Running the Data for Better Lives and Better Work
As part of my job, I work with data every day. I collect it, match it, aggregate it, and analyze it. The other day, it occurred to me how much I also use data in my everyday life without even thinking about it. I collect data about my work hours, our household budget, my daughter’s eating and sleep schedules, weekly workouts, groceries, etc. Although my personal data files are much smaller than those I use for work and the analysis is much simpler, the purpose of collecting and analyzing both is the same—I want information about what is happening. I want to know what has happened and what is currently happening. I also want to know how things have changed over time to see what may happen in the future. Data are important because without data, the only record of what has happened and is happening is our memory of events. Personal experience has taught me that memory is often an approximation of what really happened.
The data I keep personally tell the story of my habits and my day; the data I use for work can tell an agency’s story. It can describe the work the agency does and the clients they serve, and it can show how those things have changed over time. Data can also indicate where additional resources are required, what those resources should be, and can inform the agency about their practice’s effectiveness (are the services provided having the desired effect on client outcomes?). However, whether that story is fact or fiction depends on the quality of the data recorded. In order for data to tell a factual and interesting story, data captured by the system must reflect things that the agency cares about, and the data must be entered accurately.
As I mentioned above, I keep data regarding my workouts. In particular, I keep data regarding my running schedule: the frequency, pace, and duration of my runs and how those things look over time. In order to do so, I record the starting and stopping time of each run, the number of miles I ran, and the date of the run. Much like these elements are essential for examining my personal running schedule, agencies must determine which data elements are essential for examining and describing their practice. If the agency is interested in examining recurrence measures, they must determine what those measures are and make sure that the information required to track recurrence is entered into their system. They also must make sure that the system has the necessary requirements to match and follow one client or group within the system over time. Once the system is set up to store essential data, the next step is relating the importance of the data itself and the data’s accuracy to staff who enter it.
I enter data about my running schedule because it is important to me and it improves my performance. I realize that if I enter the times or the number of miles incorrectly, my average pace will be incorrect and the data will not be able to provide useful information to answer questions I have about my schedule. Similarly, it is important that agency staff who enter data about clients and services understand how data can help them, the agency, and their clients. Data can demonstrate how much work they are doing, where there are gaps in resources, and how their client populations change over time. If workers understand that data can help them personally and help improve their practices, and if the data are useful to them, they are more likely to make sure it is entered accurately.
Andrea Bogie is a researcher at NCCD.
Andrea, thanks for sharing how you use data in your everyday life. Makes the idea of data analysis much less daunting!