How can you make BI data more engaging for non-technical audiences?

Understand the business / functional requirements from the non-tech users and after analyzing developed dashboards/reports that may fulfil their desired outcome and can help them to take actionable decisions on time. To make it interactive, using the right visuals to display the right information is what BI expert has to do.

Interestingly while communicating with business users the user becomes more important than the visualisation itself. Understanding the audience's background, interests, and learning style is crucial for effective communication. This could be different for different audiences and of course it's impossible to tailor the data story for each. Still, you can try to use Gen AI platforms like Super AI to help generate user persona and build data stories based on them.

In my experience, we should use simple charts that can convey information more quickly. Choosing the right color scheme plays a key role in highlighting an important data point. We can also take into account infographics visual to break down complex information into more understandable format along with incorporating icons and images.

Here are a few tips to make BI data more accessible to non-technical audiences: Instead of tables of data, use visualizations such as charts, graphs and dashboards. These visualizations are easier to understand. Instead of being overwhelmed by too much data, focus visualizations on core metrics and insights. Highlight what’s relevant. Use dashboards and dashboards to tell stories and emphasize trends and relationships. Create custom data views and analytics for various business roles, such as Finance, Marketing etc. Use plain language to explain insights from data, rather than technical jargon.

1. Audience understanding: Tailor data presentations to match non-technical audiences' needs and preferences. 2. Research roles and objectives: John researched his sales team's objectives to create a BI dashboard highlighting key performance metrics. 3. Simplify complexity: Present data in a clear, concise, and visually appealing manner. 4. Use storytelling: Sarah used real-life examples to illustrate data insights and make them more relatable. 5. Focus on relevance: Highlight data that directly impacts the audience's goals and challenges. 6. Interactive visuals: Incorporate interactive charts and graphs for a more engaging experience. 7. Seek feedback: Gather input from non-technical users to continuously improve data presentations.

My 3-point rule, which has helped me in laying a solid foundation for data storytelling: 1. Simplification: BI transforms complex data sets into understandable narratives, making it easier for teams to grasp key insights and trends without getting lost in the numbers. 2. Contextualization: It places data within the context of business goals and challenges, allowing decision-makers to see the relevance of insights to their strategic objectives. 3. Engagement: Data storytelling with BI fosters engagement by connecting data points to real-world outcomes, motivating teams to take informed actions based on compelling evidence. Which one is the most useful?

This is part of the 'Art of Demo-ing'. Presenting a pain point and ways to overcome with a story from data owned by audience (do you read PoCs?), make so much sense. Ex: problem-solution-benefit or a before-after-impact, to guide your audience through the data and show them the value and implications. Using simpler and clear ways of conveying; sometimes from other companies in their industry or from other industries too is very effective. Over selling ourselves with Jargon may help depending on the audiences, but Keep It Simple and Stupid (KISS) will hardly-ever go the wrong way. Analogy, example, even a relevant joke can help grab attention. Important and difficult at times is telling a story without voice (slides). Use getsuper.ai.

Humans are always excited about relations and comparisons through stories soteeling a story that connects to your data would be a great communicating factor that would glue you and your audience together for a longer period of time, which would make them understand your work better.

I often see dashboards with acronyms, jargon and colors without any legend or definition. Your audience will change; make sure to define all key metrics in simple terminology.

Data Story telling is very critical to hook up the audience with your dashboards or analysis. Dashboard can be boring if the data or chart is not presented in the right context. Start with a problem and try and solve the problem by creating a story with your solution and attach charts and graphs along with the flow of the story. The audience will then understand the correct way to use the dashboards and generate value from it.

These days there so many chart types available and so many of them overlap with each other in terms of what they convey. There are equally large proportion of people/leaders who advocate their own preference of charts and chart types. But remember: 1. KISS never fails 2. Context of the Visualization is utmost important 3. How humans perceive various chart types (including tables) must be understood. 4. Effective use of Colours (do NOT Overdo) or placement on screen needs attention 5. Interactivity between charts on screen deserves its due importance 6. Some basic textual guidance is advangeous (do not overdue) 7. Set standards for colour/text/placements/etc, helps in the long run.

It is important to understand what we are trying to show and if it can be simplified? Not every user is going to understand box and whiskers graph and some are not even going to understand the stacked column charts. Working in the agile way to get continuous feedback from the audience helps in saving a lot of trouble at the end.

"Save your pies for dessert!" Pie charts make it challenging to see the difference between values. Consider using stacked bar charts instead.

Utilize the below basics while designing the visuals: - Keep it simple - Do not clutter the page with too many charts - Keep the design and theme appealing - Use the soothing colors or use brand specific colors - Use labels, legends, axis appropriately - Choose correct chart for specific analysis

One thing I've found helpful is to visualize the data using charts, graphs, and other visual elements. Instead of presenting raw numbers, I create visually appealing visuals that help convey the key insights at a glance. I use simple and intuitive visualizations, such as bar charts or pie charts, to make complex data more understandable for non-technical audiences. This approach not only makes the data more engaging but also enhances comprehension and retention.

Easy Forecast, Non-Complex Structure, and little optimizing over the components with keeping the re-design in mind where the end user may use the Tool or Product for the first time can help!

In my experience, allowing audiences to interact with the data has been highly effective in engaging non-technical users. I create interactive dashboards or reports where users can explore the data themselves by applying filters, drilling down into details, or selecting specific metrics. This hands-on approach not only empowers users to discover insights at their own pace but also fosters a deeper understanding and appreciation of the data.

Once again KISS is valuable and so is to ensure not to overdo anything. Interactivity helps understand data in a clean and quick manner. Make sure it is neat clean and more obvious (with short bullet point (one point) text. Drill downs/buttons/drop downs/etc etc are good. But making a single "Mother of All Dashboards" is a big NO. Avoid serving too many contexts in a single screen. Subtle, Elegant, NOT too busy are considered good comments for our dashboards. Implied filters in a chart to filter the rest of the content, is an effective & intuitive use of screen space as well as interactions.

Letting people play with data makes BI more interesting for non-tech audiences. Clickable stuff helps them dig deeper. It's like going on an adventure, figuring out things like solving puzzles. This way, they understand better and get more into it, making the whole data thing more fun and exciting.

Interacting with the data is an advantage of using a BI tool, such as Power BI. Just remember who your audience is (and will be). Is your report intuitive without any training required? If interacting with your report requires explanation, training or is hidden somewhere I would only find if curious enough to explore, then you should consider removing it or enhancing it to make it intuitive. Add a button rather than relying on the user to find an option in the right click menu.

This is another effective way to attract and stick. Basic visual characters ('$' for Revenue, Triangles pointing up or down with Red/green colour, '|' - pipe signs for separators are logical) are used by many. Using Smileys in some corporate dashboards/visuals could be creative. Using short phrases by the title of the visual/dashboard could be useful too (maybe change it with every release which helps audience easily to track versions), coud be beneficial in the long run.

I also find it's helpful to use concrete, tangible objects when explaining abstract concepts. For example, a dollar sign for profit, a person when monitoring churn. It's easier to recall things we recognize.

Present BI data in the form of compelling narratives that evoke emotions relevant to the audience's experiences or challenges. For example, instead of simply displaying charts and graphs, frame the data within a story that highlights the impact on customers, employees, or the community. Use language that resonates emotionally and helps the audience connect with the data on a personal level.

While working on projects, I've discovered the power of infusing emotion and humor into BI data presentations. I incorporate anecdotes or examples that resonate with the audience's experiences, evoking emotions and making the data more relatable. Additionally, I use light-hearted humor to lighten the atmosphere and keep the audience engaged. By adding a human touch to the data, I create a more enjoyable and memorable experience for non-technical audiences.

Adding feelings and jokes can make BI data more fun for non-tech people. It's like putting emojis in your texts to make them more interesting. By making the data more relatable and funny, it's easier to understand and remember. It's like making a boring class more entertaining with jokes and stories.

In my experience, continuously seeking feedback and striving to improve is essential for making BI data more engaging for non-technical audiences. After each presentation or interaction, I actively solicit feedback from the audience to understand what resonated with them and what could be improved. I use this feedback to refine my data presentations, incorporating suggestions and making adjustments to better meet the audience's needs and preferences. This iterative process ensures that each presentation is more engaging and effective than the last.

As Feedbacks are the most useful insight any business has, BI owners can understand how simple can we furthermore Breakdown it into, also at times the design if the product in order to keep it minimalistic and appealing, it becomes more of a Task for user, we can use simple yet easy to understand design structure.

Consider if the data story meets the business user's objectives. The engagement will increase with the relevancy. You can tell someone how rockets are being commercialized or you can tell someone how they can launch a satellite with commercial rockets.

Muy sencillo. Una audiencia no técnica no quiere datos, quiere conclusiones, propuestas, resultados, ideas, en definitiva, quiere algo de valor. Organiza tu discurso alrededor de los hallazgos y muestra sólo la información necesaria para demostrar tus conclusiones. Si además utilizas un lenguaje sencillo y directo, le das un toque personal a la presentación, cuentas una historia y a?ades un poco de humor, tendrás el éxito asegurado.