The 2016 Democratic caucuses in Iowa were close, hotly contested, and left supporters of candidate Bernie Sanders frustrated. The caucuses operated as usual—voters show up at a variety of sites around the state, herd into corners of rooms to express their first preference of candidates, realign if their candidates are “non-viable,” and then that final alignment is translated into “state delegate equivalents,” which turn into the way of measuring “victory” from the caucuses. Only those delegate equivalent totals were reported. Questions arose about what happened in those earlier stages of the process.

Reform efforts looked at increasing transparency. “First alignment,” “final alignment,” and “state delegate equivalents” would all be reported.

Of course, increased disclosure means increased complexity in reporting results (related, in part, to the “app” fiasco). And increased disclosure also means increased opportunities to look back at consistency.

It turns out that there have been extensive inconsistencies in how some of the results have been reported.

Truth be told, such inconsistencies probably happen each year. Herd hundreds of people into a gymnasium, line them up in corners, and ask volunteers to count them? Probably some errors are going to happen.

For the most part, these errors are assuredly (1) innocent (e.g., due to incompetence, not malice); (2) randomly distributed (i.e., not likely to systematically favor one candidate over another); and (3) less important if the “state delegate equivalents” are the right result even if other inaccuracies exist.

For instance, suppose a candidate is listed as having 40 supporters (20% of those present) in the “first alignment” but only 39 supporters (19.5% of those present) in the “final alignment,” when present (new) rules forbid “realigning” if your candidate is “viable” (i.e., has at least 15% support) in the first alignment? If the error is in the tabulation of the “first alignment,” it doesn’t actually matter when it comes to the final alignment that translates into the state delegate equivalents.

In previous years, we’d never find that error. But that error is also immaterial to the result. Granted, it exposes this year that the math was not precise, or that there were some errors at some stages of the process, or that volunteer caucus workers were not as careful as they ought to have been—and one can draw preferred inferences from those new details.

All this is to say, the fuzziness of the caucus results worked in previous years because these errors were never disclosed publicly, likely were randomly distributed, and at least sometimes never altered the ultimate results. But more transparency leads to more complexity. And more complexity leads to more highlights of errors or inconsistencies. Ironically, perhaps, the increased transparency has undermined confidence in the results.

Time will tell whether this means changes for the Iowa caucuses. But these are simply my initial thoughts that transparency may yield complexity, which creates its own challenges.