You're struggling to get your financial data to tell a story. How can you make it more compelling?

1-Define your core message at the earliest stage that enables a structured and relevant presentation of financial data. 2-Use charts and infographics to visualize the data, complex trends and correlations at a glance. 3-Use summaries and highlight key points to make the data more digestible and more engaging. 4-Analyse the data, establish connections with industry benchmarks, or historical data, and interpret the results. 5-Know your audience and tailor your financial data accordingly to improve engagement. 6-Highlight your data with real-world scenarios to anchor your findings and render them more relatable and understandable. 7-Transform your presentation into a narrative by crafting a story with a clear beginning, middle and an end.

The most important part is to understand the audience for whom you are preparing the data. Start your research about the audience, if the data needs to be more numbers or more snippets. Looking into old presentations that worked will help you. Understand that setting the tone of the presentation is also important as per the audience

If one finds themselves facing challenges in crafting a compelling narrative with their financial data, there are several strategies to consider. Firstly, exploring data visualization tools can transform raw figures into visually engaging insights, enhancing comprehension and retention. Additionally, contextualizing the data within broader industry trends or market dynamics can add depth and relevance to the narrative. Lastly, seeking feedback from peers or mentors can provide valuable perspectives on how to refine and enhance the storytelling aspect of financial data presentation. Ultimately, it's about combining creativity with analytical rigor to captivate audiences and convey meaningful insights.

I think before that (making charts, graphs, and committing to Tell a story), You need to make sure that there Is a story; otherwise, you are not being fair to your audience. If you feel that some key elements/attributes that could help a potential narrative are missing, you need to embark on a Data Enrichment journey to help you tell a consistent narrative.

Para elegir una audiencia y objetivo que permita que los datos cuenten una historia convincente, es crucial identificar primero quiénes son los usuarios finales y cuál es el propósito principal del análisis de datos (Few, 2013). Luego, es necesario comprender las necesidades y expectativas específicas de esa audiencia para adaptar la presentación de los datos de manera relevante y efectiva (Krum, 2013). Además, es importante seleccionar los datos más pertinentes y significativos para respaldar la narrativa que se desea comunicar, manteniendo un enfoque claro y conciso (Iliinsky & Steele, 2011).

Remember that your presentation needs to be sold. Build a storyboard of what all charts can be prepared with the data you have. Use relevant labels only, don't over-populate the charts. Let AI and in app recommendations choose the chart for you. Use charts which are easy to explain.

Visuals are the thing which can help in keeping audience engaged. Can take help of evolving tech. to get best out of what we have in mind .

No matter what tool you use, get that data in MS Excel to get started quickly as you start on the presentation. Use PowerPoint for your final presentation. You may use Canva or other such AI apps that can beautify your presentations.

I have used Tableau for building visualizations and they are one of the best in the industry for just seamless drag and drop options to tell a story. The main thing to remember is that your data needs to be clean and accurate, else the tool is limited in what it can do. Spend the extra time to get your data layer ready before you focus on the user facing experience.

Certainly! Fintech tools offer a range of options to create and customize visuals for various purposes such as financial reports, presentations, data analysis, and more.

Even with all the great visualization tools out there, having a working knowledge of Excel is timeless. You can make beautiful dashboards in Excel that are dynamic based on input/driver cells. Excel also has a very low barrier to entry since it's so ingrained in most companies versus finding a new tool that people may not be familiar with.

I've used Tableau and Power BI to create financial data visualizations. Although I like both, in my experience, Tableau is more user-friendly than Power BI for financial analysts who lack extensive technical knowledge. Regardless of the data visualization tool you use, it's crucial to ensure that the underlying data is accurate. Finance teams often partner with IT to improve data hygiene. The data must be free of duplicates, errors, and inconsistencies. If the data isn't "clean", your visualizations will be inaccurate and could result in poor financial decisions.

Avoid the following at all costs: Misleading scaling: Using non-zero baselines or inconsistent scales on visualizations. Inaccurate/missing labels: Visualizations should have clear and accurate labels for axes, data points, and legends. Overplotting: too many data points or lines can make it difficult to discern patterns. 3D effects: 3D bars or pie charts, can distort data and make it challenging to interpret accurately. Inadequate context: missing background information for the data can leave the audience puzzled. Pie charts for complex data: when used for complex data with many categories they can be very misleading. Truncated axes: exaggerate differences or trends in data; start axes at zero to avoid misrepresentation.

Appropriation is key of success so whenever we talk about finance it has to be accurate as numbers are going to be deal with .

Be selective when showing data points that support the main narrative, but do not omit other important attributes. Use consistent color schemes and legends across multiple visualizations and prevent confusing viewers. Actively emphasize skewed data points, and outliers, by using appropriate statistical measures. This is one of the most important reasons that you resort to visualizations at times.

Auditing your visuals and presentation is critical. Then having others review is key. Something you thought made perfect sense may not make sense to others. This is a great opportunity to get feedback and refine your visuals to ensure your story is engaging. Nothing makes an audience lose trust in an analysis faster than erroneous or misleading information.

To explain your data as a story, start with a storyboard. Draw on a notepad or make a rough presentation to work on your flow. Ensure that the story is memorable so build your characters accordingly. Use a simple language. Start with a why to keep the audience engaged. Show them an insight like a magic trick, the audience should relate with data as well as keep them engrossed. Then end the story like a superhero killing the villain. End on a good and a happy note showing expected results. Run your presentation through a few colleagues before your presentation.

Aim for simplicity and clarity in your visualizations, focusing on conveying key insights and tailoring visualizations to your target audience's knowledge level and needs. Also, when possible, embedding interactive visualizations and providing interactive elements or drill-down options enables viewers to explore the data more effectively.

To improve your skills, practice consistently and set specific goals. Break down the task into smaller parts and focus on one aspect at a time. Seek feedback and learn from your mistakes. Stay motivated and committed, even when progress seems slow. Remember, practice makes progress.

Keep it simple. It's easy to try and overcomplicate an analysis in order to make it look fancy or try and impress leaders. A visual is only as good as it is understandable. Find the simplest way to communicate your story and try that first and then iterate as needed.