Communication is Everything

06.02.2017 |

Episode #9 of the course An introduction to data science by Roger Peng

 

Today, you’ll learn about the importance of good communication and some core concepts to think about to make your communication as clear and informative as possible.

Communication is fundamental to good data analysis. Data analysis is an inherently verbal process that requires constant discussion. There are lots of good books that address the “how-to” of giving formal presentations, either in the form of a talk or written piece. In this section, we will focus on how to use routine communication as one of the tools needed to perform a good data analysis to convey the key points of your data analysis when communicating informally and formally.

Communication is both one of the tools of data analysis and also the final product of data analysis; there is no point in doing a data analysis if you’re not going to communicate your process and results to an audience. A good data analyst communicates informally multiple times during the data analysis process and also gives careful thought to communicating the final results so that the analysis is as useful and informative as possible to the wider audience it was intended for.

The main purpose of routine communication is to gather data, which is part of the epicyclic process for each core activity. You gather data by communicating your results, and the responses you receive from your audience should inform the next steps in your data analysis. The types of responses you receive include not only answers to specific questions, but also commentary and questions your audience has in response to your report (either written or oral). The form that your routine communication takes depends on what the goal of the communication is.

There are three main types of informal communication, and they are classified based on the objectives you have for the communication: (1) to answer a very focused question, which is often a technical question or a question aimed at gathering a fact, (2) to help you work through some results that are puzzling or not quite what you expected, and (3) to get general impressions and feedback as a means of identifying issues that had not occurred to you so that you can refine your data analysis.

Focusing on a few core concepts will help you achieve your objectives when planning routine communication. These concepts are:

  1. Audience: Know your audience, and when you have control over who the audience is, select the right audience for the kind of feedback you are looking for. In some cases, such as when you are delivering an interim report to your boss or your team, the audience may be predetermined. Your audience may be composed of other data analysts, the individual(s) who initiated the question, your boss and/or other managers or executive team members, non-data analysts who are content experts, and/or someone representing the general public.

  2. Content: Be focused and concise, but provide sufficient information for the audience to understand the information you are presenting and question(s) you are asking.

  3. Style: Avoid jargon. Unless you are communicating about a focused, highly technical issue to a highly technical audience, it is best to use language and figures and tables that can be understood by a more general audience.

  4. Attitude: Have an open, collaborative attitude so that you are ready to fully engage in a dialogue and so that your audience gets the message that your goal is not to “defend” your question or work, but rather to get their input so that you can do your best work.

Remember that a key purpose of communication is to gather data (in addition to transmitting it). It is useful to deliberately cultivate a receptive and positive attitude prior to communicating by putting your ego and insecurities aside. If you can do this successfully, it will serve you well. I have known many people who have had highly successful careers based largely on their positive and welcoming attitude toward feedback and constructive criticism.

 

Recommended book

“Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World” by Bruce Schneier