Data which is not actionable is, most simply, data that is not usable or useful. And/or not used (these things are not synonymous). There is a vast amount of data in the world that is in-actionable by this definition, so let me get a bit more specific about some of the ways in which data is NOT actionable, some of which may overlap but I hope will, in general, provide more clarity.
- Data may not be usable because it was collected poorly and so resulting data have major flaws in reliability, validity, and/or relevancy.
- Data may not be usable because it was collected without a clear purpose or plan for use. This can also lead to relevancy issues.
- Data may not be usable or useful because it doesn’t answer the question it’s collection set out to ask, also an issue of relevancy but rather than not having a plan or purpose established, in this case the plan is not executed well — the research questions aren’t translated into data collection tools appropriately, the wrong tools are used, or, potentially, the research questions aren’t particularly answerable.
- Data may not be useful in context of a development cycle, e.g. improvement of a service or program. Lots of information is interesting, but doesn’t contribute meaningfully to understanding whether something is working or not, and how to make improvements, course changes or corrections, or innovations.
- Data is not used. Often because stakeholders, or decision makers, don’t find, make, or grant themselves the time and energy to consider and use it. This is the most common, I think. Vast quantities of data sit on shelves and hard drives, in either raw, original form, or in fully analyzed, reported form. There are a number of reasons this can and does happen.
- And then there is data that is poorly used, neglected, or misused…. Also rendering it inactionable, or at least not wisely acted upon.
Patton discusses many of these issues, includes really wonderful examples, and includes exploration of the politics of use in much more depth in his Utilization Focused Evaluation (start with page 5 to 20 and 24 to 26 in the 4th edition — though he is focused on program evaluation I feel the context and concepts he discusses apply to any evaluative thinking context, and I that is part of his argument as well).
…I feel a future post topic coming here – examples of what it means, or can look like, to use data and use it wisely… anyone have any really wonderful real life examples to share?
What do you think? Did I miss any key pieces? Disagree with anything?
Is ‘actionable data’ just a buzzword? Does it have meaning and application; is it a useful concept? Does it ring true in your experiences interacting with the gobs of information you encounter in your professional or personal life?