# Sharing Data Early and Often By:: [[Brian Heath]] 2023-06-15 People fall into one of two camps when it comes to sharing data. The first is to hold back the data until everything is sufficiently "figured out" and "checked." Here data is only shared once it is correct and well-understood because decision-makers will immediately make decisions as soon as the data is available. Any missed errors or dynamics will immediately propagate throughout the organization, and it may be impossible to reverse decisions when data errors or misunderstandings are identified. The first issue with this belief system is it assumes data is a constant and objective representation of reality. Data is fluid, never-ending, subjective, and constantly changing. It is easy to let perfection be the enemy of good and never deliver any data. The second issue is this belief system assumes decision-makers are incapable of dealing with uncertainty and evolving situations. In short, this belief system does not treat decision-makers as informed adults. Perhaps they are unaware of the assumptions baked into the data and possible gaps. But whose fault is that? Might it be the analyst's responsibility to share this with the data? Holding back data until it is "perfect" is slow to act, shortsighted in possibilities, and demonstrates low data maturity and organizational understanding. The other camp shares curated data as it becomes available so the decision-makers are constantly informed and updated on the situation. The data may be flawed, but it is still shared. The sample size may be too small for statistical relevance. Still, suppose the analysts have excellently developed the organization's analytics competency. In that case, there is no reason the data could not be delivered with the short reminder of the small sample size. If it does nothing, it alleviates organizational anxiety about what is happening. Yes, the results may change, but there is comfort in knowing data exists and the data team is on it. Furthermore, it would be a great learning experience for the organization if early conclusions changed as more data was collected. It highlights confirmation bias and makes statistic theories something tangible. Keeping all the data locked away because one is scared of what will happen reflects insecurity. This could be internally motivated, or it could be imposed on you via the organization. If the organization demands data perfection, quit as soon as possible. It's an impossible ask and not worth the physical and mental side effects. #### Related Items [[Data]] [[Analytics]] [[Organization]] [[Business]] [[Work]] [[Perception]] [[Anxiety]]