How do you present complex data simply?

Generally an Engineering and or Analytics team will have 2 types of audiences - 1. Technical audience - These are data operational, analysts and engineers who are close to code and data bases and data. 2. Non - Technical audience - these are your tenants and senior management- these cover directors and CxOs Your dashboards should be designed keeping non technical audience in mind. Dashboards should be compelling and convey story at the first glance. Dashboards could provide drill through into detail of reports Technical audience will deep dive into reports of those dashboards and will by default understand your presentations and dashboards if your story is conveyed

Defining your target audience is key. For example I am working on a project right now that will be reporting KPI’s for marketing, sales, finance and product. To avoid have a dashboard that is to busy I would segment these by department for easy readability and access.

A holistic communication approach often involves embracing multi-modality, leveraging multiple formats simultaneously or sequentially. For instance, a report can be accompanied by an interactive dashboard for a deep dive or a slide deck summarizing key insights. Different formats can cater to varied feedback mechanisms. While a dashboard might provide real-time feedback, a report may have embedded forms for structured feedback. Understanding this can influence which format you lean on at different stages of your communication. An advantage of multi-modality is the adaptability it offers. You can trust another if one mode doesn't resonate with an audience. This flexibility can be invaluable in evolving scenarios.

As a biomedical engineering grad student, I can't emphasize enough how crucial this advice is. Whether it's explaining the intricacies of a novel medical device to fellow engineers or presenting research findings to clinicians or policymakers, understanding your audience is key. It's not just about what you say but how you say it. Our field is so multidisciplinary, and audiences can range from highly technical to practically non-technical. Tailoring your message appropriately can make all the difference in effectively conveying the significance of biomedical engineering advancements and their real-world impact. It's about bridging that gap between innovation and understanding, and that's where the true magic of communication happens!

Stay concise and straightforward. Avoid using flashy visual aids that don't add genuine value to the analysis, even if some might perceive them as impressive. Remember, visual aids serve as a language, so you should assess whether your audience can understand them without additional explanation. The most effective visual aids convey the message and value on their own, requiring no interpretation. You're not explaning the visual aids but discussing potential solutions and future prospects.

Crafting a compelling data-driven narrative demands strategic use of visual aids. Infographics distill complexity into digestible nuggets, while charts unveil trends at a glance. Present to execs? Elevate with impactful summaries, spotlighting key insights. Dive into specifics for analysts, coupling visuals with explanations. Interactive visuals engage, fostering deeper exploration. Tailor visuals to your audience, letting them uncover the story effortlessly. 📊🖼️ #VisualStorytelling

Using pictures to explain things helps clarify complex things better. It's like when you show a picture to show something instead of just using words. For example, if you want to show how things are spread out, you can use a picture with bars. Similarly, to depict changes over time, a line indicating upward or downward movement can be used. Picking the right picture helps make your point better. When conveying information to others, incorporating visuals that correspond with the subject being discussed aids in comprehension and retention. Much like a picture simplifies explanations, the fitting visual representation can elucidate the shared information with others.

I've found this method very helpful for simplifying presentations: when presenting complex data, consider three versions - a 30-second summary, a 2-3 minute version with main points, and a one-page overview. This approach narrows down the core message and highlights essential data, preparing you for in-depth discussions if necessary.

In my opinion the most important aspect is to really understand your data and the audience, if you really have a good grasp of both you should be able to present any sort of data. This is my strategy for very complex pieces of information: 1. Write down the most important finding in your dataset (after analysis - can still have technical language)… bullet points are very useful. 2. Organize the information from the bullet points in a logical way, this will allow you to “tell a story” that would make sense. 3. Replace technical words for a simpler version or a common word for it. Evaluate if the message is still the same. 4. Summarize the info from point #3 This simple approach is a game changer.

Here’s a streamlined framework marrying data with storytelling: • Table of Contents: Begin with a concise outline. • Project Overview: Set the context, akin to a story’s backdrop. • North Star Metrics: Introduce key metrics as central elements. • Insights & Recommendations: Reveal findings with visual aids, echoing a plot’s progression. • Technical Process: Briefly outline your approach and assumptions. • Caveats and Next Steps: Address potential twists and future pathways. • Appendix: Offer detailed insights into your process or provide supplementary visuals, akin to a novel’s endnotes. By transitioning from overarching context to detailed insights and potential future paths, your presentation will keep your audience engaged throughout.

Every data analysis should reflect in a “so what” - actions that you can take based on data. A lot of the time people analyze data without coming up with actionable insights and that’s the most critical part.

I recommend people select one key message for each type of visualization and explicitly stating this when presenting them. Each visualization can then be used as a signpost for your data story: taking the audience from the focus problem to the question and the final conclusion. In addition to this helping you figure out why you're presenting a piece of analysis in the first place, it's a practical approach for making your data story more accessible.

Share alternative theories, other sources of data, other explanations and do talk about shortcomings. IF you are upfront about those, people are more likely to accept the rest.

Everyone who looks at data, wants to see its evolution. Past may not be a guarantee for the future, however past creates the story with an effective and strategic use of data. And our projections base themselves to some extent on the past learnings from the data analysis and reporting. Your projected self( evolution of business) therefore dictates what story needs to be told for the future success and where in your past are the seeds (datasets, analytics) can be found to make a pursuasive case to those looking at your analysis and future.