# Truthful Data Stories By:: [[Brian Heath]] 2023-03-08 Analytics professionals know how easy it is to bend data to tell different stories. Leaving out a few "outlier" data points, slicing the data at time intervals, or highlighting the right combination of metrics in orange versus blue can all lead to different stories. Most of these methods are legitimate, but there is always a chance something goes amiss, either intentionally or unintentionally, and the entire story is wrong. In my experience, analytics professionals rarely misrepresent data intentionally. Those who pick the profession have an innate sense of truth and accuracy. This is as beneficial as it is troublesome. It is beneficial because organizations can trust analytics professionals to represent the data truthfully. It is troublesome because the truth is hard to come by philosophically and politically. Sometimes analytics professionals present their truth and not the truth of the leader or the organization. Egos get in the way, people stop listening to each other, and finger-pointing begins. This is why it is important for analytics professionals to build trust by not only knowing their truth but the truth of those they are supporting. However, one endless headache for the analytics professional is when people misuse or abuse data for their means. Think of the politician who tells only one side of the story or the salesperson who charms away issues seen in the data by highlighting the irrelevant incompleteness of the data. To analytics professionals, these violate the spirit of the analysis. It cuts down to our core, and anger builds. There are two responses. Bring out the data weapons to prove them and their truth wrong. Only the most charismatic, thick-skinned, and politically savvy analytics professional can successfully pull this off. The other response is to attempt to cut these people off from the data via educational requirements, security protocols, and job descriptions. These often go too far, and now the organization is starved for data and analysis. The analytics professional is now alienated. Their value is questioned. Analysis is now a luxury, and luxuries are the first to go when times get tough. As a profession, we must find better ways to deal with and accept the stories people will tell with the data. This journey begins with better understanding truth, humanity, and ourselves. #### Related Items [[Truth]] [[Data]] [[Analytics]] [[Storytelling]] [[Value]] [[Philosophy]]