There Are No Facts … Without Data

art03x-image-editedRecently a Trump surrogate said that “There are no such things as facts.” More ridiculous words could not be spoken – and that describes the tactic one of the two ruling parties in the U.S. took with their approach to the presidential campaign. Facts do not matter anymore. As a data person, the statement really sent me reeling. The real problem is that there are people in this post-fact world that are, in fact, anti-fact.

There are three facts people should keep in mind when it comes to facts:

1. There is ALWAYS data to support facts.
2. A fact does not have to be believable for it to be a fact.
3. People will believe what they want to believe.

The original purpose of this article was to be a rant focused on my post-election blues. I have turned it into more “food for thought” when it comes to data and what facts really are.

There is ALWAYS Data to Support Facts

A statement cannot be a fact unless there is data to support it. The data may not always be readily available – however if the fact is “checked” to be true there needs to be verifiable data. Just because a statement is repeated over and over again does not make the statement any truer.

What is a fact? The dictionary says that a fact is something that exists; reality; truth. The dictionary definition does not help very much. Some people live in an alternative reality and believe what they want to believe.

Some things are facts and can be verified. One plus one equals two. Milk goes sour if you keep it too long. Mary purchased six boxes of Kleenex on Saturday from the Kmart in downtown Pittsburgh at twelve noon. The sun will come up – tomorrow (bet your bottom dollar). These things are all facts.

In the business world, investments are made to assure that the best quality data is available for the people that will make decisions using that data. But even with the best possible data, decisions made from that data are not facts. There are many influences on the outcome of decisions. Decisions are not facts.

Probabilities are not facts either. Data is analyzed every day by data scientists to provide the best possible probabilities and predictive capabilities. Yet the decisions made from even the greatest big data are not facts unless all certainty can be assured. And that is not typically the case.

If a statement is not undeniably provable with data, the statement becomes an opinion or hypothesis. The statement is just not a fact.

Skeptics will say that data can be “spun” to say what you want it to say. This statement is undeniable. But again, the truth is in the details provided by the data.

“American Airline leads all airlines in on-time arrivals” is an example of an easy statement for AA to make. The airlines make statements like this all the time. I fly AA enough to know that this statement cannot possibly be a fact. Further verification will help you to understand that the airline was just counting Charlotte to Pittsburgh flights on the second Wednesday of the month. Always look for the asterisk to learn the data that was used (or not used) to determine what is factual.

A Fact Does Not Need to be Believable (or Believed) to be a Fact

As I stated earlier, false statements do not become more factual the more you say or hear them. The recent U.S. election and the rise of fake news and repeated falsehoods may cause a person to reevaluate that last statement. Statements such as “global warming is a hoax” (scientific data disproves this fact), “taxes are the highest in the U.S.A.” (statistics say otherwise), and “the POTUS is not a U.S Citizen” (disproved with a birth certificate) were repeated time and again as fact when in fact they were or are false.

Believability is based on three factors: 1) point of reference and 2) the level of knowledge of the subject and 3) the data that supports a fact. All of these factors need to be considered.

Point of reference and experiential factors are important. In business and in life, someone who feels as though “the system” has failed them typically has reasons to feel that way. Whether the reasons are their own doing or not does not seem to matter. Our experiences influence what we believe to be fact.

Data scientists use data and their analytical abilities to find and interpret data sources. Some data scientists work diligently to remove the experiential factors to interpret the facts. Other data scientists focus on analyzing experiential factors to best learn how their results will be interpreted.

The level of knowledge someone has about a “factual” statement, the subject of the statement or the data supporting the statement also plays a big role in what is believed and what is not believed. Many people seem to make up facts based on their biases and preferences.

People Will Believe What They Want to Believe

If there is demonstrable data that verifies a factual statement, it does not matter if you believe statement. The hard data (that represents the facts) makes it true. The statement “believe what you want to believe” should be forever stricken from the lexicon.

There is nothing that can be done about people believing what they want to believe. Fact checking has become commonplace. The Associated Press (AP) is initiating actions to place a validation or certification mark on all AP stories considered news worthy. These marks demonstrate that the AP has seen, and reviewed, and used the data that supports news statements.

Even though the AP, and I’m assuming other news organizations will follow, is taking steps to differentiate between fact and fiction, people will continue to lean on their biases rather than learn about the data that is behind some of the things they believe or have been told to believe.

From my perspective, that is a fact of life. Facts must be supported by data.

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Robert S. Seiner

Robert S. Seiner

Robert (Bob) S. Seiner is the President and Principal of KIK Consulting & Educational Services and the Publisher Emeritus of The Data Administration Newsletter. Seiner is a thought-leader in the fields of data governance and metadata management. KIK (which stands for “knowledge is king”) offers consulting, mentoring and educational services focused on Non-Invasive Data Governance, data stewardship, data management and metadata management solutions. Seiner is the author of the industry’s top selling book on data governance – Non-Invasive Data Governance: The Path of Least Resistance and Greatest Success (Technics Publications 2014) and the followup book - Non-Invasive Data Governance Strikes Again: Gaining Experience and Perspective (Technics 2023), and has hosted the popular monthly webinar series on data governance called Real-World Data Governance (w Dataversity) since 2012. Seiner holds the position of Adjunct Faculty and Instructor for the Carnegie Mellon University Heinz College Chief Data Officer Executive Education program.

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