woman throwing confetti

Analytics Strategy for Surveys-at-Work: Casey-Fink

The words “analytics strategy” can be scary, but really it’s just a) identifying what we want to know about content and how it gets used; and b) defining clearly how we’re going to do that. Today’s post shares an excellent, non-tech example.

In a previous post, I introduced a working-out-loud case study — an analytics strategy I’m developing around a survey. This post shares some common information around the survey I’m going to be working with, so you can compare/contrast your thinking with my writing and learn with me.

The toughest and scariest part is just the inertia of getting started. Question-storming is an approach I’m going to use, but I want to acknowledge that even for me, I’m apprehensive at the start of every analytics strategy.

Bokeh night
Acknowledging whatever caveats and biases I need to, up front, helps me “bokeh” the part of my mind that stays focused on doing stuff right — so I can focus on the task at hand, which is coming up with questions that encourage helpful conversations with team members and stakeholders. Those conversations must yield more applicable or interesting questions, and vet/weed out what I’ll introduce.

I like to think that the feeling I have that “I’m not an expert, I don’t have all the answers… I don’t even know what questions to ask” is a healthy reflex. Which is why, for me, the first sharable draft is meant to be a social object I use to inform a second-draft — usually the one we start referencing in JIRA, so within a meeting or two we might be “done enough” to move forward with planning for the first few sprints of work.

The “Casey-Fink” Survey

For today, though, I want to share an analytics strategy that’s well-vetted, not originally put together by big data brains but rather big nursing brains. The analytics strategy I’m developing is like a para-analysis of something well-researched, applied locally, shared globally and then became an industry standard, of sorts.

The Casey-Fink Graduate Nurse Experience Survey (CFGNES) is cited in hundreds of nursing industry journals, as well as academic research. The survey is used to assess the workplace experience of a newly graduated nurse. In their research, Casey & Fink demonstrated up to 35% of new nurses leave nursing in their first two years on the job (and of course I’m really short-cutting things) because of a few drivers:

  • Support
  • Patient Safety
  • Stress
  • Communication/Leadership
  • Professional Satisfaction

Analytics Opportunities

As part of their survey’s release, Casey & Fink include a document that not only details these drivers, but the psychometric model, or the specific methodology used to inform how to make sense of the data, in terms of what it says about people. In addition, Casey & Fink released documentation on how they map variables in the survey to their interpretation of the results as well as the actual algorithms used to calculate the survey results for correct interpretation.

Casey & Fink offer a fully realized analytics strategy for their survey. Nursing administrators and leadership use the survey results in hospitals as a social object to spur the conversations necessary to make constructive changes and improvements to encourage the healthy start of long careers in nursing.



One response to “Analytics Strategy for Surveys-at-Work: Casey-Fink”

  1. […] my last post, I shared a bit of background on the Casey-Fink Graduate Nursing Experience Survey, which I’m using in an ongoing case-study on how to approach analytics strategy. […]