Anxiety about automation isn’t new—at a 1962 press conference, President John F. Kennedy said the major domestic challenge of the 1960s was to “maintain full employment at a time when automation… is replacing men.”
Today, 55 years after JFK made that statement, automation still inspires nail-biting, but it also delivers promise—especially around analytics. Gartner predicts that more than 40 percent of data science tasks will be automated by 2020, but instead of putting people out of work, it will help to increase productivity and broaden usage of data and analytics by “citizen data scientists.”1
That’s where you, the potential citizen data scientist, come in. One of the major benefits of digital growth is the ability to collect and process more data than ever before. And you don’t need an advanced degree in statistics to do so—just some guidance, practice and training. Here are three tips to get you started:
1. Learn how to recognize what’s relevant
The key to using data analytics is understanding which data is relevant to which area of the business, and how these things match up to your objectives. For example, are you tasked with building a better customer relationship cycle? Use your data to measure your current customer touchpoints and identify where they can be improved.
2. Start small and build your experience
Using your company’s overall data strategy as a guide, identify areas in your line of business that could be improved with data. When needed, collaborate with colleagues from other departments and use the insights gained to change minor processes or create new ones. Using analytics in this targeted, collaborative way will not only give you experience, it will also enable you to help your organization identify and apply data solutions on a larger scale.
3. Build your skills
To make use of your organization’s data, you need the right resources—technology, time, and training. Technology is not in short supply, but to make the most of it, and to make a significant contribution to performance improvement across your organization, you also need to be willing to put in the effort and time to learn how to use the tools. With relevant training and a commitment to change, you can also inspire your colleagues to do the same.
Organizations are beginning to understand the value of analyzing the ever-increasing volume of information they collect on customers and the business. They are also increasingly aware of the importance of their employees in analyzing patterns and extracting groundbreaking insights from their data. With a bit of effort on your part, you can lead your company toward better business decisions and play a significant role in its digital future.
We’ll examine the impact big data has for the business in a few weeks. Up next week, we’ll take a look at step two—how to choose the right technology for your digital transformation.
Image sources: Flaticon via Freepik.com; alteration of book cover, “Our Friend the Atom,” by Heinz Haber/Disney
1. Gartner defines a citizen data scientist as “a person who creates or generates models that use advanced diagnostic analytics or predictive and prescriptive capabilities, but whose primary job function is outside the field of statistics and analytics.”
Jen is an award-winning journalist who writes about workplace productivity and technology for Vitalyst. She believes in the power of using plain language, especially when writing about technology, and lists “achieving and enabling clarity” among her life goals.