Read time: 4 minutes
I vividly recall my first analysis as a data scientist. I was brimming with pride. I had gathered masses of data, processed it, and presented a set of amazing insights.
However, I soon realised the real challenge. It was not just producing great analyses but inspiring action based on those insights. To make a difference, I had to evolve my approach and transform data into actionable information.
In this newsletter I'll share the pivotal moments that shaped my journey and present a three-step plan to deliver impactful data insights.
What is “actionable” data?
Now, before we dive into the three steps, it’s probably worth getting on the same page in terms of what I mean by “actionable” data. Here’s my take:
Information that someone uses to take one course of action over others.
There are two subtle but important points to note:
“information that someone uses.” I consider data to be actionable if it is actually used or actioned. Yes yes, I can make all sorts of recommendations to decision makers but the data is useless unless they care about the problem enough to seek guidance.
“take a course of action.“ Behind this one is that the data must help decision makers navigate between actions they can truly take. Recommending “double investment” might be completely impossible.
With this out of the way, let’s walk through the three steps..
1. Find the Right Problems
Rather than jumping straight into data analysis, I learned the importance of engaging decision makers and understanding the problems they cared deeply about solving. I began asking questions such as:
What challenges are you currently facing?
What specific problems are you grappling with?
How does the outcome of these challenges impact you?
Do you have all the necessary resources, or could you use some help?
Would additional information be valuable to you?
By aligning the data analysis with the decision makers' interests and pain points, I ensured that the insights provided would be relevant and compelling.
2. Explore the Options
In the past, I made the mistake of assuming that data would reveal the right course of action. However, I came to understand that it's crucial to consider the available options and potential actions before diving into analysis.
I started asking decision makers questions like:
What potential solutions have you been considering?
What are the current options on the table?
Are there any actions you've already ruled out?
Are there any desirable actions that you can't take due to constraints?
Understanding the decision makers' available choices allowed me to frame the data analysis in a more relevant and practical context.
3. Connect Data to Actions
With a clear understanding of the problem and the available actions, I delved into the data. Instead of just presenting insights, I focused on how each possible action could address the problem at hand. The result was a compelling summary that decision makers could readily act upon, such as:
We're aiming to solve [insert problem here].
After considering [insert possible actions here], our data suggests that [action X] is likely to be the most successful approach.
This analysis dives into why.
By diving into a problem that mattered, then connecting the data directly to feasible actions, decision makers were equipped (and inspired) to take informed steps.
Give me the summary, Simon!
Over time I’ve learned that delivering impactful insights involves more than just presenting data. It requires (1) understanding the specific problems that decision makers are invested in, (2) exploring the options, and (3) connecting the data to actionable steps. Here’s a small graphic if you want a quick reminder:
This three-step plan can help data specialists to provide insights tha have a tangible impact instead of just presenting numbers on a page. I hope this approach helps to elevate your data analyses to new heights of effectiveness and usefulness!
Thanks for reading!
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Love it, thank you for writing this. The first step is crucial and often neglected.