27. Data Analytics - Share Data Through the Art of Visualization - Week 4

Learn how to present the data using a framework.

Learn about the art and science of presenting.

Learn preparation, Q&A, and handling objections.


Definitions:

Hypothesis // theory you're trying to prove or disprove with data

Curse of Knowledge // knowing something, it will be hard to imagine others might not know too

The colleague test // do a test-run of your presentation to colleagues who have no knowledge of data

        - Don't assume audience know everything.


Framework:

        - Framework of presentation starts with your understanding of the business task


Data Analyst Two Key Responsibilities:

        - Analyze the data

        - Present your findings effectively


Important aspects to a presentation

        - Define your purpose // set the core message clear

        - Keep it concise // don't be wordy

        - Have some logical flow to your presentation

        - Make the presentation visually compelling

        - How easy is it to understand?


Presentation Tips:

        1. Channel your excitement. Take your energy to present with passion.

        2. Start with the broader ideas

        3. Use the five second rule

                - Wait five seconds after showing data visualization. 

                - Then ask if audience understands, if not, then explain it.

                - Give audience another five seconds to let it sink in.

                - Tell the conclusion

        4. Preparation is key


        Understand the audience to keep them engage:

                - Audience may not always see the steps you took to reach a conclusion. Curse of Knowledge

                - Audience has a lot on their mind already. Life stuff.

                - Audience can be easily distracted

                - Understand your stakeholder's expectations

                - Make sure you have a clear understanding of the objective and what stakeholders wanted


        How you speak:

                - keep your sentences short

                - build in intentional pauses

                - keep the pitch of your sentences level


        Be mindful of nervous habits:

                - Stay still and move with purpose

                - Practice good posture

                - Make positive eye contact


Be prepared to consider any limitations of your data by:

        - Critically analyzing the correlations

        - Looking at the context

        - Understanding the strengths and weakness of the tools


Preparing for the Q&A:

        Before presentation:

            - assemble and prepare questions

            - discuss presentation with your manager, other analyst, other friendly contacts in organization

            - as manager/other analysts what questions are normally asked by specific audience in the past

            - seek comments, feedback, questions on the deck or the document of your analysis

            - brainstorm tricky questions or unclear parts a day before the presentation

            - practice

        During presentation:

            - prepare to respond to things you find and effectively and accurately explain findings

            - address potential questions that may come up

            - avoid having a single derail a presentation and propose following-up offline

            - put supplementary visualizations and content in the appendix to help answer questions


Handing Objections:

        Types:

            - about the data // where data from? what systems came from? what transformation happen?

            - about the analysis // is it reproducible? where was feedback from? 

            - about the findings // does the findings exist in previous time periods? 

                                                were differences controlled?


        Responding to possible objections:

            - Communicate any assumptions

            - Explain why your analysis might be different than expected

            - Acknowledge that those objections are valid and take steps to investigate further


Bad vs Good Slideshow Presentation:

        - Bad:

                - No story, no logical flow, no titles

                - Too much text, hard to understand, uneven and inconsistent format (no theme).

                 - No conclusion or recommendation slide

        - Good:

                - Introduction slide, title, presenter, date last updated.

                - Outline of presentation, table of content

                - Purple statement > tell story with data > conclusion > appendix > Q/A slide


How to work data into your presentations:

        1. Help audience understand what data was available during data collection

        2. Establish initial hypothesis, the theory you're trying to prove or disprove with data

                - Establish hypothesis early in presentation helps audience understand the data

        3. Explain the solution to the business task using examples and visualizations


        *McCandless Method moves from the general to the specific

                1. Introduce graphic by name, whos presenting

                2. Answer obvious questions before the audience might ask. Helps audience focus on other

                    stuff

                3. State the insight of your graphic. Get everyone on same page, show key takeaways.

                4. Call out data to support that insight. Give lots of examples to support.

                5. Tell your audience why it matters. Present possible business impact of the solution and

                    actions stakeholders can take


Q&A Best Practices:

        - Listen to the whole question

        - Repeat the question (if necessary) // helps make sure you're understanding the question

        - Understand the context // who is the audience, what are their concerns

        - Involve the whole audience

        - Keep your responses short and to the point


Appendix:

        - Holds more additional detailed data for reference


Additional Resources:


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