What's the best way to present data findings to non-technical stakeholders?

To effectively convey complex data to a non-technical audience, focus on understanding your audience's level of data knowledge, their objectives, and how they intend to use the data for decision-making. Tailor your presentation to match their needs and preferences, simplifying complex details to make the information accessible and actionable for them.

?? Know Your Audience (KYA) is the key to success in preparing and presenting data to stakeholders. ?????? A senior executive (like VP's) face frequent context changes. Such cases start with a context and provide a 60-second overview. The presentation should have a visual to tie back the background and story. ?? Think from the stakeholder's perspective what is in it for them and present the finding accordingly, especially if you expect a decision. ?? One of the common anti-patterns is reading or interpreting the data from the presenter's perspective. Interpret in stakeholders' perspective or leave the interpretations to them by providing the context. ?? Build a common ground for feedback and collaboration.

KYA is a concept that applies for many domains of life. You know that because you don't communicate the same way to 2 different friends. #1 Do your research before on who they are and what is important to them. #2 Speak Their Language: Don’t flood them with jargon; I can tell you they'll hate you if you do. Please keep the vocabulary and concepts simple. You're not here to impress. #3 Tell them it's ok to interrupt if something is not clear. #4 Visual Fiesta: Throw in vibrant visuals and relatable analogies because everyone understand that. Ultimate test: The Role Reversal to put yourself in their shoes. What would make you say "this is non-sense".

Typically, an audience will be someone with a business problem that Data Science solves. Talk to this person beforehand to understand their pain points. Make sure that your data science solution covers these pain points and make sure that your presentation covers how the solution addresses them.

I've always found presentations dull and ineffective. What works best: 6-pagers narratives. (thanks Amazon) They require better organization and deeper understanding of the topic at hand that enables a deep-dive into the problem. They foster an environment of focus and active (speed) reading and thoughtful discussion during meetings. The structure of a 6-pager typically includes: - a problem statement - analysis of the current situation - proposed solution - supporting data - anticipated challenges - questions - next steps It is not shared until the meeting starts so the team has the most time to perfect the document. Attendees spend 20 minutes reading the memo in silence. The last 40 minutes are spent commenting it live.

Competing interests arise in data analysis, from novices to experts. Some manipulate data for personal gain, while others doubt it due to intuition. Jupyter Notebooks offer the best solution, allowing non-technical analysis for the less savvy and code-based evidence for skeptics, ensuring data integrity.

One of the better methods to convey findings in the data science domain is to use a jupyter notebook. The notebooks allow the presenter to present text and graphs for the non technical folks as well as the code for the technical folks. This helps reach a wider range of audience who can comfortably understand the presentation

A power point presentation is by far the best way to go about your format. You will be able to reuse slides at a later time for another presentation. If you are going to send the slides out, you can add comments to notes to have the person read your explanation of the slides. Use a lot of figures. A picture tells a thousand words.

#1 Simplifying the data can be visually performed by: - Using clean lines - Using few colors - Removing titles on both axis - Avoiding complex visualisations → Remove unnecessary elements ruthlessly, break down complexity into smaller parts. #2 Chart-Message Harmony → Consider the message you want to convey, then choose the chart type that best supports that message. #3 Guided Insights The Economist are experts, they subtly guide readers to the intended insights by having: - A title that tells the story unequivocally. - A subtitle that defines the units of the graph - The most important lines or dimensions in bold - A short explanation at the right place

From my journey in the realm of data, I've often likened the process of simplifying data to sculpting. Just as a sculptor chips away excess stone to reveal the masterpiece within, we, as data professionals, need to distill vast amounts of data to its essence. It's a delicate balance - ensuring clarity without sacrificing depth. I've sat through presentations where data was so oversimplified it lost its impact, and others where its complexity was overwhelming. The art lies in crafting a narrative where the data speaks clearly, resonates with the audience, and drives the message home. It's not just about showcasing data, but about making it a compelling, memorable story.

Start with a business problem. How does your solution address this problem? How much more money will the company make if they use the solution? How much less money will the company make if they use the solution? Whenever possible put things into simple terms that have $ signs attached to them.

The key objective of any presentation is to tell a story, and everyone likes stories. Structure is very important to capture audience attention just like in a good movie. You can you story telling styles like - 'Problem-Solution-Result', 'Three-Act Structure', The Hero's Journey, Emotional Arc and so on. Telling data stories uses data as motivators and enablers rather than being lost into how data was processed or analyzed using shiny AI models.

Storyboarding is probably one of the most important skills for a Data Scientist. Being succinct and simple is important because this way it becomes easier to grasp the crux of the matter. Linking and presenting the data to business outcomes through graphs, dashboards or business frameworks is a highly appreciated skill in this field. Moreover storyboarding makes the insights way more powerful and actionable in the real world.

If you start your story with a business problem relevant to the stakeholder, this is an easy story to tell in every case. Don't keep going on and on. Get to the point on the first slide and use the rest of the discussion to setup the next steps.

If you want to explain do it rapidly for the sake of the story! If you feel like lines of code could help I'm sorry to say it will not. I have been there, people yawn. They're simply not as nerdy as we are ! and that's ok ;)

Actually, I disagree with this point. When presenting to a non-technical stakeholder, I generally put the minutiae into the appendix of my presentation. That way it doesn't distract from the key message(s), but the content is still available if needed to address audience questions. Of course, it is important to know your audience. If the primary decisionmaker has a reputation for drilling into the technical details, then it may be better to include it upfront.

It almost never necessary to explain your methods to a business audience. They don't know what you're talking about and they don't care. If you feel you have to do this, work on establishing trust with your audience. You are the expert, behave accordingly.

Agreed. I’m general, keeping technical terms to a minimum or nonexistent is best. Explain it as simply as possible leading with the end result. Jupyter notebooks are best because there is transparency.

A good way to receive feedback for data/ any presentation is - if there is possibility pre-align with stakeholders individually / in smaller-groups before the meeting (offline at least) that would help incorporate their diverse feedback to best prepare for the meeting.

Data visualization is a powerful tool for making data findings more understandable and accessible to stakeholders. Visuals are the universal language that everyone understands. Visuals simplify the complex data finding and make them understandable to non-IT stakeholders. Line charts and area charts can easily make them understand patterns in the data. A lot of charts and visuals are there, one should use the simple charts that best suit the data-driven decision. Drill-down charts are easy to understand by non-it stakeholders as they can quickly satisfy stakeholders by answering on-the-fly questions. Cards are a wonderful way of displaying KPIs of the business that help the businesses to take quick decisions.