Three Considerations When Working with Data as a Tool
What tools do you have in your tool chest? A few weeks back, I was working to help summarize multiple data sets with over 100,000 rows each and containing a dozen data elements. It was a ‘mountain’ of a task that brought computer processing to a turtle-like pace. After pushing my machine along, I began to think about the different ways this data could be used to solve big problems we had been facing on the project and develop sound solutions that were backed with our findings.
Data is regularly used by more than data scientists and analyst roles to perform everyday tasks and job functions. I began to think about other areas where data has been recently playing a part in my work and noted a few thoughts to be aware of during projects and solutions. As you encounter the need to engage data, here are some considerations:
Where is your data coming from?
Commonly used, and a preferred methodology, formal data gathering is one of the ways to establish data sets that provide trend analysis, future projections, and support varying hypotheses. Likely, you have experienced formal data gathering firsthand. This can be everything from interviews, questionnaires, and surveys.
Recently, I posted on Linkedin using its poll tool asking about the feature’s perceived value. While I am interested in how many individuals use the polling tool, I also wanted to prove out a hypothesis with the post by the way I designed the question set. If LinkedIn users do not engage with polls, then my poll should have a 100 percent result for question 1 (see below image).
What is your perspective on LinkedIn polls that appear on your timeline?
They are helpful and engaging
I do not respond to the polls
The structure of the survey provided me with a limited data set that shared that 65% of respondents find the tool beneficial, however, there was not a fair alternatively phrased response to choose from. When collecting data, think about how the data will be organized and analyzed after it is collected. Putting yourself in a position that yields confusing or incomplete data can be costly to your business decision making.
What Story Are You Intending to Tell With Your Data?
Who is your audience and what do they need awareness into? Data driven decision making is only as powerful as we can then narrate the meaning of the numbers to our intended consumers. While I have not mastered the art of storytelling with data, it is a skill that I focus on regularly. When done well, you will use a combination of skills to gather, sort, format, and summarize the information in a meaningful way.
One of the most common ways to tell a story around data is with a dashboard. Using a tool with charts, tables, triggers, and brief summary text visually highlights the story you want the data to tell. A few minutes reviewing a dashboard can allow someone to gain a high-level perspective, and as a result better decisions can be made.
My roles across different projects have demanded a heavy use of both static and dynamic dashboards to help leaders of entities understand what their data means. I am constantly looking for new ways to use data to help a leadership make the next big decision, adjust action in the moment, and more accurately forecast for the future.
How Will Your Data Enable Others?
Raw data is the formal way to report on elements and allows opportunity for sifting, slicing, and filtering to look at it from different angles. Excel sheets with thousands of rows of data with only a simple column header can be daunting. When presented with data in this format, think about the questions you are looking to answer, and where that can be found in this data set. Take time to filter and sort data to make it digestible and position the audience to use it in a meaningful way. Remembering the story at the beginning of this post, I talked about the 100,000 rows of data: it was raw and required a lot of work (and processing power) to make it digestible.
Informal data can be considered anecdotal. This type of data can be used, but caution should be exercised when decision making is being considered. Anecdotal data can be used to ask new questions, guide next steps of exploration, or help you establish a formal data gathering technique to verify the hypothesis.
We often log feedback from users in our projects to improve their experiences using our processes and tools. The feedback is not quantitative and may be inconsistent in terms of the number of responses or format received. However, we are able to use it to make minor adjustments to our communication strategy, user experience with the tools, and explain trends in the raw data that have been seen.
Before you launch that next poll, survey, or open Excel…
Ask yourself what your goal is with the data being collected. Understanding your purpose with the data will guide you through the process of selecting the correct collection method, type of data you want to collect, tools you can utilize, and position you to articulate the outcomes to your audience. By using these considerations I have uncovered more opportunities to make increasingly sound decisions with data possible.
Written by Jared Riter, Senior Consultant
