Assess Design Research Program
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My next step was to create a spreadsheet to catalogue roughly what we had so I could get a grasp of the size of the data sets and the foci for each (each study was targeted at a different aspect of the software usage, interface, and end-users). Once this step was complete, I met with research program stakeholders (my boss and a few others who had been waiting on these results for a while) and I explained to them what we had and gave them a few options for how we could proceed with clearing the backlog.
The backlog of research was enormous, and to analyze, present, and use it all would not have made much sense because some of what had been collected was no longer useful due to changes in the software development lifecycle and direction that program managers had taken in terms of capability expansion for this software.
Due to that and other emerging priorities, we agreed that only certain aspects of the data backlog would be presented and we would archive the rest. This means that only certain case studies that still had actionable outcomes would be delivered as coherent data analyses to the interested parties, not the entire repository for all studies conducted before my time.
I set up a deadline and milestone tracker for myself to make progress toward each of the data analysis and results presentations that were our new, targeted focus. Throughout these milestones, I set up checkpoints where I would check in with people who were waiting on the information and relay the progress being made.
One of the biggest outcomes of this experience was not just the data from the backlog that was presented to people who needed it to do their jobs, but it was the educational aspect of how to look at data. I was able to use my knowledge to teach engineers, managers, and designers how to think about research and streamline the process for collecting and analyzing data so that the design research program would not consume so much time and lead to a backlog in the first place. I set up parameters for data collection: one aspect of one tool, for instance, or two similar aspects of different tools, tested simultaneously (A-B Study). Most of all, I learned that there is great power in using research to uncover hidden elements in behavior, but only if the data and knowledge gets transferred to the right people at the right time.
