand-the-tool part? You do not mention the data itself, but we can do everything right and still get the wrong insights because we misinterpreted the data.

    Jon: You are factually right. Kyd is emphasizing his ready-made dashboards (like the IncSight QnE) and I was forgetting about the e-book – I actually bought it a few years ago. I’m using his example because he targets those users that are more interested on a fast implementation with their current skills than on getting new skills (well, that’s my perception, anyway…).

  4. Very good discussion. I agree with Doug. As with anything in life, you need to know what you want to build, then plan for it and eventually do it.

    In this case, knowing is understanding the data, learning what matters.

    Planning is when you draw some rough sketches of the dashboards (or charts or reports), decide on alternatives and figure out the final layout.

    Implementation is when the tool and techniques come in to picture. In my case Excel is the tool and techniques are knowing the formulas, data massaging techniques and obviously charting (and a bit of trickery like conditional formatting, vba, form controls etc.)

    Here is a post where all three are shown to make a project status dashboard: http://chandoo.org/wp/2009/10/06/project-status-dashboard/

    While I agree with your “teach fishing” theory, most of the time people dont want to become fishers. They want to become hunters, dancers or coffee guzzlers. They just want fish for a side dish 😉

    I think a moderate approach like give the fish, but encourage readers to learn fishing is better. That is what I do on PHD. From time to time I provide free templates (or even paid templates), but also write tutorials on how to do these. It has been working alright and readers seem to enjoy both.

  5. Chandoo: We can’t be specialists in everything. We just need to learn enough to make our work easier, more enjoyable and aligned with our goals in life (easier said than done).

    Given our limited resources (time), the challenge is to know what we need to know and prioritize it accordingly. Do we need a good default/template? Do we need to become a specialist? What about learning the key points just to remove some roadblocks somewhere else? There is no black and white.

    (Great post, by the way. Thanks for sharing.)

  6. Perhaps I can share some of my humble thoughts from 10 years experience with businesses both within the UK and internationally. Data visualisation should not be seen as the medicine to cure a business problem. It can only be applied when a thorough understanding of the business problem has been fully analysed, and it is deemed appropriate to implement a strategic KPI or monitor/measure a process. Simply the business problem or strategic requirement needs to be conceptualised before a solution can be synthesised. Only then can you propose a method of managing the solution. If data visualisation is the proposed solution, is the available data reliable, clean and with no duplicates, what is the data management process, who and when will the data be updated, implemented and verified? Get these soft issues wrong and the effort in producing a dashboard will be wasted.

    My approach to visualisation is based upon flying and particularly landing a helicopter on an oil rig out at sea. Firstly, a ‘Red alert’, management needs to take immediate action, ‘Amber alert’ be aware that corrective action is needed to correct an aspect of the process, and finally trend monitoring – a quick scan to monitor process performance. Similar to flying your eyes need to be outside of the cockpit the majority of the time, with only a quick scan to monitor that all systems are OK. If management cannot understand my dashboard within 20 seconds then I have failed.

    So to answer the exam question core skills: are you looking for a doctor or a nurse?
    If the doctor then sound business skills, a bag full of business and analysis tools, good bedside manner and ability to listen. And armed with Stephen Few’s methodology on dash board design you are ready to go!

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