why is the message being communicated?
There are four purposes for communicating data science results:
to increase knowledge, to instruct, to facilitate informed decision-making, and to persuade. Which of these applies to the messages you are sending?
what is your approach for gaining attention?
Communicators have both active and passive strategies available to them. Active strategy are synchronous, i.e. they demand the audience's attention. E.g. a pitch provided to management. Passive strategies are asynchronous, they can reach their audiences at their convenience - if at all. E.g. sending out an infographic in the internal newsletter and relying on information-seeking audiences to read it. The “push-pull” model combines both strategies by sending messages to audiences (push), while also making information and materials available to interested parties (pull).
what factors influence receipt and intepretation
Contextual factors include other sources of information, personal experience, and competing priorities and are often outside the control of those sending messages. These factors can have influence at various points during the communication process and can even prevent effective communication.
what outcome do you wish to communicate?
Once storylines are determined, messages must be developed. Messages – chunks of information that support the storyline – should be based on understanding built up through the application of data science methods. Each message should be able to stand alone by communicating a single idea, but, collectively, the messages should provide rationale for the larger theme (i.e., the storyline).
how will you incorporate various sources
Sources are differentiated based on the intimacy of contact, with interpersonal sources involving one-on-one interaction and mediated sources involving one-to-many interactions. Communication often involves a mix of both interpersonal and mediated sources, such as when data received from another (e.g., census data) becomes part of interpersonal communication (e.g., presentation to a senior manager).
by which means will your story be delivered?
To have a better chance of reaching the intended audience, data scientists should consider the following factors: