When it comes to analyzing data trends (changes in data over time), it's important to keep in mind that the data does not have to be perfect (data never is!) in order for it to be useful.

In a conversation with a client recently, the client pointed out that their membership dashboard over several years is not 100% accurate, and therefore can't be trusted. They explained that some of the data for certain years was inaccurate (sometimes as much as only 95% accurate). And thus they didn't think the trending data was useful.

But here's the thing: the point of trending data is to see trends. Is membership growing? It is flat? Is it shrinking? Unless you're dealing with really small data sets (e.g., 50 members), a few percentage points off perfect is unlikely to affect the overall trends.

As the old saying goes, don't let perfect be the enemy of good. If you're trying to detect trends, "close enough" is very likely to get you the information you need to act.