In its description of the report, Soluto says that its "big-data frustration analytics" are unique because they're based on "long-term, ongoing analysis of a huge number of PCs" and take into account events like the ones mentioned above (i.e. crashes, etc).
This leads to not entering data, to frustration and to using workarounds, e. g. double documentation with paper.
As people turn to "big data" out of frustration – even desperation – experts caution that data has its limits, as well as dangers.
Aspinall et al. (2015) reported that when respondents moved into a green space zone, their electroencephalography (EEG) recorder data showed lower frustration, attentional engagement, and arousal, but higher meditation.
16 Care had traditionally been face-to-face, but continuing to use this model to try to respond quickly to the telemetry data had its frustrations.
Many also expressed frustration with data they deemed inadequate, such as short-term trials in relatively healthy people.
One of the things I thought was so exciting about writing this paper is it puts data to that deep frustration that we see in younger generations right now.
Furthermore, the waiting time increased due to data entry causing more frustration to the patients, for example, "The patient upset because of waiting time" (FG3).
Cost-effectiveness data--especially wide variation between discounted and undiscounted data results--caused frustration among panelists regarding the real significance of these metrics, especially since discounting disadvantages children, which was seen as inequitable.
This approach was chosen because the target users were not experienced in handling computers, and mandatory data entry may cause frustration and dangerously detract users from the care process.
