Analytical skills are essential for making data-driven decisions, but they are not enough on their own. You also need to communicate your findings effectively and take action on them. In this article, you will learn how to do that in six steps.
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Before you start analyzing data, you need to have a clear and specific goal in mind. What problem are you trying to solve? What question are you trying to answer? What outcome are you hoping to achieve? Having a goal will help you focus your analysis, choose the right methods and tools, and measure your results.
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To effectively translate analytical findings into meaningful actions, define objectives, communicate findings, prioritize key insights, link them to business strategy, create an action plan, involve stakeholders, align with decision-making processes, implement incremental changes, monitor progress, encourage continuous improvement, provide training and support, communicate internal changes, measure and quantify impact, celebrate successes, and document lessons learned. This dynamic process requires collaboration, adaptability, and a commitment to using data-driven insights for positive change within the organization.
The next step is to gather the relevant data that will help you achieve your goal. Depending on your data source, you may need to use different techniques to access, extract, and store your data. You also need to ensure that your data is accurate, complete, and consistent. You can use various methods to clean your data, such as removing duplicates, outliers, and errors, filling in missing values, and standardizing formats.
Once you have your data ready, you can start applying analytical techniques to explore, visualize, and interpret your data. You can use descriptive statistics to summarize your data, inferential statistics to test hypotheses and draw conclusions, and predictive analytics to forecast future trends and scenarios. You can also use tools like Excel, Python, R, or Tableau to create charts, graphs, and dashboards that illustrate your findings.
After you have analyzed your data, you need to communicate your findings to your audience, whether it is your boss, your client, or your team. You need to tailor your communication style and format to suit your audience's needs, preferences, and expectations. You can use reports, presentations, or stories to convey your findings, and use visuals, narratives, and examples to make them engaging and memorable. You also need to highlight the key insights, implications, and recommendations that emerge from your analysis.
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At a technical level, communicating findings has to do with summarizing the analytics work performed. However, the most important component is taking this technical output and conveying it to stakeholders/clients in way that matters to them the most. While I love to look at statistical metrics after an analytics project is completed, I know my clients want to understand how this translates to dollars and cents for their business. Understanding client KPI's at the outset of a project is vital. With this knowledge, reports can be created on the back-end that show how an analytics solution will improve these KPI's in practice. Clients want to know how their $1 spent will return $10 in value.
Communicating your findings is not enough; you also need to take action on them. You need to translate your recommendations into concrete and feasible actions that will help you achieve your goal. You can use frameworks like SMART (Specific, Measurable, Achievable, Relevant, and Time-bound) or OKR (Objectives and Key Results) to define your actions, assign responsibilities, and track progress. You also need to align your actions with your organizational strategy, culture, and resources.
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Turning recommendations into action requires a work breakdown structure that's actionable. Oftentimes, recommendations are high-level [qualitative] descriptions of what needs to be done but not worded in a way that's necessarily actionable. Recommendations should be decomposed into incremental steps that can be completed in ways that are [quantitatively] measurable. A 'definition of done' should also be agreed upon to make sure everyone involved knows when it's considered complete or not. SMART goals and OKRs are effective techniques but often used too loosely, leaving too much room for interpretation resulting in incomplete work or shattered expectations. Be sure to define SMART goals/OKRs in ways that are clear and measurable.
The final step is to evaluate your results and measure the impact of your actions. You need to compare your actual results with your expected results, and identify any gaps, challenges, or opportunities for improvement. You can use metrics like KPIs (Key Performance Indicators) or ROI (Return on Investment) to quantify your results, and use feedback, surveys, or interviews to qualitatively assess your results. You also need to document your results, share your learnings, and celebrate your successes.