Thomas C. Redman in Harvard Business Review Blog: “Slowly but steadily, data are forcing their way into every nook and cranny of every industry, company, and job. Managers who aren’t data savvy, who can’t conduct basic analyses, interpret more complex ones, and interact with data scientists are already at a disadvantage. Companies without a large and growing cadre of data-savvy managers are similarly disadvantaged.
Fortunately, you don’t have to be a data scientist or a Bayesian statistician to tease useful insights from data. This post explores an exercise I’ve used for 20 years to help those with an open mind (and a pencil, paper, and calculator) get started. One post won’t make you data savvy, but it will help you become data literate, open your eyes to the millions of small data opportunities, and enable you work a bit more effectively with data scientists, analytics, and all things quantitative.
While the exercise is very much a how-to, each step also illustrates an important concept in analytics — from understanding variation to visualization.
First, start with something that interests, even bothers, you at work, like consistently late-starting meetings. Whatever it is, form it up as a question and write it down: “Meetings always seem to start late. Is that really true?”
Next, think through the data that can help answer your question, and develop a plan for creating them. Write down all the relevant definitions and your protocol for collecting the data. For this particular example, you have to define when the meeting actually begins. Is it the time someone says, “Ok, let’s begin.”? Or the time the real business of the meeting starts? Does kibitzing count?
Now collect the data. It is critical that you trust the data. And, as you go, you’re almost certain to find gaps in data collection. You may find that even though a meeting has started, it starts anew when a more senior person joins in. Modify your definition and protocol as you go along.
Sooner than you think, you’ll be ready to start drawing some pictures. Good pictures make it easier for you to both understand the data and communicate main points to others. There are plenty of good tools to help, but I like to draw my first picture by hand. My go-to plot is a time-series plot, where the horizontal axis has the date and time and the vertical axis has the variable of interest. Thus, a point on the graph below (click for a larger image) is the date and time of a meeting versus the number of minutes late….”
How to Start Thinking Like a Data Scientist
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