Learning #2: Work more strategically, identifying key stakeholders and their concrete needs rather than making assumptions and jumping into analysis.
During these stakeholder meetings, we came up with one or two concrete use cases that we could explore with each group right away. By breaking down and exploring individual use cases, we avoided devoting large chunks of time to creating a bulky report that lacked context—a report that stakeholders might skim briefly, then discard. Pursuing individual use cases enabled easier execution, evaluation, and refinement.
By starting small, we could focus our efforts on the most important use cases, then build on our success over time. By demonstrating clear impact and positive outcomes early on, we increased stakeholder buy-in and confidence.
Learning #3: Break large daunting tasks into more manageable chunks, then iterate, test, and refine incrementally.
The next time you feel overwhelmed by large amounts of data, take a deep breath and acknowledge that you already have the skills you need. Take a step back and think about what you’re trying to achieve overall. Ask yourself these questions:
- What is your ideal outcome?
- Who are your stakeholders?
- What are they trying to accomplish?
- What data is available?
- What analytical methods are available?
- How can you use this data to help answer your stakeholders’ burning questions?
- Who else can help you analyze the data?
- How can you make your output optimally digestible and impactful?
Applying Design Thinking When Working with Data
You can apply the design-thinking process shown in Figure 1 when tackling data problems.
Image source: “What Is Design Thinking? A Comprehensive Beginner’s Guide,” by Emily Stevens, on Career Foundry.
To act on your product-usage data, follow these steps:
- Empathize—Identify the stakeholders for your data analysis.
- Define—Identify your stakeholders’ main goals, questions, and the problems they need to solve.
- Ideate—Determine concrete use cases for the data for each set of stakeholders.
- Prototype—Compile, synthesize, and analyze the relevant data for each use case.
- Test—Present your data findings and insights to your stakeholders, asking whether they’re useful and actionable.
- Iterate and refine—Based on stakeholder feedback, iterate and refine your analysis and data presentation as necessary.
- Expand—Add more use cases and repeat this process.
Data collection alone is not enough. You need to make sense of your data, then act on it. Instead of becoming overwhelmed by analysis paralysis and falling into inaction or waiting for the perfect solution to come to you, jump in and put your design-thinking skills to work. Identify the key stakeholders who could and should act on the available data, then learn about and understand their core questions. Instead of working in isolation and making assumptions, collaborate with your stakeholders to review the available data and brainstorm possible use cases. Working together and starting with concrete use cases can save you countless time and effort and make your work infinitely more impactful.