There were 39 organizations that participated in both the 2018 survey (year 1) and the 2019 survey (year 2). Data were analyzed to examine whether turnover, vacancy rates, and hourly wages (starting, average, and highest) changed significantly from year 1 to year 2. Organizations who completed the 2018 survey in year 1 were invited to attend a 2-day workshop about understanding their data and selecting workforce interventions. The organizations who attended the 2-day workshop were then able to receive individual consultation from staff at the University of Minnesota’s Institute on Community Integration. They were also invited to attend webinars about workforce interventions. The assumption at the beginning of the project was that turnover and vacancy rates would decrease and wages would increase after this intervention.
Two limitations make interpretation of the results difficult. First, the underlying assumption of a study looking at change over time is that conditions remain the same, including the measurement tool. The survey was reduced in length and a few new items were added after the first year, which is not uncommon. However, the survey was completely reformatted. The order of items, the format of some items, and the overall survey format were changed. Second, the 2-day Understanding Your Data workshop occurred mid-September 2019. The individual consultations did not begin until November 2019, and not all organizations had their first individual consultation before the end of 2019. Though webinars were key components of the intervention, they were not scheduled to begin until January 2020.
Therefore, due to the lack of consistent measurement tools from year 1 to year 2 and the later delivery of the intervention, any statistically significant results cannot be directly connected to the intervention. Significant increases or decreases may be due to the intervention, but they also may be due to the change in format of the survey. The change in the format may have made the experience better or worse. We simply do not know.
Lastly, samples were too small to do analyses by region.
DSP Turnover (Crude Separation Rate)
DSP Vacancy Rate
Organizations provided data on wages for all of their DSPs, their part-time DSPs, and their full-time DSPs. The average starting wages for DSPs from 2018 (year 1) and 2019 (year 2) are shown in Figure 17.
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