Date Published August 18, 2016 - Last Updated 7 Years, 70 Days, 5 Hours, 2 Minutes ago
If you’ve been asked to provide data, always ask why it's needed. Being the resident data geek here at HDI, I often get requests for data, stats, or metrics. Customers ask for specific information about the industry, and I occasionally receive internal requests for specific data sets or data points about our community. I’ve been playing with data and helping people engage with it long enough to know that the information being requested isn't always the best or right information. If I understand the need the information will satisfy, I can meet those needs much better (and often easier and faster) than if I don’t know exactly what they plan to do with the information. Taking the time to ask what the objective is for the requested information not only saves time but also helps the other parties accomplish their goals or better answer their questions.
In my conversations with the HDI community, I've learned that this step is so often skipped in support organizations. Leaders ask a data analyst to pull a specific set of data or to run certain metrics without sharing information about the purpose or end goal with that data analyst. But it's very possible the requestor might not be intimately familiar with the data, and as with anything, you don’t know what you don’t know. At the same time. the analyst works under the assumption that the requestor knows exactly what they need, and provides the information requested; the data provided can be both time-consuming and inappropriate for the set intentions.
I understand that this concept is somewhat abstract and that data talk can be off-putting, so let me share a story that illustrates this scenario very nicely: It was the 4th of July and my family was spending the weekend at my dad’s house. A friend of my dad’s had offered to paint my daughter’s face before we headed off to the parade. I thought that was a great idea, as it would keep my busy five-year-old occupied as I hurried to get dressed and packed for the day.
Shortly after my daughter had picked out her design, she burst into the guest room where I was getting ready and told me she needed a hair brush. Pressed for time, I didn’t bother to ask her why she needed a hair brush, I just started searching through all the bags and digging through the piles of clothing and toiletries the kids had pulled out earlier. When you have a daughter with super-curly hair, you don’t brush it with a normal brush, so I kept on looking. I thought, maybe the face painter was going to jazz up her hair as well as her face.
We didn’t have much time, so I just kept on searching. Finally, I asked my daughter why she needed a hair brush—which, obviously, I should have done much earlier. She informed me that the artist wanted to pull her wild curls away from her face so it didn’t get in the way when painting the butterfly masterpiece. With that information, I sighed, knowing I should have asked earlier (I mean, I am a researcher), took two steps into the bathroom, picked up a head band from the counter, pulled her mane away from her face, and put it on her head.
The face-painting friend had sent my kindergartner to ask me for what she thought was a solution to her problem. I assumed the artist knew exactly what she needed when she requested a hair brush. I didn't ask the question that could have saved me a lot of time and given her a better solution than using a hair brush on that curly head.
The moral of the story? Take the time to discuss the objective before deciding on and working to provide a solution. There's often a gap in the understanding of the data being requested. The analyst can take into account the properties of the data (e.g., source, sample, parameters, dates, thresholds) that are important when analyzing and utilizing the results.
Data without understanding can be dangerous. If decisions are made or actions are taken from the incorrect information, it can be less helpful than making these moves from no information. If you’ve been asked to provide information, don’t assume the person requesting it knows everything he might need to know about the data. If you’re requesting information, let the analyst know what your objective is—he or she might be able to steer you in a more appropriate direction. In some cases, it's possible that a superior solution already exists that you are unaware of but will better meet your needs. Discuss why the executive team wants that specific metric, or what question your management team is trying to answer with the data set they are requesting. If the data patron and the data analysts are both in the know, they can work together to come up with the best solution.
Jenny Rains is HDI's event marketing manager. Prior to moving into her current role, she was HDI's senior research analyst. Before coming to HDI, Jenny was the research/data analyst for one of the largest school districts in Colorado. Her areas of expertise include survey development, research design, data analysis, program evaluation, and project management.