What do you do if stakeholders struggle to understand your data analysis results?

Collect feedback. Adjust the terms used in the results. Reevaluate the visual presentation of information. Simplify, not all data always needs to be shown. Present the results and leave a support channel for questions. Collect usage metrics.

Break down complex data into simpler, more digestible formats. Avoid technical jargon and focus on the most relevant data points. Simplification helps stakeholders focus on what matters most without getting overwhelmed.

Try putting yourself into the shoes of your stakeholders: What is important for them so they are successful in their role? Once you find this essential piece, see how your data can tell a compelling story enabling them to be (more) successful.. and as result your data becomes more understandable. As a result of this process, you might need to simplify data tremendously to showcase only most relevant bit.

1. Simplify Data - Break down complex concepts. - Use analogies and avoid jargon. 2. Visualize Data Effectively - Use graphs, charts, and infographics. - Ensure visuals are clear and informative. 3. Provide Contextual Information - Frame data within relevant contexts. - Explain relevance to stakeholders’ goals.

If stakeholders struggle to understand your data analysis results: - Simplify your language - Focus on the story - Use Visuals - Check for understanding For example, Imagine you're analyzing website traffic and find the homepage gets the most visits but conversions are higher on the product page. Explain this plainly and visually (like a bar chart) to show where visitors go and what action they take. #Happy_Learning

Annotations can serve as a powerful visual aid in data analysis, helping to direct the viewer's attention to specific areas of a plot and clarify the significance of the data presented. In some cases, a document containing a series of annotated screenshots from a dashboard can be an effective way to narrate your analysis. This approach allows you to sequentially build the story, ensuring that each point is clearly communicated and understood. This method can be particularly useful when dealing with stakeholders who may prefer traditional reports or are less familiar with interactive BI tools.

A picture is worth of thousand words means having a visual representation of the results as it can give them a clear picture of what they are looking for, at first glance. The most common way is to use different types of charts and graphs to display the information. Furthermore, infographics, cheat sheets, and carousels can be used as well. Visuals can help you the information quickly such as a bar graph that can show the min and max at first glance, or if you have a line chart or scatter plot, it can show the common trend and then the outlier sitting outside the common trend will be quite obvious.

Incorporate charts, graphs, and infographics that visually represent the data. Visual aids can help stakeholders quickly grasp trends, comparisons, and statistics at a glance, which might be missed in text-heavy reports.

- **Simplify Visual Information** - Avoid overcrowding visuals with excessive data. - Use simple, direct graph types for clarity. - **Contextual Relevance** - Tie visuals directly to the audience's interests or business objectives. - Provide legends and captions that contextualize data within the viewer's experience. - **Regular Updates and Accuracy** - Ensure data in visuals is up-to-date and accurate. - Revise and adjust visual aids regularly to reflect the most current data.

Not only do visuals help to tell the story, but they also help to validate our analysis. Does an upward/downward trend in the data fit the reality? If your data says that over the last year, team A is most productive after 3:30 p.m. every Tuesday then a line graph denoting the trend with 52 lines laid over the 5 workdays is much easier to consume than a table showing 365 rows of data

Tailor the visual aids to match the stakeholders' preferences and expertise, ensuring maximum impact. Also, add brief explanations and context to each visual to help guide stakeholders through the data. Regular feedback allows you to refine visuals based on input, improving communication effectiveness.

Identify gaps in stakeholders' understanding and address them directly. This might involve explaining data collection methods, analytical techniques, or the implications of your findings, ensuring stakeholders have the foundational knowledge needed to understand the results.

To further bridge the knowledge gap, encourage stakeholders to ask questions and provide feedback during presentations. This interaction allows you to address specific areas of confusion and adjust your explanation accordingly. Facilitating an open dialogue ensures that stakeholders are actively engaged and their concerns are addressed, enhancing their understanding and trust in the data analysis process.

I actively engage stakeholders through various interactive formats like demos, tech talks, fireside chats, one-on-one meetings, and working sessions. This approach helps me effectively communicate with them and understand their concerns. By brainstorming together, we identify and address specific pain points, ensuring that everyone's needs are met and fostering a collaborative environment. This method not only clarifies any confusion but also enhances the relevance and impact of our solutions.

Offer your interpretation and actionable recommendations, and be open to discussion and questions to ensure everyone is on the same page. Tailor your communication to their level of understanding and follow up to address any lingering doubts or confusion, aiming to make the insights accessible and meaningful to all involved.

Understanding who your consumers are allows you to prepare data and create visual aids that are not only accessible but also interactive. By making the data easy to understand and engage with, you ensure that stakeholders can effectively draw insights and make informed decisions, appreciating the full value of the analysis you provide.

Provide ongoing support after your initial presentation. This could include Q&A sessions, additional documentation, or even follow-up meetings to revisit the data as stakeholders digest the information.

Execution and the time to market are essential in today's AI-driven ecosystem. - After providing the data analysis the stakeholders require ongoing support to implement the recommendation - Schedule regular meetings to answer their queries and questions - Provide detailed reports and documentation for their reference - Monitor the output from the implementation report and validate your recommendation and findings Example: You have provided the data analysis (bag of words, n-grams, topic modelling) of which theme/idea will be effective for YouTube ads for the product by providing keywords and metrics. Evaluate the sales and YouTube Trends to support the stakeholders and provide them with the next steps for implementation.

Actively listen to your stakeholders while they attempt to interpret the results without your help. This will help you identify the root cause of their struggle. E.g. Did they expect a clear cut answer on a written report and you provided an exploratory interactive dashboard instead? When stakeholders struggle to understand data analysis results, I find it's often due to a mismatch in expectations regarding the presentation of these results