ashton-kutcher

Ashton Kutcher and Digital Analytics

  |  August 19, 2013   |  Comments

What an actor/investor can teach us about our work and lives.

This may be a little odd, but this post is actually influenced by Ashton Kutcher (yes, the same man who gave us the amazing film "Dude, Where's My Car?"). After being given an award at a recent award show, Kutcher didn't use his time slot to give the acceptance speech that we're accustomed to hearing. No, instead he used his celebrity influence to give some great life advice to millions of teens. However, his advice doesn't apply just to teens who are still finding their way through middle school. While his message is crafted for his target audience of teens, with a little tweaking his speech holds true to most everyone.

Opportunity

Kutcher's speech is broken into three parts, the first being opportunity. Kutcher goes on to explain that opportunity looks a lot like hard work. While I agree that hard work is definitely important, I would actually rephrase this to be productive work. As an analyst, creating a report does not exactly equate to success. Yes, doing data dumps and getting all of the stakeholders their reports will allow you to check off a box on your to-do list, but is that information actually being used? Are your talents being utilized to their fullest potential? In most cases, my guess would be no.

I understand in a lot of organizations the analytics department tends to be understaffed and overloaded with reporting or implementation tasks, so it's easy to lose sight of the higher level goal to get through the week's tasks. If this is the case for your organization, my advice is to put your head down, roll up your sleeves, and automate. It will take some time initially, but find ways to automate and reduce the actual time spent on your daily tasks, whether it be through the use of technology like APIs or Excel macros, or by speaking to your colleagues and discovering what can be cut and what can stay. These are methods that I have seen firsthand allow me to check off those necessary to-dos, while focusing more time on the second topic of Kutcher's speech, being sexy.

Be Sexy

Yes, being sexy. Kutcher goes on to say that the sexiest thing a person can be is smart. So assuming that analytics is the career path you enjoy and want to stay on, get smarter at it. If you're lacking a technical background, beef that up through something like Codecademy. If you're lacking a quantitative analysis background, grow that through courses on Udacity or Coursera. Your potential is only limited by the time you put into your work, but your time is limited. As you get smarter at what you do, you'll find that you do it faster, make fewer mistakes, and have more time to become even smarter. It's a virtuous circle of success.

Building Your Life

The third item Kutcher speaks about is living your life, more specifically, building your life. As mentioned, this was influenced by Steve Jobs' life and work. Love him or hate him, Jobs was a pivotal figure in changing the way millions of people work and live. Future generations will feel his influence because he understood that just because something doesn't currently exist, doesn't mean it can't exist. So if you've made it to this step, build your life. Start solving problems that you face every day, because chances are there are thousands of people who struggle with the same things. This is usually a very difficult task to perform. But, don't forget that new solutions are created everyday. So get started solving problems, and make your life what you want it to be.

Image on home page via Shutterstock.

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ABOUT THE AUTHOR

Robert Miller

Robert Miller is a Senior Analyst at Search Discovery. He is actively involved in industry organizations, such as the Analysis Exchange and the Digital Analytics Association.

With the Analysis Exchange, he helps non-profits capitalize on their website data, and educates aspiring digital analysts about the foundation of digital analytics, from the implementation of a digital analytics tool to performing analysis and making data-driven recommendations for organizations.

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